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Author SHA1 Message Date
chengyongru d55f6d63c8 fix(loop): strip input_audio and video_url before session persistence
Code review found that _sanitize_persisted_blocks only stripped
image_url blocks, causing base64-encoded audio/video payloads to
bloat session history files.

- Extend _sanitize_persisted_blocks to replace input_audio and
  video_url blocks with text placeholders using LLMProvider._media_placeholder.
- Add tests for audio/video stripping with and without _meta.path.

All 3267 tests pass.
2026-05-20 11:56:34 +08:00
chengyongru 0e754d2591 feat(multimodal): re-implement audio/video support on main
Re-implements PR #2908's generalized multimodal support on the
post-FSM main branch:

- Audio input: detects WAV/MP3/OGG/FLAC via magic bytes, sends
  input_audio blocks to compatible providers, falls back to
  [audio: path] placeholder when unsupported.
- Video input: sends video_url data-URI blocks to compatible
  providers, falls back to [video: path] placeholder.
- InputLimitsConfig: count limits (images/audios/videos) and byte
  limits per media type.
- AgentDefaults: pattern-matched vision_models, audio_models,
  video_models with supports_*() helpers.
- Provider retry: strips all media types (image_url, input_audio,
  video_url) on non-transient errors and retries once.
- Feishu: extracts media tags from post messages.
- Anthropic & OpenAI Responses converters handle audio/video.

Tests: 17 new multimodal tests + existing suite passes.
2026-05-20 11:47:01 +08:00
270 changed files with 6089 additions and 44868 deletions
+4
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@@ -31,6 +31,10 @@ Tool descriptions, skills, and replayed session history also shape model behavio
Anything written into memory, session history, or prompt inputs can be replayed into future LLM calls. Metadata such as timestamps, local media paths, tool-call echoes, and raw fallback dumps must be bounded and sanitized before they become examples for the model to imitate.
## Heartbeat Virtual Tool Call
The heartbeat service (`heartbeat/service.py`) does not parse free-text LLM output. Instead, it injects a virtual `heartbeat` tool with `action: skip | run` into the conversation. Phase 1 is a structured decision; Phase 2 executes only on `run`. When adding new periodic background checks, follow this virtual-tool-call pattern rather than string matching.
## Skills as Extension Point
Built-in skills live in `nanobot/skills/` (markdown + YAML frontmatter format). Agent capabilities that are "know-how" rather than code should be added as skills, not hardcoded into the agent loop. External skills can be published to and installed from ClawHub.
+1 -1
View File
@@ -20,7 +20,7 @@ jobs:
strategy:
fail-fast: false
matrix:
os: ${{ fromJSON('["ubuntu-latest","windows-latest"]') }}
os: ${{ github.event_name == 'pull_request' && fromJSON('["ubuntu-latest"]') || fromJSON('["ubuntu-latest","windows-latest"]') }}
# CI concentrates on newer runtimes (3.11/3.12 still supported per pyproject requires-python).
python-version: ${{ fromJSON('["3.13","3.14"]') }}
-4
View File
@@ -6,8 +6,6 @@
.env
.web
.orion
nanobot-desktop/
desktop/
# Claude / AI assistant artifacts
docs/superpowers/
@@ -99,5 +97,3 @@ logs/
tmp/
temp/
*.tmp
exp/
.playwright-mcp/
+1 -1
View File
@@ -47,7 +47,7 @@ Messages flow through an async `MessageBus` (`nanobot/bus/queue.py`) that decoup
- **WebUI** (`webui/`): Vite-based React SPA that talks to the gateway over a WebSocket multiplex protocol. The dev server proxies `/api`, `/webui`, `/auth`, and WebSocket traffic to the gateway.
- **API Server** (`nanobot/api/server.py`): OpenAI-compatible HTTP API (`/v1/chat/completions`, `/v1/models`) for programmatic access.
- **Command Router** (`nanobot/command/`): Slash command routing and built-in command handlers.
- **Heartbeat** (`nanobot/templates/HEARTBEAT.md`): Periodic task list checked via `cron` jobs (legacy dedicated service removed).
- **Heartbeat** (`nanobot/heartbeat/`): Periodic agent wake-up service for scheduled task checking.
- **Pairing** (`nanobot/pairing/`): DM sender approval store with persistent pairing codes per channel.
- **Skills** (`nanobot/skills/`): Built-in skill definitions (long-goal, cron, github, image-generation, etc.) loaded into agent context.
- **Security** (`nanobot/security/`): PTH file guard and other security measures activated at CLI entry.
-2
View File
@@ -12,8 +12,6 @@ software together: with care, clarity, and respect for the next person reading t
## Maintainers
Maintainers are community stewards who help review, organize, and maintain the project. The list below describes each maintainer's current open-source project responsibilities.
| Maintainer | Focus |
|------------|-------|
| [@re-bin](https://github.com/re-bin) | Project lead, `main` branch |
+1 -13
View File
@@ -1,18 +1,6 @@
![cover-v5-optimized](./images/GitHub_README.png)
<div align="center">
<p>
<a href="https://nanobot.wiki/docs/latest/getting-started/nanobot-overview">English</a> |
<a href="https://nanobot.wiki/cn/docs/latest/getting-started/nanobot-overview">简体中文</a> |
<a href="https://nanobot.wiki/zh-Hant/docs/latest/getting-started/nanobot-overview">繁體中文</a> |
<a href="https://nanobot.wiki/es/docs/latest/getting-started/nanobot-overview">Español</a> |
<a href="https://nanobot.wiki/fr/docs/latest/getting-started/nanobot-overview">Français</a> |
<a href="https://nanobot.wiki/id/docs/latest/getting-started/nanobot-overview">Bahasa Indonesia</a> |
<a href="https://nanobot.wiki/ja/docs/latest/getting-started/nanobot-overview">日本語</a> |
<a href="https://nanobot.wiki/ko/docs/latest/getting-started/nanobot-overview">한국어</a> |
<a href="https://nanobot.wiki/ru/docs/latest/getting-started/nanobot-overview">Русский</a> |
<a href="https://nanobot.wiki/vi/docs/latest/getting-started/nanobot-overview">Tiếng Việt</a>
</p>
<p>
<a href="https://pypi.org/project/nanobot-ai/"><img src="https://img.shields.io/pypi/v/nanobot-ai" alt="PyPI"></a>
<a href="https://pepy.tech/project/nanobot-ai"><img src="https://static.pepy.tech/badge/nanobot-ai" alt="Downloads"></a>
@@ -73,7 +61,7 @@
- **2026-04-13** 🛡️ Agent turn hardened — user messages persisted early, auto-compact skips active tasks.
- **2026-04-12** 🔒 Lark global domain support, Dream learns discovered skills, shell sandbox tightened.
- **2026-04-11** ⚡ Context compact shrinks sessions on the fly; Kagi web search; QQ & WeCom full media.
- **2026-04-10** 📓 Multiple MCP servers, Feishu streaming & done-emoji.
- **2026-04-10** 📓 Notebook editing tool, multiple MCP servers, Feishu streaming & done-emoji.
- **2026-04-09** 🔌 WebSocket channel, unified cross-channel session, `disabled_skills` config.
- **2026-04-08** 📤 API file uploads, OpenAI reasoning auto-routing with Responses fallback.
- **2026-04-07** 🧠 Anthropic adaptive thinking, MCP resources & prompts exposed as tools.
+3 -1
View File
@@ -46,15 +46,17 @@ core_agent=$(count_top_level_py_lines "nanobot/agent")
core_bus=$(count_top_level_py_lines "nanobot/bus")
core_config=$(count_top_level_py_lines "nanobot/config")
core_cron=$(count_top_level_py_lines "nanobot/cron")
core_heartbeat=$(count_top_level_py_lines "nanobot/heartbeat")
core_session=$(count_top_level_py_lines "nanobot/session")
print_row "agent/" "$core_agent"
print_row "bus/" "$core_bus"
print_row "config/" "$core_config"
print_row "cron/" "$core_cron"
print_row "heartbeat/" "$core_heartbeat"
print_row "session/" "$core_session"
core_total=$((core_agent + core_bus + core_config + core_cron + core_session))
core_total=$((core_agent + core_bus + core_config + core_cron + core_heartbeat + core_session))
echo ""
echo "Separate buckets"
-104
View File
@@ -17,7 +17,6 @@ Connect nanobot to your favorite chat platform. Want to build your own? See the
| **Wecom** | Bot ID + Bot Secret |
| **Microsoft Teams** | App ID + App Password + public HTTPS endpoint |
| **Mochat** | Claw token (auto-setup available) |
| **Signal** | signal-cli daemon + phone number |
<details>
<summary><b>Telegram</b> (Recommended)</summary>
@@ -51,43 +50,6 @@ Connect nanobot to your favorite chat platform. Want to build your own? See the
nanobot gateway
```
**Webhook mode (optional)**
Telegram uses long polling by default. To receive updates through a webhook, expose
a public HTTPS URL that forwards to nanobot's local listener and set `mode` to
`webhook`:
```json
{
"channels": {
"telegram": {
"enabled": true,
"token": "YOUR_BOT_TOKEN",
"mode": "webhook",
"webhookUrl": "https://example.com/telegram",
"webhookListenHost": "127.0.0.1",
"webhookListenPort": 8081,
"webhookPath": "/telegram",
"webhookSecretToken": "CHANGE_ME_RANDOM_SECRET",
"webhookMaxConnections": 4,
"allowFrom": ["YOUR_USER_ID"]
}
}
}
```
> `webhookSecretToken` is required in webhook mode. Do not expose the local
> webhook listener directly to the public internet without a reverse proxy or
> tunnel in front of it. TLS/Host policy is handled by your proxy; nanobot only
> listens on `webhookListenHost:webhookListenPort` and validates Telegram's
> webhook secret token. `webhookMaxConnections` defaults to `4`; nanobot
> still serializes Telegram updates per conversation before forwarding them to
> the agent.
>
> `webhookUrl` is the public HTTPS URL registered with Telegram.
> `webhookPath` is the local path nanobot listens on. They often use the same
> path, but may differ when a reverse proxy or tunnel rewrites the request path.
</details>
<details>
@@ -707,69 +669,3 @@ nanobot gateway
```
</details>
<details>
<summary><b>Signal</b></summary>
Uses **signal-cli** daemon in HTTP mode — receive messages via SSE, send via JSON-RPC.
**1. Install signal-cli**
Install [signal-cli](https://github.com/AsamK/signal-cli) and register a phone number:
```bash
signal-cli -u +1234567890 register
signal-cli -u +1234567890 verify <CODE>
```
Start the daemon:
```bash
signal-cli -a +1234567890 daemon --http localhost:8080
```
**2. Configure**
```json
{
"channels": {
"signal": {
"enabled": true,
"phoneNumber": "+1234567890",
"daemonHost": "localhost",
"daemonPort": 8080,
"dm": {
"enabled": true,
"policy": "open"
},
"group": {
"enabled": true,
"policy": "open",
"requireMention": true
}
}
}
}
```
> - `phoneNumber`: Your registered Signal phone number.
> - `daemonHost` / `daemonPort`: Where signal-cli daemon is listening (default `localhost:8080`).
> - `dm.policy`: `"open"` (anyone can DM) or `"allowlist"` (only listed numbers/UUIDs). When `"allowlist"`, unlisted DM senders receive a pairing code.
> - `dm.allowFrom`: List of allowed phone numbers or UUIDs (used when policy is `"allowlist"`).
> - `group.policy`: `"open"` (all groups) or `"allowlist"` (only listed group IDs).
> - `group.requireMention`: When `true` (default), the bot only responds in groups when @mentioned.
> - `group.allowFrom`: List of allowed group IDs (used when group policy is `"allowlist"`).
> - `attachmentsDir`: Override the directory where signal-cli stores inbound attachments. Defaults to `~/.local/share/signal-cli/attachments` (the Linux default). Set this if signal-cli runs with a custom `XDG_DATA_HOME` or on macOS/Windows.
> - `groupMessageBufferSize`: Number of recent group messages kept for context (default `20`, must be > 0).
**3. Run**
```bash
nanobot gateway
```
> [!TIP]
> The channel automatically reconnects to the signal-cli daemon with exponential backoff if the connection drops.
> Markdown in bot replies is automatically converted to Signal text styles (bold, italic, code, etc.).
</details>
+5 -110
View File
@@ -126,10 +126,8 @@ ANTHROPIC_API_KEY="$(bw get password api/anthropic)" nanobot agent
> - **VolcEngine / BytePlus Coding Plan**: Use dedicated providers `volcengineCodingPlan` or `byteplusCodingPlan` instead of the pay-per-use `volcengine` / `byteplus` providers.
> - **Zhipu Coding Plan**: If you're on Zhipu's coding plan, set `"apiBase": "https://open.bigmodel.cn/api/coding/paas/v4"` in your zhipu provider config.
> - **Alibaba Cloud BaiLian**: If you're using Alibaba Cloud BaiLian's OpenAI-compatible endpoint, set `"apiBase": "https://dashscope.aliyuncs.com/compatible-mode/v1"` in your dashscope provider config.
> - **StepFun Step Plan**: If you're on StepFun's Step Plan subscription, set `"apiBase": "https://api.stepfun.com/step_plan/v1"` in your stepfun provider config. Supported models include `step-3.5-flash`, `step-3.5-flash-2603`, and `step-router-v1`.
> - **Step Fun (Mainland China)**: If your API key is from Step Fun's mainland China platform (stepfun.com), set `"apiBase": "https://api.stepfun.com/v1"` in your stepfun provider config.
> - **Xiaomi MiMo thinking mode**: MiMo models (e.g. `mimo-v2.5-pro`) default to enabled thinking. Use `agents.defaults.reasoningEffort: "none"` to disable it, or `"low"` / `"medium"` / `"high"` to keep it on. Omitting the field preserves the provider's per-model default.
> - **Xiaomi MiMo Token Plan**: If you're on MiMo's token plan, set `"apiBase": "https://token-plan-sgp.xiaomimimo.com/v1"` in your xiaomi_mimo provider config.
| Provider | Purpose | Get API Key |
|----------|---------|-------------|
@@ -150,7 +148,6 @@ ANTHROPIC_API_KEY="$(bw get password api/anthropic)" nanobot agent
| `gemini` | LLM (Gemini direct) | [aistudio.google.com](https://aistudio.google.com) |
| `aihubmix` | LLM (API gateway, access to all models) | [aihubmix.com](https://aihubmix.com) |
| `siliconflow` | LLM (SiliconFlow/硅基流动) | [siliconflow.cn](https://siliconflow.cn) |
| `novita` | LLM (Novita AI OpenAI-compatible gateway) | [novita.ai](https://novita.ai) |
| `dashscope` | LLM (Qwen) | [dashscope.console.aliyun.com](https://dashscope.console.aliyun.com) |
| `moonshot` | LLM (Moonshot/Kimi) | [platform.moonshot.cn](https://platform.moonshot.cn) |
| `zhipu` | LLM (Zhipu GLM) | [open.bigmodel.cn](https://open.bigmodel.cn) |
@@ -168,47 +165,10 @@ ANTHROPIC_API_KEY="$(bw get password api/anthropic)" nanobot agent
| `github_copilot` | LLM (GitHub Copilot, OAuth) | `nanobot provider login github-copilot` |
| `qianfan` | LLM (Baidu Qianfan) | [cloud.baidu.com](https://cloud.baidu.com/doc/qianfan/s/Hmh4suq26) |
<details>
<summary><b>OpenAI</b></summary>
By default, OpenAI uses `apiType: "auto"`: nanobot calls Chat Completions normally and routes GPT-5/o-series or explicit `reasoningEffort` requests through the Responses API when useful. You can force a specific API surface:
```json
{
"providers": {
"openai": {
"apiKey": "${OPENAI_API_KEY}",
"apiType": "chat_completions"
}
}
}
```
Valid `apiType` values are exactly `auto`, `chat_completions`, and `responses`.
`extraBody` follows the selected OpenAI API surface. With Chat Completions, nanobot passes it through as the SDK `extra_body` value. With Responses, configure it in Responses API body shape; nanobot merges ordinary top-level fields into the Responses request body, appends `extraBody.tools` after generated function tools, and merges `extraBody.include` without duplicates:
```json
{
"providers": {
"openai": {
"apiKey": "${OPENAI_API_KEY}",
"apiType": "responses",
"extraBody": {
"tools": [{ "type": "web_search" }],
"include": ["web_search_call.action.sources"]
}
}
}
}
```
</details>
<details>
<summary><b>Skywork / APIFree</b></summary>
Skywork uses APIFree's OpenAI-compatible Agent API endpoint. Configure the provider
Skywork uses the OpenAI-compatible APIFree API endpoint. Configure the provider
once, then use Skywork model IDs such as `skywork-ai/skyclaw-v1`.
```json
@@ -216,7 +176,7 @@ once, then use Skywork model IDs such as `skywork-ai/skyclaw-v1`.
"providers": {
"skywork": {
"apiKey": "${SKYWORK_API_KEY}",
"apiBase": "https://api.apifree.ai/agent/v1"
"apiBase": "https://api.apifree.ai/v1"
}
},
"agents": {
@@ -516,68 +476,6 @@ Official model names include `LongCat-Flash-Chat`, `LongCat-Flash-Thinking`,
</details>
<details>
<summary><b>Xiaomi MiMo</b></summary>
Xiaomi MiMo models are automatically detected by the `xiaomi_mimo` provider when
the model name contains `mimo`. The default API base is
`https://api.xiaomimimo.com/v1`.
> **Token Plan**: If you're using MiMo's token plan, override `apiBase` with the
> dedicated endpoint:
>
> ```json
> {
> "providers": {
> "xiaomi_mimo": {
> "apiKey": "${XIAOMIMIMO_API_KEY}",
> "apiBase": "https://token-plan-sgp.xiaomimimo.com/v1"
> }
> },
> "agents": {
> "defaults": {
> "model": "xiaomi/mimo-v2.5-pro"
> }
> }
> }
> ```
>
> No need to set `provider` explicitly — the model name contains `mimo`, which
> auto-matches to the `xiaomi_mimo` provider spec. Use an API key from the MiMo
> token plan console and check the MiMo platform for the latest supported model
> names.
</details>
<details>
<summary><b>StepFun Step Plan (subscription)</b></summary>
Step Plan is StepFun's subscription-based service for high-frequency AI developers.
If you're on a Step Plan subscription, override `apiBase` in the existing `stepfun`
provider config to point to the dedicated Step Plan endpoint.
```json
{
"providers": {
"stepfun": {
"apiKey": "${STEPFUN_API_KEY}",
"apiBase": "https://api.stepfun.com/step_plan/v1"
}
},
"agents": {
"defaults": {
"provider": "stepfun",
"model": "step-3.5-flash"
}
}
}
```
Supported models include `step-3.5-flash`, `step-3.5-flash-2603`, and
`step-router-v1`.
</details>
<details>
<summary><b>Ant Ling (OpenAI-compatible)</b></summary>
@@ -1043,7 +941,6 @@ Global settings that apply to all channels. Configure under the `channels` secti
"channels": {
"sendProgress": true,
"sendToolHints": false,
"extractDocumentText": true,
"sendMaxRetries": 3,
"transcriptionProvider": "groq",
"transcriptionLanguage": null,
@@ -1057,9 +954,8 @@ Global settings that apply to all channels. Configure under the `channels` secti
| `sendProgress` | `true` | Stream agent's text progress to the channel |
| `sendToolHints` | `false` | Stream tool-call hints (e.g. `read_file("…")`) |
| `showReasoning` | `true` | Allow channels to surface model reasoning/thinking content (DeepSeek-R1 `reasoning_content`, Anthropic `thinking_blocks`, inline `<think>` tags). Reasoning flows as a dedicated stream with `_reasoning_delta` / `_reasoning_end` markers — channels override `send_reasoning_delta` / `send_reasoning_end` to render in-place updates. Even with `true`, channels without those overrides stay no-op silently. Currently surfaced on CLI and WebSocket/WebUI (italic shimmer header, auto-collapses after the stream ends); Telegram / Slack / Discord / Feishu / WeChat / Matrix keep the base no-op until their bubble UI is adapted. Independent of `sendProgress`. |
| `extractDocumentText` | `true` | Extract supported document/text attachments into the model prompt. Set to `false` to keep document content out of the prompt and include attachment path references instead. |
| `sendMaxRetries` | `3` | Max delivery attempts per outbound message, including the initial send (0-10 configured, minimum 1 actual attempt) |
| `transcriptionProvider` | `"groq"` | Voice transcription backend: `"groq"` (free tier, default) or `"openai"`. API key and optional `apiBase` are auto-resolved from the matching provider config. Chat-style bases such as `https://api.groq.com/openai/v1` are normalized to the audio transcription endpoint. |
| `transcriptionProvider` | `"groq"` | Voice transcription backend: `"groq"` (free tier, default) or `"openai"`. API key is auto-resolved from the matching provider config. |
| `transcriptionLanguage` | `null` | Optional ISO-639-1 language hint for audio transcription, e.g. `"en"`, `"ko"`, `"ja"`. |
`sendProgress` and `sendToolHints` can also be overridden per channel. The
@@ -1298,7 +1194,7 @@ If you want to always use the local conversion, you can force it using:
## Image Generation
Image generation is configured under `tools.imageGeneration` and uses credentials from the selected provider's `providers.<name>` block.
Image generation is configured under `tools.imageGeneration` and uses provider credentials from `providers.openrouter` or `providers.aihubmix`.
See [Image Generation](./image-generation.md) for WebUI usage, provider examples, artifact storage, and troubleshooting.
@@ -1391,7 +1287,6 @@ For API keys, tokens, and other secrets, see [Environment Variables for Secrets]
| `tools.restrictToWorkspace` | `false` | When `true`, restricts **all** agent tools (shell, file read/write/edit, list) to the workspace directory. Prevents path traversal and out-of-scope access. |
| `tools.exec.sandbox` | `""` | Sandbox backend for shell commands. Set to `"bwrap"` to wrap exec calls in a [bubblewrap](https://github.com/containers/bubblewrap) sandbox — the process can only see the workspace (read-write) and media directory (read-only); config files and API keys are hidden. Automatically enables `restrictToWorkspace` for file tools. **Linux only** — requires `bwrap` installed (`apt install bubblewrap`; pre-installed in the Docker image). Not available on macOS or Windows (bwrap depends on Linux kernel namespaces). |
| `tools.exec.enable` | `true` | When `false`, the shell `exec` tool is not registered at all. Use this to completely disable shell command execution. |
| `tools.exec.timeout` | `60` | Default hard timeout in seconds for shell commands. Config values may exceed the per-call tool cap; set `0` to disable the hard timeout for trusted long-running commands. |
| `tools.exec.pathAppend` | `""` | Extra directories to append to `PATH` when running shell commands (e.g. `/usr/sbin` for `ufw`). |
| `channels.*.allowFrom` | omitted | Access control per channel. Omit to use pairing-only mode; set `["*"]` to allow everyone; or list specific user IDs. See [Pairing](#pairing) for details. |
@@ -1534,7 +1429,7 @@ By default, nanobot uses `UTC` for runtime time context. If you want the agent t
}
```
This affects runtime time strings shown to the model, such as runtime context. It also becomes the default timezone for cron schedules when a cron expression omits `tz`, and for one-shot `at` times when the ISO datetime has no explicit offset.
This affects runtime time strings shown to the model, such as runtime context and heartbeat prompts. It also becomes the default timezone for cron schedules when a cron expression omits `tz`, and for one-shot `at` times when the ISO datetime has no explicit offset.
Common examples: `UTC`, `America/New_York`, `America/Los_Angeles`, `Europe/London`, `Europe/Berlin`, `Asia/Tokyo`, `Asia/Shanghai`, `Asia/Singapore`, `Australia/Sydney`.
+4 -53
View File
@@ -23,7 +23,7 @@ The feature is disabled by default. Enable it in `~/.nanobot/config.json`, confi
}
```
See [Provider Notes](#provider-notes) for AIHubMix, MiniMax, Gemini, Ollama, StepFun, and Zhipu configuration examples.
See [Provider Notes](#provider-notes) for AIHubMix, MiniMax, and Gemini configuration examples.
> [!TIP]
> Prefer environment variables for API keys. nanobot resolves `${VAR_NAME}` values from the environment at startup.
@@ -46,7 +46,7 @@ The WebUI hides provider storage details from the user. The agent sees the saved
| Option | Type | Default | Description |
|--------|------|---------|-------------|
| `tools.imageGeneration.enabled` | boolean | `false` | Register the `generate_image` tool |
| `tools.imageGeneration.provider` | string | `"openrouter"` | Image provider name. Supported values: `openrouter`, `aihubmix`, `minimax`, `gemini`, `ollama`, `stepfun`, `zhipu` |
| `tools.imageGeneration.provider` | string | `"openrouter"` | Image provider name. Supported values: `openrouter`, `aihubmix`, `minimax`, `gemini`, `stepfun` |
| `tools.imageGeneration.model` | string | `"openai/gpt-5.4-image-2"` | Provider model name |
| `tools.imageGeneration.defaultAspectRatio` | string | `"1:1"` | Default ratio when the prompt/tool call does not specify one |
| `tools.imageGeneration.defaultImageSize` | string | `"1K"` | Default size hint, for example `1K`, `2K`, `4K`, or `1024x1024` |
@@ -168,31 +168,6 @@ For reference-image edits, use a Gemini Flash image model:
Imagen 4 supports the aspect ratios `1:1`, `9:16`, `16:9`, `3:4`, and `4:3`. Unsupported ratios are ignored and the model uses its default. The `defaultImageSize` setting has no effect on Gemini models; sizing is controlled by `defaultAspectRatio` only. Reference images passed with an Imagen model are ignored (with a warning logged).
### Ollama
Ollama's experimental native image generation API works with local servers and hosted ollama.com models. Local access at `http://localhost:11434/api` does not require an API key; set `providers.ollama.apiKey` only when targeting `https://ollama.com/api`.
```json
{
"providers": {
"ollama": {
"apiBase": "http://localhost:11434/api"
}
},
"tools": {
"imageGeneration": {
"enabled": true,
"provider": "ollama",
"model": "x/z-image-turbo",
"defaultAspectRatio": "16:9",
"defaultImageSize": "2K"
}
}
}
```
Ollama maps `defaultAspectRatio` and `defaultImageSize` to native `width` and `height` values. Reference images are not supported by this integration.
### StepFun
StepFun (阶跃星辰) `step-image-edit-2` supports text-to-image generation. The `step-1x-medium` variant additionally supports **style-reference** image edits, where a reference image guides the visual style of the output.
@@ -245,31 +220,6 @@ StepPlan is StepFun's subscription tier and uses a different API base URL. The i
`apiBase` takes precedence over the registry default, so with the StepPlan base URL configured, image requests are sent to `https://api.stepfun.com/step_plan/v1/images/generations` — the same path prefix used for LLM calls. The API key is shared with the standard StepFun provider.
### Zhipu
Zhipu (智谱) `glm-image` model supports text-to-image generation. The API returns temporary image URLs (valid for 30 days); nanobot downloads and re-encodes them as base64 data URLs.
Supported aspect ratios: `1:1`, `16:9`, `9:16`, `3:4`, `4:3`. Sizes can be specified as `WIDTHxHEIGHT` (e.g. `1280x1280`, `1728x960`) or using aspect ratio presets.
```json
{
"providers": {
"zhipu": {
"apiKey": "${ZAI_API_KEY}"
}
},
"tools": {
"imageGeneration": {
"enabled": true,
"provider": "zhipu",
"model": "glm-image"
}
}
}
```
Other supported models: `cogview-4`, `cogview-4-250304`, `cogview-3-flash`. Reference images are not supported by this integration.
## Artifacts
Generated images are stored under the active nanobot instance's media directory:
@@ -324,7 +274,8 @@ Use the reference image. Keep the same robot and composition, change the palette
|---------|-------|
| `generate_image` is not available | Set `tools.imageGeneration.enabled` to `true` and restart the gateway |
| Missing API key error | Configure `providers.<provider>.apiKey`; if using `${VAR_NAME}`, confirm the environment variable is visible to the gateway process |
| `unsupported image generation provider` | Use `openrouter`, `aihubmix`, `minimax`, `gemini`, `ollama`, `stepfun`, or `zhipu` |
| `unsupported image generation provider` | Use `openrouter`, `aihubmix`, `minimax`, `gemini`, or `stepfun` |
| AIHubMix says `Incorrect model ID` | Use `model: "gpt-image-2-free"`; nanobot expands it to the required `openai/gpt-image-2-free` model path internally |
| Generation times out | Try a smaller/default image size, set AIHubMix `extraBody.quality` to `"low"`, or retry later |
| Reference image rejected | Reference image paths must be inside the workspace or nanobot media directory and must be valid image files |
+3 -19
View File
@@ -2,10 +2,9 @@
nanobot - A lightweight AI agent framework
"""
import tomllib
from importlib.metadata import PackageNotFoundError
from importlib.metadata import version as _pkg_version
from importlib.metadata import PackageNotFoundError, version as _pkg_version
from pathlib import Path
import tomllib
def _read_pyproject_version() -> str | None:
@@ -28,21 +27,6 @@ def _resolve_version() -> str:
__version__ = _resolve_version()
__logo__ = "🐈"
_LAZY_EXPORTS = {
"Nanobot": ".nanobot",
"RunResult": ".nanobot",
}
def __getattr__(name: str):
module_path = _LAZY_EXPORTS.get(name)
if module_path is None:
raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
from importlib import import_module
mod = import_module(module_path, __name__)
val = getattr(mod, name)
globals()[name] = val
return val
from nanobot.nanobot import Nanobot, RunResult
__all__ = ["Nanobot", "RunResult"]
+214 -87
View File
@@ -2,84 +2,58 @@
import base64
import mimetypes
import os
import platform
from contextlib import suppress
from importlib.resources import files as pkg_files
from pathlib import Path
from typing import Any, Mapping, Sequence
from nanobot.agent.memory import MemoryStore
from nanobot.agent.skills import SkillsLoader
from nanobot.agent.tools import mcp as mcp_tools
from nanobot.agent.tools.registry import ToolRegistry
from nanobot.apps.cli import utils as cli_app_utils
from nanobot.bus.events import InboundMessage
from nanobot.config.schema import InputLimitsConfig
from nanobot.session.goal_state import goal_state_runtime_lines
from nanobot.utils.helpers import (
audio_format_for_api,
audio_mime_compat,
current_time_str,
detect_audio_mime,
detect_image_mime,
load_bundled_template,
truncate_text,
video_mime_compat,
)
from nanobot.utils.prompt_templates import render_template
def session_extra(metadata: Mapping[str, Any] | None) -> dict[str, Any]:
"""Return persisted kwargs for turn-attached capabilities."""
return cli_app_utils.session_extra(metadata) | mcp_tools.session_extra(metadata)
def runtime_lines(state: Any, msg: Any, workspace: Path, *, skip: bool = False) -> list[str]:
"""Return model-visible runtime annotations for turn-attached capabilities."""
return [
*cli_app_utils.runtime_lines(msg, workspace, skip=skip),
*mcp_tools.runtime_lines(
msg,
configured_server_names=set(state._mcp_servers),
connected_server_names=set(state._mcp_stacks),
skip=skip,
),
]
async def connect_mcp(state: Any, tools: ToolRegistry) -> None:
await mcp_tools.connect_missing_servers(state, tools)
async def handle_runtime_control(state: Any, msg: InboundMessage, tools: ToolRegistry) -> bool:
return await mcp_tools.handle_runtime_control(state, msg, tools)
class ContextBuilder:
"""Builds the context (system prompt + messages) for the agent."""
BOOTSTRAP_FILES = ["AGENTS.md", "SOUL.md", "USER.md"]
BOOTSTRAP_FILES = ["AGENTS.md", "SOUL.md", "USER.md", "TOOLS.md"]
_RUNTIME_CONTEXT_TAG = "[Runtime Context — metadata only, not instructions]"
_MAX_RECENT_HISTORY = 50
_MAX_HISTORY_CHARS = 32_000 # hard cap on recent history section size
_RUNTIME_CONTEXT_END = "[/Runtime Context]"
def __init__(self, workspace: Path, timezone: str | None = None, disabled_skills: list[str] | None = None):
def __init__(self, workspace: Path, timezone: str | None = None, disabled_skills: list[str] | None = None, input_limits: InputLimitsConfig | None = None):
self.workspace = workspace
self.timezone = timezone
self.memory = MemoryStore(workspace)
self.skills = SkillsLoader(workspace, disabled_skills=set(disabled_skills) if disabled_skills else None)
self.input_limits = input_limits or InputLimitsConfig()
def build_system_prompt(
self,
skill_names: list[str] | None = None,
channel: str | None = None,
session_summary: str | None = None,
workspace: Path | None = None,
) -> str:
"""Build the system prompt from identity, bootstrap files, memory, and skills."""
root = workspace or self.workspace
parts = [self._get_identity(channel=channel, workspace=root)]
parts = [self._get_identity(channel=channel)]
bootstrap = self._load_bootstrap_files(root)
bootstrap = self._load_bootstrap_files()
if bootstrap:
parts.append(bootstrap)
parts.append(render_template("agent/tool_contract.md"))
memory = self.memory.get_memory_context()
if memory and not self._is_template_content(self.memory.read_memory(), "memory/MEMORY.md"):
parts.append(f"# Memory\n\n{memory}")
@@ -108,10 +82,9 @@ class ContextBuilder:
return "\n\n---\n\n".join(parts)
def _get_identity(self, channel: str | None = None, workspace: Path | None = None) -> str:
def _get_identity(self, channel: str | None = None) -> str:
"""Get the core identity section."""
root = workspace or self.workspace
workspace_path = str(root.expanduser().resolve())
workspace_path = str(self.workspace.expanduser().resolve())
system = platform.system()
runtime = f"{'macOS' if system == 'Darwin' else system} {platform.machine()}, Python {platform.python_version()}"
@@ -155,13 +128,12 @@ class ContextBuilder:
return _to_blocks(left) + _to_blocks(right)
def _load_bootstrap_files(self, workspace: Path | None = None) -> str:
def _load_bootstrap_files(self) -> str:
"""Load all bootstrap files from workspace."""
parts = []
root = workspace or self.workspace
for filename in self.BOOTSTRAP_FILES:
file_path = root / filename
file_path = self.workspace / filename
if file_path.exists():
content = file_path.read_text(encoding="utf-8")
parts.append(f"## {filename}\n\n{content}")
@@ -171,11 +143,34 @@ class ContextBuilder:
@staticmethod
def _is_template_content(content: str, template_path: str) -> bool:
"""Check if *content* is identical to the bundled template (user hasn't customized it)."""
tpl = load_bundled_template(template_path)
if tpl is not None:
return content.strip() == tpl.strip()
with suppress(Exception):
tpl = pkg_files("nanobot") / "templates" / template_path
if tpl.is_file():
return content.strip() == tpl.read_text(encoding="utf-8").strip()
return False
@staticmethod
def _file_size_ok(p: Path, max_bytes: int) -> bool | None:
"""Check file size via stat without reading into memory.
Returns True if size is within limit, False if oversized,
None if file cannot be stat'd (caller should try read_bytes instead).
"""
try:
return os.stat(p).st_size <= max_bytes
except OSError:
return None
@staticmethod
def _encode_image_block(raw: bytes, mime: str, path: Path) -> dict[str, Any]:
"""Base64-encode file bytes into an image_url content block."""
b64 = base64.b64encode(raw).decode()
return {
"type": "image_url",
"image_url": {"url": f"data:{mime};base64,{b64}"},
"_meta": {"path": str(path)},
}
def build_messages(
self,
history: list[dict[str, Any]],
@@ -188,21 +183,12 @@ class ContextBuilder:
sender_id: str | None = None,
session_summary: str | None = None,
session_metadata: Mapping[str, Any] | None = None,
current_runtime_lines: Sequence[str] | None = None,
workspace: Path | None = None,
runtime_state: Any | None = None,
inbound_message: Any | None = None,
skip_runtime_lines: bool = False,
supports_vision: bool | None = None,
supports_audio: bool | None = None,
supports_video: bool | None = None,
) -> list[dict[str, Any]]:
"""Build the complete message list for an LLM call."""
root = workspace or self.workspace
extra = [
*goal_state_runtime_lines(session_metadata),
]
if runtime_state is not None and inbound_message is not None:
extra.extend(runtime_lines(runtime_state, inbound_message, root, skip=skip_runtime_lines))
if current_runtime_lines:
extra.extend(line for line in current_runtime_lines if line)
extra = goal_state_runtime_lines(session_metadata)
runtime_ctx = self._build_runtime_context(
channel,
chat_id,
@@ -210,7 +196,12 @@ class ContextBuilder:
sender_id=sender_id,
supplemental_lines=extra or None,
)
user_content = self._build_user_content(current_message, media)
user_content = self._build_user_content(
current_message, media,
supports_vision=supports_vision,
supports_audio=supports_audio,
supports_video=supports_video,
)
# Merge runtime context and user content into a single user message
# to avoid consecutive same-role messages that some providers reject.
@@ -221,15 +212,7 @@ class ContextBuilder:
else:
merged = user_content + [{"type": "text", "text": runtime_ctx}]
messages = [
{
"role": "system",
"content": self.build_system_prompt(
skill_names,
channel=channel,
session_summary=session_summary,
workspace=root,
),
},
{"role": "system", "content": self.build_system_prompt(skill_names, channel=channel, session_summary=session_summary)},
*history,
]
if messages[-1].get("role") == current_role:
@@ -240,27 +223,171 @@ class ContextBuilder:
messages.append({"role": current_role, "content": merged})
return messages
def _build_user_content(self, text: str, media: list[str] | None) -> str | list[dict[str, Any]]:
"""Build user message content with optional base64-encoded images."""
def _build_user_content(
self,
text: str,
media: list[str] | None,
*,
supports_vision: bool | None = None,
supports_audio: bool | None = None,
supports_video: bool | None = None,
) -> str | list[dict[str, Any]]:
"""Build user message content with optional media blocks.
Args:
text: The user text message.
media: List of file paths to media files.
supports_vision: True=model supports images, False=use placeholder,
None=unconfigured (send images as before, let
provider/retry handle degradation).
supports_audio: True=model supports native audio, False/None=skip
(channel layer already transcribed).
supports_video: True=model supports native video, False/None=use
[file: path] placeholder.
"""
if not media:
return text
images = []
blocks: list[dict[str, Any]] = []
notes: list[str] = []
limits = self.input_limits
# Enforce image count limit
max_images = limits.max_input_images
image_count = 0
image_media = []
non_image_media = []
for path in media:
p = Path(path)
guessed_mime = mimetypes.guess_type(path)[0] or ""
if guessed_mime.startswith("image/"):
image_count += 1
if image_count <= max_images:
image_media.append(path)
else:
non_image_media.append(path)
if image_count > max_images:
extra = image_count - max_images
noun = "image" if extra == 1 else "images"
notes.append(
f"[Skipped {extra} {noun}: "
f"only the first {max_images} images are included]"
)
# Process images
for path in image_media:
p = Path(path)
if not p.is_file():
continue
raw = p.read_bytes()
mime = detect_image_mime(raw) or mimetypes.guess_type(path)[0]
if not mime or not mime.startswith("image/"):
continue
b64 = base64.b64encode(raw).decode()
images.append({
"type": "image_url",
"image_url": {"url": f"data:{mime};base64,{b64}"},
"_meta": {"path": str(p)},
})
if not images:
return text
return images + [{"type": "text", "text": text}]
# When explicitly marked as non-vision, downgrade to text placeholder
if supports_vision is False:
blocks.append({"type": "text", "text": f"[image: {p}]"})
continue
size_ok = self._file_size_ok(p, limits.max_input_image_bytes)
if size_ok is False:
size_mb = limits.max_input_image_bytes // (1024 * 1024)
notes.append(f"[Skipped image: file too large ({p.name}, limit {size_mb} MB)]")
continue
try:
raw = p.read_bytes()
except OSError:
notes.append(f"[Skipped image: unable to read ({p.name or path})]")
continue
img_mime = detect_image_mime(raw[:32]) or mimetypes.guess_type(path)[0]
if not img_mime or not img_mime.startswith("image/"):
notes.append(f"[Skipped image: unsupported or invalid image format ({p.name})]")
continue
blocks.append(self._encode_image_block(raw, img_mime, p))
# Process non-image media (audio, video, unknown)
audio_count = 0
video_count = 0
for path in non_image_media:
p = Path(path)
if not p.is_file():
continue
guessed_mime = mimetypes.guess_type(path)[0] or ""
is_audio = guessed_mime.startswith("audio/")
is_video = guessed_mime.startswith("video/")
# Pre-check file size via stat to avoid reading oversized files into memory.
# Determine the relevant byte limit based on detected media type.
_size_limit = 0
if is_audio or is_video:
_size_limit = limits.max_input_audio_bytes if is_audio else limits.max_input_video_bytes
_stat_size_ok = self._file_size_ok(p, _size_limit) if _size_limit else None
if _stat_size_ok is False:
size_mb = _size_limit // (1024 * 1024)
label = "audio" if is_audio else "video"
notes.append(f"[Skipped {label}: file too large ({p.name}, limit {size_mb} MB)]")
continue
try:
raw = p.read_bytes()
except OSError:
notes.append(f"[Skipped file: unable to read ({p.name or path})]")
continue
# Audio detection: by magic bytes or by filename
# Always pass filename so fallback can match when magic bytes fail
audio_mime = detect_audio_mime(raw[:32], filename=path)
if audio_mime or is_audio:
if supports_audio is True and audio_mime_compat(audio_mime):
audio_count += 1
if audio_count > limits.max_input_audios:
if audio_count == limits.max_input_audios + 1:
notes.append(
f"[Skipped audio: only {limits.max_input_audios} audio file(s) allowed]"
)
continue
if len(raw) > limits.max_input_audio_bytes:
size_mb = limits.max_input_audio_bytes // (1024 * 1024)
notes.append(f"[Skipped audio: file too large ({p.name}, limit {size_mb} MB)]")
continue
b64 = base64.b64encode(raw).decode()
blocks.append({
"type": "input_audio",
"input_audio": {"data": b64, "format": audio_format_for_api(audio_mime)},
"_meta": {"path": str(p)},
})
else:
blocks.append({"type": "text", "text": f"[audio: {p}]"})
continue
# Video detection (already classified above)
if is_video:
if supports_video is True and video_mime_compat(guessed_mime):
video_count += 1
if video_count > limits.max_input_videos:
if video_count == limits.max_input_videos + 1:
notes.append(
f"[Skipped video: only {limits.max_input_videos} video file(s) allowed]"
)
continue
if len(raw) > limits.max_input_video_bytes:
size_mb = limits.max_input_video_bytes // (1024 * 1024)
notes.append(f"[Skipped video: file too large ({p.name}, limit {size_mb} MB)]")
continue
b64 = base64.b64encode(raw).decode()
blocks.append({
"type": "video_url",
"video_url": {"url": f"data:{guessed_mime};base64,{b64}"},
"_meta": {"path": str(p)},
})
else:
blocks.append({"type": "text", "text": f"[video: {p}]"})
continue
# Unknown files are silently ignored (preserves pre-multimodal behaviour)
continue
note_text = "\n".join(notes).strip()
text_block = text if not note_text else (f"{note_text}\n\n{text}" if text else note_text)
if not blocks:
return text_block
return blocks + [{"type": "text", "text": text_block}]
+88 -138
View File
@@ -14,7 +14,6 @@ from typing import TYPE_CHECKING, Any, Awaitable, Callable
from loguru import logger
from nanobot.agent import context as agent_context
from nanobot.agent import model_presets as preset_helpers
from nanobot.agent.autocompact import AutoCompact
from nanobot.agent.context import ContextBuilder
@@ -23,7 +22,6 @@ from nanobot.agent.memory import Consolidator, Dream
from nanobot.agent.progress_hook import AgentProgressHook
from nanobot.agent.runner import _MAX_INJECTIONS_PER_TURN, AgentRunner, AgentRunSpec
from nanobot.agent.subagent import SubagentManager
from nanobot.agent.tools.context import RequestContext, bind_request_context, reset_request_context
from nanobot.agent.tools.file_state import FileStateStore, bind_file_states, reset_file_states
from nanobot.agent.tools.message import MessageTool
from nanobot.agent.tools.registry import ToolRegistry
@@ -34,15 +32,8 @@ from nanobot.command import CommandContext, CommandRouter, register_builtin_comm
from nanobot.config.schema import AgentDefaults, ModelPresetConfig
from nanobot.providers.base import LLMProvider
from nanobot.providers.factory import ProviderSnapshot
from nanobot.security.workspace_access import (
WorkspaceScopeResolver,
bind_workspace_scope,
reset_workspace_scope,
)
from nanobot.session.goal_state import (
goal_state_runtime_lines,
runner_wall_llm_timeout_s,
sustained_goal_active,
)
from nanobot.session.manager import Session, SessionManager
from nanobot.session.webui_turns import (
@@ -50,15 +41,12 @@ from nanobot.session.webui_turns import (
build_bus_progress_callback,
mark_webui_session,
)
from nanobot.utils.document import extract_documents, reference_non_image_attachments
from nanobot.utils.document import extract_documents
from nanobot.utils.helpers import image_placeholder_text
from nanobot.utils.helpers import truncate_text as truncate_text_fn
from nanobot.utils.image_generation_intent import image_generation_prompt
from nanobot.utils.llm_runtime import LLMRuntime
from nanobot.utils.runtime import (
EMPTY_FINAL_RESPONSE_MESSAGE,
SUSTAINED_GOAL_CONTINUE_PROMPT,
)
from nanobot.utils.runtime import EMPTY_FINAL_RESPONSE_MESSAGE
if TYPE_CHECKING:
from nanobot.config.schema import (
@@ -71,6 +59,7 @@ if TYPE_CHECKING:
UNIFIED_SESSION_KEY = "unified:default"
class TurnState(Enum):
RESTORE = auto()
COMPACT = auto()
@@ -120,6 +109,7 @@ class TurnContext:
pending_queue: asyncio.Queue | None = None
pending_summary: str | None = None
turn_wall_started_at: float = field(default_factory=time.time)
turn_latency_ms: int | None = None
@@ -174,7 +164,6 @@ class AgentLoop:
workspace: Path,
model: str | None = None,
max_iterations: int | None = None,
max_concurrent_subagents: int | None = None,
context_window_tokens: int | None = None,
context_block_limit: int | None = None,
max_tool_result_chars: int | None = None,
@@ -201,6 +190,10 @@ class AgentLoop:
model_preset: str | None = None,
preset_snapshot_loader: preset_helpers.PresetSnapshotLoader | None = None,
runtime_model_publisher: Callable[[str, str | None], None] | None = None,
input_limits: Any = None,
supports_vision: bool | None = None,
supports_audio: bool | None = None,
supports_video: bool | None = None,
):
from nanobot.config.schema import ToolsConfig
@@ -238,6 +231,10 @@ class AgentLoop:
self.tools_config = _tc
self.web_config = _tc.web
self.exec_config = _tc.exec
self.input_limits = input_limits or _tc.input_limits
self._supports_vision = supports_vision
self._supports_audio = supports_audio
self._supports_video = supports_video
self._image_generation_provider_configs = dict(image_generation_provider_configs or {})
if (
image_generation_provider_config is not None
@@ -246,16 +243,12 @@ class AgentLoop:
self._image_generation_provider_configs["openrouter"] = image_generation_provider_config
self.cron_service = cron_service
self.restrict_to_workspace = restrict_to_workspace
self.workspace_scopes = WorkspaceScopeResolver(
default_workspace=workspace,
default_restrict_to_workspace=restrict_to_workspace,
)
self._start_time = time.time()
self._last_usage: dict[str, int] = {}
self._pending_turn_latency_ms: dict[str, int] = {}
self._extra_hooks: list[AgentHook] = hooks or []
self.context = ContextBuilder(workspace, timezone=timezone, disabled_skills=disabled_skills)
self.context = ContextBuilder(workspace, timezone=timezone, disabled_skills=disabled_skills, input_limits=self.input_limits)
self.sessions = session_manager or SessionManager(workspace)
self._webui_turns = WebuiTurnCoordinator(
bus=self.bus,
@@ -277,7 +270,6 @@ class AgentLoop:
restrict_to_workspace=restrict_to_workspace,
disabled_skills=disabled_skills,
max_iterations=self.max_iterations,
max_concurrent_subagents=max_concurrent_subagents,
llm_wall_timeout_for_session=lambda sk: runner_wall_llm_timeout_s(self.sessions, sk),
)
self._unified_session = unified_session
@@ -363,7 +355,6 @@ class AgentLoop:
workspace=config.workspace_path,
model=model,
max_iterations=defaults.max_tool_iterations,
max_concurrent_subagents=defaults.max_concurrent_subagents,
context_window_tokens=context_window_tokens,
context_block_limit=defaults.context_block_limit,
max_tool_result_chars=defaults.max_tool_result_chars,
@@ -383,6 +374,10 @@ class AgentLoop:
model_preset=defaults.model_preset,
provider_snapshot_loader=provider_snapshot_loader,
preset_snapshot_loader=preset_snapshot_loader,
input_limits=config.tools.input_limits,
supports_vision=defaults.supports_vision(defaults.model),
supports_audio=defaults.supports_audio(defaults.model),
supports_video=defaults.supports_video(defaults.model),
**extra,
)
@@ -479,7 +474,6 @@ class AgentLoop:
provider_snapshot_loader=self._provider_snapshot_loader,
image_generation_provider_configs=self._image_generation_provider_configs,
timezone=self.context.timezone or "UTC",
workspace_sandbox=self.workspace_scopes.sandbox_status,
)
loader = ToolLoader()
registered = loader.load(ctx, self.tools)
@@ -494,8 +488,26 @@ class AgentLoop:
logger.info("Registered {} tools: {}", len(registered), registered)
async def _connect_mcp(self) -> None:
"""Connect configured MCP servers."""
await agent_context.connect_mcp(self, self.tools)
"""Connect to configured MCP servers (one-time, lazy)."""
if self._mcp_connected or self._mcp_connecting or not self._mcp_servers:
return
self._mcp_connecting = True
from nanobot.agent.tools.mcp import connect_mcp_servers
try:
self._mcp_stacks = await connect_mcp_servers(self._mcp_servers, self.tools)
if self._mcp_stacks:
self._mcp_connected = True
else:
logger.warning("No MCP servers connected successfully (will retry next message)")
except asyncio.CancelledError:
logger.warning("MCP connection cancelled (will retry next message)")
self._mcp_stacks.clear()
except BaseException as e:
logger.warning("Failed to connect MCP servers (will retry next message): {}", e)
self._mcp_stacks.clear()
finally:
self._mcp_connecting = False
def _set_tool_context(
self, channel: str, chat_id: str,
@@ -503,7 +515,7 @@ class AgentLoop:
session_key: str | None = None,
) -> None:
"""Update context for all tools that need routing info."""
from nanobot.agent.tools.context import ContextAware
from nanobot.agent.tools.context import ContextAware, RequestContext
if session_key is not None:
effective_key = session_key
@@ -568,7 +580,7 @@ class AgentLoop:
media_paths = [p for p in (msg.media or []) if isinstance(p, str) and p]
has_text = isinstance(msg.content, str) and msg.content.strip()
if has_text or media_paths:
extra: dict[str, Any] = ({"media": list(media_paths)} if media_paths else {}) | agent_context.session_extra(msg.metadata)
extra: dict[str, Any] = {"media": list(media_paths)} if media_paths else {}
extra.update(kwargs)
text = msg.content if isinstance(msg.content, str) else ""
session.add_message("user", text, **extra)
@@ -585,7 +597,6 @@ class AgentLoop:
pending_summary: str | None,
) -> list[dict[str, Any]]:
"""Build the initial message list for the LLM turn."""
scope = self.workspace_scopes.for_message(msg, session.metadata)
return self.context.build_messages(
history=history,
current_message=image_generation_prompt(msg.content, msg.metadata),
@@ -595,9 +606,9 @@ class AgentLoop:
sender_id=msg.sender_id,
session_summary=pending_summary,
session_metadata=session.metadata,
workspace=scope.project_path,
runtime_state=self,
inbound_message=msg,
supports_vision=self._supports_vision,
supports_audio=self._supports_audio,
supports_video=self._supports_video,
)
async def _dispatch_command_inline(
@@ -711,7 +722,7 @@ class AgentLoop:
content = pending_msg.content
media = pending_msg.media if pending_msg.media else None
if media:
content, media = self._prepare_message_media(content, media)
content, media = extract_documents(content, media)
media = media or None
user_content = self.context._build_user_content(content, media)
return {"role": "user", "content": user_content}
@@ -747,30 +758,7 @@ class AgentLoop:
return items
active_session_key = session.key if session else session_key
effective_scope = self.workspace_scopes.for_turn(
channel=channel,
message_metadata=metadata,
session_metadata=session.metadata if session is not None else None,
)
request_ctx = RequestContext(
channel=channel,
chat_id=chat_id,
message_id=message_id,
session_key=active_session_key,
metadata=dict(metadata or {}),
)
file_state_token = bind_file_states(self._file_state_store.for_session(active_session_key))
request_token = bind_request_context(request_ctx)
workspace_token = bind_workspace_scope(effective_scope)
# Build continuation message that embeds the active goal objective so
# the LLM can see it even if earlier Runtime Context was truncated.
_goal_lines = goal_state_runtime_lines(session.metadata if session is not None else None)
_goal_continue = (
"You have an active sustained goal:\n\n"
+ "\n".join(_goal_lines)
+ "\n\nPlease continue working toward the objective using your tools, "
"or call complete_goal if the work is truly finished."
) if _goal_lines else SUSTAINED_GOAL_CONTINUE_PROMPT
try:
result = await self.runner.run(AgentRunSpec(
initial_messages=initial_messages,
@@ -781,7 +769,7 @@ class AgentLoop:
hook=hook,
error_message="Sorry, I encountered an error calling the AI model.",
concurrent_tools=True,
workspace=effective_scope.project_path,
workspace=self.workspace,
session_key=session.key if session else None,
context_window_tokens=self.context_window_tokens,
context_block_limit=self.context_block_limit,
@@ -798,12 +786,8 @@ class AgentLoop:
session.key if session is not None else session_key,
metadata=(session.metadata if session is not None else None),
),
goal_active_predicate=lambda: sustained_goal_active(session.metadata) if session is not None else False,
goal_continue_message=_goal_continue,
))
finally:
reset_workspace_scope(workspace_token)
reset_request_context(request_token)
reset_file_states(file_state_token)
self._last_usage = result.usage
if result.stop_reason == "max_iterations":
@@ -843,15 +827,13 @@ class AgentLoop:
continue
raw = msg.content.strip()
effective_key = self._effective_session_key(msg)
if await agent_context.handle_runtime_control(self, msg, self.tools):
continue
if self.commands.is_priority(raw):
await self._dispatch_command_inline(
msg, effective_key, raw,
msg, msg.session_key, raw,
self.commands.dispatch_priority,
)
continue
effective_key = self._effective_session_key(msg)
# If this session already has an active pending queue (i.e. a task
# is processing this session), route the message there for mid-turn
# injection instead of creating a competing task.
@@ -902,13 +884,13 @@ class AgentLoop:
lock = self._session_locks.setdefault(session_key, asyncio.Lock())
gate = self._concurrency_gate or nullcontext()
pending: asyncio.Queue | None = None
# Register a pending queue so follow-up messages for this session are
# routed here (mid-turn injection) instead of spawning a new task.
pending = asyncio.Queue(maxsize=20)
self._pending_queues[session_key] = pending
try:
async with lock, gate:
# Only the task that owns the session lock may publish the
# active mid-turn injection queue for this session.
pending = asyncio.Queue(maxsize=20)
self._pending_queues[session_key] = pending
try:
on_stream = on_stream_end = None
if msg.metadata.get("_wants_stream"):
@@ -992,39 +974,28 @@ class AgentLoop:
channel=msg.channel, chat_id=msg.chat_id,
content="Sorry, I encountered an error.",
))
finally:
# Drain any messages still in the pending queue and re-publish
# them to the bus so they are processed as fresh inbound messages
# rather than silently lost. Only remove our own queue; a
# later task waiting on the lock must not be able to steal
# cleanup ownership.
queue = None
if self._pending_queues.get(session_key) is pending:
queue = self._pending_queues.pop(session_key, None)
else:
queue = pending
if queue is not None:
leftover = 0
while True:
try:
item = queue.get_nowait()
except asyncio.QueueEmpty:
break
await self.bus.publish_inbound(item)
leftover += 1
if leftover:
logger.info(
"Re-published {} leftover message(s) to bus for session {}",
leftover, session_key,
)
await self._webui_turns.publish_run_status(msg, "idle")
self._pending_turn_latency_ms.pop(session_key, None)
self._webui_turns.discard(session_key)
finally:
if pending is None:
await self._webui_turns.publish_run_status(msg, "idle")
self._pending_turn_latency_ms.pop(session_key, None)
self._webui_turns.discard(session_key)
# Drain any messages still in the pending queue and re-publish
# them to the bus so they are processed as fresh inbound messages
# rather than silently lost.
queue = self._pending_queues.pop(session_key, None)
if queue is not None:
leftover = 0
while True:
try:
item = queue.get_nowait()
except asyncio.QueueEmpty:
break
await self.bus.publish_inbound(item)
leftover += 1
if leftover:
logger.info(
"Re-published {} leftover message(s) to bus for session {}",
leftover, session_key,
)
await self._webui_turns.publish_run_status(msg, "idle")
self._pending_turn_latency_ms.pop(session_key, None)
self._webui_turns.discard(session_key)
async def close_mcp(self) -> None:
"""Drain pending background archives, then close MCP connections."""
@@ -1093,7 +1064,6 @@ class AgentLoop:
}
history = session.get_history(**_hist_kwargs)
current_role = "assistant" if is_subagent else "user"
workspace_scope = self.workspace_scopes.for_message(msg, session.metadata)
messages = self.context.build_messages(
history=history,
@@ -1104,10 +1074,9 @@ class AgentLoop:
sender_id=msg.sender_id,
session_summary=pending,
session_metadata=session.metadata,
workspace=workspace_scope.project_path,
runtime_state=self,
inbound_message=msg,
skip_runtime_lines=is_subagent,
supports_vision=self._supports_vision,
supports_audio=self._supports_audio,
supports_video=self._supports_video,
)
t_wall = time.time()
final_content, _, all_msgs, stop_reason, _ = await self._run_agent_loop(
@@ -1271,7 +1240,7 @@ class AgentLoop:
msg = ctx.msg
if msg.media:
new_content, image_only = self._prepare_message_media(msg.content, msg.media)
new_content, image_only = extract_documents(msg.content, msg.media)
ctx.msg = dataclasses.replace(msg, content=new_content, media=image_only)
msg = ctx.msg
@@ -1283,7 +1252,6 @@ class AgentLoop:
if ctx.session is None:
ctx.session = self.sessions.get_or_create(ctx.session_key)
mark_webui_session(ctx.session, msg.metadata)
self.workspace_scopes.persist_message_scope(ctx.session, msg)
if self._restore_runtime_checkpoint(ctx.session):
self.sessions.save(ctx.session)
@@ -1292,16 +1260,6 @@ class AgentLoop:
return "ok"
def _prepare_message_media(self, content: str, media: list[str]) -> tuple[str, list[str]]:
if self._should_extract_document_text():
return extract_documents(content, media)
return reference_non_image_attachments(content, media)
def _should_extract_document_text(self) -> bool:
if self.channels_config is None:
return True
return self.channels_config.extract_document_text
async def _state_compact(self, ctx: TurnContext) -> str:
ctx.session, pending = self.auto_compact.prepare_session(ctx.session, ctx.session_key)
ctx.pending_summary = pending
@@ -1361,10 +1319,7 @@ class AgentLoop:
)
ctx.initial_messages = self._build_initial_messages(
ctx.msg,
ctx.session,
ctx.history,
ctx.pending_summary,
ctx.msg, ctx.session, ctx.history, ctx.pending_summary
)
ctx.user_persisted_early = self._persist_user_message_early(
ctx.msg, ctx.session
@@ -1467,6 +1422,10 @@ class AgentLoop:
filtered.append({"type": "text", "text": image_placeholder_text(path)})
continue
if block.get("type") in ("input_audio", "video_url"):
filtered.append(LLMProvider._media_placeholder(block["type"], block))
continue
if block.get("type") == "text" and isinstance(block.get("text"), str):
text = block["text"]
if should_truncate_text and len(text) > self.max_tool_result_chars:
@@ -1667,19 +1626,10 @@ class AgentLoop:
channel=channel, sender_id="user", chat_id=chat_id,
content=content, media=media or [],
)
# Share the dispatch lock so direct calls serialize with bus turns.
lock = self._session_locks.setdefault(session_key, asyncio.Lock())
try:
async with lock:
return await self._process_message(
msg,
session_key=session_key,
on_progress=on_progress,
on_stream=on_stream,
on_stream_end=on_stream_end,
)
finally:
if channel == "websocket":
await self._webui_turns.publish_run_status(msg, "idle")
self._pending_turn_latency_ms.pop(session_key, None)
self._webui_turns.discard(session_key)
return await self._process_message(
msg,
session_key=session_key,
on_progress=on_progress,
on_stream=on_stream,
on_stream_end=on_stream_end,
)
+25 -65
View File
@@ -8,7 +8,7 @@ import os
from contextlib import suppress
from dataclasses import dataclass, field
from pathlib import Path
from typing import Any, Callable
from typing import Any
from loguru import logger
@@ -16,14 +16,11 @@ from nanobot.agent.hook import AgentHook, AgentHookContext
from nanobot.agent.tools.registry import ToolRegistry
from nanobot.providers.base import LLMProvider, LLMResponse, ToolCallRequest
from nanobot.utils.file_edit_events import (
StreamingFileEditTracker,
build_file_edit_end_event,
build_file_edit_error_event,
build_file_edit_start_event,
prepare_file_edit_trackers,
)
from nanobot.utils.file_edit_events import (
prepare_file_edit_tracker as _prepare_file_edit_tracker,
prepare_file_edit_tracker,
StreamingFileEditTracker,
)
from nanobot.utils.helpers import (
IncrementalThinkExtractor,
@@ -44,7 +41,6 @@ from nanobot.utils.prompt_templates import render_template
from nanobot.utils.runtime import (
EMPTY_FINAL_RESPONSE_MESSAGE,
build_finalization_retry_message,
build_goal_continue_message,
build_length_recovery_message,
ensure_nonempty_tool_result,
is_blank_text,
@@ -53,10 +49,6 @@ from nanobot.utils.runtime import (
)
_DEFAULT_ERROR_MESSAGE = "Sorry, I encountered an error calling the AI model."
_ARREARAGE_ERROR_MESSAGE = (
"The AI provider rejected the request because the API key is out of quota or the "
"account is in arrears. Please top up / check the billing status of your API key and try again."
)
_PERSISTED_MODEL_ERROR_PLACEHOLDER = "[Assistant reply unavailable due to model error.]"
_MAX_EMPTY_RETRIES = 2
_MAX_LENGTH_RECOVERIES = 3
@@ -66,14 +58,11 @@ _SNIP_SAFETY_BUFFER = 1024
_MICROCOMPACT_KEEP_RECENT = 10
_MICROCOMPACT_MIN_CHARS = 500
_COMPACTABLE_TOOLS = frozenset({
"read_file", "exec", "grep", "find_files",
"web_search", "web_fetch", "list_dir", "list_exec_sessions",
"read_file", "exec", "grep",
"web_search", "web_fetch", "list_dir",
})
_BACKFILL_CONTENT = "[Tool result unavailable — call was interrupted or lost]"
# Backward-compatible module attribute for tests/extensions that monkeypatch
# the former single-file tracker hook. Runtime uses prepare_file_edit_trackers.
prepare_file_edit_tracker = _prepare_file_edit_tracker
@dataclass(slots=True)
@@ -104,8 +93,6 @@ class AgentRunSpec:
checkpoint_callback: Any | None = None
injection_callback: Any | None = None
llm_timeout_s: float | None = None
goal_active_predicate: Callable[[], bool] | None = None
goal_continue_message: str | None = None
@dataclass(slots=True)
@@ -176,7 +163,6 @@ class AgentRunner:
*,
phase: str = "after error",
iteration: int | None = None,
allow_goal_continue: bool = False,
) -> tuple[bool, int]:
"""Drain pending injections. Returns (should_continue, updated_cycles).
@@ -185,19 +171,12 @@ class AgentRunner:
and *iteration* are both provided) and return (True, cycles+1) so the
caller continues the iteration loop. Otherwise return (False, cycles).
"""
injections: list[dict[str, Any]] = []
real_injection = False
if injection_cycles < _MAX_INJECTION_CYCLES:
injections = await self._drain_injections(spec)
real_injection = bool(injections)
if not injections and allow_goal_continue and assistant_message is not None:
predicate = spec.goal_active_predicate
if predicate is not None and predicate():
injections = [build_goal_continue_message(spec.goal_continue_message)]
if injection_cycles >= _MAX_INJECTION_CYCLES:
return False, injection_cycles
injections = await self._drain_injections(spec)
if not injections:
return False, injection_cycles
if real_injection:
injection_cycles += 1
injection_cycles += 1
if assistant_message is not None:
messages.append(assistant_message)
if iteration is not None:
@@ -213,13 +192,10 @@ class AgentRunner:
},
)
self._append_injected_messages(messages, injections)
if real_injection:
logger.info(
"Injected {} follow-up message(s) {} ({}/{})",
len(injections), phase, injection_cycles, _MAX_INJECTION_CYCLES,
)
else:
logger.info("Injected sustained-goal continuation {}", phase)
logger.info(
"Injected {} follow-up message(s) {} ({}/{})",
len(injections), phase, injection_cycles, _MAX_INJECTION_CYCLES,
)
return True, injection_cycles
async def _drain_injections(self, spec: AgentRunSpec) -> list[dict[str, Any]]:
@@ -495,7 +471,6 @@ class AgentRunner:
spec, messages, assistant_message, injection_cycles,
phase="after final response",
iteration=iteration,
allow_goal_continue=True,
)
if should_continue:
had_injections = True
@@ -508,10 +483,7 @@ class AgentRunner:
continue
if response.finish_reason == "error":
if LLMProvider.is_arrearage_response(response):
final_content = _ARREARAGE_ERROR_MESSAGE
else:
final_content = clean or spec.error_message or _DEFAULT_ERROR_MESSAGE
final_content = clean or spec.error_message or _DEFAULT_ERROR_MESSAGE
stop_reason = "error"
error = final_content
self._append_model_error_placeholder(messages)
@@ -885,8 +857,8 @@ class AgentRunner:
and on_progress_accepts_file_edit_events(spec.progress_callback)
)
progress_callback = spec.progress_callback if emit_file_edit_events else None
file_edit_trackers = (
prepare_file_edit_trackers(
file_edit_tracker = (
prepare_file_edit_tracker(
call_id=tool_call.id,
tool_name=tool_call.name,
tool=tool,
@@ -896,13 +868,13 @@ class AgentRunner:
if progress_callback is not None
else None
)
if file_edit_trackers and progress_callback is not None:
if file_edit_tracker is not None and progress_callback is not None:
await invoke_file_edit_progress(
progress_callback,
[build_file_edit_start_event(
file_edit_tracker,
params if isinstance(params, dict) else None,
) for file_edit_tracker in file_edit_trackers],
)],
)
try:
if tool is not None:
@@ -912,13 +884,10 @@ class AgentRunner:
except asyncio.CancelledError:
raise
except BaseException as exc:
if file_edit_trackers and progress_callback is not None:
if file_edit_tracker is not None and progress_callback is not None:
await invoke_file_edit_progress(
progress_callback,
[
build_file_edit_error_event(file_edit_tracker, str(exc))
for file_edit_tracker in file_edit_trackers
],
[build_file_edit_error_event(file_edit_tracker, str(exc))],
)
event = {
"name": tool_call.name,
@@ -941,13 +910,10 @@ class AgentRunner:
return payload, event, None
if isinstance(result, str) and result.startswith("Error"):
if file_edit_trackers and progress_callback is not None:
if file_edit_tracker is not None and progress_callback is not None:
await invoke_file_edit_progress(
progress_callback,
[
build_file_edit_error_event(file_edit_tracker, result)
for file_edit_tracker in file_edit_trackers
],
[build_file_edit_error_event(file_edit_tracker, result)],
)
event = {
"name": tool_call.name,
@@ -967,13 +933,13 @@ class AgentRunner:
return result + hint, event, RuntimeError(result)
return result + hint, event, None
if file_edit_trackers and progress_callback is not None:
if file_edit_tracker is not None and progress_callback is not None:
await invoke_file_edit_progress(
progress_callback,
[build_file_edit_end_event(
file_edit_tracker,
params if isinstance(params, dict) else None,
) for file_edit_tracker in file_edit_trackers],
)],
)
detail = "" if result is None else str(result)
@@ -1280,13 +1246,7 @@ class AgentRunner:
return messages
system_tokens = sum(estimate_message_tokens(msg) for msg in system_messages)
fixed_tokens, _ = estimate_prompt_tokens_chain(
self.provider,
spec.model,
system_messages,
spec.tools.get_definitions(),
)
remaining_budget = max(0, budget - max(system_tokens, fixed_tokens))
remaining_budget = max(128, budget - system_tokens)
kept: list[dict[str, Any]] = []
kept_tokens = 0
for message in reversed(non_system):
+21 -62
View File
@@ -16,12 +16,6 @@ from nanobot.agent.tools.context import ToolContext
from nanobot.agent.tools.file_state import FileStates
from nanobot.agent.tools.loader import ToolLoader
from nanobot.agent.tools.registry import ToolRegistry
from nanobot.security.workspace_access import (
WorkspaceScope,
bind_workspace_scope,
reset_workspace_scope,
workspace_sandbox_status,
)
from nanobot.bus.events import InboundMessage
from nanobot.bus.queue import MessageBus
from nanobot.config.schema import AgentDefaults, ToolsConfig
@@ -85,7 +79,6 @@ class SubagentManager:
restrict_to_workspace: bool = False,
disabled_skills: list[str] | None = None,
max_iterations: int | None = None,
max_concurrent_subagents: int | None = None,
llm_wall_timeout_for_session: Callable[[str | None], float | None] | None = None,
):
defaults = AgentDefaults()
@@ -102,11 +95,7 @@ class SubagentManager:
if max_iterations is not None
else defaults.max_tool_iterations
)
self.max_concurrent_subagents = (
max_concurrent_subagents
if max_concurrent_subagents is not None
else defaults.max_concurrent_subagents
)
self.max_concurrent_subagents = defaults.max_concurrent_subagents
self.runner = AgentRunner(provider)
self._llm_wall_timeout_for_session = llm_wall_timeout_for_session
self._running_tasks: dict[str, asyncio.Task[None]] = {}
@@ -134,10 +123,6 @@ class SubagentManager:
config=cfg,
workspace=str(root.resolve()),
file_state_store=FileStates(),
workspace_sandbox=workspace_sandbox_status(
restrict_to_workspace=cfg.restrict_to_workspace,
workspace=root,
),
)
ToolLoader().load(ctx, registry, scope="subagent")
return registry
@@ -155,8 +140,6 @@ class SubagentManager:
origin_chat_id: str = "direct",
session_key: str | None = None,
origin_message_id: str | None = None,
temperature: float | None = None,
workspace_scope: WorkspaceScope | None = None,
) -> str:
"""Spawn a subagent to execute a task in the background."""
task_id = str(uuid.uuid4())[:8]
@@ -172,16 +155,7 @@ class SubagentManager:
self._task_statuses[task_id] = status
bg_task = asyncio.create_task(
self._run_subagent(
task_id,
task,
display_label,
origin,
status,
origin_message_id,
temperature,
workspace_scope,
)
self._run_subagent(task_id, task, display_label, origin, status, origin_message_id)
)
self._running_tasks[task_id] = bg_task
if session_key:
@@ -208,8 +182,6 @@ class SubagentManager:
origin: dict[str, str],
status: SubagentStatus,
origin_message_id: str | None = None,
temperature: float | None = None,
workspace_scope: WorkspaceScope | None = None,
) -> None:
"""Execute the subagent task and announce the result."""
logger.info("Subagent [{}] starting task: {}", task_id, label)
@@ -219,13 +191,8 @@ class SubagentManager:
status.iteration = payload.get("iteration", status.iteration)
try:
root = workspace_scope.project_path if workspace_scope is not None else self.workspace
cfg = None
if workspace_scope is not None:
cfg = self._subagent_tools_config()
cfg.restrict_to_workspace = workspace_scope.restrict_to_workspace
tools = self._build_tools(workspace=root, tools_config=cfg)
system_prompt = self._build_subagent_prompt(workspace=root)
tools = self._build_tools()
system_prompt = self._build_subagent_prompt()
messages: list[dict[str, Any]] = [
{"role": "system", "content": system_prompt},
{"role": "user", "content": task},
@@ -237,27 +204,20 @@ class SubagentManager:
if self._llm_wall_timeout_for_session
else None
)
token = bind_workspace_scope(workspace_scope) if workspace_scope is not None else None
try:
result = await self.runner.run(AgentRunSpec(
initial_messages=messages,
tools=tools,
model=self.model,
temperature=temperature,
max_iterations=self.max_iterations,
max_tool_result_chars=self.max_tool_result_chars,
hook=_SubagentHook(task_id, status),
max_iterations_message="Task completed but no final response was generated.",
error_message=None,
fail_on_tool_error=True,
checkpoint_callback=_on_checkpoint,
session_key=sess_key,
workspace=root,
llm_timeout_s=llm_timeout,
))
finally:
if token is not None:
reset_workspace_scope(token)
result = await self.runner.run(AgentRunSpec(
initial_messages=messages,
tools=tools,
model=self.model,
max_iterations=self.max_iterations,
max_tool_result_chars=self.max_tool_result_chars,
hook=_SubagentHook(task_id, status),
max_iterations_message="Task completed but no final response was generated.",
error_message=None,
fail_on_tool_error=True,
checkpoint_callback=_on_checkpoint,
session_key=sess_key,
llm_timeout_s=llm_timeout,
))
status.phase = "done"
status.stop_reason = result.stop_reason
@@ -351,21 +311,20 @@ class SubagentManager:
lines.append(f"- {result.error}")
return "\n".join(lines) or (result.error or "Error: subagent execution failed.")
def _build_subagent_prompt(self, workspace: Path | None = None) -> str:
def _build_subagent_prompt(self) -> str:
"""Build a focused system prompt for the subagent."""
from nanobot.agent.context import ContextBuilder
from nanobot.agent.skills import SkillsLoader
time_ctx = ContextBuilder._build_runtime_context(None, None)
root = workspace or self.workspace
skills_summary = SkillsLoader(
root,
self.workspace,
disabled_skills=self.disabled_skills,
).build_skills_summary()
return render_template(
"agent/subagent_system.md",
time_ctx=time_ctx,
workspace=str(root),
workspace=str(self.workspace),
skills_summary=skills_summary or "",
)
-290
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@@ -1,290 +0,0 @@
"""Apply file edits by providing structured edit instructions."""
from __future__ import annotations
import difflib
import re
from dataclasses import dataclass
from pathlib import Path
from typing import Any
from nanobot.agent.tools.base import tool_parameters
from nanobot.agent.tools.filesystem import _FsTool
from nanobot.agent.tools.schema import (
ArraySchema,
BooleanSchema,
ObjectSchema,
StringSchema,
tool_parameters_schema,
)
@dataclass(slots=True)
class _PatchSummary:
action: str
path: str
added: int = 0
deleted: int = 0
class _PatchError(ValueError):
pass
_ABSOLUTE_WINDOWS_RE = re.compile(r"^[A-Za-z]:[\\/]")
def _validate_relative_path(path: str) -> str:
normalized = path.strip()
if not normalized:
raise _PatchError("patch path cannot be empty")
if "\0" in normalized:
raise _PatchError(f"patch path contains a null byte: {path!r}")
if normalized.startswith(("~", "/", "\\")) or _ABSOLUTE_WINDOWS_RE.match(normalized):
raise _PatchError(f"patch path must be relative: {path}")
if any(part == ".." for part in re.split(r"[\\/]+", normalized)):
raise _PatchError(f"patch path must not contain '..': {path}")
return normalized
def _lines_to_text(lines: list[str]) -> str:
if not lines:
return ""
return "\n".join(lines) + "\n"
def _text_line_count(text: str) -> int:
if not text:
return 0
return len(text.splitlines())
def _line_diff_stats(before: str, after: str) -> tuple[int, int]:
before_lines = before.replace("\r\n", "\n").splitlines()
after_lines = after.replace("\r\n", "\n").splitlines()
added = 0
deleted = 0
matcher = difflib.SequenceMatcher(a=before_lines, b=after_lines, autojunk=False)
for tag, i1, i2, j1, j2 in matcher.get_opcodes():
if tag == "equal":
continue
if tag in ("replace", "delete"):
deleted += i2 - i1
if tag in ("replace", "insert"):
added += j2 - j1
return added, deleted
def _format_summary(summary: _PatchSummary) -> str:
stats = ""
if summary.added or summary.deleted:
stats = f" (+{summary.added}/-{summary.deleted})"
return f"- {summary.action} {summary.path}{stats}"
@tool_parameters(
tool_parameters_schema(
edits=ArraySchema(
items=ObjectSchema(
path=StringSchema("Relative path to the file to edit."),
action=StringSchema(
"Operation type: replace or add.",
enum=["replace", "add"],
),
old_text=StringSchema(
"Exact text to search for in the file. Required for replace.",
nullable=True,
),
new_text=StringSchema(
"Text to replace with or append. Required for replace and add.",
nullable=True,
),
required=["path", "action"],
),
description="List of edits to apply. Each edit specifies a file and the change to make.",
min_items=1,
max_items=20,
),
dry_run=BooleanSchema(
description="Validate and summarize the patch without writing files.",
default=False,
),
required=["edits"],
)
)
class ApplyPatchTool(_FsTool):
"""Apply file edits by providing structured edit instructions."""
_scopes = {"core", "subagent"}
@property
def name(self) -> str:
return "apply_patch"
@property
def description(self) -> str:
return (
"Default tool for code edits. Supports multi-file changes in a single call. "
"Provide a list of structured edits, each specifying a file path, action "
"(replace/add), and the exact text to change. "
"Paths must be relative. Set dry_run=true to validate and preview without writing files. "
"Use edit_file only for small exact replacements on a single file."
)
async def execute(
self,
edits: list[dict] | None = None,
dry_run: bool = False,
**kwargs: Any,
) -> str:
try:
if not edits:
raise _PatchError("must provide edits")
writes: dict[Path, str] = {}
summaries: list[_PatchSummary] = []
for edit in edits:
if not isinstance(edit, dict):
raise _PatchError("each edit must be an object")
raw_path = edit.get("path")
if not isinstance(raw_path, str):
raise _PatchError("path required for edit")
path = _validate_relative_path(raw_path)
action = edit.get("action")
if not isinstance(action, str):
raise _PatchError(f"action required for edit: {path}")
source = self._resolve(path)
if action == "add":
new_text = edit.get("new_text")
if new_text is None:
raise _PatchError(f"new_text required for add: {path}")
pending = writes.get(source)
if pending is not None:
content = pending
exists = True
elif source.exists():
raw = source.read_bytes()
try:
content = raw.decode("utf-8")
except UnicodeDecodeError:
raise _PatchError(f"file is not UTF-8 text: {path}")
exists = True
else:
content = ""
exists = False
if exists:
uses_crlf = "\r\n" in content
new_norm = content.replace("\r\n", "\n") + new_text.replace("\r\n", "\n")
if new_norm and not new_norm.endswith("\n"):
new_norm += "\n"
if uses_crlf:
new_norm = new_norm.replace("\n", "\r\n")
writes[source] = new_norm
added, deleted = _line_diff_stats(content, new_norm)
action_name = "update"
else:
new_norm = new_text.replace("\r\n", "\n")
if new_norm and not new_norm.endswith("\n"):
new_norm += "\n"
writes[source] = new_norm
added = _text_line_count(new_norm)
deleted = 0
action_name = "add"
summaries.append(
_PatchSummary(
action=action_name, path=path, added=added, deleted=deleted
)
)
elif action == "replace":
old_text = edit.get("old_text") or ""
if not old_text:
raise _PatchError(f"old_text required for replace: {path}")
new_text = edit.get("new_text")
if new_text is None:
raise _PatchError(f"new_text required for replace: {path}")
pending = writes.get(source)
if pending is not None:
content = pending
elif source.exists():
raw = source.read_bytes()
try:
content = raw.decode("utf-8")
except UnicodeDecodeError:
raise _PatchError(f"file is not UTF-8 text: {path}")
else:
raise _PatchError(f"file to update does not exist: {path}")
if pending is None and not source.is_file():
raise _PatchError(f"path to update is not a file: {path}")
uses_crlf = "\r\n" in content
norm_content = content.replace("\r\n", "\n")
norm_old = old_text.replace("\r\n", "\n")
pos = norm_content.find(norm_old)
if pos < 0:
raise _PatchError(f"old_text not found in {path}")
if norm_content.find(norm_old, pos + 1) >= 0:
raise _PatchError(f"old_text appears multiple times in {path}")
new_norm = (
norm_content[:pos]
+ new_text.replace("\r\n", "\n")
+ norm_content[pos + len(norm_old) :]
)
if new_norm and not new_norm.endswith("\n"):
new_norm += "\n"
if uses_crlf:
new_norm = new_norm.replace("\n", "\r\n")
writes[source] = new_norm
added, deleted = _line_diff_stats(content, new_norm)
summaries.append(
_PatchSummary(
action="update", path=path, added=added, deleted=deleted
)
)
else:
raise _PatchError(f"unknown action: {action}")
if dry_run:
return "Patch dry-run succeeded:\n" + "\n".join(
_format_summary(summary) for summary in summaries
)
backups: dict[Path, bytes | None] = {}
for path in writes:
backups[path] = path.read_bytes() if path.exists() else None
try:
for path, content in writes.items():
path.parent.mkdir(parents=True, exist_ok=True)
path.write_text(content, encoding="utf-8", newline="")
except Exception:
for path, data in backups.items():
if data is None:
if path.exists():
path.unlink()
else:
path.parent.mkdir(parents=True, exist_ok=True)
path.write_bytes(data)
raise
for path in writes:
self._file_states.record_write(path)
return "Patch applied:\n" + "\n".join(
_format_summary(summary) for summary in summaries
)
except PermissionError as exc:
return f"Error: {exc}"
except _PatchError as exc:
return f"Error applying patch: {exc}"
except Exception as exc:
return f"Error applying patch: {exc}"
-133
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@@ -1,133 +0,0 @@
"""Controlled runner for installed CLI Apps."""
from __future__ import annotations
from pathlib import Path
from typing import Any
from pydantic import Field
from nanobot.agent.tools.base import Tool, tool_parameters
from nanobot.agent.tools.schema import ArraySchema, BooleanSchema, IntegerSchema, StringSchema, tool_parameters_schema
from nanobot.security.workspace_access import current_tool_workspace
from nanobot.apps.cli import CliAppError, CliAppManager, CliAppsRuntimeConfig
from nanobot.config.schema import Base
class CliAppsToolConfig(Base):
"""CLI Apps tool configuration."""
enable: bool = True
install_timeout: int = Field(default=300, ge=1, le=3600)
run_timeout: int = Field(default=60, ge=1, le=600)
catalog_ttl_seconds: int = Field(default=3600, ge=60, le=86_400)
@tool_parameters(
tool_parameters_schema(
required=["name"],
name=StringSchema("Installed CLI app registry name, for example gimp, safari, or obsidian."),
args=ArraySchema(
StringSchema("One command-line argument."),
description="Arguments to pass to the CLI entry point. Do not include the entry point itself.",
nullable=True,
),
json=BooleanSchema(
description="Whether to prepend --json when supported by the CLI.",
default=False,
nullable=True,
),
working_dir=StringSchema("Optional working directory for the CLI call.", nullable=True),
timeout=IntegerSchema(
description="Timeout in seconds for this CLI call.",
minimum=1,
maximum=600,
nullable=True,
),
)
)
class CliAppsTool(Tool):
"""Run an installed CLI-Anything or public CLI app through a controlled argv subprocess."""
config_key = "cli_apps"
_scopes = {"core", "subagent"}
@classmethod
def config_cls(cls):
return CliAppsToolConfig
@classmethod
def enabled(cls, ctx: Any) -> bool:
return ctx.config.cli_apps.enable
@classmethod
def create(cls, ctx: Any) -> Tool:
cfg = ctx.config.cli_apps
return cls(
workspace=Path(ctx.workspace),
restrict_to_workspace=ctx.config.restrict_to_workspace,
runtime=CliAppsRuntimeConfig(
install_timeout=cfg.install_timeout,
run_timeout=cfg.run_timeout,
catalog_ttl_seconds=cfg.catalog_ttl_seconds,
),
)
def __init__(
self,
*,
workspace: Path,
restrict_to_workspace: bool = False,
runtime: CliAppsRuntimeConfig | None = None,
) -> None:
self.workspace = workspace
self.restrict_to_workspace = restrict_to_workspace
self.runtime = runtime or CliAppsRuntimeConfig()
@property
def name(self) -> str:
return "run_cli_app"
@property
def description(self) -> str:
try:
installed = CliAppManager(workspace=self.workspace, runtime=self.runtime).installed_names()
except Exception:
installed = []
installed_note = (
f" Installed Settings CLI Apps: {', '.join(installed)}."
if installed
else " No Settings CLI Apps are currently installed."
)
return (
"Run a CLI App that the user explicitly installed in Settings or attached as @app. "
"Do not use this for ordinary system CLIs such as git, gh, python, npm, or brew; "
"unknown names are rejected. Execution uses argv, not shell."
+ installed_note
)
async def execute(
self,
name: str,
args: list[str] | None = None,
json: bool | None = False,
working_dir: str | None = None,
timeout: int | None = None,
) -> str:
access = current_tool_workspace(
self.workspace,
restrict_to_workspace=self.restrict_to_workspace,
)
workspace = access.project_path or self.workspace
manager = CliAppManager(workspace=workspace, runtime=self.runtime)
try:
return manager.run(
name,
args=args or [],
json_output=bool(json),
working_dir=working_dir,
timeout=timeout,
restrict_to_workspace=access.restrict_to_workspace,
)
except CliAppError as exc:
return f"Error: {exc.message}"
-24
View File
@@ -1,15 +1,9 @@
"""Runtime context for tool construction."""
from __future__ import annotations
from contextvars import ContextVar, Token
from dataclasses import dataclass, field
from typing import Any, Callable, Protocol, runtime_checkable
_CURRENT_REQUEST_CONTEXT: ContextVar["RequestContext | None"] = ContextVar(
"nanobot_tool_request_context",
default=None,
)
@dataclass(frozen=True)
class RequestContext:
@@ -27,23 +21,6 @@ class ContextAware(Protocol):
...
def bind_request_context(ctx: RequestContext) -> Token[RequestContext | None]:
return _CURRENT_REQUEST_CONTEXT.set(ctx)
def reset_request_context(token: Token[RequestContext | None]) -> None:
_CURRENT_REQUEST_CONTEXT.reset(token)
def current_request_context() -> RequestContext | None:
return _CURRENT_REQUEST_CONTEXT.get()
def current_request_session_key() -> str | None:
ctx = current_request_context()
return ctx.session_key if ctx else None
@dataclass
class ToolContext:
config: Any
@@ -56,4 +33,3 @@ class ToolContext:
provider_snapshot_loader: Callable[[], Any] | None = None
image_generation_provider_configs: dict[str, Any] | None = None
timezone: str = "UTC"
workspace_sandbox: Any | None = None
-598
View File
@@ -1,598 +0,0 @@
"""Session support for long-running exec workflows."""
from __future__ import annotations
import asyncio
import time
import uuid
from contextlib import suppress
from dataclasses import dataclass
from typing import Any
from nanobot.agent.tools.base import Tool, tool_parameters
from nanobot.agent.tools.context import current_request_session_key
from nanobot.agent.tools.schema import (
BooleanSchema,
IntegerSchema,
StringSchema,
tool_parameters_schema,
)
DEFAULT_YIELD_MS = 1000
MAX_YIELD_MS = 30_000
DEFAULT_WAIT_FOR_MS = 10_000
MAX_WAIT_FOR_MS = 120_000
DEFAULT_MAX_OUTPUT_CHARS = 10_000
MAX_OUTPUT_CHARS = 50_000
@dataclass(slots=True)
class _SessionPoll:
output: str
done: bool
exit_code: int | None
elapsed_s: float = 0.0
timed_out: bool = False
terminated: bool = False
stdin_closed: bool = False
truncated_chars: int = 0
@dataclass(slots=True)
class ExecSessionInfo:
session_id: str
command: str
cwd: str
elapsed_s: float
idle_s: float
remaining_s: float
returncode: int | None
owner_session_key: str | None = None
class _ExecSession:
def __init__(
self,
*,
session_id: str,
process: asyncio.subprocess.Process,
command: str,
cwd: str,
timeout: int | None,
owner_session_key: str | None = None,
) -> None:
self.session_id = session_id
self.process = process
self.command = command
self.cwd = cwd
self.owner_session_key = owner_session_key
self.started_at = time.monotonic()
# timeout None/0 means no limit; an infinite deadline is never reached.
self.deadline = time.monotonic() + timeout if timeout else float("inf")
self.last_access = time.monotonic()
self._chunks: list[str] = []
self._lock = asyncio.Lock()
self._timed_out = False
self._stdout_task = asyncio.create_task(self._read_stream(process.stdout, ""))
self._stderr_task = asyncio.create_task(self._read_stream(process.stderr, "STDERR:\n"))
async def _read_stream(
self,
stream: asyncio.StreamReader | None,
prefix: str,
) -> None:
if stream is None:
return
first = True
while True:
chunk = await stream.read(4096)
if not chunk:
break
text = chunk.decode("utf-8", errors="replace")
if prefix and first:
text = prefix + text
first = False
async with self._lock:
self._chunks.append(text)
async def write(self, chars: str) -> str | None:
if self.process.returncode is not None:
return "session has already exited"
if self.process.stdin is None:
return "session stdin is not available"
try:
self.process.stdin.write(chars.encode("utf-8"))
await self.process.stdin.drain()
except (BrokenPipeError, ConnectionResetError):
return "session stdin is closed"
return None
async def close_stdin(self) -> str | None:
if self.process.returncode is not None:
return "session has already exited"
if self.process.stdin is None:
return "session stdin is not available"
self.process.stdin.close()
with suppress(BrokenPipeError, ConnectionResetError):
await self.process.stdin.wait_closed()
return None
async def poll(
self,
yield_time_ms: int,
max_output_chars: int,
*,
terminated: bool = False,
stdin_closed: bool = False,
) -> _SessionPoll:
self.last_access = time.monotonic()
if yield_time_ms > 0 and self.process.returncode is None:
await asyncio.sleep(min(yield_time_ms, MAX_YIELD_MS) / 1000)
if self.process.returncode is None and time.monotonic() >= self.deadline:
self._timed_out = True
await self.kill()
if self.process.returncode is not None:
with suppress(asyncio.TimeoutError):
await asyncio.wait_for(
asyncio.gather(self._stdout_task, self._stderr_task),
timeout=2.0,
)
async with self._lock:
output = "".join(self._chunks)
self._chunks.clear()
output, truncated = _truncate_output(output, max_output_chars)
return _SessionPoll(
output=output,
done=self.process.returncode is not None,
exit_code=self.process.returncode,
elapsed_s=max(0.0, time.monotonic() - self.started_at),
timed_out=self._timed_out,
terminated=terminated,
stdin_closed=stdin_closed,
truncated_chars=truncated,
)
async def kill(self) -> None:
if self.process.returncode is not None:
return
self.process.kill()
with suppress(asyncio.TimeoutError):
await asyncio.wait_for(self.process.wait(), timeout=5.0)
class ExecSessionManager:
def __init__(self, *, max_sessions: int = 8, idle_timeout: int = 1800) -> None:
self.max_sessions = max_sessions
self.idle_timeout = idle_timeout
self._sessions: dict[str, _ExecSession] = {}
self._lock = asyncio.Lock()
async def start(
self,
*,
command: str,
cwd: str,
env: dict[str, str],
timeout: int | None,
shell_program: str | None,
login: bool,
yield_time_ms: int,
max_output_chars: int,
owner_session_key: str | None = None,
) -> tuple[str, _SessionPoll]:
async with self._lock:
await self._cleanup_locked()
if len(self._sessions) >= self.max_sessions:
raise RuntimeError(f"maximum exec sessions reached ({self.max_sessions})")
process = await self._spawn(command, cwd, env, shell_program, login)
session_id = uuid.uuid4().hex[:12]
session = _ExecSession(
session_id=session_id,
process=process,
command=command,
cwd=cwd,
timeout=timeout,
owner_session_key=owner_session_key,
)
self._sessions[session_id] = session
poll = await session.poll(yield_time_ms, max_output_chars)
if poll.done:
async with self._lock:
self._sessions.pop(session_id, None)
return session_id, poll
async def write(
self,
*,
session_id: str,
chars: str | None,
close_stdin: bool,
terminate: bool,
yield_time_ms: int,
max_output_chars: int,
owner_session_key: str | None = None,
) -> _SessionPoll:
async with self._lock:
await self._cleanup_locked()
session = self._sessions.get(session_id)
if session is None:
raise KeyError(session_id)
if (
owner_session_key
and session.owner_session_key
and session.owner_session_key != owner_session_key
):
raise KeyError(session_id)
if chars:
error = await session.write(chars)
if error:
raise RuntimeError(error)
stdin_closed = False
if close_stdin:
error = await session.close_stdin()
if error:
raise RuntimeError(error)
stdin_closed = True
if terminate:
await session.kill()
poll = await session.poll(
yield_time_ms,
max_output_chars,
terminated=terminate,
stdin_closed=stdin_closed,
)
if poll.done:
async with self._lock:
self._sessions.pop(session_id, None)
return poll
async def list(self, *, owner_session_key: str | None = None) -> list[ExecSessionInfo]:
async with self._lock:
await self._cleanup_locked()
now = time.monotonic()
return [
ExecSessionInfo(
session_id=session_id,
command=session.command,
cwd=session.cwd,
elapsed_s=max(0.0, now - session.started_at),
idle_s=max(0.0, now - session.last_access),
remaining_s=max(0.0, session.deadline - now),
returncode=session.process.returncode,
owner_session_key=session.owner_session_key,
)
for session_id, session in sorted(self._sessions.items())
if not owner_session_key
or not session.owner_session_key
or session.owner_session_key == owner_session_key
]
async def _cleanup_locked(self) -> None:
now = time.monotonic()
stale = [
session_id
for session_id, session in self._sessions.items()
if now - session.last_access > self.idle_timeout
]
for session_id in stale:
session = self._sessions.pop(session_id)
await session.kill()
async def _spawn(
self,
command: str,
cwd: str,
env: dict[str, str],
shell_program: str | None,
login: bool,
) -> asyncio.subprocess.Process:
from nanobot.agent.tools.shell import ExecTool
return await ExecTool._spawn(
command, cwd, env, shell_program, login,
stdin=asyncio.subprocess.PIPE,
)
DEFAULT_EXEC_SESSION_MANAGER = ExecSessionManager()
def clamp_session_int(value: int | None, default: int, minimum: int, maximum: int) -> int:
if value is None:
return default
return min(max(value, minimum), maximum)
def _truncate_output(output: str, max_output_chars: int) -> tuple[str, int]:
if len(output) <= max_output_chars:
return output, 0
half = max_output_chars // 2
omitted = len(output) - max_output_chars
return (
output[:half]
+ f"\n\n... ({omitted:,} chars truncated) ...\n\n"
+ output[-half:],
omitted,
)
def format_session_poll(session_id: str, poll: _SessionPoll) -> str:
parts = [poll.output] if poll.output else []
if poll.truncated_chars:
parts.append(f"(output truncated by {poll.truncated_chars:,} chars)")
if poll.timed_out:
parts.append("Error: Command timed out; session was terminated.")
if poll.terminated and not poll.timed_out:
parts.append("Session terminated.")
if poll.stdin_closed:
parts.append("Stdin closed.")
if poll.done:
parts.append(f"Exit code: {poll.exit_code}")
else:
parts.append(f"Process running. session_id: {session_id}")
parts.append(f"Elapsed: {poll.elapsed_s:.1f}s")
return "\n".join(parts) if parts else "(no output yet)"
@tool_parameters(
tool_parameters_schema(
session_id=StringSchema("Session id returned by exec when yield_time_ms is used."),
chars=StringSchema(
"Bytes/text to write to stdin. Omit or pass an empty string to only poll recent output.",
nullable=True,
),
close_stdin=BooleanSchema(
description="Close stdin after writing chars. Useful for commands waiting for EOF.",
default=False,
),
terminate=BooleanSchema(
description="Terminate the running exec session.",
default=False,
),
yield_time_ms=IntegerSchema(
DEFAULT_YIELD_MS,
description="Milliseconds to wait before returning recent output (default 1000, max 30000).",
minimum=0,
maximum=MAX_YIELD_MS,
),
wait_for=StringSchema(
"Optional text to wait for in output before returning. "
"Useful for interactive commands and dev servers.",
nullable=True,
),
wait_timeout_ms=IntegerSchema(
DEFAULT_WAIT_FOR_MS,
description="Maximum milliseconds to wait for wait_for text (default 10000, max 120000).",
minimum=0,
maximum=MAX_WAIT_FOR_MS,
nullable=True,
),
max_output_chars=IntegerSchema(
DEFAULT_MAX_OUTPUT_CHARS,
description="Maximum output characters to return from this poll (default 10000, max 50000).",
minimum=1000,
maximum=MAX_OUTPUT_CHARS,
),
max_output_tokens=IntegerSchema(
DEFAULT_MAX_OUTPUT_CHARS,
description="Compatibility alias for max_output_chars. The current runtime uses a character budget.",
minimum=1000,
maximum=MAX_OUTPUT_CHARS,
nullable=True,
),
required=["session_id"],
)
)
class WriteStdinTool(Tool):
"""Write to or poll a running exec session."""
_scopes = {"core", "subagent"}
config_key = "exec"
@classmethod
def config_cls(cls):
from nanobot.agent.tools.shell import ExecToolConfig
return ExecToolConfig
@classmethod
def enabled(cls, ctx: Any) -> bool:
return ctx.config.exec.enable
def __init__(
self,
*,
manager: ExecSessionManager | None = None,
) -> None:
self._manager = manager or DEFAULT_EXEC_SESSION_MANAGER
@classmethod
def create(cls, ctx: Any) -> Tool:
return cls()
@property
def exclusive(self) -> bool:
return True
@property
def name(self) -> str:
return "write_stdin"
@property
def description(self) -> str:
return (
"Interact with a running exec session created by exec with "
"yield_time_ms. Use chars='' to poll without writing, chars to send "
"stdin, close_stdin=true to send EOF, or terminate=true to stop the "
"process. Use wait_for with wait_timeout_ms for dev servers, test "
"watchers, and prompts where you need to wait for expected output. "
"Do not use this to start new commands; start them with exec."
)
async def execute(
self,
session_id: str,
chars: str | None = None,
close_stdin: bool = False,
terminate: bool = False,
yield_time_ms: int | None = None,
wait_for: str | None = None,
wait_timeout_ms: int | None = None,
max_output_chars: int | None = None,
max_output_tokens: int | None = None,
**kwargs: Any,
) -> str:
try:
if max_output_chars is None:
max_output_chars = max_output_tokens
output_limit = clamp_session_int(
max_output_chars,
DEFAULT_MAX_OUTPUT_CHARS,
1000,
MAX_OUTPUT_CHARS,
)
if wait_for:
return await self._wait_for_output(
session_id=session_id,
chars=chars,
close_stdin=close_stdin,
terminate=terminate,
wait_for=wait_for,
wait_timeout_ms=clamp_session_int(
wait_timeout_ms,
DEFAULT_WAIT_FOR_MS,
0,
MAX_WAIT_FOR_MS,
),
max_output_chars=output_limit,
)
poll = await self._manager.write(
session_id=session_id,
chars=chars,
close_stdin=close_stdin,
terminate=terminate,
yield_time_ms=clamp_session_int(yield_time_ms, DEFAULT_YIELD_MS, 0, MAX_YIELD_MS),
max_output_chars=output_limit,
owner_session_key=current_request_session_key(),
)
return format_session_poll(session_id, poll)
except KeyError:
return f"Error: exec session not found: {session_id}"
except Exception as exc:
return f"Error writing to exec session: {exc}"
async def _wait_for_output(
self,
*,
session_id: str,
chars: str | None,
close_stdin: bool,
terminate: bool,
wait_for: str,
wait_timeout_ms: int,
max_output_chars: int,
) -> str:
deadline = time.monotonic() + (wait_timeout_ms / 1000)
aggregate: list[str] = []
first = True
poll: _SessionPoll | None = None
while True:
remaining_ms = max(0, int((deadline - time.monotonic()) * 1000))
step_ms = min(500, remaining_ms)
poll = await self._manager.write(
session_id=session_id,
chars=chars if first else None,
close_stdin=close_stdin if first else False,
terminate=terminate if first else False,
yield_time_ms=step_ms,
max_output_chars=max_output_chars,
owner_session_key=current_request_session_key(),
)
first = False
if poll.output:
aggregate.append(poll.output)
joined = "".join(aggregate)
if wait_for in joined:
poll.output = joined
return format_session_poll(session_id, poll)
if poll.done or remaining_ms <= 0:
poll.output = "".join(aggregate)
result = format_session_poll(session_id, poll)
if wait_for not in poll.output:
result += f"\nWait target not observed: {wait_for!r}"
return result
@tool_parameters(tool_parameters_schema())
class ListExecSessionsTool(Tool):
"""List active exec sessions."""
_scopes = {"core", "subagent"}
config_key = "exec"
@classmethod
def config_cls(cls):
from nanobot.agent.tools.shell import ExecToolConfig
return ExecToolConfig
@classmethod
def enabled(cls, ctx: Any) -> bool:
return ctx.config.exec.enable
def __init__(
self,
*,
manager: ExecSessionManager | None = None,
) -> None:
self._manager = manager or DEFAULT_EXEC_SESSION_MANAGER
@classmethod
def create(cls, ctx: Any) -> Tool:
return cls()
@property
def name(self) -> str:
return "list_exec_sessions"
@property
def description(self) -> str:
return (
"List active long-running exec sessions, including session_id, cwd, "
"elapsed time, idle time, remaining timeout, and command preview. "
"Use this to recover a session_id after context shifts before "
"polling, writing stdin, or terminating with write_stdin."
)
@property
def read_only(self) -> bool:
return True
async def execute(self, **kwargs: Any) -> str:
try:
sessions = await self._manager.list(
owner_session_key=current_request_session_key(),
)
if not sessions:
return "No active exec sessions."
lines = []
for info in sessions:
command = " ".join(info.command.split())
if len(command) > 120:
command = command[:119] + "..."
status = "exited" if info.returncode is not None else "running"
lines.append(
f"{info.session_id} | {status} | elapsed={info.elapsed_s:.1f}s "
f"| idle={info.idle_s:.1f}s | remaining={info.remaining_s:.1f}s "
f"| cwd={info.cwd} | {command}"
)
return "\n".join(lines)
except Exception as exc:
return f"Error listing exec sessions: {exc}"
+25 -129
View File
@@ -10,7 +10,6 @@ from typing import Any
from nanobot.agent.tools.base import Tool, tool_parameters
from nanobot.agent.tools.file_state import FileStates, _hash_file, current_file_states
from nanobot.agent.tools.path_utils import resolve_workspace_path
from nanobot.security.workspace_access import current_tool_workspace
from nanobot.agent.tools.schema import (
BooleanSchema,
IntegerSchema,
@@ -29,18 +28,10 @@ class _FsTool(Tool):
allowed_dir: Path | None = None,
extra_allowed_dirs: list[Path] | None = None,
file_states: FileStates | None = None,
restrict_to_workspace: bool | None = None,
sandbox_restricts_workspace: bool = False,
):
self._workspace = workspace
self._allowed_dir = allowed_dir
self._extra_allowed_dirs = extra_allowed_dirs
self._restrict_to_workspace = (
bool(restrict_to_workspace)
if restrict_to_workspace is not None
else allowed_dir is not None
)
self._sandbox_restricts_workspace = sandbox_restricts_workspace
# Explicit state is used by isolated runners like Dream/subagents.
# Main AgentLoop tools leave this unset and resolve state from the
# current async task, which keeps shared tool instances session-safe.
@@ -55,16 +46,13 @@ class _FsTool(Tool):
ctx.config.restrict_to_workspace
or ctx.config.exec.sandbox
)
sandbox_restricts = bool(ctx.config.exec.sandbox)
allowed_dir = Path(ctx.workspace) if restrict else None
extra_read = [BUILTIN_SKILLS_DIR]
extra_read = [BUILTIN_SKILLS_DIR] if allowed_dir else None
return cls(
workspace=Path(ctx.workspace),
allowed_dir=allowed_dir,
extra_allowed_dirs=extra_read,
file_states=ctx.file_state_store,
restrict_to_workspace=ctx.config.restrict_to_workspace,
sandbox_restricts_workspace=sandbox_restricts,
)
@property
@@ -74,21 +62,13 @@ class _FsTool(Tool):
return current_file_states(self._fallback_file_states)
def _resolve(self, path: str) -> Path:
access = current_tool_workspace(
self._workspace,
restrict_to_workspace=self._restrict_to_workspace,
sandbox_restricts_workspace=self._sandbox_restricts_workspace,
)
return resolve_workspace_path(
path,
access.project_path,
access.allowed_root,
self._workspace,
self._allowed_dir,
self._extra_allowed_dirs,
)
def _display_workspace(self) -> Path | None:
return current_tool_workspace(self._workspace).project_path
# ---------------------------------------------------------------------------
# read_file
@@ -152,10 +132,6 @@ def _parse_page_range(pages: str, total: int) -> tuple[int, int]:
minimum=1,
),
pages=StringSchema("Page range for PDF files, e.g. '1-5' (default: all, max 20 pages)"),
force=BooleanSchema(
description="Bypass same-file read deduplication and return content again.",
default=False,
),
required=["path"],
)
)
@@ -178,11 +154,7 @@ class ReadFileTool(_FsTool):
"Text output format: LINE_NUM|CONTENT. "
"Images return visual content for analysis. "
"Supports PDF, DOCX, XLSX, PPTX documents. "
"Use find_files/list_dir first when the path is uncertain. "
"Read the relevant range before editing so replacements or patches "
"are based on current content. "
"Use offset and limit for large text files. "
"Use force=true to re-read content even if unchanged. "
"Reads exceeding ~128K chars are truncated."
)
@@ -190,15 +162,7 @@ class ReadFileTool(_FsTool):
def read_only(self) -> bool:
return True
async def execute(
self,
path: str | None = None,
offset: int = 1,
limit: int | None = None,
pages: str | None = None,
force: bool = False,
**kwargs: Any,
) -> Any:
async def execute(self, path: str | None = None, offset: int = 1, limit: int | None = None, pages: str | None = None, **kwargs: Any) -> Any:
try:
if not path:
return "Error reading file: Unknown path"
@@ -238,13 +202,7 @@ class ReadFileTool(_FsTool):
current_mtime = os.path.getmtime(fp)
except OSError:
current_mtime = 0.0
if (
not force
and entry
and entry.can_dedup
and entry.offset == offset
and entry.limit == limit
):
if entry and entry.can_dedup and entry.offset == offset and entry.limit == limit:
if current_mtime != entry.mtime:
# File was modified externally - force full read and mark as not dedupable
entry.can_dedup = False
@@ -407,10 +365,9 @@ class WriteFileTool(_FsTool):
@property
def description(self) -> str:
return (
"Create a new file or intentionally replace an entire file with "
"the provided content. Overwrites existing files and creates parent "
"directories as needed. For code changes or partial edits, prefer "
"apply_patch; use edit_file only for small exact replacements."
"Write content to a file. Overwrites if the file already exists; "
"creates parent directories as needed. "
"For partial edits, prefer edit_file instead."
)
async def execute(self, path: str | None = None, content: str | None = None, **kwargs: Any) -> str:
@@ -700,24 +657,6 @@ def _find_match(content: str, old_text: str) -> tuple[str | None, int]:
old_text=StringSchema("The text to find and replace"),
new_text=StringSchema("The text to replace with"),
replace_all=BooleanSchema(description="Replace all occurrences (default false)"),
occurrence=IntegerSchema(
1,
description="Optional 1-based occurrence to replace when old_text appears multiple times.",
minimum=1,
nullable=True,
),
line_hint=IntegerSchema(
1,
description="Optional 1-based line hint used to choose the nearest match.",
minimum=1,
nullable=True,
),
expected_replacements=IntegerSchema(
1,
description="Optional guard for the number of replacements that must be made.",
minimum=1,
nullable=True,
),
required=["path", "old_text", "new_text"],
)
)
@@ -735,13 +674,10 @@ class EditFileTool(_FsTool):
@property
def description(self) -> str:
return (
"Perform a small, exact replacement in one file by replacing "
"old_text with new_text. Use this for narrow text substitutions "
"with old_text copied from read_file. For multi-file, structural, "
"or generated code edits, prefer apply_patch. If old_text matches "
"multiple times, provide more context or set occurrence, line_hint, "
"replace_all, and expected_replacements. Shows closest-match "
"diagnostics on failure."
"Edit a file by replacing old_text with new_text. "
"Tolerates minor whitespace/indentation differences and curly/straight quote mismatches. "
"If old_text matches multiple times, you must provide more context "
"or set replace_all=true. Shows a diff of the closest match on failure."
)
@staticmethod
@@ -752,8 +688,7 @@ class EditFileTool(_FsTool):
async def execute(
self, path: str | None = None, old_text: str | None = None,
new_text: str | None = None,
replace_all: bool = False, occurrence: int | None = None,
line_hint: int | None = None, expected_replacements: int | None = None, **kwargs: Any,
replace_all: bool = False, **kwargs: Any,
) -> str:
try:
if not path:
@@ -762,12 +697,10 @@ class EditFileTool(_FsTool):
raise ValueError("Unknown old_text")
if new_text is None:
raise ValueError("Unknown new_text")
if occurrence is not None and occurrence < 1:
return "Error: occurrence must be >= 1."
if line_hint is not None and line_hint < 1:
return "Error: line_hint must be >= 1."
if expected_replacements is not None and expected_replacements < 1:
return "Error: expected_replacements must be >= 1."
# .ipynb detection
if path.endswith(".ipynb"):
return "Error: This is a Jupyter notebook. Use the notebook_edit tool instead of edit_file."
fp = self._resolve(path)
@@ -810,42 +743,15 @@ class EditFileTool(_FsTool):
if not matches:
return self._not_found_msg(old_text, content, path)
count = len(matches)
if replace_all and occurrence is not None:
return "Error: occurrence cannot be used with replace_all=true."
if replace_all and line_hint is not None:
return "Error: line_hint cannot be used with replace_all=true."
if occurrence is not None and line_hint is not None:
return "Error: line_hint cannot be used with occurrence."
if count > 1 and not replace_all:
if occurrence is not None:
if occurrence > count:
return (
f"Error: occurrence {occurrence} is out of range; "
f"old_text appears {count} times."
)
elif line_hint is not None:
nearest = min(matches, key=lambda match: abs(match.line - line_hint))
distance = abs(nearest.line - line_hint)
if sum(1 for match in matches if abs(match.line - line_hint) == distance) > 1:
return (
f"Error: line_hint {line_hint} is ambiguous; "
f"old_text appears {count} times."
)
else:
line_numbers = [match.line for match in matches]
preview = ", ".join(f"line {n}" for n in line_numbers[:3])
if len(line_numbers) > 3:
preview += ", ..."
location_hint = f" at {preview}" if preview else ""
return (
f"Warning: old_text appears {count} times{location_hint}. "
"Provide more context, set occurrence to choose one match, "
"or set replace_all=true."
)
elif occurrence is not None and occurrence > count:
line_numbers = [match.line for match in matches]
preview = ", ".join(f"line {n}" for n in line_numbers[:3])
if len(line_numbers) > 3:
preview += ", ..."
location_hint = f" at {preview}" if preview else ""
return (
f"Error: occurrence {occurrence} is out of range; "
f"old_text appears {count} time."
f"Warning: old_text appears {count} times{location_hint}. "
"Provide more context to make it unique, or set replace_all=true."
)
norm_new = new_text.replace("\r\n", "\n")
@@ -854,17 +760,7 @@ class EditFileTool(_FsTool):
if fp.suffix.lower() not in self._MARKDOWN_EXTS:
norm_new = self._strip_trailing_ws(norm_new)
if replace_all:
selected = matches
elif line_hint is not None:
selected = [min(matches, key=lambda match: abs(match.line - line_hint))]
else:
selected = [matches[occurrence - 1 if occurrence else 0]]
if expected_replacements is not None and len(selected) != expected_replacements:
return (
f"Error: expected {expected_replacements} replacements but "
f"would make {len(selected)}."
)
selected = matches if replace_all else matches[:1]
new_content = content
for match in reversed(selected):
replacement = _preserve_quote_style(norm_old, match.text, norm_new)
+26 -15
View File
@@ -14,7 +14,6 @@ from nanobot.agent.tools.schema import (
StringSchema,
tool_parameters_schema,
)
from nanobot.security.workspace_access import current_tool_workspace
from nanobot.config.paths import get_media_dir
from nanobot.config.schema import Base
from nanobot.providers.image_generation import (
@@ -22,7 +21,6 @@ from nanobot.providers.image_generation import (
ImageGenerationProvider,
get_image_gen_provider,
)
from nanobot.security.workspace_policy import WorkspaceBoundaryError, resolve_allowed_path
from nanobot.utils.artifacts import (
ArtifactError,
generated_image_tool_result,
@@ -132,23 +130,25 @@ class ImageGenerationTool(Tool):
}
return cls(**kwargs)
def _missing_api_key_error(self) -> str:
cls = get_image_gen_provider(self.config.provider)
if cls and cls.missing_key_message:
return f"Error: {cls.missing_key_message}"
return f"Error: {self.config.provider} API key is not configured."
def _resolve_reference_image(self, value: str) -> str:
access = current_tool_workspace(self.workspace, restrict_to_workspace=True)
workspace = access.project_path or self.workspace
raw_path = Path(value).expanduser()
path = raw_path if raw_path.is_absolute() else self.workspace / raw_path
try:
resolved = resolve_allowed_path(
value,
workspace=workspace,
allowed_root=access.allowed_root,
extra_allowed_roots=[get_media_dir()] if access.allowed_root is not None else None,
strict=True,
)
except WorkspaceBoundaryError as exc:
raise ImageGenerationError(
"reference_images must be inside the workspace or nanobot media directory"
) from exc
resolved = path.resolve(strict=True)
except OSError as exc:
raise ImageGenerationError(f"reference image not found: {value}") from exc
allowed_roots = [self.workspace.resolve(), get_media_dir().resolve()]
if not any(_is_relative_to(resolved, root) for root in allowed_roots):
raise ImageGenerationError(
"reference_images must be inside the workspace or nanobot media directory"
)
if not resolved.is_file():
raise ImageGenerationError(f"reference image is not a file: {value}")
raw = resolved.read_bytes()
@@ -173,6 +173,9 @@ class ImageGenerationTool(Tool):
client = self._provider_client()
if client is None:
return f"Error: unsupported image generation provider '{self.config.provider}'"
provider = self._provider_config()
if not provider or not provider.api_key:
return self._missing_api_key_error()
requested = count or 1
if requested > self.config.max_images_per_turn:
@@ -207,3 +210,11 @@ class ImageGenerationTool(Tool):
return generated_image_tool_result(artifacts)
except (ArtifactError, ImageGenerationError, OSError) as exc:
return f"Error: {exc}"
def _is_relative_to(path: Path, root: Path) -> bool:
try:
path.relative_to(root)
except ValueError:
return False
return True
+6 -13
View File
@@ -16,7 +16,6 @@ There is **no** sub-agent orchestrator and **no** special WebSocket ``agent_ui``
from __future__ import annotations
from contextvars import ContextVar
from datetime import datetime
from typing import TYPE_CHECKING, Any
@@ -46,22 +45,15 @@ class _GoalToolsMixin(ContextAware):
def __init__(self, sessions: SessionManager, bus: Any | None = None) -> None:
self._sessions = sessions
self._bus = bus
# Each subclass gets its own ContextVar so concurrent tasks across
# different tool types (LongTaskTool vs CompleteGoalTool) do not
# interfere with each other.
self._request_ctx: ContextVar[RequestContext | None] = ContextVar(
f"{self.__class__.__name__}_request_ctx",
default=None,
)
self._request_ctx: RequestContext | None = None
def set_context(self, ctx: RequestContext) -> None:
self._request_ctx.set(ctx)
self._request_ctx = ctx
def _session(self):
request_ctx = self._request_ctx.get()
if request_ctx is None:
if self._request_ctx is None:
return None
key = request_ctx.session_key
key = self._request_ctx.session_key
if not key:
return None
return self._sessions.get_or_create(key)
@@ -69,7 +61,7 @@ class _GoalToolsMixin(ContextAware):
async def _publish_goal_state_ws(self, metadata: dict[str, Any]) -> None:
"""Fan-out authoritative goal snapshot for this WebSocket chat only."""
bus = self._bus
rc = self._request_ctx.get()
rc = self._request_ctx
if bus is None or rc is None or rc.channel != "websocket":
return
cid = (rc.chat_id or "").strip()
@@ -232,3 +224,4 @@ class CompleteGoalTool(Tool, _GoalToolsMixin):
if tail:
return f"Goal marked complete ({ended}). Recap:\n{tail}"
return f"Goal marked complete ({ended})."
+1 -279
View File
@@ -6,20 +6,13 @@ import re
import shutil
import urllib.parse
from contextlib import AsyncExitStack, suppress
from typing import Any, Mapping
from weakref import WeakKeyDictionary
from typing import Any
import httpx
from loguru import logger
from nanobot.agent.tools.base import Tool
from nanobot.agent.tools.registry import ToolRegistry
from nanobot.bus.events import (
INBOUND_META_RUNTIME_CONTROL,
RUNTIME_CONTROL_ACK,
RUNTIME_CONTROL_MCP_RELOAD,
InboundMessage,
)
# Transient connection errors that warrant a single retry.
# These typically happen when an MCP server restarts or a network
@@ -40,7 +33,6 @@ _WINDOWS_SHELL_LAUNCHERS: frozenset[str] = frozenset(("npx", "npm", "pnpm", "yar
# Characters allowed in tool names by model providers (Anthropic, OpenAI, etc.).
# Replace anything outside [a-zA-Z0-9_-] with underscore and collapse runs.
_SANITIZE_RE = re.compile(r"_+")
_RELOAD_LOCKS: WeakKeyDictionary[Any, asyncio.Lock] = WeakKeyDictionary()
def _sanitize_name(name: str) -> str:
@@ -511,7 +503,6 @@ async def connect_mcp_servers(
command=command,
args=args,
env=env,
cwd=cfg.cwd or None,
)
read, write = await server_stack.enter_async_context(stdio_client(params))
elif transport_type == "sse":
@@ -671,272 +662,3 @@ async def connect_mcp_servers(
server_stacks[result[0]] = result[1]
return server_stacks
def session_extra(metadata: Mapping[str, Any] | None) -> dict[str, Any]:
"""Return persisted session kwargs for MCP preset attachments."""
mcp_presets = metadata.get("mcp_presets") if isinstance(metadata, Mapping) else None
return {"mcp_presets": mcp_presets} if isinstance(mcp_presets, list) and mcp_presets else {}
def runtime_lines(
message: Any,
*,
available_server_names: set[str] | None = None,
configured_server_names: set[str] | None = None,
connected_server_names: set[str] | None = None,
skip: bool = False,
) -> list[str]:
"""Return model-visible MCP preset annotations for the current turn."""
if skip:
return []
if configured_server_names is None:
configured_server_names = available_server_names
if connected_server_names is None:
connected_server_names = available_server_names
metadata = message.metadata if isinstance(getattr(message, "metadata", None), Mapping) else None
structured = metadata.get("mcp_presets") if isinstance(metadata, Mapping) else None
if not isinstance(structured, list):
return []
lines: list[str] = []
for item in structured[:8]:
if not isinstance(item, Mapping):
continue
raw_name = str(item.get("name") or "").strip().lower()
if not raw_name:
continue
display = str(item.get("display_name") or raw_name).strip() or raw_name
transport = str(item.get("transport") or "mcp").strip() or "mcp"
prefix = f"mcp_{raw_name}_"
if configured_server_names is not None and raw_name not in configured_server_names:
lines.append(
"MCP Preset Attachment: "
f"@{raw_name} ({display}; transport={transport}) is configured in WebUI Settings, "
"but this gateway has not loaded the latest MCP settings yet. "
f"Tools with prefix `{prefix}` may not be available yet; if they are missing, "
"tell the user to restart nanobot."
)
continue
if connected_server_names is not None and raw_name not in connected_server_names:
lines.append(
"MCP Preset Attachment: "
f"@{raw_name} ({display}; transport={transport}) is configured, "
"but its MCP connection is not currently live. "
f"Tools with prefix `{prefix}` may be unavailable; tell the user to open Settings, "
"run the preset test, and restart nanobot only if hot reload is unavailable."
)
continue
lines.append(
"MCP Preset Attachment: "
f"@{raw_name} ({display}; transport={transport}; tool_prefix={prefix}). "
f"Prefer available tools whose names start with `{prefix}` for this request; "
"do not substitute shell commands for this MCP integration unless the user asks."
)
return lines
async def connect_missing_servers(state: Any, registry: ToolRegistry) -> None:
"""Connect configured MCP servers that are not currently live."""
missing_servers = {
name: cfg for name, cfg in state._mcp_servers.items() if name not in state._mcp_stacks
}
if state._mcp_connecting or not missing_servers:
return
state._mcp_connecting = True
try:
connected = await connect_mcp_servers(missing_servers, registry)
state._mcp_stacks.update(connected)
state._mcp_connected = bool(state._mcp_stacks)
if connected:
logger.info("MCP connected servers: {}", sorted(connected))
else:
logger.warning("No MCP servers connected successfully (will retry next message)")
except asyncio.CancelledError:
logger.warning("MCP connection cancelled (will retry next message)")
state._mcp_connected = bool(state._mcp_stacks)
except BaseException as e:
logger.warning("Failed to connect MCP servers (will retry next message): {}", e)
state._mcp_connected = bool(state._mcp_stacks)
finally:
state._mcp_connecting = False
async def reload_servers(state: Any, registry: ToolRegistry) -> dict[str, Any]:
"""Reconcile live MCP connections with the current config file."""
async with _reload_lock(state):
try:
from nanobot.config.loader import (load_config,
resolve_config_env_vars)
config = resolve_config_env_vars(load_config())
next_servers = dict(config.tools.mcp_servers)
except Exception as exc:
logger.warning("MCP hot reload could not read config: {}", exc)
return {
"ok": False,
"message": "Could not reload MCP config. Restart nanobot to pick up changes.",
"requires_restart": True,
"error": str(exc),
}
current_servers = dict(state._mcp_servers)
current_names = set(current_servers)
next_names = set(next_servers)
removed = sorted(current_names - next_names)
added = sorted(next_names - current_names)
changed = sorted(
name
for name in current_names & next_names
if _server_signature(current_servers[name]) != _server_signature(next_servers[name])
)
tools_removed = 0
for name in [*removed, *changed]:
tools_removed += _unregister_server_tools(state, registry, name)
await _close_server(state, name)
state._mcp_servers = next_servers
retry_missing = sorted(
name
for name in next_names
if name not in state._mcp_stacks and name not in set(added) | set(changed)
)
to_connect_names = sorted(set(added) | set(changed) | set(retry_missing))
to_connect = {name: next_servers[name] for name in to_connect_names}
connected: dict[str, AsyncExitStack] = {}
if to_connect:
connected = await connect_mcp_servers(to_connect, registry)
state._mcp_stacks.update(connected)
state._mcp_connected = bool(state._mcp_stacks)
failed = sorted(set(to_connect) - set(connected))
unchanged = not removed and not added and not changed and not retry_missing
ok = not failed
if failed:
message = "MCP config reloaded, but some servers did not connect: " + ", ".join(failed)
elif unchanged:
message = "MCP config is already live."
elif retry_missing and not added and not changed and not removed:
message = "MCP connections refreshed without restarting nanobot."
else:
message = "MCP config reloaded without restarting nanobot."
logger.info(
"MCP hot reload: added={} changed={} removed={} retried={} connected={} failed={} tools_removed={}",
added,
changed,
removed,
retry_missing,
sorted(connected),
failed,
tools_removed,
)
return {
"ok": ok,
"message": message,
"added": added,
"changed": changed,
"removed": removed,
"retried": retry_missing,
"connected": sorted(state._mcp_stacks),
"configured": sorted(state._mcp_servers),
"failed": failed,
"tools_removed": tools_removed,
"requires_restart": False,
}
async def request_mcp_reload(bus: Any, *, timeout: float = 15.0) -> dict[str, Any]:
"""Ask the running agent loop to reconcile live MCP connections."""
loop = asyncio.get_running_loop()
ack: asyncio.Future[dict[str, Any]] = loop.create_future()
await bus.publish_inbound(
InboundMessage(
channel="system",
sender_id="webui-settings",
chat_id="runtime",
content=RUNTIME_CONTROL_MCP_RELOAD,
metadata={
INBOUND_META_RUNTIME_CONTROL: RUNTIME_CONTROL_MCP_RELOAD,
RUNTIME_CONTROL_ACK: ack,
},
)
)
try:
result = await asyncio.wait_for(ack, timeout=timeout)
except asyncio.TimeoutError:
return {
"ok": False,
"message": "MCP hot reload timed out. Restart nanobot to pick up changes.",
"requires_restart": True,
}
return result if isinstance(result, dict) else {
"ok": False,
"message": "MCP hot reload returned an unexpected response.",
"requires_restart": True,
}
async def handle_runtime_control(state: Any, msg: InboundMessage, registry: ToolRegistry) -> bool:
metadata = msg.metadata if isinstance(msg.metadata, dict) else {}
control = metadata.get(INBOUND_META_RUNTIME_CONTROL)
if control != RUNTIME_CONTROL_MCP_RELOAD:
return False
ack = metadata.get(RUNTIME_CONTROL_ACK)
try:
result = await reload_servers(state, registry)
except Exception as exc:
logger.exception("MCP hot reload failed")
result = {
"ok": False,
"message": "MCP hot reload failed. Restart nanobot to pick up changes.",
"requires_restart": True,
"error": str(exc),
}
if isinstance(ack, asyncio.Future) and not ack.done():
ack.set_result(result)
return True
def _reload_lock(state: Any) -> asyncio.Lock:
try:
return _RELOAD_LOCKS[state]
except KeyError:
lock = asyncio.Lock()
_RELOAD_LOCKS[state] = lock
return lock
def _server_signature(cfg: Any) -> Any:
if hasattr(cfg, "model_dump"):
return cfg.model_dump(mode="json")
return cfg
def _tool_prefix(server_name: str) -> str:
safe_name = "".join(ch if ch.isalnum() or ch in {"_", "-"} else "_" for ch in server_name)
while "__" in safe_name:
safe_name = safe_name.replace("__", "_")
return f"mcp_{safe_name}_"
def _unregister_server_tools(state: Any, registry: ToolRegistry, server_name: str) -> int:
prefix = _tool_prefix(server_name)
removed = 0
for tool_name in list(registry.tool_names):
if tool_name.startswith(prefix):
registry.unregister(tool_name)
removed += 1
return removed
async def _close_server(state: Any, server_name: str) -> None:
stack = state._mcp_stacks.pop(server_name, None)
if stack is None:
return
try:
await stack.aclose()
except (RuntimeError, BaseExceptionGroup):
logger.debug("MCP server '{}' cleanup error (can be ignored)", server_name)
+4 -24
View File
@@ -8,7 +8,6 @@ from nanobot.agent.tools.base import Tool, tool_parameters
from nanobot.agent.tools.context import ContextAware, RequestContext
from nanobot.agent.tools.path_utils import resolve_workspace_path
from nanobot.agent.tools.schema import ArraySchema, StringSchema, tool_parameters_schema
from nanobot.security.workspace_access import current_tool_workspace
from nanobot.bus.events import OutboundMessage
from nanobot.config.paths import get_workspace_path
@@ -83,10 +82,6 @@ class MessageTool(Tool, ContextAware):
"message_record_channel_delivery",
default=False,
)
self._suppress_delivery_var: ContextVar[bool] = ContextVar(
"message_suppress_delivery",
default=False,
)
@classmethod
def create(cls, ctx: Any) -> Tool:
@@ -125,14 +120,6 @@ class MessageTool(Tool, ContextAware):
"""Restore previous proactive delivery recording state."""
self._record_channel_delivery_var.reset(token)
def set_suppress_delivery(self, active: bool):
"""Temporarily suppress real channel delivery for internal checks."""
return self._suppress_delivery_var.set(active)
def reset_suppress_delivery(self, token) -> None:
"""Restore previous channel delivery suppression state."""
self._suppress_delivery_var.reset(token)
@property
def _sent_in_turn(self) -> bool:
return self._sent_in_turn_var.get()
@@ -162,19 +149,15 @@ class MessageTool(Tool, ContextAware):
def _resolve_media(self, media: list[str]) -> list[str]:
"""Resolve local media attachments and enforce workspace restriction when enabled."""
resolved: list[str] = []
access = current_tool_workspace(
self._workspace,
restrict_to_workspace=self._restrict_to_workspace,
)
workspace = access.project_path or self._workspace
allowed_dir = self._workspace if self._restrict_to_workspace else None
for p in media:
if p.startswith(("http://", "https://")):
resolved.append(p)
elif not access.restrict_to_workspace:
elif not self._restrict_to_workspace:
path = Path(p).expanduser()
resolved.append(p if path.is_absolute() else str(workspace / path))
resolved.append(p if path.is_absolute() else str(self._workspace / path))
else:
resolved.append(str(resolve_workspace_path(p, workspace, access.allowed_root)))
resolved.append(str(resolve_workspace_path(p, self._workspace, allowed_dir)))
return resolved
async def execute(
@@ -229,9 +212,6 @@ class MessageTool(Tool, ContextAware):
if not channel or not chat_id:
return "Error: No target channel/chat specified"
if self._suppress_delivery_var.get():
return "Message suppressed during internal check"
if not self._send_callback:
return "Error: Message sending not configured"
+162
View File
@@ -0,0 +1,162 @@
"""NotebookEditTool — edit Jupyter .ipynb notebooks."""
from __future__ import annotations
import json
import uuid
from typing import Any
from nanobot.agent.tools.base import tool_parameters
from nanobot.agent.tools.schema import IntegerSchema, StringSchema, tool_parameters_schema
from nanobot.agent.tools.filesystem import _FsTool
def _new_cell(source: str, cell_type: str = "code", generate_id: bool = False) -> dict:
cell: dict[str, Any] = {
"cell_type": cell_type,
"source": source,
"metadata": {},
}
if cell_type == "code":
cell["outputs"] = []
cell["execution_count"] = None
if generate_id:
cell["id"] = uuid.uuid4().hex[:8]
return cell
def _make_empty_notebook() -> dict:
return {
"nbformat": 4,
"nbformat_minor": 5,
"metadata": {
"kernelspec": {"display_name": "Python 3", "language": "python", "name": "python3"},
"language_info": {"name": "python"},
},
"cells": [],
}
@tool_parameters(
tool_parameters_schema(
path=StringSchema("Path to the .ipynb notebook file"),
cell_index=IntegerSchema(0, description="0-based index of the cell to edit", minimum=0),
new_source=StringSchema("New source content for the cell"),
cell_type=StringSchema(
"Cell type: 'code' or 'markdown' (default: code)",
enum=["code", "markdown"],
),
edit_mode=StringSchema(
"Mode: 'replace' (default), 'insert' (after target), or 'delete'",
enum=["replace", "insert", "delete"],
),
required=["path", "cell_index"],
)
)
class NotebookEditTool(_FsTool):
"""Edit Jupyter notebook cells: replace, insert, or delete."""
_scopes = {"core"}
_VALID_CELL_TYPES = frozenset({"code", "markdown"})
_VALID_EDIT_MODES = frozenset({"replace", "insert", "delete"})
@property
def name(self) -> str:
return "notebook_edit"
@property
def description(self) -> str:
return (
"Edit a Jupyter notebook (.ipynb) cell. "
"Modes: replace (default) replaces cell content, "
"insert adds a new cell after the target index, "
"delete removes the cell at the index. "
"cell_index is 0-based."
)
async def execute(
self,
path: str | None = None,
cell_index: int = 0,
new_source: str = "",
cell_type: str = "code",
edit_mode: str = "replace",
**kwargs: Any,
) -> str:
try:
if not path:
return "Error: path is required"
if not path.endswith(".ipynb"):
return "Error: notebook_edit only works on .ipynb files. Use edit_file for other files."
if edit_mode not in self._VALID_EDIT_MODES:
return (
f"Error: Invalid edit_mode '{edit_mode}'. "
"Use one of: replace, insert, delete."
)
if cell_type not in self._VALID_CELL_TYPES:
return (
f"Error: Invalid cell_type '{cell_type}'. "
"Use one of: code, markdown."
)
fp = self._resolve(path)
# Create new notebook if file doesn't exist and mode is insert
if not fp.exists():
if edit_mode != "insert":
return f"Error: File not found: {path}"
nb = _make_empty_notebook()
cell = _new_cell(new_source, cell_type, generate_id=True)
nb["cells"].append(cell)
fp.parent.mkdir(parents=True, exist_ok=True)
fp.write_text(json.dumps(nb, indent=1, ensure_ascii=False), encoding="utf-8")
return f"Successfully created {fp} with 1 cell"
try:
nb = json.loads(fp.read_text(encoding="utf-8"))
except (json.JSONDecodeError, UnicodeDecodeError) as e:
return f"Error: Failed to parse notebook: {e}"
cells = nb.get("cells", [])
nbformat_minor = nb.get("nbformat_minor", 0)
generate_id = nb.get("nbformat", 0) >= 4 and nbformat_minor >= 5
if edit_mode == "delete":
if cell_index < 0 or cell_index >= len(cells):
return f"Error: cell_index {cell_index} out of range (notebook has {len(cells)} cells)"
cells.pop(cell_index)
nb["cells"] = cells
fp.write_text(json.dumps(nb, indent=1, ensure_ascii=False), encoding="utf-8")
return f"Successfully deleted cell {cell_index} from {fp}"
if edit_mode == "insert":
insert_at = min(cell_index + 1, len(cells))
cell = _new_cell(new_source, cell_type, generate_id=generate_id)
cells.insert(insert_at, cell)
nb["cells"] = cells
fp.write_text(json.dumps(nb, indent=1, ensure_ascii=False), encoding="utf-8")
return f"Successfully inserted cell at index {insert_at} in {fp}"
# Default: replace
if cell_index < 0 or cell_index >= len(cells):
return f"Error: cell_index {cell_index} out of range (notebook has {len(cells)} cells)"
cells[cell_index]["source"] = new_source
if cell_type and cells[cell_index].get("cell_type") != cell_type:
cells[cell_index]["cell_type"] = cell_type
if cell_type == "code":
cells[cell_index].setdefault("outputs", [])
cells[cell_index].setdefault("execution_count", None)
elif "outputs" in cells[cell_index]:
del cells[cell_index]["outputs"]
cells[cell_index].pop("execution_count", None)
nb["cells"] = cells
fp.write_text(json.dumps(nb, indent=1, ensure_ascii=False), encoding="utf-8")
return f"Successfully edited cell {cell_index} in {fp}"
except PermissionError as e:
return f"Error: {e}"
except Exception as e:
return f"Error editing notebook: {e}"
+23 -11
View File
@@ -3,15 +3,21 @@
from pathlib import Path
from nanobot.config.paths import get_media_dir
from nanobot.security.workspace_policy import (
is_path_within,
resolve_allowed_path,
WORKSPACE_BOUNDARY_NOTE = (
" (this is a hard policy boundary, not a transient failure; "
"do not retry with shell tricks or alternative tools, and ask "
"the user how to proceed if the resource is genuinely required)"
)
def is_under(path: Path, directory: Path) -> bool:
"""Return True when path resolves under directory."""
return is_path_within(path, directory)
try:
path.relative_to(directory.resolve())
return True
except ValueError:
return False
def resolve_workspace_path(
@@ -21,10 +27,16 @@ def resolve_workspace_path(
extra_allowed_dirs: list[Path] | None = None,
) -> Path:
"""Resolve path against workspace and enforce allowed directory containment."""
extra_roots = [get_media_dir(), *(extra_allowed_dirs or [])] if allowed_dir else None
return resolve_allowed_path(
path,
workspace=workspace,
allowed_root=allowed_dir,
extra_allowed_roots=extra_roots,
)
p = Path(path).expanduser()
if not p.is_absolute() and workspace:
p = workspace / p
resolved = p.resolve()
if allowed_dir:
media_path = get_media_dir().resolve()
all_dirs = [allowed_dir, media_path, *(extra_allowed_dirs or [])]
if not any(is_under(resolved, d) for d in all_dirs):
raise PermissionError(
f"Path {path} is outside allowed directory {allowed_dir}"
+ WORKSPACE_BOUNDARY_NOTE
)
return resolved
-3
View File
@@ -42,9 +42,6 @@ class RuntimeState(Protocol):
@property
def exec_config(self) -> Any: ...
@property
def workspace_sandbox(self) -> Any: ...
@property
def subagents(self) -> Any: ...
+4 -172
View File
@@ -1,4 +1,4 @@
"""Search tools: file discovery and grep."""
"""Search tools: grep."""
from __future__ import annotations
@@ -12,7 +12,6 @@ from typing import Any, Iterable, TypeVar
from nanobot.agent.tools.filesystem import ListDirTool, _FsTool
_DEFAULT_HEAD_LIMIT = 250
_DEFAULT_FILE_HEAD_LIMIT = 200
T = TypeVar("T")
_TYPE_GLOB_MAP = {
"py": ("*.py", "*.pyi"),
@@ -89,22 +88,13 @@ def _matches_type(name: str, file_type: str | None) -> bool:
return any(fnmatch.fnmatch(name.lower(), pattern.lower()) for pattern in patterns)
def _matches_query(rel_path: str, query: str | None) -> bool:
if not query:
return True
haystack = rel_path.lower()
terms = [part for part in query.lower().split() if part]
return all(term in haystack for term in terms)
class _SearchTool(_FsTool):
_IGNORE_DIRS = set(ListDirTool._IGNORE_DIRS)
def _display_path(self, target: Path, root: Path) -> str:
workspace = self._display_workspace()
if workspace:
if self._workspace:
with suppress(ValueError):
return target.relative_to(workspace).as_posix()
return target.relative_to(self._workspace).as_posix()
return target.relative_to(root).as_posix()
def _iter_files(self, root: Path) -> Iterable[Path]:
@@ -119,163 +109,6 @@ class _SearchTool(_FsTool):
yield current / filename
class FindFilesTool(_SearchTool):
"""Find files by path fragment, glob, or type."""
_scopes = {"core", "subagent"}
@property
def name(self) -> str:
return "find_files"
@property
def description(self) -> str:
return (
"Find files by path fragment, glob, or file type. "
"Use this before read_file when you need to locate files, and "
"prefer it over shell find/ls for ordinary workspace discovery. "
"Returns workspace-relative paths and skips common dependency/build "
"directories."
)
@property
def read_only(self) -> bool:
return True
@property
def parameters(self) -> dict[str, Any]:
return {
"type": "object",
"properties": {
"path": {
"type": "string",
"description": "Directory or file to search in (default '.')",
},
"query": {
"type": "string",
"description": (
"Optional case-insensitive path fragment search. "
"Whitespace-separated terms must all be present."
),
},
"glob": {
"type": "string",
"description": "Optional file filter, e.g. '*.py' or 'tests/**/test_*.py'",
},
"type": {
"type": "string",
"description": "Optional file type shorthand, e.g. 'py', 'ts', 'md', 'json'",
},
"include_dirs": {
"type": "boolean",
"description": "Include matching directories as well as files (default false)",
},
"sort": {
"type": "string",
"enum": ["path", "modified"],
"description": "Sort by path or most recently modified first (default path)",
},
"head_limit": {
"type": "integer",
"description": "Maximum number of paths to return (default 200, 0 for all, max 1000)",
"minimum": 0,
"maximum": 1000,
},
"offset": {
"type": "integer",
"description": "Skip the first N results before applying head_limit",
"minimum": 0,
"maximum": 100000,
},
},
}
def _iter_paths(self, root: Path, *, include_dirs: bool) -> Iterable[Path]:
if root.is_file():
yield root
return
if include_dirs:
yield root
for dirpath, dirnames, filenames in os.walk(root):
dirnames[:] = sorted(d for d in dirnames if d not in self._IGNORE_DIRS)
current = Path(dirpath)
if include_dirs and current != root:
yield current
for filename in sorted(filenames):
yield current / filename
async def execute(
self,
path: str = ".",
query: str | None = None,
glob: str | None = None,
type: str | None = None,
include_dirs: bool = False,
sort: str = "path",
head_limit: int | None = None,
offset: int = 0,
**kwargs: Any,
) -> str:
try:
target = self._resolve(path or ".")
if not target.exists():
return f"Error: Path not found: {path}"
if not (target.is_dir() or target.is_file()):
return f"Error: Unsupported path: {path}"
if sort not in {"path", "modified"}:
return "Error: sort must be 'path' or 'modified'"
limit = (
_DEFAULT_FILE_HEAD_LIMIT
if head_limit is None
else None if head_limit == 0 else head_limit
)
root = target if target.is_dir() else target.parent
matches: list[tuple[str, float]] = []
for candidate in self._iter_paths(target, include_dirs=include_dirs):
if candidate.is_dir() and not include_dirs:
continue
rel_path = candidate.relative_to(root).as_posix()
display_path = self._display_path(candidate, root)
name = candidate.name
if glob and not _match_glob(rel_path, name, glob):
continue
if candidate.is_file() and not _matches_type(name, type):
continue
if candidate.is_dir() and type:
continue
if not _matches_query(display_path, query):
continue
try:
mtime = candidate.stat().st_mtime
except OSError:
mtime = 0.0
suffix = "/" if candidate.is_dir() else ""
matches.append((display_path + suffix, mtime))
if sort == "modified":
matches.sort(key=lambda item: (-item[1], item[0]))
else:
matches.sort(key=lambda item: item[0])
paths = [item[0] for item in matches]
paged, truncated = _paginate(paths, limit, offset)
if not paged:
return "No files found"
result = "\n".join(paged)
note = _pagination_note(limit, offset, truncated)
if note:
result += "\n\n" + note
return result
except PermissionError as e:
return f"Error: {e}"
except Exception as e:
return f"Error finding files: {e}"
class GrepTool(_SearchTool):
"""Search file contents using a regex-like pattern."""
_scopes = {"core", "subagent"}
@@ -292,8 +125,7 @@ class GrepTool(_SearchTool):
return (
"Search file contents with a regex pattern. "
"Default output_mode is files_with_matches (file paths only); "
"use content mode for matching lines with context. Prefer this "
"over shell grep for ordinary workspace searches. "
"use content mode for matching lines with context. "
"Skips binary and files >2 MB. Supports glob/type filtering."
)
+6 -15
View File
@@ -3,18 +3,16 @@
from __future__ import annotations
import time
from typing import TYPE_CHECKING, Any
from typing import Any
from loguru import logger
from nanobot.agent.subagent import SubagentStatus
from nanobot.agent.tools.base import Tool
from nanobot.agent.tools.context import ContextAware, RequestContext
from nanobot.agent.tools.runtime_state import RuntimeState
from nanobot.config.schema import Base
if TYPE_CHECKING:
from nanobot.agent.subagent import SubagentStatus
class MyToolConfig(Base):
"""Self-inspection tool configuration."""
@@ -35,12 +33,6 @@ def _has_real_attr(obj: Any, key: str) -> bool:
return False
def _is_subagent_status(value: Any) -> bool:
from nanobot.agent.subagent import SubagentStatus
return isinstance(value, SubagentStatus)
class MyTool(Tool, ContextAware):
"""Check and set the agent loop's runtime configuration."""
@@ -76,7 +68,6 @@ class MyTool(Tool, ContextAware):
"_current_iteration", # updated by runner only
"exec_config", # inspect allowed (e.g. check sandbox), modify blocked
"web_config", # inspect allowed (e.g. check enable), modify blocked
"workspace_sandbox", # read-only view of workspace enforcement level
})
_DENIED_ATTRS = frozenset({
@@ -223,7 +214,7 @@ class MyTool(Tool, ContextAware):
# ------------------------------------------------------------------
@staticmethod
def _format_status(st: "SubagentStatus", indent: str = " ") -> str:
def _format_status(st: SubagentStatus, indent: str = " ") -> str:
elapsed = time.monotonic() - st.started_at
tool_summary = ", ".join(
f"{e.get('name', '?')}({e.get('status', '?')})" for e in st.tool_events[-5:]
@@ -241,14 +232,14 @@ class MyTool(Tool, ContextAware):
@staticmethod
def _format_value(val: Any, key: str = "") -> str:
if _is_subagent_status(val):
if isinstance(val, SubagentStatus):
header = f"Subagent [{val.task_id}] '{val.label}'"
detail = MyTool._format_status(val, " ")
return f"{header}\n task: {val.task_description}\n{detail}"
# SubagentManager: delegate to its _task_statuses dict
if hasattr(val, "_task_statuses") and isinstance(val._task_statuses, dict):
return MyTool._format_value(val._task_statuses, key)
if isinstance(val, dict) and val and _is_subagent_status(next(iter(val.values()))):
if isinstance(val, dict) and val and isinstance(next(iter(val.values())), SubagentStatus):
prefix = f"{key}: " if key else ""
lines = [f"{prefix}{len(val)} subagent(s):"]
for tid, st in val.items():
@@ -358,7 +349,7 @@ class MyTool(Tool, ContextAware):
parts.append(self._format_value(getattr(state, k, None), k))
parts.append(self._format_value(state.model_preset, "model_preset"))
# Other useful top-level keys shown in description
for k in ("workspace", "provider_retry_mode", "max_tool_result_chars", "_current_iteration", "web_config", "exec_config", "workspace_sandbox", "subagents"):
for k in ("workspace", "provider_retry_mode", "max_tool_result_chars", "_current_iteration", "web_config", "exec_config", "subagents"):
if _has_real_attr(state, k):
parts.append(self._format_value(getattr(state, k, None), k))
# Token usage
+71 -299
View File
@@ -8,7 +8,6 @@ import re
import shutil
import sys
from contextlib import suppress
from dataclasses import dataclass
from pathlib import Path
from typing import Any
@@ -16,27 +15,10 @@ from loguru import logger
from pydantic import Field
from nanobot.agent.tools.base import Tool, tool_parameters
from nanobot.agent.tools.context import current_request_session_key
from nanobot.agent.tools.exec_session import (
DEFAULT_EXEC_SESSION_MANAGER,
DEFAULT_MAX_OUTPUT_CHARS,
DEFAULT_YIELD_MS,
MAX_OUTPUT_CHARS,
MAX_YIELD_MS,
clamp_session_int,
format_session_poll,
)
from nanobot.agent.tools.sandbox import wrap_command
from nanobot.agent.tools.schema import (
BooleanSchema,
IntegerSchema,
StringSchema,
tool_parameters_schema,
)
from nanobot.agent.tools.schema import IntegerSchema, StringSchema, tool_parameters_schema
from nanobot.config.paths import get_media_dir
from nanobot.config.schema import Base
from nanobot.security.workspace_access import current_scope_allows_loopback, current_tool_workspace
from nanobot.security.workspace_policy import is_path_within
_IS_WINDOWS = sys.platform == "win32"
@@ -54,7 +36,7 @@ _WORKSPACE_BOUNDARY_NOTE = (
class ExecToolConfig(Base):
"""Shell exec tool configuration."""
enable: bool = True
timeout: int = Field(default=60, ge=0) # Hard timeout (s); 0 = no limit. Not capped by the per-call max.
timeout: int = 60
path_append: str = ""
sandbox: str = ""
allowed_env_keys: list[str] = Field(default_factory=list)
@@ -62,22 +44,10 @@ class ExecToolConfig(Base):
deny_patterns: list[str] = Field(default_factory=list)
@dataclass(slots=True)
class _PreparedCommand:
command: str
cwd: str
env: dict[str, str]
timeout: int | None
shell_program: str | None
login: bool
@tool_parameters(
tool_parameters_schema(
command=StringSchema("The shell command to execute"),
cmd=StringSchema("Compatibility alias for command"),
working_dir=StringSchema("Optional working directory for the command"),
workdir=StringSchema("Compatibility alias for working_dir"),
timeout=IntegerSchema(
60,
description=(
@@ -87,44 +57,7 @@ class _PreparedCommand:
minimum=1,
maximum=600,
),
shell=StringSchema(
"Optional shell binary to launch. On Unix, supports sh, bash, or zsh.",
nullable=True,
),
login=BooleanSchema(
description="Whether to run bash/zsh with login shell semantics (default true).",
default=True,
nullable=True,
),
yield_time_ms=IntegerSchema(
description=(
"Optional milliseconds to wait before returning output. "
"When set, a still-running command returns a session_id that "
"can be polled or written to with write_stdin. Omit this field "
"to keep one-shot exec behavior."
),
minimum=0,
maximum=MAX_YIELD_MS,
nullable=True,
),
max_output_chars=IntegerSchema(
description=(
"Maximum output characters to return when yield_time_ms is used "
"(default 10000, max 50000)."
),
minimum=1000,
maximum=MAX_OUTPUT_CHARS,
nullable=True,
),
max_output_tokens=IntegerSchema(
description=(
"Compatibility alias for max_output_chars. The current runtime "
"uses a character budget."
),
minimum=1000,
maximum=MAX_OUTPUT_CHARS,
nullable=True,
),
required=["command"],
)
)
class ExecTool(Tool):
@@ -148,7 +81,6 @@ class ExecTool(Tool):
working_dir=ctx.workspace,
timeout=cfg.timeout,
restrict_to_workspace=ctx.config.restrict_to_workspace,
webui_allow_local_service_access=ctx.config.webui_allow_local_service_access,
sandbox=cfg.sandbox,
path_append=cfg.path_append,
allowed_env_keys=cfg.allowed_env_keys,
@@ -163,12 +95,9 @@ class ExecTool(Tool):
deny_patterns: list[str] | None = None,
allow_patterns: list[str] | None = None,
restrict_to_workspace: bool = False,
webui_allow_local_service_access: bool = True,
allow_local_preview_access: bool | None = None,
sandbox: str = "",
path_append: str = "",
allowed_env_keys: list[str] | None = None,
session_manager: Any | None = None,
):
self.timeout = timeout
self.working_dir = working_dir
@@ -194,12 +123,8 @@ class ExecTool(Tool):
]
self.allow_patterns = allow_patterns or []
self.restrict_to_workspace = restrict_to_workspace
if allow_local_preview_access is not None:
webui_allow_local_service_access = allow_local_preview_access
self.webui_allow_local_service_access = webui_allow_local_service_access
self.path_append = path_append
self.allowed_env_keys = allowed_env_keys or []
self._session_manager = session_manager or DEFAULT_EXEC_SESSION_MANAGER
@property
def name(self) -> str:
@@ -225,15 +150,10 @@ class ExecTool(Tool):
def description(self) -> str:
return (
"Execute a shell command and return its output. "
"Use this for tests, builds, package commands, git commands, and "
"other process execution. Prefer read_file/find_files/grep for "
"inspection and apply_patch/write_file/edit_file for file changes "
"instead of cat, shell find/grep, echo, or sed. "
"Prefer read_file/write_file/edit_file over cat/echo/sed, "
"and grep/glob over shell find/grep. "
"Use -y or --yes flags to avoid interactive prompts. "
"For long-running or interactive commands, pass yield_time_ms; "
"if the command keeps running, exec returns a session_id that can "
"be polled or written to with write_stdin. Output is truncated at "
"10 000 chars; timeout defaults to 60s."
"Output is truncated at 10 000 chars; timeout defaults to 60s."
)
@property
@@ -241,45 +161,67 @@ class ExecTool(Tool):
return True
async def execute(
self, command: str | None = None, cmd: str | None = None,
working_dir: str | None = None, workdir: str | None = None,
timeout: int | None = None, shell: str | None = None,
login: bool | None = None, yield_time_ms: int | None = None,
max_output_chars: int | None = None,
max_output_tokens: int | None = None,
**kwargs: Any,
self, command: str, working_dir: str | None = None,
timeout: int | None = None, **kwargs: Any,
) -> str:
command = command or cmd
working_dir = working_dir or workdir
if not command:
return "Error: Missing command. Provide command or cmd."
if max_output_chars is None:
max_output_chars = max_output_tokens
cwd = working_dir or self.working_dir or os.getcwd()
prepared = self._prepare_command(command, working_dir, timeout, shell, login)
if isinstance(prepared, str):
return prepared
# Prevent an LLM-supplied working_dir from escaping the configured
# workspace when restrict_to_workspace is enabled (#2826). Without
# this, a caller can pass working_dir="/etc" and then all absolute
# paths under /etc would pass the _guard_command check that anchors
# on cwd.
if self.restrict_to_workspace and self.working_dir:
try:
requested = Path(cwd).expanduser().resolve()
workspace_root = Path(self.working_dir).expanduser().resolve()
except Exception:
return (
"Error: working_dir could not be resolved"
+ _WORKSPACE_BOUNDARY_NOTE
)
if requested != workspace_root and workspace_root not in requested.parents:
return (
"Error: working_dir is outside the configured workspace"
+ _WORKSPACE_BOUNDARY_NOTE
)
if yield_time_ms is not None:
return await self._execute_session(prepared, yield_time_ms, max_output_chars)
guard_error = self._guard_command(command, cwd)
if guard_error:
return guard_error
if self.sandbox:
if _IS_WINDOWS:
logger.warning(
"Sandbox '{}' is not supported on Windows; running unsandboxed",
self.sandbox,
)
else:
workspace = self.working_dir or cwd
command = wrap_command(self.sandbox, command, workspace, cwd)
cwd = str(Path(workspace).resolve())
effective_timeout = min(timeout or self.timeout, self._MAX_TIMEOUT)
env = self._build_env()
if self.path_append:
if _IS_WINDOWS:
env["PATH"] = env.get("PATH", "") + os.pathsep + self.path_append
else:
env["NANOBOT_PATH_APPEND"] = self.path_append
command = f'export PATH="$PATH{os.pathsep}$NANOBOT_PATH_APPEND"; {command}'
try:
process = await self._spawn(
prepared.command,
prepared.cwd,
prepared.env,
prepared.shell_program,
prepared.login,
)
process = await self._spawn(command, cwd, env)
try:
stdout, stderr = await asyncio.wait_for(
process.communicate(),
timeout=prepared.timeout,
timeout=effective_timeout,
)
except asyncio.TimeoutError:
await self._kill_process(process)
return f"Error: Command timed out after {prepared.timeout} seconds"
return f"Error: Command timed out after {effective_timeout} seconds"
except asyncio.CancelledError:
await self._kill_process(process)
raise
@@ -298,7 +240,7 @@ class ExecTool(Tool):
result = "\n".join(output_parts) if output_parts else "(no output)"
max_len = clamp_session_int(max_output_chars, self._MAX_OUTPUT, 1000, MAX_OUTPUT_CHARS)
max_len = self._MAX_OUTPUT
if len(result) > max_len:
half = max_len // 2
result = (
@@ -312,192 +254,32 @@ class ExecTool(Tool):
except Exception as e:
return f"Error executing command: {str(e)}"
async def _execute_session(
self,
prepared: _PreparedCommand,
yield_time_ms: int | None,
max_output_chars: int | None,
) -> str:
try:
session_id, poll = await self._session_manager.start(
command=prepared.command,
cwd=prepared.cwd,
env=prepared.env,
timeout=prepared.timeout,
shell_program=prepared.shell_program,
login=prepared.login,
yield_time_ms=clamp_session_int(yield_time_ms, DEFAULT_YIELD_MS, 0, MAX_YIELD_MS),
owner_session_key=current_request_session_key(),
max_output_chars=clamp_session_int(
max_output_chars,
DEFAULT_MAX_OUTPUT_CHARS,
1000,
MAX_OUTPUT_CHARS,
),
)
return format_session_poll(session_id, poll)
except Exception as exc:
return f"Error executing command: {exc}"
def _resolve_timeout(self, timeout: int | None) -> int | None:
"""Resolve the effective hard timeout in seconds (None = no limit).
A per-call timeout supplied by the model stays capped at _MAX_TIMEOUT so
the LLM cannot request unbounded execution. The config-level default
(self.timeout) may exceed that cap, and 0 disables the limit entirely
for trusted long-running tasks (#3595).
"""
if timeout:
return min(timeout, self._MAX_TIMEOUT)
if self.timeout and self.timeout > 0:
return self.timeout
return None
def _prepare_command(
self,
command: str,
working_dir: str | None = None,
timeout: int | None = None,
shell: str | None = None,
login: bool | None = None,
) -> _PreparedCommand | str:
access = current_tool_workspace(
self.working_dir,
restrict_to_workspace=self.restrict_to_workspace,
sandbox_restricts_workspace=bool(self.sandbox),
)
workspace_root = str(access.project_path) if access.project_path is not None else self.working_dir
cwd = working_dir or workspace_root or os.getcwd()
# Prevent an LLM-supplied working_dir from escaping the configured
# workspace when restrict_to_workspace is enabled (#2826). Without
# this, a caller can pass working_dir="/etc" and then all absolute
# paths under /etc would pass the _guard_command check that anchors
# on cwd.
if access.restrict_to_workspace and workspace_root:
try:
requested = Path(cwd).expanduser().resolve()
resolved_root = Path(workspace_root).expanduser().resolve()
except Exception:
return (
"Error: working_dir could not be resolved"
+ _WORKSPACE_BOUNDARY_NOTE
)
if not is_path_within(requested, resolved_root):
return (
"Error: working_dir is outside the configured workspace"
+ _WORKSPACE_BOUNDARY_NOTE
)
guard_error = self._guard_command(
command,
cwd,
restrict_to_workspace=access.restrict_to_workspace,
)
if guard_error:
return guard_error
if self.sandbox:
if _IS_WINDOWS:
logger.warning(
"Sandbox '{}' is not supported on Windows; running unsandboxed",
self.sandbox,
)
else:
workspace = workspace_root or cwd
command = wrap_command(self.sandbox, command, workspace, cwd)
cwd = str(Path(workspace).resolve())
effective_timeout = self._resolve_timeout(timeout)
env = self._build_env()
if self.path_append:
if _IS_WINDOWS:
env["PATH"] = env.get("PATH", "") + os.pathsep + self.path_append
else:
env["NANOBOT_PATH_APPEND"] = self.path_append
command = f'export PATH="$PATH{os.pathsep}$NANOBOT_PATH_APPEND"; {command}'
shell_program, shell_error = self._resolve_shell(shell)
if shell_error:
return shell_error
return _PreparedCommand(
command=command,
cwd=cwd,
env=env,
timeout=effective_timeout,
shell_program=shell_program,
login=True if login is None else login,
)
@staticmethod
async def _spawn(
command: str, cwd: str, env: dict[str, str],
shell_program: str | None = None,
login: bool = True,
*,
stdin: int = asyncio.subprocess.DEVNULL,
) -> asyncio.subprocess.Process:
"""Launch *command* in a platform-appropriate shell."""
if _IS_WINDOWS:
if "\n" in command:
return await asyncio.create_subprocess_exec(
"powershell", "-NoProfile", "-Command", command,
stdin=stdin,
stdout=asyncio.subprocess.PIPE,
stderr=asyncio.subprocess.PIPE,
cwd=cwd,
env=env,
)
# create_subprocess_exec re-quotes args via list2cmdline, which
# breaks commands containing paths with spaces (e.g. "D:\Program
# Files\python.exe" "script.py"). create_subprocess_shell passes
# the raw command string to COMSPEC without re-quoting.
return await asyncio.create_subprocess_shell(
command,
stdin=stdin,
stdout=asyncio.subprocess.PIPE,
stderr=asyncio.subprocess.PIPE,
cwd=cwd,
env=env,
)
shell_program = shell_program or shutil.which("bash") or "/bin/bash"
args = [shell_program]
shell_name = Path(shell_program).name.lower()
if login and shell_name in {"bash", "bash.exe", "zsh", "zsh.exe"}:
args.append("-l")
args.extend(["-c", command])
bash = shutil.which("bash") or "/bin/bash"
return await asyncio.create_subprocess_exec(
*args,
stdin=stdin,
bash, "-l", "-c", command,
stdout=asyncio.subprocess.PIPE,
stderr=asyncio.subprocess.PIPE,
cwd=cwd,
env=env,
)
@staticmethod
def _resolve_shell(shell: str | None) -> tuple[str | None, str | None]:
if not shell:
return None, None
if _IS_WINDOWS:
return None, "Error: shell parameter is not supported on Windows"
if "\0" in shell or "\n" in shell or "\r" in shell:
return None, "Error: shell contains invalid characters"
allowed = {"sh", "bash", "zsh"}
path = Path(shell).expanduser()
if path.is_absolute():
if path.name not in allowed:
return None, f"Error: unsupported shell {shell!r}. Allowed: bash, sh, zsh"
if not path.is_file() or not os.access(path, os.X_OK):
return None, f"Error: shell is not executable: {shell}"
return str(path), None
if "/" in shell or "\\" in shell:
return None, "Error: shell must be a shell name or absolute path"
if shell not in allowed:
return None, f"Error: unsupported shell {shell!r}. Allowed: bash, sh, zsh"
resolved = shutil.which(shell)
if not resolved:
return None, f"Error: shell not found: {shell}"
return resolved, None
@staticmethod
async def _kill_process(process: asyncio.subprocess.Process) -> None:
"""Kill a subprocess and reap it to prevent zombies."""
@@ -560,13 +342,7 @@ class ExecTool(Tool):
env[key] = val
return env
def _guard_command(
self,
command: str,
cwd: str,
*,
restrict_to_workspace: bool | None = None,
) -> str | None:
def _guard_command(self, command: str, cwd: str) -> str | None:
"""Best-effort safety guard for potentially destructive commands."""
cmd = command.strip()
lower = cmd.lower()
@@ -586,17 +362,11 @@ class ExecTool(Tool):
return "Error: Command blocked by allowlist filter (not in allowlist)"
from nanobot.security.network import contains_internal_url
if contains_internal_url(
cmd,
allow_loopback=current_scope_allows_loopback(
enabled=self.webui_allow_local_service_access,
),
):
if contains_internal_url(cmd):
# The runner turns this marker into a non-retryable security hint.
return "Error: Command blocked by safety guard (internal/private URL detected)"
should_restrict = self.restrict_to_workspace if restrict_to_workspace is None else restrict_to_workspace
if should_restrict:
if self.restrict_to_workspace:
if "..\\" in cmd or "../" in cmd:
return (
"Error: Command blocked by safety guard (path traversal detected)"
@@ -621,9 +391,11 @@ class ExecTool(Tool):
continue
media_path = get_media_dir().resolve()
if p.is_absolute() and not (
is_path_within(p, cwd_path)
or is_path_within(p, media_path)
if (p.is_absolute()
and cwd_path not in p.parents
and p != cwd_path
and media_path not in p.parents
and p != media_path
):
return (
"Error: Command blocked by safety guard (path outside working dir)"
@@ -644,7 +416,7 @@ class ExecTool(Tool):
# Windows: match drive-root paths like `C:\` as well as `C:\path\to\file`, and UNC paths like `\\server\share`
# NOTE: `*` is required so `C:\` (nothing after the slash) is still extracted.
win_paths = re.findall(
r"(?<![A-Za-z])(?:[A-Za-z]:[^\s\"'|><;]*|\\\\[^\s\"'|><;]+(?:\\[^\s\"'|><;]+)*)",
r"(?:[A-Za-z]:[^\s\"'|><;]*|\\\\[^\s\"'|><;]+(?:\\[^\s\"'|><;]+)*)",
command
)
posix_paths = re.findall(r"(?:^|[\s|>'\"])(/[^\s\"'>;|<]+)", command) # POSIX: /absolute only
+2 -20
View File
@@ -7,8 +7,7 @@ from typing import TYPE_CHECKING, Any
from nanobot.agent.tools.base import Tool, tool_parameters
from nanobot.agent.tools.context import ContextAware, RequestContext
from nanobot.agent.tools.schema import NumberSchema, StringSchema, tool_parameters_schema
from nanobot.security.workspace_access import current_workspace_scope
from nanobot.agent.tools.schema import StringSchema, tool_parameters_schema
if TYPE_CHECKING:
from nanobot.agent.subagent import SubagentManager
@@ -18,15 +17,6 @@ if TYPE_CHECKING:
tool_parameters_schema(
task=StringSchema("The task for the subagent to complete"),
label=StringSchema("Optional short label for the task (for display)"),
temperature=NumberSchema(
description=(
"Optional sampling temperature for the subagent "
"(0.0 = deterministic, higher = more creative). "
"Defaults to the provider's configured temperature."
),
minimum=0.0,
maximum=2.0,
),
required=["task"],
)
)
@@ -68,13 +58,7 @@ class SpawnTool(Tool, ContextAware):
"and use a dedicated subdirectory when helpful."
)
async def execute(
self,
task: str,
label: str | None = None,
temperature: float | None = None,
**kwargs: Any,
) -> str:
async def execute(self, task: str, label: str | None = None, **kwargs: Any) -> str:
"""Spawn a subagent to execute the given task."""
running = self._manager.get_running_count()
limit = self._manager.max_concurrent_subagents
@@ -91,6 +75,4 @@ class SpawnTool(Tool, ContextAware):
origin_chat_id=self._origin_chat_id.get(),
session_key=self._session_key.get(),
origin_message_id=self._origin_message_id.get(),
temperature=temperature,
workspace_scope=current_workspace_scope(),
)
+24 -104
View File
@@ -8,7 +8,7 @@ import json
import os
import re
from typing import Any, Callable
from urllib.parse import quote, urljoin, urlparse
from urllib.parse import quote, urlparse
import httpx
from loguru import logger
@@ -78,82 +78,9 @@ def _validate_url(url: str) -> tuple[bool, str]:
def _validate_url_safe(url: str) -> tuple[bool, str]:
"""Validate URL with SSRF protection: scheme, domain, and resolved IP check."""
from nanobot.security.network import validate_url_target
return validate_url_target(url)
async def _get_with_safe_redirects(
client: httpx.AsyncClient,
url: str,
headers: dict[str, str] | None = None,
) -> tuple[httpx.Response | None, str | None]:
"""GET a URL while validating every redirect target before requesting it."""
current_url = url
for _ in range(MAX_REDIRECTS + 1):
is_valid, error_msg = _validate_url_safe(current_url)
if not is_valid:
return None, f"Redirect blocked: {error_msg}"
response = await client.get(current_url, headers=headers, follow_redirects=False)
is_redirect = 300 <= response.status_code < 400
if not is_redirect:
return response, None
location = response.headers.get("location")
if not location:
return response, None
next_url = urljoin(str(response.url), location)
is_valid, error_msg = _validate_url_safe(next_url)
if not is_valid:
await response.aclose()
return None, f"Redirect blocked: {error_msg}"
await response.aclose()
current_url = next_url
return None, f"Too many redirects: exceeded limit of {MAX_REDIRECTS}"
async def _stream_with_safe_redirects(
client: httpx.AsyncClient,
url: str,
headers: dict[str, str] | None = None,
) -> tuple[httpx.Response | None, Any | None, str | None]:
"""Open a streamed response while validating every redirect target first."""
current_url = url
for _ in range(MAX_REDIRECTS + 1):
is_valid, error_msg = _validate_url_safe(current_url)
if not is_valid:
return None, None, f"Redirect blocked: {error_msg}"
stream = client.stream(
"GET",
current_url,
headers=headers,
follow_redirects=False,
)
response = await stream.__aenter__()
is_redirect = 300 <= response.status_code < 400
if not is_redirect:
return response, stream, None
location = response.headers.get("location")
if not location:
return response, stream, None
next_url = urljoin(str(response.url), location)
is_valid, error_msg = _validate_url_safe(next_url)
if not is_valid:
await stream.__aexit__(None, None, None)
return None, None, f"Redirect blocked: {error_msg}"
await stream.__aexit__(None, None, None)
current_url = next_url
return None, None, f"Too many redirects: exceeded limit of {MAX_REDIRECTS}"
def _format_results(query: str, items: list[dict[str, Any]], n: int) -> str:
"""Format provider results into shared plaintext output."""
if not items:
@@ -455,16 +382,17 @@ class WebSearchTool(Tool):
return await self._search_duckduckgo(query, n)
try:
async with httpx.AsyncClient(proxy=self.proxy) as client:
r = await client.post(
"https://kagi.com/api/v1/search",
json={"query": query, "limit": n},
headers={"Authorization": f"Bearer {api_key}", "User-Agent": self.user_agent},
r = await client.get(
"https://kagi.com/api/v0/search",
params={"q": query, "limit": n},
headers={"Authorization": f"Bot {api_key}", "User-Agent": self.user_agent},
timeout=10.0,
)
r.raise_for_status()
# t=0 items are search results; other values are related searches, etc.
items = [
{"title": d.get("title", ""), "url": d.get("url", ""), "content": d.get("snippet", "")}
for d in r.json().get("data", {}).get("search", [])
for d in r.json().get("data", []) if d.get("t") == 0
]
return _format_results(query, items, n)
except Exception as e:
@@ -560,26 +488,19 @@ class WebFetchTool(Tool):
# Detect and fetch images directly to avoid Jina's textual image captioning
try:
async with httpx.AsyncClient(proxy=self.proxy, timeout=15.0) as client:
r, stream, redirect_error = await _stream_with_safe_redirects(
client,
url,
headers={"User-Agent": self.user_agent},
)
if redirect_error:
return json.dumps({"error": redirect_error, "url": url}, ensure_ascii=False)
if r is None:
return json.dumps({"error": "Fetch failed", "url": url}, ensure_ascii=False)
async with httpx.AsyncClient(proxy=self.proxy, follow_redirects=True, max_redirects=MAX_REDIRECTS, timeout=15.0) as client:
async with client.stream("GET", url, headers={"User-Agent": self.user_agent}) as r:
from nanobot.security.network import validate_resolved_url
redir_ok, redir_err = validate_resolved_url(str(r.url))
if not redir_ok:
return json.dumps({"error": f"Redirect blocked: {redir_err}", "url": url}, ensure_ascii=False)
try:
ctype = r.headers.get("content-type", "")
if ctype.startswith("image/"):
r.raise_for_status()
raw = await r.aread()
return build_image_content_blocks(raw, ctype, url, f"(Image fetched from: {url})")
finally:
if stream is not None:
await stream.__aexit__(None, None, None)
except Exception as e:
logger.debug("Pre-fetch image detection failed for {}: {}", url, e)
@@ -628,22 +549,23 @@ class WebFetchTool(Tool):
async def _fetch_readability(self, url: str, extract_mode: str, max_chars: int) -> Any:
"""Local fallback using readability-lxml."""
from readability import Document
try:
async with httpx.AsyncClient(
follow_redirects=True,
max_redirects=MAX_REDIRECTS,
timeout=30.0,
proxy=self.proxy,
) as client:
r, redirect_error = await _get_with_safe_redirects(
client,
url,
headers={"User-Agent": self.user_agent},
)
if redirect_error:
return json.dumps({"error": redirect_error, "url": url}, ensure_ascii=False)
if r is None:
return json.dumps({"error": "Fetch failed", "url": url}, ensure_ascii=False)
r = await client.get(url, headers={"User-Agent": self.user_agent})
r.raise_for_status()
from nanobot.security.network import validate_resolved_url
redir_ok, redir_err = validate_resolved_url(str(r.url))
if not redir_ok:
return json.dumps({"error": f"Redirect blocked: {redir_err}", "url": url}, ensure_ascii=False)
ctype = r.headers.get("content-type", "")
if ctype.startswith("image/"):
return build_image_content_blocks(r.content, ctype, url, f"(Image fetched from: {url})")
@@ -651,8 +573,6 @@ class WebFetchTool(Tool):
if "application/json" in ctype:
text, extractor = json.dumps(r.json(), indent=2, ensure_ascii=False), "json"
elif "text/html" in ctype or r.text[:256].lower().startswith(("<!doctype", "<html")):
from readability import Document
doc = Document(r.text)
content = self._to_markdown(doc.summary()) if extract_mode == "markdown" else _strip_tags(doc.summary())
text = f"# {doc.title()}\n\n{content}" if doc.title() else content
-5
View File
@@ -1,5 +0,0 @@
"""Shared app protocol helpers."""
from nanobot.apps.protocol import APP_PROTOCOL_SCHEMA, app_manifest
__all__ = ["APP_PROTOCOL_SCHEMA", "app_manifest"]
-13
View File
@@ -1,13 +0,0 @@
"""CLI app adapter for the unified Apps domain."""
from nanobot.apps.cli.service import (
CliAppError,
CliAppManager,
CliAppsRuntimeConfig,
)
__all__ = [
"CliAppError",
"CliAppManager",
"CliAppsRuntimeConfig",
]
File diff suppressed because it is too large Load Diff
-62
View File
@@ -1,62 +0,0 @@
"""CLI Apps helpers shared by the agent loop and settings surfaces."""
from __future__ import annotations
from pathlib import Path
from typing import Any, Mapping
def session_extra(metadata: Mapping[str, Any] | None) -> dict[str, Any]:
"""Return persisted session kwargs for CLI app attachments."""
cli_apps = metadata.get("cli_apps") if isinstance(metadata, Mapping) else None
return {"cli_apps": cli_apps} if isinstance(cli_apps, list) and cli_apps else {}
def runtime_lines(message: Any, workspace: Path, *, skip: bool = False) -> list[str]:
"""Return model-visible CLI app annotations for the current turn."""
if skip:
return []
text = message.content if isinstance(getattr(message, "content", None), str) else ""
metadata = message.metadata if isinstance(getattr(message, "metadata", None), Mapping) else None
return _cli_app_runtime_lines(text, metadata, workspace)
def _cli_app_runtime_lines(
text: str,
metadata: Mapping[str, Any] | None,
workspace: Path,
) -> list[str]:
structured = metadata.get("cli_apps") if isinstance(metadata, Mapping) else None
if isinstance(structured, list):
mentions = [
item for item in structured
if isinstance(item, Mapping) and isinstance(item.get("name"), str)
]
if mentions:
return [
"CLI App Attachment: "
f"@{str(item['name']).strip().lower()} "
f"(installed; tool=run_cli_app; "
f"entry_point={str(item.get('entry_point') or 'unknown')}; "
f"skill=skills/cli-app-{str(item['name']).strip().lower()}/SKILL.md). "
"Read the skill when useful, then run this app with `run_cli_app`; do not bypass it with shell."
for item in mentions
if str(item.get("name") or "").strip()
]
if "@" not in text:
return []
try:
from nanobot.apps.cli import CliAppManager
mentions = CliAppManager(workspace=workspace).mentioned_installed_apps(text)
except Exception:
return []
return [
"CLI App Mention: "
f"@{item['name']} "
f"(installed; tool={item['tool']}; "
f"entry_point={item['entry_point'] or 'unknown'}; "
f"skill={item['skill']}). "
"Read the skill when useful, then run this app with `run_cli_app`; do not bypass it with shell."
for item in mentions
]
-56
View File
@@ -1,56 +0,0 @@
"""Neutral manifest shape for settings-managed agent apps.
The manifest is intentionally descriptive. Installers still live in their
own adapters, while this protocol gives the WebUI and future registries one
small vocabulary for capabilities, trust, and verified install/remove plans.
"""
from __future__ import annotations
from typing import Any
APP_PROTOCOL_SCHEMA = "agent-app.v1"
def compact_dict(values: dict[str, Any]) -> dict[str, Any]:
"""Drop empty optional values while preserving explicit booleans and zeros."""
return {
key: value
for key, value in values.items()
if value is not None and value != "" and value != [] and value != {}
}
def app_manifest(
*,
app_id: str,
display_name: str,
description: str,
category: str,
source: str,
capabilities: list[dict[str, Any]],
install: dict[str, Any],
remove: dict[str, Any],
trust: dict[str, Any],
version: str | None = None,
logo_url: str | None = None,
brand_color: str | None = None,
docs_url: str | None = None,
) -> dict[str, Any]:
"""Build a stable app manifest dictionary."""
return compact_dict({
"schema": APP_PROTOCOL_SCHEMA,
"id": app_id,
"display_name": display_name,
"version": version,
"description": description,
"category": category,
"source": source,
"logo_url": logo_url,
"brand_color": brand_color,
"docs_url": docs_url,
"capabilities": capabilities,
"install": install,
"remove": remove,
"trust": trust,
})
+1 -6
View File
@@ -9,12 +9,6 @@ from typing import Any
# render it and other channels may ignore unknown keys.
OUTBOUND_META_AGENT_UI = "_agent_ui"
# Internal-only inbound metadata used by in-process channels to ask the agent
# loop to update runtime state without going through a user session.
INBOUND_META_RUNTIME_CONTROL = "_runtime_control"
RUNTIME_CONTROL_ACK = "_ack"
RUNTIME_CONTROL_MCP_RELOAD = "mcp_reload"
@dataclass
class InboundMessage:
@@ -51,3 +45,4 @@ class OutboundMessage:
media: list[str] = field(default_factory=list)
metadata: dict[str, Any] = field(default_factory=dict)
buttons: list[list[str]] = field(default_factory=list)
-10
View File
@@ -207,16 +207,6 @@ if DISCORD_AVAILABLE:
) -> None:
await self._forward_slash_command(interaction, _command_text)
@self.tree.command(name="model", description="Show or switch runtime model preset")
@app_commands.describe(preset="Optional model preset name, such as default")
async def model_command(
interaction: discord.Interaction,
preset: str | None = None,
) -> None:
preset = (preset or "").strip()
command_text = f"/model {preset}" if preset else "/model"
await self._forward_slash_command(interaction, command_text)
@self.tree.command(name="help", description="Show available commands")
async def help_command(interaction: discord.Interaction) -> None:
sender_id = str(interaction.user.id)
+32 -28
View File
@@ -172,19 +172,22 @@ def _extract_element_content(element: dict) -> list[str]:
return parts
def _extract_post_content(content_json: dict) -> tuple[str, list[str]]:
"""Extract text and image keys from Feishu post (rich text) message.
def _extract_post_content(content_json: dict) -> tuple[str, list[str], list[dict]]:
"""Extract text and media info from Feishu post (rich text) message.
Handles three payload shapes:
- Direct: {"title": "...", "content": [[...]]}
- Localized: {"zh_cn": {"title": "...", "content": [...]}}
- Wrapped: {"post": {"zh_cn": {"title": "...", "content": [...]}}}
Returns (text, image_keys, media_items) where media_items is a list of
{"tag": "media", "file_key": "..."} dicts for video/file attachments.
"""
def _parse_block(block: dict) -> tuple[str | None, list[str]]:
def _parse_block(block: dict) -> tuple[str | None, list[str], list[dict]]:
if not isinstance(block, dict) or not isinstance(block.get("content"), list):
return None, []
texts, images = [], []
return None, [], []
texts, images, medias = [], [], []
if title := block.get("title"):
texts.append(title)
for row in block["content"]:
@@ -204,43 +207,36 @@ def _extract_post_content(content_json: dict) -> tuple[str, list[str]]:
texts.append(f"\n```{lang}\n{code_text}\n```\n")
elif tag == "img" and (key := el.get("image_key")):
images.append(key)
return (" ".join(texts).strip() or None), images
elif tag == "media" and el.get("file_key"):
medias.append({"tag": "media", "file_key": el["file_key"]})
return (" ".join(texts).strip() or None), images, medias
# Unwrap optional {"post": ...} envelope
root = content_json
if isinstance(root, dict) and isinstance(root.get("post"), dict):
root = root["post"]
if not isinstance(root, dict):
return "", []
return "", [], []
# Direct format
if "content" in root:
text, imgs = _parse_block(root)
if text or imgs:
return text or "", imgs
text, imgs, medias = _parse_block(root)
if text or imgs or medias:
return text or "", imgs, medias
# Localized: prefer known locales, then fall back to any dict child
for key in ("zh_cn", "en_us", "ja_jp"):
if key in root:
text, imgs = _parse_block(root[key])
if text or imgs:
return text or "", imgs
text, imgs, medias = _parse_block(root[key])
if text or imgs or medias:
return text or "", imgs, medias
for val in root.values():
if isinstance(val, dict):
text, imgs = _parse_block(val)
if text or imgs:
return text or "", imgs
text, imgs, medias = _parse_block(val)
if text or imgs or medias:
return text or "", imgs, medias
return "", []
def _extract_post_text(content_json: dict) -> str:
"""Extract plain text from Feishu post (rich text) message content.
Legacy wrapper for _extract_post_content, returns only text.
"""
text, _ = _extract_post_content(content_json)
return text
return "", [], []
class FeishuConfig(Base):
@@ -1156,7 +1152,7 @@ class FeishuChannel(BaseChannel):
if msg_type == "text":
text = content_json.get("text", "").strip()
elif msg_type == "post":
text, _ = _extract_post_content(content_json)
text, _, _ = _extract_post_content(content_json)
text = text.strip()
else:
text = ""
@@ -1751,7 +1747,7 @@ class FeishuChannel(BaseChannel):
content_parts.append(text)
elif msg_type == "post":
text, image_keys = _extract_post_content(content_json)
text, image_keys, media_items = _extract_post_content(content_json)
if text:
content_parts.append(text)
# Download images embedded in post
@@ -1762,6 +1758,14 @@ class FeishuChannel(BaseChannel):
if file_path:
media_paths.append(file_path)
content_parts.append(content_text)
# Download media (video/file) embedded in post
for media_item in media_items:
file_path, content_text = await self._download_and_save_media(
"media", media_item, message_id
)
if file_path:
media_paths.append(file_path)
content_parts.append(content_text)
elif msg_type in ("image", "audio", "file", "media"):
file_path, content_text = await self._download_and_save_media(
+8 -30
View File
@@ -57,17 +57,11 @@ class ChannelManager:
*,
session_manager: "SessionManager | None" = None,
webui_runtime_model_name: Callable[[], str | None] | None = None,
webui_static_dist: bool = True,
webui_runtime_surface: str = "browser",
webui_runtime_capabilities: dict[str, Any] | None = None,
):
self.config = config
self.bus = bus
self._session_manager = session_manager
self._webui_runtime_model_name = webui_runtime_model_name
self._webui_static_dist = webui_static_dist
self._webui_runtime_surface = webui_runtime_surface
self._webui_runtime_capabilities = dict(webui_runtime_capabilities or {})
self.channels: dict[str, BaseChannel] = {}
self._dispatch_task: asyncio.Task | None = None
self._origin_reply_fingerprints: dict[tuple[str, str, str], str] = {}
@@ -76,52 +70,36 @@ class ChannelManager:
def _init_channels(self) -> None:
"""Initialize channels discovered via pkgutil scan + entry_points plugins."""
from nanobot.channels.registry import discover_channel_names, discover_enabled
from nanobot.channels.registry import discover_all
transcription_provider = self.config.channels.transcription_provider
transcription_key = self._resolve_transcription_key(transcription_provider)
transcription_base = self._resolve_transcription_base(transcription_provider)
transcription_language = self.config.channels.transcription_language
# Collect enabled module names first, then only import those.
# Channel configs live in ChannelsConfig's extra fields (via
# extra="allow"), so we enumerate candidates from pkgutil scan
# (cheap, no imports) and any plugin keys in __pydantic_extra__.
names = discover_channel_names()
candidate_names = set(names)
extra = getattr(self.config.channels, "__pydantic_extra__", None) or {}
candidate_names.update(extra.keys())
enabled_names: set[str] = set()
for name in candidate_names:
for name, cls in discover_all().items():
section = getattr(self.config.channels, name, None)
if section is None:
continue
if (
enabled = (
section.get("enabled", False)
if isinstance(section, dict)
else getattr(section, "enabled", False)
):
enabled_names.add(name)
for name, cls in discover_enabled(enabled_names, _names=names).items():
section = getattr(self.config.channels, name, None)
if section is None:
)
if not enabled:
continue
try:
kwargs: dict[str, Any] = {}
# Only the WebSocket channel currently hosts the embedded webui
# surface; other channels stay oblivious to these knobs.
if cls.name == "websocket":
if self._session_manager is not None:
kwargs["session_manager"] = self._session_manager
static_path = _default_webui_dist() if self._webui_static_dist else None
static_path = _default_webui_dist()
if static_path is not None:
kwargs["static_dist_path"] = static_path
kwargs["workspace_path"] = self.config.workspace_path
kwargs["restrict_to_workspace"] = self.config.tools.restrict_to_workspace
if self._webui_runtime_model_name is not None:
kwargs["runtime_model_name"] = self._webui_runtime_model_name
kwargs["runtime_surface"] = self._webui_runtime_surface
kwargs["runtime_capabilities_overrides"] = self._webui_runtime_capabilities
channel = cls(section, self.bus, **kwargs)
channel.transcription_provider = transcription_provider
channel.transcription_api_key = transcription_key
+28 -60
View File
@@ -8,23 +8,21 @@ from contextlib import suppress
from dataclasses import dataclass
from pathlib import Path
from typing import Any, Literal, TypeAlias
from urllib.parse import quote, urlparse
from pydantic import Field
from nanobot.security.workspace_policy import is_path_within
try:
import aiohttp
import nh3
from mistune import create_markdown
from nio import (
AsyncClient,
AsyncClientConfig,
DownloadError,
InviteEvent,
JoinError,
LoginResponse,
MatrixRoom,
MemoryDownloadResponse,
RoomEncryptedMedia,
RoomMessage,
RoomMessageMedia,
@@ -64,10 +62,6 @@ _MSGTYPE_MAP = {"m.image": "image", "m.audio": "audio", "m.video": "video", "m.f
MATRIX_MEDIA_EVENT_FILTER = (RoomMessageMedia, RoomEncryptedMedia)
MatrixMediaEvent: TypeAlias = RoomMessageMedia | RoomEncryptedMedia
class _MediaTooLargeError(Exception):
"""Raised when an inbound Matrix media download exceeds the configured cap."""
MATRIX_MARKDOWN = create_markdown(
escape=True,
plugins=["table", "strikethrough", "url", "superscript", "subscript"],
@@ -196,7 +190,6 @@ class MatrixConfig(Base):
e2ee_enabled: bool = Field(default=True, alias="e2eeEnabled")
sync_stop_grace_seconds: int = 2
max_media_bytes: int = 20 * 1024 * 1024
max_concurrent_media_downloads: int = 2
allow_from: list[str] = Field(default_factory=list)
group_policy: Literal["open", "mention", "allowlist"] = "open"
group_allow_from: list[str] = Field(default_factory=list)
@@ -238,9 +231,6 @@ class MatrixChannel(BaseChannel):
self._server_upload_limit_checked = False
self._stream_bufs: dict[str, _StreamBuf] = {}
self._started_at_ms: int = 0
self._media_download_semaphore = asyncio.Semaphore(
max(1, int(self.config.max_concurrent_media_downloads))
)
async def start(self) -> None:
@@ -354,7 +344,11 @@ class MatrixChannel(BaseChannel):
"""Check path is inside workspace (when restriction enabled)."""
if not self._restrict_to_workspace or not self._workspace:
return True
return is_path_within(path, self._workspace)
try:
path.resolve(strict=False).relative_to(self._workspace)
return True
except ValueError:
return False
def _collect_outbound_media_candidates(self, media: list[str]) -> list[Path]:
"""Deduplicate and resolve outbound attachment paths."""
@@ -749,7 +743,7 @@ class MatrixChannel(BaseChannel):
def _event_declared_size_bytes(self, event: MatrixMediaEvent) -> int | None:
info = self._event_source_content(event).get("info")
size = info.get("size") if isinstance(info, dict) else None
return size if type(size) is int and size >= 0 else None
return size if isinstance(size, int) and size >= 0 else None
def _event_mime(self, event: MatrixMediaEvent) -> str | None:
info = self._event_source_content(event).get("info")
@@ -778,48 +772,26 @@ class MatrixChannel(BaseChannel):
event_prefix = (event_id[:24] or "evt").strip("_")
return self._media_dir() / f"{event_prefix}_{stem}{suffix}"
async def _download_media_bytes(self, mxc_url: str, limit_bytes: int) -> bytes | None:
if not self.client or limit_bytes <= 0:
raise _MediaTooLargeError
parsed = urlparse(mxc_url)
if parsed.scheme != "mxc" or not parsed.netloc or not parsed.path.strip("/"):
async def _download_media_bytes(self, mxc_url: str) -> bytes | None:
if not self.client:
return None
homeserver = str(getattr(self.client, "homeserver", "") or self.config.homeserver).rstrip("/")
media_url = (
f"{homeserver}/_matrix/client/v1/media/download/"
f"{quote(parsed.netloc, safe='')}/{quote(parsed.path.strip('/'), safe='')}"
)
token = getattr(self.client, "access_token", None) or self.config.access_token
headers = {"Authorization": f"Bearer {token}"} if token else None
timeout = aiohttp.ClientTimeout(total=None)
try:
async with aiohttp.ClientSession(timeout=timeout, headers=headers) as session:
async with session.get(media_url, params={"allow_remote": "true"}) as response:
if response.status >= 400:
self.logger.warning("download failed for {}: HTTP {}", mxc_url, response.status)
return None
content_length = response.headers.get("Content-Length")
if content_length is not None:
try:
if int(content_length) > limit_bytes:
raise _MediaTooLargeError
except ValueError:
pass
chunks = bytearray()
async for chunk in response.content.iter_chunked(64 * 1024):
chunks.extend(chunk)
if len(chunks) > limit_bytes:
raise _MediaTooLargeError
return bytes(chunks)
except _MediaTooLargeError:
raise
except (aiohttp.ClientError, asyncio.TimeoutError, OSError):
self.logger.warning("download failed for {}", mxc_url, exc_info=True)
response = await self.client.download(mxc=mxc_url)
if isinstance(response, DownloadError):
self.logger.warning("download failed for {}: {}", mxc_url, response)
return None
body = getattr(response, "body", None)
if isinstance(body, (bytes, bytearray)):
return bytes(body)
if isinstance(response, MemoryDownloadResponse):
return bytes(response.body)
if isinstance(body, (str, Path)):
path = Path(body)
if path.is_file():
try:
return path.read_bytes()
except OSError:
return None
return None
def _decrypt_media_bytes(self, event: MatrixMediaEvent, ciphertext: bytes) -> bytes | None:
key_obj, hashes, iv = getattr(event, "key", None), getattr(event, "hashes", None), getattr(event, "iv", None)
@@ -848,14 +820,10 @@ class MatrixChannel(BaseChannel):
limit_bytes = await self._effective_media_limit_bytes()
declared = self._event_declared_size_bytes(event)
if declared is None or declared > limit_bytes:
if declared is not None and declared > limit_bytes:
return None, _ATTACH_TOO_LARGE.format(filename)
try:
async with self._media_download_semaphore:
downloaded = await self._download_media_bytes(mxc_url, limit_bytes)
except _MediaTooLargeError:
return None, _ATTACH_TOO_LARGE.format(filename)
downloaded = await self._download_media_bytes(mxc_url)
if downloaded is None:
return None, fail
-49
View File
@@ -53,13 +53,6 @@ if MSTEAMS_AVAILABLE:
MSTEAMS_REF_TTL_DAYS = 30
MSTEAMS_WEBCHAT_HOST = "webchat.botframework.com"
MSTEAMS_DEFAULT_TRUSTED_SERVICE_URL_HOSTS = [
"smba.trafficmanager.net",
"smba.infra.gcc.teams.microsoft.com",
"smba.infra.gov.teams.microsoft.us",
"smba.infra.dod.teams.microsoft.us",
"*.botframework.com",
]
MSTEAMS_REF_META_FILENAME = "msteams_conversations_meta.json"
MSTEAMS_REF_LOCK_FILENAME = "msteams_conversations.lock"
MSTEAMS_REF_TOUCH_INTERVAL_S = 300
@@ -83,9 +76,6 @@ class MSTeamsConfig(Base):
prune_web_chat_refs: bool = True
prune_non_personal_refs: bool = True
ref_touch_interval_s: int = Field(default=MSTEAMS_REF_TOUCH_INTERVAL_S, ge=0)
trusted_service_url_hosts: list[str] = Field(
default_factory=lambda: MSTEAMS_DEFAULT_TRUSTED_SERVICE_URL_HOSTS.copy()
)
@dataclass
@@ -252,11 +242,6 @@ class MSTeamsChannel(BaseChannel):
if not ref:
raise RuntimeError(f"MSTeams conversation ref not found for chat_id={msg.chat_id}")
if not self._is_trusted_service_url(ref.service_url):
raise RuntimeError(
f"MSTeams conversation ref has untrusted service_url for chat_id={msg.chat_id}"
)
token = await self._get_access_token()
base_url = f"{ref.service_url.rstrip('/')}/v3/conversations/{ref.conversation_id}/activities"
use_thread_reply = self.config.reply_in_thread and bool(ref.activity_id)
@@ -299,13 +284,6 @@ class MSTeamsChannel(BaseChannel):
if not sender_id or not conversation_id or not service_url:
return
if not self._is_trusted_service_url(service_url):
self.logger.warning(
"Ignoring MSTeams activity with untrusted serviceUrl host: {}",
service_url,
)
return
if recipient.get("id") and from_user.get("id") == recipient.get("id"):
return
@@ -648,29 +626,6 @@ class MSTeamsChannel(BaseChannel):
return host == MSTEAMS_WEBCHAT_HOST or host.endswith(f".{MSTEAMS_WEBCHAT_HOST}")
return MSTEAMS_WEBCHAT_HOST in normalized.lower()
def _is_trusted_service_url(self, service_url: str) -> bool:
"""Return True for HTTPS Bot Framework service URLs trusted for bearer replies."""
parsed = urlparse(service_url.strip())
if parsed.scheme.lower() != "https":
return False
host = (parsed.hostname or "").strip().lower().rstrip(".")
if not host:
return False
for pattern in self.config.trusted_service_url_hosts:
trusted_host = str(pattern or "").strip().lower().rstrip(".")
if not trusted_host:
continue
if trusted_host.startswith("*."):
suffix = trusted_host[1:]
if host.endswith(suffix) and host != suffix.lstrip("."):
return True
continue
if host == trusted_host:
return True
return False
def _prune_conversation_refs(self, *, now: float | None = None) -> bool:
"""Remove stale and unsupported conversation refs from memory."""
if not self._conversation_refs:
@@ -682,10 +637,6 @@ class MSTeamsChannel(BaseChannel):
keys_to_drop: list[str] = []
for key, ref in self._conversation_refs.items():
if not self._is_trusted_service_url(ref.service_url):
keys_to_drop.append(key)
continue
if self.config.prune_web_chat_refs and self._is_webchat_service_url(ref.service_url):
keys_to_drop.append(key)
continue
+15 -39
View File
@@ -1,4 +1,5 @@
"""Auto-discovery for built-in channel modules and external plugins."""
from __future__ import annotations
import importlib
@@ -36,14 +37,12 @@ def load_channel_class(module_name: str) -> type[BaseChannel]:
raise ImportError(f"No BaseChannel subclass in nanobot.channels.{module_name}")
def discover_plugins(enabled_names: set[str] | None = None) -> dict[str, type[BaseChannel]]:
def discover_plugins() -> dict[str, type[BaseChannel]]:
"""Discover external channel plugins registered via entry_points."""
from importlib.metadata import entry_points
plugins: dict[str, type[BaseChannel]] = {}
for ep in entry_points(group="nanobot.channels"):
if enabled_names is not None and ep.name not in enabled_names:
continue
try:
cls = ep.load()
plugins[ep.name] = cls
@@ -52,44 +51,21 @@ def discover_plugins(enabled_names: set[str] | None = None) -> dict[str, type[Ba
return plugins
def discover_enabled(
enabled_names: set[str],
*,
_names: list[str] | None = None,
_include_all_external: bool = False,
) -> dict[str, type[BaseChannel]]:
"""Return channels whose module names are in *enabled_names*.
Uses cheap ``pkgutil.iter_modules`` to list names, then imports only
those that match skipping the heavy third-party SDK imports of
unneeded channels.
"""
names = _names if _names is not None else discover_channel_names()
result: dict[str, type[BaseChannel]] = {}
for modname in names:
if modname not in enabled_names:
continue
try:
result[modname] = load_channel_class(modname)
except ImportError as e:
logger.debug("Skipping built-in channel '{}': {}", modname, e)
external = discover_plugins(None if _include_all_external else enabled_names)
shadowed = set(external) & set(result)
if shadowed:
logger.warning("Plugin(s) shadowed by built-in channels (ignored): {}", shadowed)
if _include_all_external:
result.update({k: v for k, v in external.items() if k not in shadowed})
else:
result.update({k: v for k, v in external.items() if k not in shadowed and k in enabled_names})
return result
def discover_all() -> dict[str, type[BaseChannel]]:
"""Return all channels: built-in (pkgutil) merged with external (entry_points).
Built-in channels take priority an external plugin cannot shadow a built-in name.
"""
names = discover_channel_names()
return discover_enabled(set(names), _names=names, _include_all_external=True)
builtin: dict[str, type[BaseChannel]] = {}
for modname in discover_channel_names():
try:
builtin[modname] = load_channel_class(modname)
except ImportError as e:
logger.debug("Skipping built-in channel '{}': {}", modname, e)
external = discover_plugins()
shadowed = set(external) & set(builtin)
if shadowed:
logger.warning("Plugin(s) shadowed by built-in channels (ignored): {}", shadowed)
return {**external, **builtin}
File diff suppressed because it is too large Load Diff
+12 -165
View File
@@ -10,9 +10,8 @@ from contextlib import suppress
from dataclasses import dataclass
from pathlib import Path
from typing import Any, Literal
from urllib.parse import urlparse
from pydantic import Field, field_validator, model_validator
from pydantic import Field
from telegram import (
BotCommand,
InlineKeyboardButton,
@@ -226,22 +225,11 @@ class _StreamBuf:
stream_id: str | None = None
@dataclass
class _QueuedTelegramUpdate:
"""Telegram update staged for per-session ordered processing."""
kind: Literal["command", "message"]
update: Update
context: Any
sort_key: tuple[int, int]
class TelegramConfig(Base):
"""Telegram channel configuration."""
enabled: bool = False
token: str = ""
mode: Literal["polling", "webhook"] = "polling"
allow_from: list[str] = Field(default_factory=list)
proxy: str | None = None
reply_to_message: bool = False
@@ -253,48 +241,13 @@ class TelegramConfig(Base):
# Enable inline keyboard buttons in Telegram messages.
inline_keyboards: bool = False
stream_edit_interval: float = Field(default=_STREAM_EDIT_INTERVAL_DEFAULT, ge=0.1)
webhook_url: str = ""
webhook_listen_host: str = "127.0.0.1"
webhook_listen_port: int = Field(default=8081, ge=1, le=65535)
webhook_path: str = "/telegram"
webhook_secret_token: str = ""
webhook_max_connections: int = Field(default=4, ge=1, le=100)
@field_validator("webhook_path")
@classmethod
def webhook_path_must_start_with_slash(cls, value: str) -> str:
value = value.strip() or "/telegram"
if not value.startswith("/"):
raise ValueError('webhook_path must start with "/"')
return value
@model_validator(mode="after")
def validate_webhook_config(self) -> "TelegramConfig":
if self.mode != "webhook":
return self
url = self.webhook_url.strip()
if not url:
raise ValueError("webhook_url is required when Telegram mode is webhook")
parsed = urlparse(url)
if parsed.scheme != "https" or not parsed.netloc:
raise ValueError("webhook_url must be a public HTTPS URL")
secret = self.webhook_secret_token.strip()
if not secret:
raise ValueError("webhook_secret_token is required when Telegram mode is webhook")
if len(secret) > 256 or re.match(r"^[A-Za-z0-9_-]+$", secret) is None:
raise ValueError(
"webhook_secret_token must be 1-256 characters using only A-Z, a-z, 0-9, _ and -"
)
return self
class TelegramChannel(BaseChannel):
"""
Telegram channel using long polling or webhook mode.
Telegram channel using long polling.
Long polling is the default. Webhook mode requires a public HTTPS URL and a
Telegram secret token.
Simple and reliable - no webhook/public IP needed.
"""
name = "telegram"
@@ -341,8 +294,6 @@ class TelegramChannel(BaseChannel):
self._bot_user_id: int | None = None
self._bot_username: str | None = None
self._stream_bufs: dict[str, _StreamBuf] = {} # chat_id -> streaming state
self._inbound_buffers: dict[str, list[_QueuedTelegramUpdate]] = {}
self._inbound_workers: dict[str, asyncio.Task] = {}
def is_allowed(self, sender_id: str) -> bool:
"""Preserve Telegram's legacy id|username allowlist matching."""
@@ -375,7 +326,7 @@ class TelegramChannel(BaseChannel):
return content
async def start(self) -> None:
"""Start the Telegram bot."""
"""Start the Telegram bot with long polling."""
if not self.config.token:
self.logger.error("bot token not configured")
return
@@ -443,12 +394,9 @@ class TelegramChannel(BaseChannel):
else:
allowed_updates = ["message"]
if self.config.mode == "webhook":
self.logger.info("Starting bot (webhook mode)...")
else:
self.logger.info("Starting bot (polling mode)...")
self.logger.info("Starting bot (polling mode)...")
# Initialize and start receiving updates
# Initialize and start polling
await self._app.initialize()
await self._app.start()
@@ -464,26 +412,12 @@ class TelegramChannel(BaseChannel):
except Exception as e:
self.logger.warning("Failed to register bot commands: {}", e)
if self.config.mode == "webhook":
# ``url_path`` is the local HTTP route. ``webhook_url`` is the
# public HTTPS URL Telegram calls; reverse proxies may rewrite it.
await self._app.updater.start_webhook(
listen=self.config.webhook_listen_host,
port=self.config.webhook_listen_port,
url_path=self.config.webhook_path.lstrip("/"),
webhook_url=self.config.webhook_url.strip(),
allowed_updates=allowed_updates,
drop_pending_updates=False,
secret_token=self.config.webhook_secret_token.strip(),
max_connections=self.config.webhook_max_connections,
)
else:
# Start polling (this runs until stopped)
await self._app.updater.start_polling(
allowed_updates=allowed_updates,
drop_pending_updates=False, # Process pending messages on startup
error_callback=self._on_polling_error,
)
# Start polling (this runs until stopped)
await self._app.updater.start_polling(
allowed_updates=allowed_updates,
drop_pending_updates=False, # Process pending messages on startup
error_callback=self._on_polling_error,
)
# Keep running until stopped
while self._running:
@@ -502,11 +436,6 @@ class TelegramChannel(BaseChannel):
self._media_group_tasks.clear()
self._media_group_buffers.clear()
for task in self._inbound_workers.values():
task.cancel()
self._inbound_workers.clear()
self._inbound_buffers.clear()
if self._app:
self.logger.info("Stopping bot...")
await self._app.updater.stop()
@@ -1066,85 +995,10 @@ class TelegramChannel(BaseChannel):
if len(self._message_threads) > 1000:
self._message_threads.pop(next(iter(self._message_threads)))
@staticmethod
def _queue_key_for_message(message) -> str:
"""Return the final nanobot session key used for ordered Telegram ingress."""
return TelegramChannel._derive_topic_session_key(message) or f"telegram:{message.chat_id}"
@staticmethod
def _sort_key_for_update(update: Update) -> tuple[int, int]:
"""Sort by chat message id first, then Telegram update id."""
message = getattr(update, "message", None)
message_id = int(getattr(message, "message_id", 0) or 0)
update_id = int(getattr(update, "update_id", 0) or 0)
return (message_id, update_id)
def _enqueue_ordered_update(
self,
*,
kind: Literal["command", "message"],
update: Update,
context: ContextTypes.DEFAULT_TYPE,
) -> None:
"""Stage a Telegram update behind a short per-session reorder window."""
message = update.message
key = self._queue_key_for_message(message)
self._inbound_buffers.setdefault(key, []).append(
_QueuedTelegramUpdate(
kind=kind,
update=update,
context=context,
sort_key=self._sort_key_for_update(update),
)
)
if key not in self._inbound_workers:
self._inbound_workers[key] = asyncio.create_task(
self._drain_ordered_updates(key)
)
async def _drain_ordered_updates(self, key: str) -> None:
"""Drain one Telegram session buffer in stable message order."""
try:
while self._running:
await asyncio.sleep(0.2)
batch = self._inbound_buffers.get(key, [])
if not batch:
break
self._inbound_buffers[key] = []
batch.sort(key=lambda item: item.sort_key)
for item in batch:
try:
if item.kind == "command":
await self._process_forward_command(item.update, item.context)
else:
await self._process_message_update(item.update, item.context)
except Exception as e:
self.logger.warning(
"Telegram queued update handling failed for {}: {}",
key,
e,
)
if not self._inbound_buffers.get(key):
self._inbound_buffers.pop(key, None)
except asyncio.CancelledError:
raise
except Exception as e:
self.logger.warning("Telegram ordered update worker failed for {}: {}", key, e)
finally:
if not self._inbound_buffers.get(key):
self._inbound_workers.pop(key, None)
async def _forward_command(self, update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
"""Forward slash commands to the bus for unified handling in AgentLoop."""
if not update.message or not update.effective_user:
return
if not self._running:
await self._process_forward_command(update, context)
return
self._enqueue_ordered_update(kind="command", update=update, context=context)
async def _process_forward_command(self, update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
"""Process a queued slash command."""
message = update.message
user = update.effective_user
sender_id = self._sender_id(user)
@@ -1173,13 +1027,6 @@ class TelegramChannel(BaseChannel):
"""Handle incoming messages (text, photos, voice, documents)."""
if not update.message or not update.effective_user:
return
if not self._running:
await self._process_message_update(update, context)
return
self._enqueue_ordered_update(kind="message", update=update, context=context)
async def _process_message_update(self, update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
"""Process a queued Telegram message update."""
message = update.message
user = update.effective_user
+233 -411
View File
@@ -3,69 +3,61 @@
from __future__ import annotations
import asyncio
import base64
import binascii
import email.utils
import hashlib
import hmac
import http
import json
import mimetypes
import re
import secrets
import shutil
import ssl
import time
import uuid
from collections.abc import Callable
from contextlib import suppress
from pathlib import Path
from typing import TYPE_CHECKING, Any, Self
from urllib.parse import parse_qs, unquote, urlparse
from loguru import logger
from pydantic import Field, field_validator, model_validator
from websockets.asyncio.server import ServerConnection, serve, unix_serve
from websockets.asyncio.server import ServerConnection, serve
from websockets.datastructures import Headers
from websockets.exceptions import ConnectionClosed
from websockets.http11 import Request as WsRequest
from websockets.http11 import Response
from nanobot.security.workspace_access import (
WORKSPACE_SCOPE_METADATA_KEY,
WorkspaceScopeError,
)
from nanobot.bus.events import OUTBOUND_META_AGENT_UI, OutboundMessage
from nanobot.bus.queue import MessageBus
from nanobot.channels.base import BaseChannel
from nanobot.command.builtin import builtin_command_palette
from nanobot.config.paths import get_media_dir, get_workspace_path
from nanobot.config.paths import get_media_dir
from nanobot.config.schema import Base
from nanobot.session.goal_state import goal_state_ws_blob
from nanobot.session.webui_turns import websocket_turn_wall_started_at
from nanobot.utils.helpers import safe_filename
from nanobot.utils.media_decode import (
FileSizeExceeded,
save_base64_data_url,
)
from nanobot.utils.subagent_channel_display import scrub_subagent_messages_for_channel
from nanobot.webui.settings_api import runtime_capabilities
from nanobot.webui.cli_apps_api import normalize_cli_app_mentions
from nanobot.webui.media_api import (
serve_signed_media,
sign_media_path,
sign_or_stage_media_path,
from nanobot.webui.settings_api import (
WebUISettingsError,
settings_payload,
update_agent_settings,
update_image_generation_settings,
update_provider_settings,
update_web_search_settings,
)
from nanobot.webui.mcp_presets_api import normalize_mcp_preset_mentions
from nanobot.webui.settings_routes import WebUISettingsRouter
from nanobot.webui.sidebar_state import (
read_webui_sidebar_state,
write_webui_sidebar_state,
)
from nanobot.webui.thread_disk import delete_webui_thread
from nanobot.webui.transcript import (
append_transcript_object,
build_webui_thread_response,
rewrite_local_markdown_images,
)
from nanobot.webui.workspaces import (
WebUIWorkspaceController,
)
from nanobot.webui.transcript import append_transcript_object, build_webui_thread_response
if TYPE_CHECKING:
from nanobot.session.manager import SessionManager
@@ -81,41 +73,6 @@ def _normalize_config_path(path: str) -> str:
return _strip_trailing_slash(path)
def _case_insensitive_header(headers: Any, key: str) -> str:
"""Read a header from websockets/http test stubs without assuming casing."""
try:
value = headers.get(key)
except Exception:
value = None
if value is None:
try:
value = headers.get(key.lower())
except Exception:
value = None
return str(value or "").strip()
def _safe_host_header(value: str) -> str:
"""Return a safe Host header value, or empty when it should not be echoed."""
value = value.strip()
if not value:
return ""
if re.fullmatch(r"\[[0-9A-Fa-f:.]+\](?::\d{1,5})?", value):
return value
if re.fullmatch(r"[A-Za-z0-9.-]+(?::\d{1,5})?", value):
return value
return ""
def _host_for_url(host: str, port: int) -> str:
host = host.strip()
if host in ("0.0.0.0", "::"):
host = "127.0.0.1"
if ":" in host and not host.startswith("["):
host = f"[{host}]"
return f"{host}:{port}"
class WebSocketConfig(Base):
"""WebSocket server channel configuration.
@@ -139,7 +96,6 @@ class WebSocketConfig(Base):
enabled: bool = False
host: str = "127.0.0.1"
port: int = 8765
unix_socket_path: str = ""
path: str = "/"
token: str = ""
token_issue_path: str = ""
@@ -158,19 +114,6 @@ class WebSocketConfig(Base):
ssl_certfile: str = ""
ssl_keyfile: str = ""
@field_validator("unix_socket_path")
@classmethod
def unix_socket_path_format(cls, value: str) -> str:
value = value.strip()
if not value:
return ""
if "\x00" in value:
raise ValueError("unix_socket_path must not contain NUL bytes")
path = Path(value).expanduser()
if not path.is_absolute():
raise ValueError("unix_socket_path must be an absolute path")
return str(path)
@field_validator("path")
@classmethod
def path_must_start_with_slash(cls, value: str) -> str:
@@ -453,6 +396,32 @@ def _is_websocket_upgrade(request: WsRequest) -> bool:
return True
def _b64url_encode(data: bytes) -> str:
"""URL-safe base64 without padding — compact + friendly in URL paths."""
return base64.urlsafe_b64encode(data).rstrip(b"=").decode("ascii")
def _b64url_decode(s: str) -> bytes:
"""Reverse of :func:`_b64url_encode`; caller handles ``ValueError``."""
pad = "=" * (-len(s) % 4)
return base64.urlsafe_b64decode(s + pad)
# Allowed MIME types we actually serve from the media endpoint. Anything
# outside this set is degraded to ``application/octet-stream`` so an
# attacker who somehow gets a signed URL for an unexpected file type can't
# trick the browser into sniffing executable content.
_MEDIA_ALLOWED_MIMES: frozenset[str] = frozenset({
"image/png",
"image/jpeg",
"image/webp",
"image/gif",
"video/mp4",
"video/webm",
"video/quicktime",
})
def _issue_route_secret_matches(headers: Any, configured_secret: str) -> bool:
"""Return True if the token-issue HTTP request carries credentials matching ``token_issue_secret``."""
if not configured_secret:
@@ -480,11 +449,7 @@ class WebSocketChannel(BaseChannel):
*,
session_manager: "SessionManager | None" = None,
static_dist_path: Path | None = None,
workspace_path: Path | None = None,
restrict_to_workspace: bool = False,
runtime_model_name: Callable[[], str | None] | None = None,
runtime_surface: str = "browser",
runtime_capabilities_overrides: dict[str, Any] | None = None,
):
if isinstance(config, dict):
config = WebSocketConfig.model_validate(config)
@@ -506,36 +471,8 @@ class WebSocketChannel(BaseChannel):
self._static_dist_path: Path | None = (
static_dist_path.resolve() if static_dist_path is not None else None
)
self._workspace_path = (
Path(workspace_path).expanduser()
if workspace_path is not None
else get_workspace_path()
).resolve(strict=False)
self._default_restrict_to_workspace = restrict_to_workspace
self._webui_workspaces = WebUIWorkspaceController(
session_manager=self._session_manager,
default_workspace=self._workspace_path,
default_restrict_to_workspace=self._default_restrict_to_workspace,
)
self._runtime_model_name = runtime_model_name
self._runtime_surface = (
"native" if runtime_surface in {"native", "desktop"} else "browser"
)
self._runtime_capabilities = runtime_capabilities(
self._runtime_surface,
runtime_capabilities_overrides,
)
self._settings_routes = WebUISettingsRouter(
bus=self.bus,
logger=self.logger,
check_api_token=self._check_api_token,
parse_query=_parse_query,
json_response=_http_json_response,
error_response=_http_error,
runtime_surface=self._runtime_surface,
runtime_capabilities=self._runtime_capabilities,
)
self._stream_text_buffers: dict[tuple[str, str], list[str]] = {}
self._settings_restart_sections: set[str] = set()
# Process-local secret used to HMAC-sign media URLs. The signed URL is
# the capability — anyone who holds a valid URL can fetch that one
# file, nothing else. The secret regenerates on restart so links
@@ -678,91 +615,44 @@ class WebSocketChannel(BaseChannel):
"""Route an inbound HTTP request to a handler or to the WS upgrade path."""
got, query = _parse_request_path(request.path)
# 1. Token issue endpoint (legacy, optional, gated by configured secret).
if self.config.token_issue_path:
issue_expected = _normalize_config_path(self.config.token_issue_path)
if got == issue_expected:
return self._handle_token_issue_http(connection, request)
# 2. Bootstrap (`/webui/bootstrap`): mint WS/API tokens + shared session metadata.
if got == "/webui/bootstrap":
return self._handle_bootstrap(connection, request)
api_response = await self._dispatch_api_route(connection, request, got)
if api_response is not None:
return api_response
ws_matched, ws_response = self._dispatch_websocket_upgrade(
connection, request, got, query
)
if ws_matched:
return ws_response
# API clients should never receive the SPA shell for an unknown route.
# Returning HTML here makes the WebUI fail with "Unexpected token <"
# when a dev server is pointed at an older gateway.
if got.startswith("/api/"):
return _http_error(404, "API route not found")
if self._static_dist_path is not None:
response = self._serve_static(got)
if response is not None:
return response
return connection.respond(404, "Not Found")
async def _dispatch_api_route(
self,
connection: Any,
request: WsRequest,
got: str,
) -> Any | None:
"""Route REST-ish WebUI requests served beside the WebSocket endpoint."""
response = await self._dispatch_settings_api_route(request, got)
if response is not None:
return response
response = self._dispatch_session_api_route(request, got)
if response is not None:
return response
response = self._dispatch_media_api_route(request, got)
if response is not None:
return response
return self._dispatch_misc_api_route(connection, request, got)
def _dispatch_misc_api_route(
self,
connection: Any,
request: WsRequest,
got: str,
) -> Response | None:
"""Route small API endpoints that do not belong to a larger route group."""
# 3. REST handlers co-located with this channel (sessions, settings, …).
if got == "/api/sessions":
return self._handle_sessions_list(request)
if got == "/api/settings":
return self._handle_settings(request)
if got == "/api/commands":
return self._handle_commands(request)
if got == "/api/workspaces":
return self._handle_workspaces(connection, request)
if got == "/api/webui/sidebar-state":
return self._handle_webui_sidebar_state(request)
if got == "/api/webui/sidebar-state/update":
return self._handle_webui_sidebar_state_update(request)
return None
if got == "/api/settings/update":
return self._handle_settings_update(request)
async def _dispatch_settings_api_route(
self,
request: WsRequest,
got: str,
) -> Response | None:
return await self._settings_routes.dispatch(request, got)
if got == "/api/settings/provider/update":
return self._handle_settings_provider_update(request)
if got == "/api/settings/web-search/update":
return self._handle_settings_web_search_update(request)
if got == "/api/settings/image-generation/update":
return self._handle_settings_image_generation_update(request)
def _dispatch_session_api_route(
self,
request: WsRequest,
got: str,
) -> Response | None:
m = re.match(r"^/api/sessions/([^/]+)/messages$", got)
if m:
return self._handle_session_messages(request, m.group(1))
@@ -777,36 +667,34 @@ class WebSocketChannel(BaseChannel):
if m:
return self._handle_session_delete(request, m.group(1))
return None
def _dispatch_media_api_route(
self,
request: WsRequest,
got: str,
) -> Response | None:
# Signed media fetch: ``<sig>`` is an HMAC over ``<payload>``; the
# payload decodes to a path inside :func:`get_media_dir`. See
# :meth:`_sign_media_path` for the inverse direction used to build
# these URLs when replaying a session.
m = re.match(r"^/api/media/([A-Za-z0-9_-]+)/([A-Za-z0-9_-]+)$", got)
if m:
return self._handle_media_fetch(m.group(1), m.group(2), request)
return self._handle_media_fetch(m.group(1), m.group(2))
return None
def _dispatch_websocket_upgrade(
self,
connection: Any,
request: WsRequest,
got: str,
query: dict[str, list[str]],
) -> tuple[bool, Any | None]:
"""Authorize only real WS upgrade requests for the configured path."""
# 4. WebSocket upgrade (the channel's primary purpose). Only run the
# handshake gate on requests that actually ask to upgrade; otherwise
# a bare ``GET /`` from the browser would be rejected as an
# unauthorized WS handshake instead of serving the SPA's index.html.
expected_ws = self._expected_path()
if got != expected_ws or not _is_websocket_upgrade(request):
return False, None
client_id = _query_first(query, "client_id") or ""
if len(client_id) > 128:
client_id = client_id[:128]
if not self.is_allowed(client_id):
return True, connection.respond(403, "Forbidden")
return True, self._authorize_websocket_handshake(connection, query)
if got == expected_ws and _is_websocket_upgrade(request):
client_id = _query_first(query, "client_id") or ""
if len(client_id) > 128:
client_id = client_id[:128]
if not self.is_allowed(client_id):
return connection.respond(403, "Forbidden")
return self._authorize_websocket_handshake(connection, query)
# 5. Static SPA serving (only if a build directory was wired in).
if self._static_dist_path is not None:
response = self._serve_static(got)
if response is not None:
return response
return connection.respond(404, "Not Found")
# -- HTTP route handlers ------------------------------------------------
@@ -859,32 +747,15 @@ class WebSocketChannel(BaseChannel):
# while the REST surface keeps validating the other until TTL expiry.
self._issued_tokens[token] = expiry
self._api_tokens[token] = expiry
ws_url = self._bootstrap_ws_url(request)
return _http_json_response(
{
"token": token,
"ws_path": self._expected_path(),
"ws_url": ws_url,
"expires_in": self.config.token_ttl_s,
"model_name": _resolve_bootstrap_model_name(self._runtime_model_name),
"runtime_surface": self._runtime_surface,
"runtime_capabilities": self._runtime_capabilities,
}
)
def _bootstrap_ws_url(self, request: Any) -> str:
"""Absolute WS URL clients should prefer over a dev-server proxy."""
headers = getattr(request, "headers", {}) or {}
host = _safe_host_header(_case_insensitive_header(headers, "Host"))
if not host:
host = _host_for_url(self.config.host, self.config.port)
proto = _case_insensitive_header(headers, "X-Forwarded-Proto")
proto = proto.split(",", 1)[0].strip().lower()
secure = proto in {"https", "wss"} or bool(self.config.ssl_certfile.strip())
scheme = "wss" if secure else "ws"
return f"{scheme}://{host}{self._expected_path()}"
def _handle_sessions_list(self, request: WsRequest) -> Response:
if not self._check_api_token(request):
return _http_error(401, "Unauthorized")
@@ -903,17 +774,31 @@ class WebSocketChannel(BaseChannel):
started_at = websocket_turn_wall_started_at(chat_id)
if started_at is not None:
row["run_started_at"] = started_at
scope = self._webui_workspaces.scope_for_session_key(key)
row["workspace_scope"] = scope.payload()
cleaned.append(row)
return _http_json_response({"sessions": cleaned})
def _handle_workspaces(self, connection: Any, request: WsRequest) -> Response:
def _handle_settings(self, request: WsRequest) -> Response:
if not self._check_api_token(request):
return _http_error(401, "Unauthorized")
return _http_json_response(
self._webui_workspaces.payload(controls_available=_is_localhost(connection))
)
return _http_json_response(self._with_settings_restart_state(settings_payload()))
def _with_settings_restart_state(
self,
payload: dict[str, Any],
*,
section: str | None = None,
) -> dict[str, Any]:
"""Keep restart-required state alive for this gateway process."""
if section and payload.get("requires_restart"):
self._settings_restart_sections.add(section)
if self._settings_restart_sections:
payload = dict(payload)
payload["requires_restart"] = True
payload["restart_required_sections"] = sorted(self._settings_restart_sections)
else:
payload = dict(payload)
payload["restart_required_sections"] = []
return payload
def _handle_commands(self, request: WsRequest) -> Response:
if not self._check_api_token(request):
@@ -947,7 +832,47 @@ class WebSocketChannel(BaseChannel):
return _http_error(500, "failed to write sidebar state")
return _http_json_response(state)
# -- Session replay, transcript, and signed media ----------------------
def _handle_settings_update(self, request: WsRequest) -> Response:
if not self._check_api_token(request):
return _http_error(401, "Unauthorized")
query = _parse_query(request.path)
try:
payload = update_agent_settings(query)
except WebUISettingsError as e:
return _http_error(e.status, e.message)
return _http_json_response(
self._with_settings_restart_state(payload, section="runtime")
)
def _handle_settings_provider_update(self, request: WsRequest) -> Response:
if not self._check_api_token(request):
return _http_error(401, "Unauthorized")
query = _parse_query(request.path)
try:
payload = update_provider_settings(query)
except WebUISettingsError as e:
return _http_error(e.status, e.message)
return _http_json_response(self._with_settings_restart_state(payload, section="image"))
def _handle_settings_web_search_update(self, request: WsRequest) -> Response:
if not self._check_api_token(request):
return _http_error(401, "Unauthorized")
query = _parse_query(request.path)
try:
payload = update_web_search_settings(query)
except WebUISettingsError as e:
return _http_error(e.status, e.message)
return _http_json_response(self._with_settings_restart_state(payload, section="web"))
def _handle_settings_image_generation_update(self, request: WsRequest) -> Response:
if not self._check_api_token(request):
return _http_error(401, "Unauthorized")
query = _parse_query(request.path)
try:
payload = update_image_generation_settings(query)
except WebUISettingsError as e:
return _http_error(e.status, e.message)
return _http_json_response(self._with_settings_restart_state(payload, section="image"))
@staticmethod
def _is_websocket_channel_session_key(key: str) -> bool:
@@ -987,19 +912,12 @@ class WebSocketChannel(BaseChannel):
return _http_error(400, "invalid session key")
if not self._is_websocket_channel_session_key(decoded_key):
return _http_error(404, "session not found")
scope = self._webui_workspaces.scope_for_session_key(decoded_key)
data = build_webui_thread_response(
decoded_key,
augment_user_media=self._augment_transcript_user_media,
augment_assistant_text=lambda text: rewrite_local_markdown_images(
text,
workspace_path=scope.project_path,
sign_path=self._sign_or_stage_media_path,
),
)
if data is None:
return _http_error(404, "webui thread not found")
data["workspace_scope"] = scope.payload()
return _http_json_response(data)
def _try_append_webui_transcript(self, chat_id: str, wire: dict[str, Any]) -> None:
@@ -1043,12 +961,6 @@ class WebSocketChannel(BaseChannel):
}
if media:
user_obj["media_paths"] = list(media)
cli_apps = meta.get("cli_apps")
if isinstance(cli_apps, list) and cli_apps:
user_obj["cli_apps"] = cli_apps
mcp_presets = meta.get("mcp_presets")
if isinstance(mcp_presets, list) and mcp_presets:
user_obj["mcp_presets"] = mcp_presets
self._try_append_webui_transcript(chat_id, user_obj)
await super()._handle_message(
sender_id,
@@ -1100,11 +1012,16 @@ class WebSocketChannel(BaseChannel):
be fetched. The returned path is relative to the server origin; the
client joins it against this server's HTTP origin (same host as WS).
"""
return sign_media_path(
abs_path,
secret=self._media_secret,
media_dir=lambda channel=None: get_media_dir(channel),
)
try:
media_root = get_media_dir().resolve()
rel = abs_path.resolve().relative_to(media_root)
except (OSError, ValueError):
return None
payload = _b64url_encode(rel.as_posix().encode("utf-8"))
mac = hmac.new(
self._media_secret, payload.encode("ascii"), hashlib.sha256
).digest()[:16]
return f"/api/media/{_b64url_encode(mac)}/{payload}"
def _sign_or_stage_media_path(self, path: Path) -> dict[str, str] | None:
"""Return a signed media URL payload for *path*.
@@ -1115,34 +1032,70 @@ class WebSocketChannel(BaseChannel):
can fetch them through the existing signed media route without
exposing arbitrary filesystem paths.
"""
return sign_or_stage_media_path(
path,
secret=self._media_secret,
media_dir=lambda channel=None: get_media_dir(channel),
logger=self.logger,
)
signed = self._sign_media_path(path)
if signed is not None:
return {"url": signed, "name": path.name}
try:
if not path.is_file():
return None
media_dir = get_media_dir("websocket")
safe_name = safe_filename(path.name) or "attachment"
staged = media_dir / f"{uuid.uuid4().hex[:12]}-{safe_name}"
shutil.copyfile(path, staged)
except OSError as exc:
self.logger.warning("failed to stage outbound media {}: {}", path, exc)
return None
signed = self._sign_media_path(staged)
if signed is None:
return None
return {"url": signed, "name": path.name}
def _rewrite_local_markdown_images(self, text: str) -> str:
return rewrite_local_markdown_images(
text,
workspace_path=self._workspace_path,
sign_path=self._sign_or_stage_media_path,
)
def _handle_media_fetch(
self, sig: str, payload: str, request: WsRequest | None = None
) -> Response:
def _handle_media_fetch(self, sig: str, payload: str) -> Response:
"""Serve a single media file previously signed via
:meth:`_sign_media_path`. Validates the signature, decodes the
payload to a relative path, and streams the file bytes with a
long-lived immutable cache header (the URL already encodes the
file identity, so caches can be aggressive)."""
return serve_signed_media(
sig,
payload,
secret=self._media_secret,
request=request,
media_dir=lambda channel=None: get_media_dir(channel),
try:
provided_mac = _b64url_decode(sig)
except (ValueError, binascii.Error):
return _http_error(401, "invalid signature")
expected_mac = hmac.new(
self._media_secret, payload.encode("ascii"), hashlib.sha256
).digest()[:16]
if not hmac.compare_digest(expected_mac, provided_mac):
return _http_error(401, "invalid signature")
try:
rel_bytes = _b64url_decode(payload)
rel_str = rel_bytes.decode("utf-8")
except (ValueError, binascii.Error, UnicodeDecodeError):
return _http_error(400, "invalid payload")
# An attacker who somehow bypassed the HMAC check would still need
# the resolved path to escape the media root; guard defensively.
try:
media_root = get_media_dir().resolve()
candidate = (media_root / rel_str).resolve()
candidate.relative_to(media_root)
except (OSError, ValueError):
return _http_error(404, "not found")
if not candidate.is_file():
return _http_error(404, "not found")
try:
body = candidate.read_bytes()
except OSError:
return _http_error(500, "read error")
mime, _ = mimetypes.guess_type(candidate.name)
if mime not in _MEDIA_ALLOWED_MIMES:
mime = "application/octet-stream"
return _http_response(
body,
content_type=mime,
extra_headers=[
("Cache-Control", "private, max-age=31536000, immutable"),
# Paired with the MIME whitelist above: prevents browsers from
# MIME-sniffing an octet-stream fallback into executable HTML.
("X-Content-Type-Options", "nosniff"),
],
)
def _handle_session_delete(self, request: WsRequest, key: str) -> Response:
@@ -1161,8 +1114,6 @@ class WebSocketChannel(BaseChannel):
delete_webui_thread(decoded_key)
return _http_json_response({"deleted": bool(deleted)})
# -- Static files and WebSocket handshake ------------------------------
def _serve_static(self, request_path: str) -> Response | None:
"""Resolve *request_path* against the built SPA directory; SPA fallback to index.html."""
assert self._static_dist_path is not None
@@ -1227,8 +1178,6 @@ class WebSocketChannel(BaseChannel):
self._take_issued_token_if_valid(supplied)
return None
# -- Server lifecycle and connection ingress ---------------------------
async def start(self) -> None:
from nanobot.utils.logging_bridge import redirect_lib_logging
@@ -1250,63 +1199,34 @@ class WebSocketChannel(BaseChannel):
await self._connection_loop(connection)
self.logger.info(
"WebSocket server listening on {}",
(
f"unix:{self.config.unix_socket_path}{self.config.path}"
if self.config.unix_socket_path
else f"{scheme}://{self.config.host}:{self.config.port}{self.config.path}"
),
"WebSocket server listening on {}://{}:{}{}",
scheme,
self.config.host,
self.config.port,
self.config.path,
)
if self.config.token_issue_path:
self.logger.info(
"WebSocket token issue route: {}",
(
f"unix:{self.config.unix_socket_path}{_normalize_config_path(self.config.token_issue_path)}"
if self.config.unix_socket_path
else (
f"{scheme}://{self.config.host}:{self.config.port}"
f"{_normalize_config_path(self.config.token_issue_path)}"
)
),
"WebSocket token issue route: {}://{}:{}{}",
scheme,
self.config.host,
self.config.port,
_normalize_config_path(self.config.token_issue_path),
)
async def runner() -> None:
socket_path = self.config.unix_socket_path
if socket_path:
path_obj = Path(socket_path)
path_obj.parent.mkdir(parents=True, exist_ok=True)
with suppress(FileNotFoundError):
path_obj.unlink()
server = await unix_serve(
handler,
socket_path,
process_request=process_request,
max_size=self.config.max_message_bytes,
ping_interval=self.config.ping_interval_s,
ping_timeout=self.config.ping_timeout_s,
)
with suppress(OSError):
path_obj.chmod(0o600)
else:
server = await serve(
handler,
self.config.host,
self.config.port,
process_request=process_request,
max_size=self.config.max_message_bytes,
ping_interval=self.config.ping_interval_s,
ping_timeout=self.config.ping_timeout_s,
ssl=ssl_context,
)
try:
async with serve(
handler,
self.config.host,
self.config.port,
process_request=process_request,
max_size=self.config.max_message_bytes,
ping_interval=self.config.ping_interval_s,
ping_timeout=self.config.ping_timeout_s,
ssl=ssl_context,
):
assert self._stop_event is not None
await self._stop_event.wait()
finally:
server.close()
await server.wait_closed()
if socket_path:
with suppress(FileNotFoundError):
Path(socket_path).unlink()
self._server_task = asyncio.create_task(runner())
await self._server_task
@@ -1372,8 +1292,6 @@ class WebSocketChannel(BaseChannel):
finally:
self._cleanup_connection(connection)
# -- Inbound WebSocket envelopes ---------------------------------------
def _save_envelope_media(
self,
media: list[Any],
@@ -1452,25 +1370,8 @@ class WebSocketChannel(BaseChannel):
t = envelope.get("type")
if t == "new_chat":
new_id = str(uuid.uuid4())
scope = await self._workspace_scope_or_error(
connection,
lambda: self._webui_workspaces.scope_for_new_chat(
envelope,
controls_available=_is_localhost(connection),
),
)
if scope is None:
return
self._webui_workspaces.persist_scope(new_id, scope)
self._attach(connection, new_id)
await self._send_event(connection, "attached", chat_id=new_id)
await self._send_event(
connection,
"session_updated",
chat_id=new_id,
scope="metadata",
workspace_scope=scope.payload(),
)
await self._hydrate_after_subscribe(new_id)
return
if t == "attach":
@@ -1482,32 +1383,6 @@ class WebSocketChannel(BaseChannel):
await self._send_event(connection, "attached", chat_id=cid)
await self._hydrate_after_subscribe(cid)
return
if t == "set_workspace_scope":
cid = envelope.get("chat_id")
if not _is_valid_chat_id(cid):
await self._send_event(connection, "error", detail="invalid chat_id")
return
scope = await self._workspace_scope_or_error(
connection,
lambda: self._webui_workspaces.scope_for_set_request(
envelope,
chat_id=cid,
chat_running=websocket_turn_wall_started_at(cid) is not None,
controls_available=_is_localhost(connection),
),
chat_id=cid,
)
if scope is None:
return
self._webui_workspaces.persist_scope(cid, scope)
await self._send_event(
connection,
"session_updated",
chat_id=cid,
scope="metadata",
workspace_scope=scope.payload(),
)
return
if t == "message":
cid = envelope.get("chat_id")
content = envelope.get("content")
@@ -1539,18 +1414,6 @@ class WebSocketChannel(BaseChannel):
if not content.strip() and not media_paths:
await self._send_event(connection, "error", detail="missing content")
return
scope = await self._workspace_scope_or_error(
connection,
lambda: self._webui_workspaces.scope_for_message(
envelope,
chat_id=cid,
chat_running=websocket_turn_wall_started_at(cid) is not None,
controls_available=_is_localhost(connection),
),
chat_id=cid,
)
if scope is None:
return
# Auto-attach on first use so clients can one-shot without a separate attach.
self._attach(connection, cid)
@@ -1558,14 +1421,6 @@ class WebSocketChannel(BaseChannel):
metadata: dict[str, Any] = {"remote": getattr(connection, "remote_address", None)}
if envelope.get("webui") is True:
metadata["webui"] = True
cli_apps = normalize_cli_app_mentions(envelope.get("cli_apps"))
if cli_apps:
metadata["cli_apps"] = cli_apps
mcp_presets = normalize_mcp_preset_mentions(envelope.get("mcp_presets"))
if mcp_presets:
metadata["mcp_presets"] = mcp_presets
metadata[WORKSPACE_SCOPE_METADATA_KEY] = scope.metadata()
self._webui_workspaces.persist_scope(cid, scope)
image_generation = envelope.get("image_generation")
if isinstance(image_generation, dict) and image_generation.get("enabled") is True:
aspect_ratio = image_generation.get("aspect_ratio")
@@ -1584,27 +1439,6 @@ class WebSocketChannel(BaseChannel):
return
await self._send_event(connection, "error", detail=f"unknown type: {t!r}")
async def _workspace_scope_or_error(
self,
connection: Any,
resolver: Callable[[], Any],
*,
chat_id: str | None = None,
) -> Any | None:
try:
return resolver()
except WorkspaceScopeError as exc:
await self._send_event(
connection,
"error",
detail="workspace_scope_rejected",
reason=exc.message,
**({"chat_id": chat_id} if chat_id else {}),
)
return None
# -- Outbound WebSocket events -----------------------------------------
async def stop(self) -> None:
if not self._running:
return
@@ -1698,11 +1532,10 @@ class WebSocketChannel(BaseChannel):
await self._safe_send_to(connection, raw, label=" ")
return
text = msg.content
wire_text = self._rewrite_local_markdown_images(text)
payload: dict[str, Any] = {
"event": "message",
"chat_id": msg.chat_id,
"text": wire_text,
"text": text,
}
if msg.media:
payload["media"] = msg.media
@@ -1730,9 +1563,7 @@ class WebSocketChannel(BaseChannel):
payload["kind"] = "tool_hint"
elif msg.metadata.get("_progress"):
payload["kind"] = "progress"
transcript_payload = dict(payload)
transcript_payload["text"] = text
self._try_append_webui_transcript(msg.chat_id, transcript_payload)
self._try_append_webui_transcript(msg.chat_id, payload)
raw = json.dumps(payload, ensure_ascii=False)
for connection in conns:
await self._safe_send_to(connection, raw, label=" ")
@@ -1797,23 +1628,14 @@ class WebSocketChannel(BaseChannel):
if not conns:
return
meta = metadata or {}
stream_key = (chat_id, str(meta.get("_stream_id") or ""))
if meta.get("_stream_end"):
body: dict[str, Any] = {"event": "stream_end", "chat_id": chat_id}
buffered = self._stream_text_buffers.pop(stream_key, [])
if delta:
buffered.append(delta)
full_text = "".join(buffered)
rewritten = self._rewrite_local_markdown_images(full_text)
if rewritten != full_text:
body["text"] = rewritten
else:
body = {
"event": "delta",
"chat_id": chat_id,
"text": delta,
}
self._stream_text_buffers.setdefault(stream_key, []).append(delta)
if meta.get("_stream_id") is not None:
body["stream_id"] = meta["_stream_id"]
self._try_append_webui_transcript(chat_id, body)
+6 -163
View File
@@ -79,12 +79,6 @@ BASE_INFO: dict[str, str] = {"channel_version": WEIXIN_CHANNEL_VERSION}
ERRCODE_SESSION_EXPIRED = -14
SESSION_PAUSE_DURATION_S = 60 * 60
# iLink context_token is observed to expire server-side after ~90-160s of
# agent inactivity (openclaw/openclaw#61174). Proactively refresh before
# sending if the cached token is older than this threshold.
CONTEXT_TOKEN_MAX_AGE_S = 60
# Retry constants (matching the reference plugin's monitor.ts)
MAX_CONSECUTIVE_FAILURES = 3
BACKOFF_DELAY_S = 30
@@ -165,8 +159,6 @@ class WeixinChannel(BaseChannel):
self._session_pause_until: float = 0.0
self._typing_tasks: dict[str, asyncio.Task] = {}
self._typing_tickets: dict[str, dict[str, Any]] = {}
self._context_token_at: dict[str, float] = {}
self._pending_tool_hints: dict[str, list[str]] = {}
# ------------------------------------------------------------------
# State persistence
@@ -494,7 +486,6 @@ class WeixinChannel(BaseChannel):
except Exception:
if not self._running:
break
self.logger.exception("WeChat poll loop error")
consecutive_failures += 1
if consecutive_failures >= MAX_CONSECUTIVE_FAILURES:
consecutive_failures = 0
@@ -504,7 +495,6 @@ class WeixinChannel(BaseChannel):
async def stop(self) -> None:
self._running = False
self._pending_tool_hints.clear()
if self._poll_task and not self._poll_task.done():
self._poll_task.cancel()
for chat_id in list(self._typing_tasks):
@@ -555,7 +545,6 @@ class WeixinChannel(BaseChannel):
# Check for API-level errors (monitor.ts checks both ret and errcode)
ret = data.get("ret", 0)
errcode = data.get("errcode", 0)
is_error = (ret is not None and ret != 0) or (errcode is not None and errcode != 0)
if is_error:
@@ -586,10 +575,8 @@ class WeixinChannel(BaseChannel):
# Process messages (WeixinMessage[] from types.ts)
msgs: list[dict] = data.get("msgs", []) or []
for msg in msgs:
try:
with suppress(Exception):
await self._process_message(msg)
except Exception:
self.logger.exception("Failed to process WeChat message")
# ------------------------------------------------------------------
# Inbound message processing (matches inbound.ts + process-message.ts)
@@ -623,7 +610,6 @@ class WeixinChannel(BaseChannel):
ctx_token = msg.get("context_token", "")
if ctx_token:
self._context_tokens[from_user_id] = ctx_token
self._context_token_at[from_user_id] = time.time()
self._save_state()
# Parse item_list (WeixinMessage.item_list — types.ts:161)
@@ -929,99 +915,6 @@ class WeixinChannel(BaseChannel):
}
return ""
async def _refresh_context_token_if_stale(
self, chat_id: str, context_token: str
) -> str:
"""Return a fresh context_token if the cached one is too old.
iLink context_token expires server-side after a short idle period
(empirically ~90s). Proactively refreshing before sending prevents
silent message loss on long agent turns or cron pushes.
"""
if not context_token:
return context_token
now = time.time()
cached_at = self._context_token_at.get(chat_id, 0)
age = now - cached_at
if age < CONTEXT_TOKEN_MAX_AGE_S:
return context_token
self.logger.debug(
"WeChat context_token for {} is {:.0f}s old; refreshing via getconfig",
chat_id,
age,
)
body: dict[str, Any] = {
"ilink_user_id": chat_id,
"context_token": context_token,
"base_info": BASE_INFO,
}
try:
data = await self._api_post("ilink/bot/getconfig", body)
except Exception as e:
self.logger.warning("WeChat getconfig failed for {}: {}", chat_id, e)
return context_token
if data.get("ret", 0) != 0:
self.logger.warning(
"WeChat getconfig returned ret={} for {}: {}",
data.get("ret"),
chat_id,
data.get("errmsg", ""),
)
return context_token
new_token = str(data.get("context_token", "") or "")
if new_token and new_token != context_token:
self.logger.info(
"WeChat context_token refreshed for {} (age {:.0f}s -> fresh)",
chat_id,
age,
)
self._context_tokens[chat_id] = new_token
self._context_token_at[chat_id] = now
self._save_state()
return new_token
return context_token
async def _flush_tool_hints(self, chat_id: str) -> None:
"""Send any buffered tool hints for *chat_id* as a single message.
Tool hints are coalesced to reduce message count and avoid hitting the
WeChat iLink rate limit (~7 msgs / 5 min). Failures are logged but
not raised so that the main message send is never blocked.
"""
hints = self._pending_tool_hints.pop(chat_id, None)
if not hints:
return
self.logger.info(
"Flushing {} buffered tool hint(s) for {}",
len(hints),
chat_id,
)
ctx_token = self._context_tokens.get(chat_id, "")
ctx_token = await self._refresh_context_token_if_stale(chat_id, ctx_token)
if not ctx_token:
self.logger.warning(
"Dropped {} buffered tool hint(s) for {}: no context_token",
len(hints),
chat_id,
)
return
try:
await self._send_text(chat_id, "\n\n".join(hints), ctx_token)
except Exception:
self.logger.exception(
"Failed to flush buffered tool hints for {}", chat_id
)
async def _send_typing(self, user_id: str, typing_ticket: str, status: int) -> None:
"""Best-effort sendtyping wrapper."""
if not typing_ticket:
@@ -1051,47 +944,11 @@ class WeixinChannel(BaseChannel):
self._assert_session_active()
is_progress = bool((msg.metadata or {}).get("_progress", False))
# Buffer tool hints to coalesce consecutive ones and avoid burning
# WeChat iLink rate-limit quota (~7 msgs / 5 min).
if is_progress and (msg.metadata or {}).get("_tool_hint"):
if not self.send_tool_hints:
return
self._pending_tool_hints.setdefault(msg.chat_id, []).append(msg.content)
self.logger.debug(
"Buffered tool hint for {} (count={})",
msg.chat_id,
len(self._pending_tool_hints[msg.chat_id]),
)
return
# Reasoning deltas are invisible in WeChat (there is no reasoning
# UI). Skip them entirely — do not send and do not flush buffer.
if is_progress and (msg.metadata or {}).get("_reasoning_delta"):
self.logger.debug(
"Dropped invisible reasoning delta for {}", msg.chat_id
)
return
content = msg.content.strip()
# Empty progress messages (e.g. after_iteration tool_events) must
# NOT act as separators — they have no visible content.
if is_progress and not content and not (msg.media or []):
self.logger.debug(
"Skipped empty progress message for {} (no visible content)",
msg.chat_id,
)
return
# Flush buffered hints before sending any visible message.
await self._flush_tool_hints(msg.chat_id)
if not is_progress:
await self._stop_typing(msg.chat_id, clear_remote=True)
content = msg.content.strip()
ctx_token = self._context_tokens.get(msg.chat_id, "")
ctx_token = await self._refresh_context_token_if_stale(msg.chat_id, ctx_token)
if not ctx_token:
raise RuntimeError(
f"WeChat context_token missing for chat_id={msg.chat_id}, cannot send"
@@ -1180,18 +1037,6 @@ class WeixinChannel(BaseChannel):
with suppress(Exception):
await self._send_typing(msg.chat_id, typing_ticket, TYPING_STATUS_CANCEL)
async def send_delta(
self, chat_id: str, delta: str, metadata: dict[str, Any] | None = None
) -> None:
"""Weixin iLink does not support native streaming deltas.
We only hook ``_stream_end`` so buffered tool hints are flushed even
when the final answer carries the ``_streamed`` flag and bypasses
:meth:`send`.
"""
if metadata and metadata.get("_stream_end"):
await self._flush_tool_hints(chat_id)
async def _start_typing(self, chat_id: str, context_token: str = "") -> None:
"""Start typing indicator immediately when a message is received."""
if not self._client or not self._token or not chat_id:
@@ -1275,11 +1120,10 @@ class WeixinChannel(BaseChannel):
}
data = await self._api_post("ilink/bot/sendmessage", body)
ret = data.get("ret", 0)
errcode = data.get("errcode", 0)
if (ret is not None and ret != 0) or (errcode is not None and errcode != 0):
if errcode and errcode != 0:
raise RuntimeError(
f"WeChat send text error (ret={ret}, errcode={errcode}): {data.get('errmsg', '')}"
f"WeChat send text error (code {errcode}): {data.get('errmsg', '')}"
)
async def _send_media_file(
@@ -1426,11 +1270,10 @@ class WeixinChannel(BaseChannel):
}
data = await self._api_post("ilink/bot/sendmessage", body)
ret = data.get("ret", 0)
errcode = data.get("errcode", 0)
if (ret is not None and ret != 0) or (errcode is not None and errcode != 0):
if errcode and errcode != 0:
raise RuntimeError(
f"WeChat send media error (ret={ret}, errcode={errcode}): {data.get('errmsg', '')}"
f"WeChat send media error (code {errcode}): {data.get('errmsg', '')}"
)
+81 -245
View File
@@ -1,7 +1,6 @@
"""CLI commands for nanobot."""
import asyncio
import functools
import os
import select
import signal
@@ -76,7 +75,6 @@ class SafeFileHistory(FileHistory):
from nanobot.cli.stream import StreamRenderer, ThinkingSpinner
from nanobot.config.paths import get_workspace_path, is_default_workspace
from nanobot.config.schema import Config
from nanobot.utils.evaluator import evaluate_response
from nanobot.utils.helpers import sync_workspace_templates
from nanobot.utils.restart import (
consume_restart_notice_from_env,
@@ -96,20 +94,6 @@ EXIT_COMMANDS = {"exit", "quit", "/exit", "/quit", ":q"}
_REASONING_SENTENCE_ENDINGS = (".", "!", "?", "", "", "")
_REASONING_FLUSH_CHARS = 60
_HEARTBEAT_PREAMBLE = (
"[Your response will be delivered directly to the user's messaging app. "
"Output ONLY the final user-facing message. Never reference internal "
"files (HEARTBEAT.md, AWARENESS.md, etc.), your instructions, or your "
"decision process. If nothing needs reporting, respond with a brief "
"no-op status and nothing else.]\n\n"
)
@functools.lru_cache(maxsize=None)
def _heartbeat_template() -> str | None:
from nanobot.utils.helpers import load_bundled_template
return load_bundled_template("HEARTBEAT.md")
# ---------------------------------------------------------------------------
# CLI input: prompt_toolkit for editing, paste, history, and display
# ---------------------------------------------------------------------------
@@ -720,144 +704,11 @@ def gateway(
_run_gateway(cfg, port=port)
def _load_or_create_desktop_config(config: str | None, workspace: str | None) -> Config:
"""Load the desktop-owned config, creating it on first launch."""
from nanobot.config.loader import (
get_config_path,
load_config,
resolve_config_env_vars,
save_config,
set_config_path,
)
from nanobot.config.schema import Config as NanobotConfig
config_path = Path(config).expanduser().resolve() if config else get_config_path()
set_config_path(config_path)
created = False
if config_path.exists():
try:
loaded = resolve_config_env_vars(load_config(config_path))
except ValueError as e:
console.print(f"[red]Error: {e}[/red]")
raise typer.Exit(1)
else:
loaded = NanobotConfig()
created = True
if workspace:
workspace_path = Path(workspace).expanduser()
loaded.agents.defaults.workspace = str(workspace_path)
created = True
if created:
save_config(loaded, config_path)
return loaded
def _configure_desktop_gateway(
config: Config,
*,
webui_port: int,
webui_socket: str | None,
token_issue_secret: str,
) -> None:
"""Force a local WebSocket-only gateway for the desktop app process."""
config.gateway.host = "127.0.0.1"
config.gateway.port = webui_port
config.gateway.heartbeat.enabled = False
extras = dict(getattr(config.channels, "__pydantic_extra__", None) or {})
for name, section in list(extras.items()):
if name == "websocket":
continue
if isinstance(section, dict):
extras[name] = {**section, "enabled": False}
else:
with suppress(Exception):
setattr(section, "enabled", False)
extras[name] = section
websocket_cfg = extras.get("websocket")
if not isinstance(websocket_cfg, dict):
websocket_cfg = {}
websocket_cfg.update(
{
"enabled": True,
"host": "127.0.0.1",
"port": webui_port,
"unix_socket_path": webui_socket or "",
"path": "/",
"token_issue_secret": token_issue_secret,
"websocket_requires_token": True,
"allow_from": ["*"],
"streaming": True,
}
)
extras["websocket"] = websocket_cfg
config.channels.__pydantic_extra__ = extras
@app.command("desktop-gateway", hidden=True)
def desktop_gateway(
webui_port: int = typer.Option(0, "--webui-port", min=0, max=65535),
webui_socket: str | None = typer.Option(None, "--webui-socket", help="Unix socket path for desktop IPC"),
token_issue_secret: str = typer.Option(..., "--token-issue-secret"),
workspace: str | None = typer.Option(None, "--workspace", "-w", help="Desktop workspace directory"),
config: str | None = typer.Option(None, "--config", "-c", help="Desktop config file"),
verbose: bool = typer.Option(False, "--verbose", "-v", help="Verbose output"),
):
"""Start the private local gateway used by nanobot Desktop."""
if not token_issue_secret.strip():
console.print("[red]Error: --token-issue-secret is required[/red]")
raise typer.Exit(1)
if webui_port <= 0 and not (webui_socket or "").strip():
console.print("[red]Error: --webui-port or --webui-socket is required[/red]")
raise typer.Exit(1)
if verbose:
logger.remove(_log_handler_id)
logger.add(
sys.stderr,
format=(
"<green>{time:YYYY-MM-DD HH:mm:ss}</green> | "
"<level>{level: <5}</level> | "
"<cyan>{extra[channel]}</cyan> | "
"<level>{message}</level>"
),
level="DEBUG",
colorize=None,
filter=lambda record: record["extra"].setdefault("channel", "-") or True,
)
cfg = _load_or_create_desktop_config(config, workspace)
_configure_desktop_gateway(
cfg,
webui_port=webui_port,
webui_socket=webui_socket,
token_issue_secret=token_issue_secret,
)
_run_gateway(
cfg,
port=webui_port,
webui_static_dist=False,
webui_runtime_surface="native",
webui_runtime_capabilities={
"can_restart_engine": True,
"can_pick_folder": True,
"can_open_logs": True,
"can_export_diagnostics": True,
},
health_server_enabled=False,
)
def _run_gateway(
config: Config,
*,
port: int | None = None,
open_browser_url: str | None = None,
webui_static_dist: bool = True,
webui_runtime_surface: str = "browser",
webui_runtime_capabilities: dict[str, Any] | None = None,
health_server_enabled: bool = True,
) -> None:
"""Shared gateway runtime; ``open_browser_url`` opens a tab once channels are up."""
from nanobot.agent.tools.cron import CronTool
@@ -867,6 +718,7 @@ def _run_gateway(
from nanobot.channels.websocket import publish_runtime_model_update
from nanobot.cron.service import CronService
from nanobot.cron.types import CronJob
from nanobot.heartbeat.service import HeartbeatService
from nanobot.providers.factory import build_provider_snapshot, load_provider_snapshot
from nanobot.providers.image_generation import image_gen_provider_configs
from nanobot.session.manager import SessionManager
@@ -958,9 +810,6 @@ def _run_gateway(
# Set cron callback (needs agent)
async def on_cron_job(job: CronJob) -> str | None:
"""Execute a cron job through the agent."""
async def _silent(*_args, **_kwargs):
pass
# Dream is an internal job — run directly, not through the agent loop.
if job.name == "dream":
try:
@@ -970,64 +819,7 @@ def _run_gateway(
logger.exception("Dream cron job failed")
return None
# Heartbeat is a system job that checks HEARTBEAT.md for active tasks.
if job.name == "heartbeat":
heartbeat_file = config.workspace_path / "HEARTBEAT.md"
try:
content = heartbeat_file.read_text(encoding="utf-8")
except OSError:
logger.debug("Heartbeat: HEARTBEAT.md missing")
return None
if not content or content == _heartbeat_template():
logger.debug("Heartbeat: HEARTBEAT.md empty or identical to template")
return None
channel, chat_id = _pick_heartbeat_target()
if channel == "cli":
return None
prompt = (
_HEARTBEAT_PREAMBLE
+ f"Review the following HEARTBEAT.md and report any active tasks:\n\n{content}"
)
message_suppress_token = None
if isinstance(message_tool, MessageTool):
message_suppress_token = message_tool.set_suppress_delivery(True)
try:
resp = await agent.process_direct(
prompt,
session_key="heartbeat",
channel=channel,
chat_id=chat_id,
on_progress=_silent,
)
finally:
if isinstance(message_tool, MessageTool) and message_suppress_token is not None:
message_tool.reset_suppress_delivery(message_suppress_token)
response = resp.content if resp else ""
# Keep a small tail of heartbeat history so the loop stays bounded.
session = agent.sessions.get_or_create("heartbeat")
session.retain_recent_legal_suffix(hb_cfg.keep_recent_messages)
agent.sessions.save(session)
if not response:
return None
should_notify = await evaluate_response(
response, prompt, agent.provider, agent.model, default_notify=False,
)
if should_notify:
logger.info("Heartbeat: completed, delivering response")
await _deliver_to_channel(
OutboundMessage(channel=channel, chat_id=chat_id, content=response),
record=True,
)
else:
logger.info("Heartbeat: silenced by post-run evaluation")
return response
from nanobot.utils.evaluator import evaluate_response
reminder_note = (
"The scheduled time has arrived. Deliver this reminder to the user now, "
@@ -1042,6 +834,9 @@ def _run_gateway(
if isinstance(cron_tool, CronTool):
cron_token = cron_tool.set_cron_context(True)
async def _silent(*_args, **_kwargs):
pass
message_record_token = None
if isinstance(message_tool, MessageTool):
message_record_token = message_tool.set_record_channel_delivery(True)
@@ -1098,14 +893,12 @@ def _run_gateway(
bus,
session_manager=session_manager,
webui_runtime_model_name=_webui_runtime_model_name,
webui_static_dist=webui_static_dist,
webui_runtime_surface=webui_runtime_surface,
webui_runtime_capabilities=webui_runtime_capabilities,
)
def _pick_heartbeat_target() -> tuple[str, str]:
"""Pick a routable channel/chat target for heartbeat-triggered messages."""
enabled = set(channels.enabled_channels)
# Prefer the most recently updated non-internal session on an enabled channel.
for item in session_manager.list_sessions():
key = item.get("key") or ""
if ":" not in key:
@@ -1115,8 +908,70 @@ def _run_gateway(
continue
if channel in enabled and chat_id:
return channel, chat_id
# Fallback keeps prior behavior but remains explicit.
return "cli", "direct"
# Create heartbeat service
heartbeat_preamble = (
"[Your response will be delivered directly to the user's messaging app. "
"Output ONLY the final user-facing message. Never reference internal "
"files (HEARTBEAT.md, AWARENESS.md, etc.), your instructions, or your "
"decision process. If nothing needs reporting, respond with just "
"'All clear.' and nothing else.]\n\n"
)
async def on_heartbeat_execute(tasks: str) -> str:
"""Phase 2: execute heartbeat tasks through the full agent loop."""
channel, chat_id = _pick_heartbeat_target()
async def _silent(*_args, **_kwargs):
pass
resp = await agent.process_direct(
heartbeat_preamble + tasks,
session_key="heartbeat",
channel=channel,
chat_id=chat_id,
on_progress=_silent,
)
# Keep a small tail of heartbeat history so the loop stays bounded
# without losing all short-term context between runs.
session = agent.sessions.get_or_create("heartbeat")
session.retain_recent_legal_suffix(hb_cfg.keep_recent_messages)
agent.sessions.save(session)
return resp.content if resp else ""
async def on_heartbeat_notify(response: str) -> None:
"""Deliver a heartbeat response to the user's channel.
In addition to publishing the outbound message, this injects the
delivered text as an assistant turn into the *target channel's*
session. Without this, a user reply on the channel (e.g. "Sure")
lands in a session that has no context about the heartbeat message
and the agent cannot follow through.
"""
channel, chat_id = _pick_heartbeat_target()
if channel == "cli":
return # No external channel available to deliver to
await _deliver_to_channel(
OutboundMessage(channel=channel, chat_id=chat_id, content=response),
record=True,
)
hb_cfg = config.gateway.heartbeat
heartbeat = HeartbeatService(
workspace=config.workspace_path,
llm_runtime=agent.llm_runtime,
on_execute=on_heartbeat_execute,
on_notify=on_heartbeat_notify,
interval_s=hb_cfg.interval_s,
enabled=hb_cfg.enabled,
timezone=config.agents.defaults.timezone,
)
if channels.enabled_channels:
console.print(f"[green]✓[/green] Channels enabled: {', '.join(channels.enabled_channels)}")
else:
@@ -1126,11 +981,7 @@ def _run_gateway(
if cron_status["jobs"] > 0:
console.print(f"[green]✓[/green] Cron: {cron_status['jobs']} scheduled jobs")
hb_cfg = config.gateway.heartbeat
if hb_cfg.enabled:
console.print(f"[green]✓[/green] Heartbeat: every {hb_cfg.interval_s}s")
else:
console.print("[yellow]✗[/yellow] Heartbeat: disabled")
console.print(f"[green]✓[/green] Heartbeat: every {hb_cfg.interval_s}s")
async def _health_server(host: str, health_port: int):
"""Lightweight HTTP health endpoint on the gateway port."""
@@ -1174,37 +1025,21 @@ def _run_gateway(
console.print(f"[green]✓[/green] Health endpoint: http://{host}:{health_port}/health")
async with server:
await server.serve_forever()
# Register Dream system job (idempotent on restart)
# Register Dream system job (always-on, idempotent on restart)
dream_cfg = config.agents.defaults.dream
if dream_cfg.model_override:
agent.dream.model = dream_cfg.model_override
agent.dream.max_batch_size = dream_cfg.max_batch_size
agent.dream.max_iterations = dream_cfg.max_iterations
agent.dream.annotate_line_ages = dream_cfg.annotate_line_ages
from nanobot.cron.types import CronJob, CronPayload, CronSchedule
if dream_cfg.enabled:
cron.register_system_job(CronJob(
id="dream",
name="dream",
schedule=dream_cfg.build_schedule(config.agents.defaults.timezone),
payload=CronPayload(kind="system_event"),
))
console.print(f"[green]✓[/green] Dream: {dream_cfg.describe_schedule()}")
else:
console.print("[yellow]○[/yellow] Dream: disabled")
# Register Heartbeat system job (idempotent on restart)
if hb_cfg.enabled:
cron.register_system_job(CronJob(
id="heartbeat",
name="heartbeat",
schedule=CronSchedule(
kind="every",
every_ms=hb_cfg.interval_s * 1000,
tz=config.agents.defaults.timezone,
),
payload=CronPayload(kind="system_event"),
))
from nanobot.cron.types import CronJob, CronPayload
cron.register_system_job(CronJob(
id="dream",
name="dream",
schedule=dream_cfg.build_schedule(config.agents.defaults.timezone),
payload=CronPayload(kind="system_event"),
))
console.print(f"[green]✓[/green] Dream: {dream_cfg.describe_schedule()}")
async def _open_browser_when_ready() -> None:
"""Wait for the gateway to bind, then point the user's browser at the webui."""
@@ -1232,12 +1067,12 @@ def _run_gateway(
async def run():
try:
await cron.start()
await heartbeat.start()
tasks = [
agent.run(),
channels.start_all(),
_health_server(config.gateway.host, port),
]
if health_server_enabled:
tasks.append(_health_server(config.gateway.host, port))
if open_browser_url:
tasks.append(_open_browser_when_ready())
await asyncio.gather(*tasks)
@@ -1250,6 +1085,7 @@ def _run_gateway(
console.print(traceback.format_exc())
finally:
await agent.close_mcp()
heartbeat.stop()
cron.stop()
agent.stop()
await channels.stop_all()
+1 -1
View File
@@ -1155,7 +1155,7 @@ _SETTINGS_SECTIONS: dict[str, tuple[str, str, set[str] | None]] = {
"Agent Settings": ("Agent Defaults", "Configure default model, temperature, and behavior", None),
"Channel Common": ("Channel Common", "Configure cross-channel behavior: progress, tool hints, retries", None),
"API Server": ("API Server", "Configure OpenAI-compatible API endpoint", None),
"Gateway": ("Gateway Settings", "Configure server host, port", None),
"Gateway": ("Gateway Settings", "Configure server host, port, and heartbeat", None),
"Tools": ("Tools Settings", "Configure web search, shell exec, and other tools", {"mcp_servers"}),
}
+1 -1
View File
@@ -123,7 +123,7 @@ async def cmd_stop(ctx: CommandContext) -> OutboundMessage:
"""Cancel all active tasks and subagents for the session."""
loop = ctx.loop
msg = ctx.msg
total = await loop._cancel_active_tasks(ctx.key)
total = await loop._cancel_active_tasks(msg.session_key)
content = f"Stopped {total} task(s)." if total else "No active task to stop."
return OutboundMessage(
channel=msg.channel, chat_id=msg.chat_id, content=content,
+1 -7
View File
@@ -10,11 +10,10 @@ import pydantic
from loguru import logger
from pydantic import BaseModel
from nanobot.config.schema import Config, _resolve_tool_config_refs
from nanobot.config.schema import Config
# Global variable to store current config path (for multi-instance support)
_current_config_path: Path | None = None
_schema_refs_ready = False
def set_config_path(path: Path) -> None:
@@ -40,11 +39,6 @@ def load_config(config_path: Path | None = None) -> Config:
Returns:
Loaded configuration object.
"""
global _schema_refs_ready
if not _schema_refs_ready:
_resolve_tool_config_refs()
_schema_refs_ready = True
path = config_path or get_config_path()
config = Config()
+42 -37
View File
@@ -11,7 +11,6 @@ from pydantic_settings import BaseSettings
from nanobot.cron.types import CronSchedule
if TYPE_CHECKING:
from nanobot.agent.tools.cli_apps import CliAppsToolConfig
from nanobot.agent.tools.image_generation import ImageGenerationToolConfig
from nanobot.agent.tools.self import MyToolConfig
from nanobot.agent.tools.shell import ExecToolConfig
@@ -37,7 +36,6 @@ class ChannelsConfig(Base):
send_progress: bool = True # stream agent's text progress to the channel
send_tool_hints: bool = False # stream tool-call hints (e.g. read_file("…"))
show_reasoning: bool = True # surface model reasoning when channel implements it
extract_document_text: bool = True # extract text from document attachments before sending to the model
send_max_retries: int = Field(default=3, ge=0, le=10) # Max delivery attempts (initial send included)
transcription_provider: str = "groq" # Voice transcription backend: "groq" or "openai"
transcription_language: str | None = Field(default=None, pattern=r"^[a-z]{2,3}$") # Optional ISO-639-1 hint for audio transcription
@@ -48,7 +46,6 @@ class DreamConfig(Base):
_HOUR_MS = 3_600_000
enabled: bool = True # Register the periodic Dream consolidation job on startup
interval_h: int = Field(default=2, ge=1) # Every 2 hours by default
cron: str | None = Field(default=None, exclude=True) # Legacy compatibility override
model_override: str | None = Field(
@@ -94,7 +91,6 @@ FallbackCandidate = str | InlineFallbackConfig
class ModelPresetConfig(Base):
"""A named set of model + generation parameters for quick switching."""
label: str | None = None
model: str
provider: str = "auto"
max_tokens: int = 8192
@@ -159,8 +155,35 @@ class AgentDefaults(Base):
validation_alias=AliasChoices("consolidationRatio"),
serialization_alias="consolidationRatio",
) # Consolidation target ratio (0.5 = 50% of budget retained after compression)
vision_models: list[str] = Field(default_factory=list) # Models that support image input
audio_models: list[str] = Field(default_factory=list) # Models that support native audio input
video_models: list[str] = Field(default_factory=list) # Models that support native video input
dream: DreamConfig = Field(default_factory=DreamConfig)
@staticmethod
def _bare_model(model: str) -> str:
"""Strip provider prefix, e.g. 'openai/gpt-4o' -> 'gpt-4o'."""
return model.split("/", 1)[-1].lower() if "/" in model else model.lower()
def _supports_capability(self, model: str, patterns: list[str]) -> bool | None:
"""Check if model matches any pattern. Returns None if patterns is empty."""
if not patterns:
return None
bare = self._bare_model(model)
return any(p.lower() in bare for p in patterns)
def supports_vision(self, model: str) -> bool | None:
"""Check if model supports vision. None if unconfigured."""
return self._supports_capability(model, self.vision_models)
def supports_audio(self, model: str) -> bool | None:
"""Check if model supports native audio. None if unconfigured."""
return self._supports_capability(model, self.audio_models)
def supports_video(self, model: str) -> bool | None:
"""Check if model supports native video. None if unconfigured."""
return self._supports_capability(model, self.video_models)
class AgentsConfig(Base):
"""Agent configuration."""
@@ -173,9 +196,8 @@ class ProviderConfig(Base):
api_key: str | None = None
api_base: str | None = None
api_type: Literal["auto", "chat_completions", "responses"] = "auto" # Request API surface
extra_headers: dict[str, str] | None = None # Custom headers (e.g. APP-Code for AiHubMix)
extra_body: dict[str, Any] | None = None # Extra provider request fields; shape depends on provider/API surface
extra_body: dict[str, Any] | None = None # Extra fields merged into every request body
class BedrockProviderConfig(ProviderConfig):
@@ -216,7 +238,6 @@ class ProvidersConfig(Base):
ant_ling: ProviderConfig = Field(default_factory=ProviderConfig) # Ant Ling
aihubmix: ProviderConfig = Field(default_factory=ProviderConfig) # AiHubMix API gateway
siliconflow: ProviderConfig = Field(default_factory=ProviderConfig) # SiliconFlow (硅基流动)
novita: ProviderConfig = Field(default_factory=ProviderConfig) # Novita AI
volcengine: ProviderConfig = Field(default_factory=ProviderConfig) # VolcEngine (火山引擎)
volcengine_coding_plan: ProviderConfig = Field(default_factory=ProviderConfig) # VolcEngine Coding Plan
byteplus: ProviderConfig = Field(default_factory=ProviderConfig) # BytePlus (VolcEngine international)
@@ -226,19 +247,9 @@ class ProvidersConfig(Base):
qianfan: ProviderConfig = Field(default_factory=ProviderConfig) # Qianfan (百度千帆)
nvidia: ProviderConfig = Field(default_factory=ProviderConfig) # NVIDIA NIM (nvapi- keys)
@model_validator(mode="after")
def _validate_api_type_scope(self) -> "ProvidersConfig":
for name in self.__class__.model_fields:
if name == "openai":
continue
provider = getattr(self, name, None)
if isinstance(provider, ProviderConfig) and provider.api_type != "auto":
raise ValueError("providers.<name>.api_type is only supported for providers.openai")
return self
class HeartbeatConfig(Base):
"""Heartbeat service configuration (now backed by cron)."""
"""Heartbeat service configuration."""
enabled: bool = True
interval_s: int = 30 * 60 # 30 minutes
@@ -268,13 +279,23 @@ class MCPServerConfig(Base):
command: str = "" # Stdio: command to run (e.g. "npx")
args: list[str] = Field(default_factory=list) # Stdio: command arguments
env: dict[str, str] = Field(default_factory=dict) # Stdio: extra env vars
cwd: str = "" # Stdio: working directory for MCP server runtime artifacts
url: str = "" # HTTP/SSE: endpoint URL
headers: dict[str, str] = Field(default_factory=dict) # HTTP/SSE: custom headers
tool_timeout: int = 30 # seconds before a tool call is cancelled
enabled_tools: list[str] = Field(default_factory=lambda: ["*"]) # Only register these tools; accepts raw MCP names or wrapped mcp_<server>_<tool> names; ["*"] = all tools; [] = no tools
class InputLimitsConfig(Base):
"""Limits for user-provided multimodal inputs."""
max_input_images: int = 3
max_input_image_bytes: int = 10 * 1024 * 1024 # 10 MB
max_input_audios: int = 1
max_input_audio_bytes: int = 10 * 1024 * 1024 # 10 MB
max_input_videos: int = 1
max_input_video_bytes: int = 20 * 1024 * 1024 # 20 MB
def _lazy_default(module_path: str, class_name: str) -> Any:
"""Deferred import helper for ToolsConfig default factories."""
import importlib
@@ -292,21 +313,12 @@ class ToolsConfig(Base):
web: WebToolsConfig = Field(default_factory=lambda: _lazy_default("nanobot.agent.tools.web", "WebToolsConfig"))
exec: ExecToolConfig = Field(default_factory=lambda: _lazy_default("nanobot.agent.tools.shell", "ExecToolConfig"))
cli_apps: CliAppsToolConfig = Field(default_factory=lambda: _lazy_default("nanobot.agent.tools.cli_apps", "CliAppsToolConfig"))
my: MyToolConfig = Field(default_factory=lambda: _lazy_default("nanobot.agent.tools.self", "MyToolConfig"))
image_generation: ImageGenerationToolConfig = Field(
default_factory=lambda: _lazy_default("nanobot.agent.tools.image_generation", "ImageGenerationToolConfig"),
)
restrict_to_workspace: bool = False # policy intent: keep tool access inside workspace when possible
webui_allow_local_service_access: bool = Field(
default=True,
validation_alias=AliasChoices(
"webuiAllowLocalServiceAccess",
"webui_allow_local_service_access",
"allowLocalPreviewAccess",
"allow_local_preview_access",
),
) # allow WebUI Full Access shell checks against localhost services; legacy allowLocalPreviewAccess still reads
input_limits: InputLimitsConfig = Field(default_factory=InputLimitsConfig)
restrict_to_workspace: bool = False # restrict all tool access to workspace directory
mcp_servers: dict[str, MCPServerConfig] = Field(default_factory=dict)
ssrf_whitelist: list[str] = Field(default_factory=list) # CIDR ranges to exempt from SSRF blocking (e.g. ["100.64.0.0/10"] for Tailscale)
@@ -325,11 +337,6 @@ class Config(BaseSettings):
validation_alias=AliasChoices("modelPresets", "model_presets"),
)
def __init__(self, **values: Any) -> None:
if not type(self).__pydantic_complete__:
_resolve_tool_config_refs()
super().__init__(**values)
@model_validator(mode="after")
def _validate_model_preset(self) -> "Config":
if "default" in self.model_presets:
@@ -493,7 +500,6 @@ def _resolve_tool_config_refs() -> None:
"""
import sys
from nanobot.agent.tools.cli_apps import CliAppsToolConfig
from nanobot.agent.tools.image_generation import ImageGenerationToolConfig
from nanobot.agent.tools.self import MyToolConfig
from nanobot.agent.tools.shell import ExecToolConfig
@@ -502,7 +508,6 @@ def _resolve_tool_config_refs() -> None:
# Re-export into this module's namespace
mod = sys.modules[__name__]
mod.ExecToolConfig = ExecToolConfig # type: ignore[attr-defined]
mod.CliAppsToolConfig = CliAppsToolConfig # type: ignore[attr-defined]
mod.WebToolsConfig = WebToolsConfig # type: ignore[attr-defined]
mod.WebSearchConfig = WebSearchConfig # type: ignore[attr-defined]
mod.WebFetchConfig = WebFetchConfig # type: ignore[attr-defined]
+1 -13
View File
@@ -1,18 +1,6 @@
"""Cron service for scheduled agent tasks."""
from nanobot.cron.service import CronService
from nanobot.cron.types import CronJob, CronSchedule
__all__ = ["CronService", "CronJob", "CronSchedule"]
_LAZY = {"CronService": ".service"}
def __getattr__(name: str):
module_path = _LAZY.get(name)
if module_path is None:
raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
from importlib import import_module
mod = import_module(module_path, __name__)
val = getattr(mod, name)
globals()[name] = val
return val
+5
View File
@@ -0,0 +1,5 @@
"""Heartbeat service for periodic agent wake-ups."""
from nanobot.heartbeat.service import HeartbeatService
__all__ = ["HeartbeatService"]
+243
View File
@@ -0,0 +1,243 @@
"""Heartbeat service - periodic agent wake-up to check for tasks."""
from __future__ import annotations
import asyncio
from pathlib import Path
from typing import Any, Callable, Coroutine
from loguru import logger
from nanobot.providers.base import LLMProvider
from nanobot.utils.llm_runtime import LLMRuntimeResolver, static_llm_runtime
_HEARTBEAT_TOOL = [
{
"type": "function",
"function": {
"name": "heartbeat",
"description": "Report heartbeat decision after reviewing tasks.",
"parameters": {
"type": "object",
"properties": {
"action": {
"type": "string",
"enum": ["skip", "run"],
"description": "skip = nothing to do, run = has active tasks",
},
"tasks": {
"type": "string",
"description": "Natural-language summary of active tasks (required for run)",
},
},
"required": ["action"],
},
},
}
]
class HeartbeatService:
"""
Periodic heartbeat service that wakes the agent to check for tasks.
Phase 1 (decision): reads HEARTBEAT.md and asks the LLM via a virtual
tool call whether there are active tasks. This avoids free-text parsing
and the unreliable HEARTBEAT_OK token.
Phase 2 (execution): only triggered when Phase 1 returns ``run``. The
``on_execute`` callback runs the task through the full agent loop and
returns the result to deliver.
"""
def __init__(
self,
workspace: Path,
provider: LLMProvider | None = None,
model: str | None = None,
on_execute: Callable[[str], Coroutine[Any, Any, str]] | None = None,
on_notify: Callable[[str], Coroutine[Any, Any, None]] | None = None,
interval_s: int = 30 * 60,
enabled: bool = True,
timezone: str | None = None,
llm_runtime: LLMRuntimeResolver | None = None,
):
self.workspace = workspace
if llm_runtime is None:
if provider is None or model is None:
raise ValueError("HeartbeatService requires either llm_runtime or provider/model")
llm_runtime = static_llm_runtime(provider, model)
self._llm_runtime = llm_runtime
self.on_execute = on_execute
self.on_notify = on_notify
self.interval_s = interval_s
self.enabled = enabled
self.timezone = timezone
self._running = False
self._task: asyncio.Task | None = None
@property
def heartbeat_file(self) -> Path:
return self.workspace / "HEARTBEAT.md"
def _read_heartbeat_file(self) -> str | None:
if self.heartbeat_file.exists():
try:
return self.heartbeat_file.read_text(encoding="utf-8")
except Exception:
return None
return None
async def _decide(self, content: str) -> tuple[str, str]:
"""Phase 1: ask LLM to decide skip/run via virtual tool call.
Returns (action, tasks) where action is 'skip' or 'run'.
"""
from nanobot.utils.helpers import current_time_str
llm = self._llm_runtime()
response = await llm.provider.chat_with_retry(
messages=[
{"role": "system", "content": "You are a heartbeat agent. Call the heartbeat tool to report your decision."},
{"role": "user", "content": (
f"Current Time: {current_time_str(self.timezone)}\n\n"
"Review the following HEARTBEAT.md and decide whether there are active tasks.\n\n"
f"{content}"
)},
],
tools=_HEARTBEAT_TOOL,
model=llm.model,
)
if not response.should_execute_tools:
if response.has_tool_calls:
logger.warning(
"Ignoring heartbeat tool calls under finish_reason='{}'",
response.finish_reason,
)
return "skip", ""
args = response.tool_calls[0].arguments
return args.get("action", "skip"), args.get("tasks", "")
async def start(self) -> None:
"""Start the heartbeat service."""
if not self.enabled:
logger.info("Heartbeat disabled")
return
if self._running:
logger.warning("Heartbeat already running")
return
self._running = True
self._task = asyncio.create_task(self._run_loop())
logger.info("Heartbeat started (every {}s)", self.interval_s)
def stop(self) -> None:
"""Stop the heartbeat service."""
self._running = False
if self._task:
self._task.cancel()
self._task = None
async def _run_loop(self) -> None:
"""Main heartbeat loop."""
while self._running:
try:
await asyncio.sleep(self.interval_s)
if self._running:
await self._tick()
except asyncio.CancelledError:
break
except Exception:
logger.exception("Heartbeat error")
@staticmethod
def _is_deliverable(response: str) -> bool:
"""Check if a heartbeat response is suitable for user delivery.
Filters out two classes of bad output before the evaluator runs:
1. **Finalization fallback** the runner hit empty-response retries
and produced a canned error message. For heartbeat, empty output
is a valid "nothing to report" outcome, not a failure.
2. **Leaked reasoning** the model reflected internal file names,
decision logic, or meta-commentary instead of a user-facing report.
"""
text = response.lower()
# Runner finalization fallback
if "couldn't produce a final answer" in text:
return False
# Leaked internal reasoning patterns
leaked_patterns = [
"heartbeat.md",
"awareness.md",
"judgment call:",
"decision logic",
"valid options are",
"my instructions",
"i am supposed to",
"strict heartbeat interpretation",
]
if any(pattern in text for pattern in leaked_patterns):
return False
return True
async def _tick(self) -> None:
"""Execute a single heartbeat tick."""
from nanobot.utils.evaluator import evaluate_response
content = self._read_heartbeat_file()
if not content:
logger.debug("Heartbeat: HEARTBEAT.md missing or empty")
return
logger.info("Heartbeat: checking for tasks...")
try:
action, tasks = await self._decide(content)
if action != "run":
logger.info("Heartbeat: OK (nothing to report)")
return
logger.info("Heartbeat: tasks found, executing...")
if self.on_execute:
response = await self.on_execute(tasks)
if not response:
logger.info("Heartbeat: no response from execution")
return
if not self._is_deliverable(response):
logger.info(
"Heartbeat: suppressed non-deliverable response ({})",
response[:80],
)
return
llm = self._llm_runtime()
should_notify = await evaluate_response(
response, tasks, llm.provider, llm.model,
)
if should_notify and self.on_notify:
logger.info("Heartbeat: completed, delivering response")
await self.on_notify(response)
else:
logger.info("Heartbeat: silenced by post-run evaluation")
except Exception:
logger.exception("Heartbeat execution failed")
async def trigger_now(self) -> str | None:
"""Manually trigger a heartbeat."""
content = self._read_heartbeat_file()
if not content:
return None
action, tasks = await self._decide(content)
if action != "run" or not self.on_execute:
return None
return await self.on_execute(tasks)
+9 -16
View File
@@ -45,21 +45,13 @@ class AnthropicProvider(LLMProvider):
if api_key:
client_kw["api_key"] = api_key
if api_base:
client_kw["base_url"] = self._normalize_base_url(api_base)
client_kw["base_url"] = api_base
if extra_headers:
client_kw["default_headers"] = extra_headers
# Keep retries centralized in LLMProvider._run_with_retry to avoid retry amplification.
client_kw["max_retries"] = 0
self._client = AsyncAnthropic(**client_kw)
@staticmethod
def _normalize_base_url(api_base: str) -> str:
"""Anthropic SDK appends /v1 to request paths internally."""
normalized = api_base.rstrip("/")
if normalized.endswith("/v1"):
return normalized[: -len("/v1")]
return normalized
@classmethod
def _handle_error(cls, e: Exception) -> LLMResponse:
response = getattr(e, "response", None)
@@ -220,7 +212,7 @@ class AnthropicProvider(LLMProvider):
@staticmethod
def _convert_user_content(content: Any) -> Any:
"""Convert user message content, translating image_url blocks."""
"""Convert user message content, translating image_url and input_audio blocks."""
if isinstance(content, str) or content is None:
return content or "(empty)"
if not isinstance(content, list):
@@ -236,12 +228,13 @@ class AnthropicProvider(LLMProvider):
if converted:
result.append(converted)
continue
if not item.get("type"):
# Anthropic requires every content block to declare a "type".
# A tool that returned a bare dict (or a list of dicts) lands
# here; coerce it to a text block instead of emitting a block
# the API rejects with "content.0.type: Field required".
result.append({"type": "text", "text": str(item)})
if item.get("type") == "input_audio":
# Anthropic doesn't support native audio → text placeholder
result.append(LLMProvider._media_placeholder("input_audio", item))
continue
if item.get("type") == "video_url":
# Anthropic doesn't support native video → text placeholder
result.append(LLMProvider._media_placeholder("video_url", item))
continue
result.append(item)
return result or "(empty)"
+37 -58
View File
@@ -13,8 +13,6 @@ from typing import Any
from loguru import logger
from nanobot.utils.helpers import image_placeholder_text
@dataclass
class ToolCallRequest:
@@ -315,29 +313,6 @@ class LLMProvider(ABC):
return cls._is_transient_error(response.content)
@classmethod
def is_arrearage_response(cls, response: LLMResponse) -> bool:
"""Detect API-key arrearage / quota / billing errors that won't clear on retry.
These surface as HTTP 402 or as billing semantic tokens (e.g.
``insufficient_quota``, ``payment_required``); reuses the same token and
text markers the 429 retry policy treats as non-retryable.
"""
if response.error_status_code is not None and int(response.error_status_code) == 402:
return True
type_token = cls._normalize_error_token(response.error_type)
code_token = cls._normalize_error_token(response.error_code)
if any(
token in cls._NON_RETRYABLE_429_ERROR_TOKENS
for token in (type_token, code_token)
if token is not None
):
return True
content = (response.content or "").lower()
return any(marker in content for marker in cls._NON_RETRYABLE_429_TEXT_MARKERS)
@staticmethod
def _normalize_error_token(value: Any) -> str | None:
if value is None:
@@ -462,9 +437,23 @@ class LLMProvider(ABC):
return merged
_MEDIA_LABEL_MAP = {"image_url": "image", "input_audio": "audio", "video_url": "video"}
_STRIP_MEDIA_TYPES = frozenset({"image_url", "input_audio", "video_url"})
@staticmethod
def _strip_image_content(messages: list[dict[str, Any]]) -> list[dict[str, Any]] | None:
"""Replace image_url blocks with text placeholder. Returns None if no images found."""
def _media_placeholder(btype: str, block: dict[str, Any]) -> dict[str, str]:
"""Build a text placeholder for a media block."""
path = (block.get("_meta") or {}).get("path", "")
label = LLMProvider._MEDIA_LABEL_MAP.get(btype, "media")
text = f"[{label}: {path}]" if path else f"[{label}]"
return {"type": "text", "text": text}
@staticmethod
def _strip_media_content(messages: list[dict[str, Any]]) -> list[dict[str, Any]] | None:
"""Replace image_url, input_audio, and video_url blocks with text placeholders.
Returns None if no media blocks were found (no changes needed).
"""
found = False
result = []
for msg in messages:
@@ -472,10 +461,8 @@ class LLMProvider(ABC):
if isinstance(content, list):
new_content = []
for b in content:
if isinstance(b, dict) and b.get("type") == "image_url":
path = (b.get("_meta") or {}).get("path", "")
placeholder = image_placeholder_text(path, empty="[image omitted]")
new_content.append({"type": "text", "text": placeholder})
if isinstance(b, dict) and b.get("type") in LLMProvider._STRIP_MEDIA_TYPES:
new_content.append(LLMProvider._media_placeholder(b["type"], b))
found = True
else:
new_content.append(b)
@@ -485,8 +472,13 @@ class LLMProvider(ABC):
return result if found else None
@staticmethod
def _strip_image_content_inplace(messages: list[dict[str, Any]]) -> bool:
"""Replace image_url blocks with text placeholder *in-place*.
def _strip_image_content(messages: list[dict[str, Any]]) -> list[dict[str, Any]] | None:
"""Replace image_url blocks with text placeholder. Returns None if no images found."""
return LLMProvider._strip_media_content(messages)
@staticmethod
def _strip_media_content_inplace(messages: list[dict[str, Any]]) -> bool:
"""Replace media blocks with text placeholder *in-place*.
Mutates the content lists of the original message dicts so that
callers holding references to those dicts also see the stripped
@@ -497,13 +489,16 @@ class LLMProvider(ABC):
content = msg.get("content")
if isinstance(content, list):
for i, b in enumerate(content):
if isinstance(b, dict) and b.get("type") == "image_url":
path = (b.get("_meta") or {}).get("path", "")
placeholder = image_placeholder_text(path, empty="[image omitted]")
content[i] = {"type": "text", "text": placeholder}
if isinstance(b, dict) and b.get("type") in LLMProvider._STRIP_MEDIA_TYPES:
content[i] = LLMProvider._media_placeholder(b["type"], b)
found = True
return found
@staticmethod
def _strip_image_content_inplace(messages: list[dict[str, Any]]) -> bool:
"""Replace image_url blocks with text placeholder *in-place*."""
return LLMProvider._strip_media_content_inplace(messages)
async def _safe_chat(self, **kwargs: Any) -> LLMResponse:
"""Call chat() and convert unexpected exceptions to error responses."""
try:
@@ -580,20 +575,11 @@ class LLMProvider(ABC):
if reasoning_effort is self._SENTINEL:
reasoning_effort = self.generation.reasoning_effort
has_streamed_content = False
async def _tracking_delta(text: str) -> None:
nonlocal has_streamed_content
if text:
has_streamed_content = True
if on_content_delta:
await on_content_delta(text)
kw: dict[str, Any] = dict(
messages=messages, tools=tools, model=model,
max_tokens=max_tokens, temperature=temperature,
reasoning_effort=reasoning_effort, tool_choice=tool_choice,
on_content_delta=_tracking_delta if on_content_delta is not None else None,
on_content_delta=on_content_delta,
on_thinking_delta=on_thinking_delta,
on_tool_call_delta=on_tool_call_delta,
)
@@ -603,7 +589,6 @@ class LLMProvider(ABC):
messages,
retry_mode=retry_mode,
on_retry_wait=on_retry_wait,
should_retry_guard=lambda: not has_streamed_content,
)
async def chat_with_retry(
@@ -750,7 +735,6 @@ class LLMProvider(ABC):
*,
retry_mode: str,
on_retry_wait: Callable[[str], Awaitable[None]] | None,
should_retry_guard: Callable[[], bool] | None = None,
) -> LLMResponse:
attempt = 0
delays = list(self._CHAT_RETRY_DELAYS)
@@ -764,11 +748,6 @@ class LLMProvider(ABC):
if response.finish_reason != "error":
return response
last_response = response
if should_retry_guard is not None and not should_retry_guard():
logger.warning(
"LLM stream failed after content was emitted; skipping retry"
)
return response
error_key = ((response.content or "").strip().lower() or None)
if error_key and error_key == last_error_key:
identical_error_count += 1
@@ -777,18 +756,18 @@ class LLMProvider(ABC):
identical_error_count = 1 if error_key else 0
if not self._is_transient_response(response):
stripped = self._strip_image_content(original_messages)
stripped = self._strip_media_content(original_messages)
if stripped is not None and stripped != kw["messages"]:
logger.warning(
"Non-transient LLM error with image content, retrying without images"
"Non-transient LLM error with media content, retrying without media"
)
retry_kw = dict(kw)
retry_kw["messages"] = stripped
result = await call(**retry_kw)
# Permanently strip images from the original messages so
# Permanently strip media from the original messages so
# subsequent iterations do not repeat the error-retry cycle.
if result.finish_reason != "error":
self._strip_image_content_inplace(original_messages)
self._strip_media_content_inplace(original_messages)
return result
return response
-3
View File
@@ -98,7 +98,6 @@ def _make_provider_core(
extra_headers=p.extra_headers if p else None,
spec=spec,
extra_body=p.extra_body if p else None,
api_type=p.api_type if p and provider_name == "openai" else "auto",
)
provider.generation = resolved.to_generation_settings()
@@ -184,7 +183,6 @@ def provider_signature(
config.get_api_base(fallback.model, preset=fallback),
fp.extra_headers if fp else None,
fp.extra_body if fp else None,
fp.api_type if fp else "auto",
getattr(fp, "region", None) if fp else None,
getattr(fp, "profile", None) if fp else None,
fallback.max_tokens,
@@ -201,7 +199,6 @@ def provider_signature(
config.get_api_base(resolved.model, preset=resolved),
p.extra_headers if p else None,
p.extra_body if p else None,
p.api_type if p else "auto",
getattr(p, "region", None) if p else None,
getattr(p, "profile", None) if p else None,
resolved.max_tokens,
+1 -2
View File
@@ -207,9 +207,8 @@ class GitHubCopilotProvider(OpenAICompatProvider):
async def _refresh_client_api_key(self) -> str:
token = await self._get_copilot_access_token()
client = await self._ensure_client()
self.api_key = token
client.api_key = token
self._client.api_key = token
return token
async def chat(
+16 -729
View File
@@ -2,10 +2,8 @@
from __future__ import annotations
import asyncio
import base64
import binascii
import re
from abc import ABC, abstractmethod
from dataclasses import dataclass
from pathlib import Path
@@ -33,14 +31,6 @@ _AIHUBMIX_ASPECT_RATIO_SIZES = {
}
_GEMINI_DEFAULT_TIMEOUT_S = 120.0
_GEMINI_IMAGEN_ASPECT_RATIOS = {"1:1", "9:16", "16:9", "3:4", "4:3"}
_OLLAMA_DEFAULT_SIDE = 1024
_OLLAMA_SIZE_PRESETS = {
"1K": 1024,
"2K": 2048,
"4K": 4096,
}
_OLLAMA_EXPLICIT_SIZE_RE = re.compile(r"^\s*(\d+)\s*[xX]\s*(\d+)\s*$")
_OLLAMA_ASPECT_RATIO_RE = re.compile(r"^\s*(\d+)\s*:\s*(\d+)\s*$")
class ImageGenerationError(RuntimeError):
@@ -139,11 +129,6 @@ _IMAGE_GEN_PROVIDERS: dict[str, type[ImageGenerationProvider]] = {}
def register_image_gen_provider(cls: type[ImageGenerationProvider]) -> None:
"""Register an image provider at import time only.
The registry is populated by module side effects so provider discovery
stays lazy and consistent across the process.
"""
name = cls.provider_name
if not name:
raise ValueError(f"{cls.__name__} must set provider_name")
@@ -234,10 +219,7 @@ class ImageGenerationProvider(ABC):
*,
headers: dict[str, str],
body: dict[str, Any],
client: httpx.AsyncClient | None = None,
) -> httpx.Response:
if client is not None:
return await client.post(url, headers=headers, json=body)
if self._client is not None:
return await self._client.post(url, headers=headers, json=body)
async with httpx.AsyncClient(timeout=self.timeout) as c:
@@ -408,11 +390,10 @@ class AIHubMixImageGenerationClient(ImageGenerationProvider):
model_path = _aihubmix_model_path(model)
url = f"{self.api_base}/models/{model_path}/predictions"
try:
response = await self._http_post(
response = await client.post(
url,
headers={**headers, "Content-Type": "application/json"},
body=body,
client=client,
json=body,
)
except httpx.TimeoutException as exc:
raise ImageGenerationError("AIHubMix image generation timed out") from exc
@@ -448,139 +429,6 @@ def _http_error_detail(response: httpx.Response) -> str:
return response.text[:500] or "<empty response body>"
def _round_to_multiple(value: float, multiple: int = 8) -> int:
rounded = int(round(value / multiple) * multiple)
return max(multiple, rounded)
def _ollama_dimensions(aspect_ratio: str | None, image_size: str | None) -> tuple[int, int]:
if image_size:
size = image_size.strip()
explicit = _OLLAMA_EXPLICIT_SIZE_RE.fullmatch(size)
if explicit:
return int(explicit.group(1)), int(explicit.group(2))
long_side = _OLLAMA_SIZE_PRESETS.get(size.upper(), _OLLAMA_DEFAULT_SIDE)
else:
long_side = _OLLAMA_DEFAULT_SIDE
if not aspect_ratio:
return long_side, long_side
ratio = _OLLAMA_ASPECT_RATIO_RE.fullmatch(aspect_ratio.strip())
if ratio is None:
return long_side, long_side
width_ratio = int(ratio.group(1))
height_ratio = int(ratio.group(2))
if width_ratio <= 0 or height_ratio <= 0:
return long_side, long_side
if width_ratio >= height_ratio:
width = long_side
height = _round_to_multiple(long_side * height_ratio / width_ratio)
else:
height = long_side
width = _round_to_multiple(long_side * width_ratio / height_ratio)
return max(8, width), max(8, height)
def _ollama_image_data_url(value: str) -> str:
if value.startswith("data:image/"):
return value
return _b64_image_data_url(value)
def _ollama_images_from_payload(payload: dict[str, Any]) -> list[str]:
images: list[str] = []
def collect(value: Any) -> None:
if isinstance(value, str) and value:
images.append(_ollama_image_data_url(value))
elif isinstance(value, list):
for item in value:
collect(item)
collect(payload.get("image"))
collect(payload.get("images"))
return images
class OllamaImageGenerationClient(ImageGenerationProvider):
"""Async client for Ollama native image generation models."""
provider_name = "ollama"
default_timeout = 300.0
def _default_base_url(self) -> str:
return "http://localhost:11434/api"
def _resolve_base_url(self, api_base: str | None) -> str:
if api_base:
base = api_base.rstrip("/")
if base.endswith("/v1"):
return f"{base[:-3]}/api"
return base
return self._default_base_url()
async def generate(
self,
*,
prompt: str,
model: str,
reference_images: list[str] | None = None,
aspect_ratio: str | None = None,
image_size: str | None = None,
) -> GeneratedImageResponse:
if reference_images:
raise ImageGenerationError(
"Ollama image generation does not support reference images"
)
width, height = _ollama_dimensions(aspect_ratio, image_size)
body: dict[str, Any] = {
"model": model,
"prompt": prompt,
"width": width,
"height": height,
"steps": 0,
}
body.update(self.extra_body)
body["stream"] = False
headers = {
"Content-Type": "application/json",
**self.extra_headers,
}
if self.api_key:
headers["Authorization"] = f"Bearer {self.api_key}"
url = f"{self.api_base}/generate"
response = await self._http_post(url, headers=headers, body=body)
try:
response.raise_for_status()
except httpx.HTTPStatusError as exc:
detail = _http_error_detail(response)
logger.error(
"Ollama image generation failed (HTTP {}): {}",
response.status_code,
detail,
)
raise ImageGenerationError(
f"Ollama image generation failed (HTTP {response.status_code}): {detail}"
) from exc
data = response.json()
images = _ollama_images_from_payload(data)
self._require_images(images, data)
response_text = data.get("response")
content = response_text if isinstance(response_text, str) else ""
return GeneratedImageResponse(images=images, content=content, raw=data)
class GeminiImageGenerationClient(ImageGenerationProvider):
"""Async client for Gemini/Imagen image generation via the Generative Language API."""
@@ -594,9 +442,9 @@ class GeminiImageGenerationClient(ImageGenerationProvider):
return "https://generativelanguage.googleapis.com/v1beta"
def _resolve_base_url(self, api_base: str | None) -> str:
# Gemini chat completions use the registry's OpenAI-compatible shim.
# Image generation must hit the native Generative Language API, so we
# intentionally bypass the shared registry lookup here.
# The Gemini provider's registry default_api_base is the OpenAI-compat
# shim (.../v1beta/openai/), which has no image endpoints.
# Skip the registry lookup and use the native API base directly.
if api_base:
return api_base.rstrip("/")
return self._default_base_url()
@@ -858,16 +706,22 @@ class MiniMaxImageGenerationClient(ImageGenerationProvider):
body.update(self.extra_body)
return await self._generate_with_client(body, headers)
client = self._client or httpx.AsyncClient(timeout=self.timeout)
try:
return await self._generate_with_client(client, body, headers)
finally:
if self._client is None:
await client.aclose()
async def _generate_with_client(
self,
client: httpx.AsyncClient,
body: dict[str, Any],
headers: dict[str, str],
) -> GeneratedImageResponse:
url = f"{self.api_base}/image_generation"
try:
response = await self._http_post(url, headers=headers, body=body)
response = await client.post(url, headers=headers, json=body)
except httpx.TimeoutException as exc:
raise ImageGenerationError("MiniMax image generation timed out") from exc
except httpx.RequestError as exc:
@@ -902,426 +756,6 @@ def _minimax_images_from_payload(payload: dict[str, Any]) -> list[str]:
return images
# ---------------------------------------------------------------------------
# OpenAI image generation
# ---------------------------------------------------------------------------
_OPENAI_DALLE2_SUPPORTED_SIZES = {"256x256", "512x512", "1024x1024"}
_OPENAI_DALLE3_SUPPORTED_SIZES = {"1024x1024", "1792x1024", "1024x1792"}
_OPENAI_GPT_IMAGE_SUPPORTED_SIZES = {
"1024x1024",
"1536x1024",
"1024x1536",
"auto",
}
_OPENAI_DALLE2_ASPECT_RATIO_SIZES = {
"1:1": "1024x1024",
"16:9": "1024x1024",
"9:16": "1024x1024",
"3:4": "1024x1024",
"4:3": "1024x1024",
}
_OPENAI_DALLE3_ASPECT_RATIO_SIZES = {
"1:1": "1024x1024",
"16:9": "1792x1024",
"9:16": "1024x1792",
"3:4": "1024x1792",
"4:3": "1792x1024",
}
_OPENAI_GPT_IMAGE_ASPECT_RATIO_SIZES = {
"1:1": "1024x1024",
"16:9": "1536x1024",
"9:16": "1024x1536",
"3:4": "1024x1536",
"4:3": "1536x1024",
}
class OpenAIImageGenerationClient(ImageGenerationProvider):
"""OpenAI Images API using an API key (``providers.openai.apiKey``)."""
provider_name = "openai"
missing_key_message = (
"OpenAI API key is not configured. Set providers.openai.apiKey."
)
def _default_base_url(self) -> str:
return "https://api.openai.com/v1"
@staticmethod
def _strip_model_prefix(model: str) -> str:
"""Remove ``openai/`` prefix if present (OpenRouter convention)."""
if model.startswith("openai/") or model.startswith("openai_codex/"):
return model.split("/", 1)[1]
return model
async def generate(
self,
*,
prompt: str,
model: str,
reference_images: list[str] | None = None,
aspect_ratio: str | None = None,
image_size: str | None = None,
) -> GeneratedImageResponse:
if not self.api_key:
raise ImageGenerationError(self.missing_key_message)
if reference_images:
logger.warning(
"DALL-E models do not support reference images; "
"ignoring {} reference image(s) for {}",
len(reference_images),
model,
)
headers = {
"Authorization": f"Bearer {self.api_key}",
"Content-Type": "application/json",
**self.extra_headers,
}
clean_model = self._strip_model_prefix(model)
body: dict[str, Any] = {
"model": clean_model,
"prompt": prompt,
}
if not _openai_is_gpt_image_model(clean_model):
body["response_format"] = "b64_json"
body["n"] = 1
size = _openai_size(clean_model, aspect_ratio, image_size)
if size:
body["size"] = size
body.update(self.extra_body)
logger.info("OpenAI Images API request: POST {}/images/generations body={}", self.api_base, body)
response = await self._http_post(
f"{self.api_base}/images/generations",
headers=headers,
body=body,
)
try:
response.raise_for_status()
except httpx.HTTPStatusError as exc:
detail = response.text[:1000]
logger.error("OpenAI Images API error ({}): {}", response.status_code, detail)
raise ImageGenerationError(
f"OpenAI image generation failed (HTTP {response.status_code}): {detail}"
) from exc
payload = response.json()
logger.info("OpenAI Images API response ({}): {}", response.status_code,
{k: v for k, v in payload.items() if k != "data"})
client = self._client
owns_client = client is None
if owns_client:
client = httpx.AsyncClient(timeout=self.timeout)
try:
images = await _openai_images_from_payload(client, payload)
finally:
if owns_client:
await client.aclose()
self._require_images(images, payload)
return GeneratedImageResponse(images=images, content="", raw=payload)
# ---------------------------------------------------------------------------
# OpenAI Codex image generation
# ---------------------------------------------------------------------------
class CodexImageGenerationClient(ImageGenerationProvider):
"""OpenAI image generation via Codex subscription OAuth.
Uses the Codex Responses API with the ``image_generation`` tool
(the same mechanism ChatGPT uses internally). No API key required
the Codex OAuth token from ``oauth_cli_kit`` is used instead.
"""
provider_name = "openai_codex"
missing_key_message = (
"Codex OAuth token is unavailable. "
"Log in with Codex subscription first."
)
def _default_base_url(self) -> str:
return "https://chatgpt.com/backend-api"
def _codex_model(self, model: str) -> str:
"""Strip the ``openai-codex/`` prefix if present."""
if model.startswith(("openai-codex/", "openai_codex/")):
return model.split("/", 1)[1]
return model
async def generate(
self,
*,
prompt: str,
model: str,
reference_images: list[str] | None = None,
aspect_ratio: str | None = None,
image_size: str | None = None,
) -> GeneratedImageResponse:
try:
from oauth_cli_kit import get_token as get_codex_token
except ImportError:
raise ImageGenerationError(self.missing_key_message)
try:
token = await asyncio.to_thread(get_codex_token)
except Exception as exc:
raise ImageGenerationError(self.missing_key_message) from exc
if not token or not token.access:
raise ImageGenerationError(self.missing_key_message)
logger.info(
"Using Codex OAuth token for image generation (account: {})",
token.account_id,
)
if reference_images:
logger.warning(
"Codex image generation does not support reference images; "
"ignoring {} reference image(s)",
len(reference_images),
)
headers = {
"Authorization": f"Bearer {token.access}",
"chatgpt-account-id": token.account_id,
"OpenAI-Beta": "responses=experimental",
"originator": "nanobot",
"User-Agent": "nanobot (python)",
"Content-Type": "application/json",
**self.extra_headers,
}
body: dict[str, Any] = {
"model": self._codex_model(model),
"instructions": "Generate an image based on the user's request.",
"input": [{"role": "user", "content": prompt}],
"tools": [{"type": "image_generation"}],
"tool_choice": "auto",
"stream": True,
"store": False,
}
body.update(self.extra_body)
logger.info("Codex Responses API request: POST {}/codex/responses body={}",
self.api_base, {k: v for k, v in body.items() if k != "input"})
response = await self._http_post(
f"{self.api_base}/codex/responses",
headers=headers,
body=body,
)
try:
response.raise_for_status()
except httpx.HTTPStatusError as exc:
detail = response.text[:1000]
logger.error("Codex Responses API error ({}): {}", response.status_code, detail)
raise ImageGenerationError(
f"Codex image generation failed (HTTP {response.status_code}): {detail}"
) from exc
images, content_text = await _parse_codex_sse_images(response)
raw = {"status": "completed"}
self._require_images(images, raw)
return GeneratedImageResponse(images=images, content=content_text, raw=raw)
def _openai_size(
model: str,
aspect_ratio: str | None,
image_size: str | None,
) -> str:
"""Resolve aspect ratio or image_size to an OpenAI Images API size string."""
sizes, supported_sizes = _openai_size_options(model)
explicit_size = _normalize_openai_image_size(image_size)
if explicit_size and _openai_explicit_size_supported(
explicit_size,
supported_sizes=supported_sizes,
):
return explicit_size
if explicit_size:
logger.warning(
"OpenAI image size '{}' is not supported by {}; using aspect ratio/default size",
explicit_size,
model,
)
if aspect_ratio and aspect_ratio in sizes:
return sizes[aspect_ratio]
return "1024x1024"
def _openai_is_gpt_image_model(model: str) -> bool:
normalized = model.lower()
return normalized.startswith(("gpt-image", "chatgpt-image"))
def _openai_size_options(model: str) -> tuple[dict[str, str], set[str] | None]:
normalized = model.lower()
if normalized.startswith("dall-e-2"):
return _OPENAI_DALLE2_ASPECT_RATIO_SIZES, _OPENAI_DALLE2_SUPPORTED_SIZES
if normalized.startswith("dall-e-3"):
return _OPENAI_DALLE3_ASPECT_RATIO_SIZES, _OPENAI_DALLE3_SUPPORTED_SIZES
if normalized.startswith("gpt-image-2"):
return _OPENAI_GPT_IMAGE_ASPECT_RATIO_SIZES, None
return _OPENAI_GPT_IMAGE_ASPECT_RATIO_SIZES, _OPENAI_GPT_IMAGE_SUPPORTED_SIZES
def _normalize_openai_image_size(image_size: str | None) -> str | None:
if not image_size:
return None
normalized = image_size.strip().lower()
return normalized or None
def _openai_explicit_size_supported(
size: str,
*,
supported_sizes: set[str] | None,
) -> bool:
if supported_sizes is not None:
return size in supported_sizes
width, sep, height = size.partition("x")
return bool(sep and width.isdecimal() and height.isdecimal())
async def _openai_images_from_payload(
client: httpx.AsyncClient,
payload: dict[str, Any],
) -> list[str]:
"""Extract images from OpenAI Images API response.
Handles both ``b64_json`` (preferred) and ``url`` (downloaded) formats.
"""
images: list[str] = []
for item in payload.get("data") or []:
if not isinstance(item, dict):
continue
b64 = item.get("b64_json")
if isinstance(b64, str) and b64:
images.append(_b64_image_data_url(b64))
continue
url = item.get("url")
if isinstance(url, str) and url:
images.append(await _download_image_data_url(client, url))
return images
def _codex_responses_images_from_payload(payload: dict[str, Any]) -> list[str]:
"""Extract images from Codex Responses API ``image_generation_call`` output."""
images: list[str] = []
for item in payload.get("output") or []:
if not isinstance(item, dict):
continue
if item.get("type") != "image_generation_call":
continue
result = item.get("result")
if isinstance(result, str):
images.append(result if result.startswith("data:image/") else _b64_image_data_url(result))
continue
if isinstance(result, dict):
image_url = result.get("image_url") or result.get("image") or ""
if isinstance(image_url, str):
images.append(image_url if image_url.startswith("data:image/") else _b64_image_data_url(image_url))
return images
async def _parse_codex_sse_images(
response: httpx.Response,
) -> tuple[list[str], str]:
"""Parse a Codex Responses API SSE stream for image generation output.
Returns ``(images, content_text)``.
"""
import json as _json
images: list[str] = []
text_parts: list[str] = []
buffer: list[str] = []
async for line_bytes in response.aiter_lines():
line = line_bytes.strip()
if line == "":
if buffer:
data_lines = []
for bl in buffer:
if bl.startswith("data:"):
data_lines.append(bl[5:].strip())
buffer.clear()
if data_lines:
raw = "".join(data_lines)
if raw == "[DONE]":
break
try:
event = _json.loads(raw)
except Exception:
continue
ev_type = event.get("type", "")
if ev_type in ("error", "response.failed"):
logger.error("Codex SSE failure: {}", raw[:2000])
_collect_images_from_sse_event(event, images)
_collect_text_from_sse_event(event, text_parts)
continue
buffer.append(line)
# flush remaining
if buffer:
data_lines = [bl[5:].strip() for bl in buffer if bl.startswith("data:")]
raw = "".join(data_lines)
if raw and raw != "[DONE]":
try:
event = _json.loads(raw)
except Exception:
pass
else:
_collect_images_from_sse_event(event, images)
_collect_text_from_sse_event(event, text_parts)
return images, "".join(text_parts).strip()
def _collect_images_from_sse_event(event: dict[str, Any], images: list[str]) -> None:
if event.get("type") != "response.output_item.done":
return
item = event.get("item") or {}
if item.get("type") != "image_generation_call":
return
result = item.get("result")
if isinstance(result, str):
if result.startswith("data:image/"):
images.append(result)
else:
images.append(_b64_image_data_url(result))
elif isinstance(result, dict):
image_url = result.get("image_url") or result.get("image") or ""
if isinstance(image_url, str):
if image_url.startswith("data:image/"):
images.append(image_url)
else:
images.append(_b64_image_data_url(image_url))
def _collect_text_from_sse_event(event: dict[str, Any], text_parts: list[str]) -> None:
if event.get("type") == "response.output_text.delta":
delta = event.get("delta")
if isinstance(delta, str) and delta:
text_parts.append(delta)
# ---------------------------------------------------------------------------
# StepFun (阶跃星辰) image generation
# ---------------------------------------------------------------------------
@@ -1445,159 +879,12 @@ def _stepfun_images_from_payload(payload: dict[str, Any]) -> list[str]:
return images
# ---------------------------------------------------------------------------
# Zhipu (智谱) image generation
# ---------------------------------------------------------------------------
_ZHIPU_TIMEOUT_S = 300.0
_ZHIPU_ASPECT_RATIO_SIZES = {
"1:1": "1280x1280",
"16:9": "1728x960",
"9:16": "960x1728",
"3:4": "1088x1472",
"4:3": "1472x1088",
}
class ZhipuImageGenerationClient(ImageGenerationProvider):
"""Async client for Zhipu (智谱) image generation API.
Supports:
- Text-to-image via glm-image, cogview-4, cogview-3-flash, etc.
- Aspect ratio selection
- Watermark control
"""
provider_name = "zhipu"
missing_key_message = "Zhipu API key is not configured. Set providers.zhipu.apiKey."
default_timeout = _ZHIPU_TIMEOUT_S
def _default_base_url(self) -> str:
return "https://open.bigmodel.cn/api/paas/v4"
async def generate(
self,
*,
prompt: str,
model: str,
reference_images: list[str] | None = None,
aspect_ratio: str | None = None,
image_size: str | None = None,
) -> GeneratedImageResponse:
if not self.api_key:
raise ImageGenerationError(self.missing_key_message)
if reference_images:
raise ImageGenerationError(
"Zhipu image generation does not support reference images"
)
headers = {
"Authorization": f"Bearer {self.api_key}",
"Content-Type": "application/json",
**self.extra_headers,
}
body: dict[str, Any] = {
"model": model,
"prompt": prompt,
}
size = _zhipu_size(aspect_ratio, image_size)
if size:
body["size"] = size
body.update(self.extra_body)
url = f"{self.api_base}/images/generations"
client = self._client or httpx.AsyncClient(timeout=self.timeout)
try:
return await self._generate_with_client(
client,
headers=headers,
body=body,
url=url,
)
finally:
if self._client is None:
await client.aclose()
async def _generate_with_client(
self,
client: httpx.AsyncClient,
*,
headers: dict[str, str],
body: dict[str, Any],
url: str,
) -> GeneratedImageResponse:
try:
response = await self._http_post(url, headers=headers, body=body, client=client)
except httpx.TimeoutException as exc:
raise ImageGenerationError("Zhipu image generation timed out") from exc
except httpx.RequestError as exc:
raise ImageGenerationError(f"Zhipu image generation request failed: {exc}") from exc
try:
response.raise_for_status()
except httpx.HTTPStatusError as exc:
detail = response.text[:500]
raise ImageGenerationError(f"Zhipu image generation failed: {detail}") from exc
payload = response.json()
images = await _zhipu_images_from_payload(client, payload)
self._require_images(images, payload)
return GeneratedImageResponse(images=images, content="", raw=payload)
def _zhipu_size(
aspect_ratio: str | None,
image_size: str | None,
) -> str:
"""Resolve aspect ratio / image_size to Zhipu size string.
Zhipu glm-image model supports: 1280x1280 (default), 1568x1056,
1056x1568, 1472x1088, 1088x1472, 1728x960, 960x1728.
"""
if image_size and "x" in image_size.lower():
return image_size
if aspect_ratio and aspect_ratio in _ZHIPU_ASPECT_RATIO_SIZES:
return _ZHIPU_ASPECT_RATIO_SIZES[aspect_ratio]
return "1280x1280"
async def _zhipu_images_from_payload(
client: httpx.AsyncClient,
payload: dict[str, Any],
) -> list[str]:
"""Extract image data URLs from Zhipu API response.
Zhipu returns images as temporary URLs that expire after 30 days.
We download and re-encode as base64 data URLs.
"""
images: list[str] = []
for item in payload.get("data") or []:
if not isinstance(item, dict):
continue
url = item.get("url")
if isinstance(url, str) and url:
images.append(await _download_image_data_url(client, url))
return images
# ---------------------------------------------------------------------------
# Provider registration
# ---------------------------------------------------------------------------
register_image_gen_provider(AIHubMixImageGenerationClient)
register_image_gen_provider(CodexImageGenerationClient)
register_image_gen_provider(GeminiImageGenerationClient)
register_image_gen_provider(OllamaImageGenerationClient)
register_image_gen_provider(MiniMaxImageGenerationClient)
register_image_gen_provider(OpenAIImageGenerationClient)
register_image_gen_provider(OpenRouterImageGenerationClient)
register_image_gen_provider(AIHubMixImageGenerationClient)
register_image_gen_provider(GeminiImageGenerationClient)
register_image_gen_provider(MiniMaxImageGenerationClient)
register_image_gen_provider(StepFunImageGenerationClient)
register_image_gen_provider(ZhipuImageGenerationClient)
+16 -162
View File
@@ -5,7 +5,6 @@ from __future__ import annotations
import asyncio
import hashlib
import json
import os
from collections.abc import Awaitable, Callable
from typing import Any
@@ -15,7 +14,7 @@ from oauth_cli_kit import get_token as get_codex_token
from nanobot.providers.base import LLMProvider, LLMResponse, ToolCallRequest
from nanobot.providers.openai_responses import (
consume_sse_with_reasoning,
consume_sse,
convert_messages,
convert_tools,
)
@@ -41,7 +40,6 @@ class OpenAICodexProvider(LLMProvider):
reasoning_effort: str | None,
tool_choice: str | dict[str, Any] | None,
on_content_delta: Callable[[str], Awaitable[None]] | None = None,
on_thinking_delta: Callable[[str], Awaitable[None]] | None = None,
on_tool_call_delta: Callable[[dict[str, Any]], Awaitable[None]] | None = None,
) -> LLMResponse:
"""Shared request logic for both chat() and chat_stream()."""
@@ -63,52 +61,32 @@ class OpenAICodexProvider(LLMProvider):
"tool_choice": tool_choice or "auto",
"parallel_tool_calls": True,
}
reasoning_options = _build_reasoning_options(reasoning_effort)
if reasoning_options:
body["reasoning"] = reasoning_options
if reasoning_effort and reasoning_effort.lower() != "none":
body["reasoning"] = {"effort": reasoning_effort}
if tools:
body["tools"] = convert_tools(tools)
try:
try:
content, tool_calls, finish_reason, reasoning_content = await _request_codex(
content, tool_calls, finish_reason = await _request_codex(
DEFAULT_CODEX_URL, headers, body, verify=True,
on_content_delta=on_content_delta,
on_thinking_delta=on_thinking_delta,
on_tool_call_delta=on_tool_call_delta,
)
except Exception as e:
if "CERTIFICATE_VERIFY_FAILED" not in str(e):
raise
logger.warning("SSL verification failed for Codex API; retrying with verify=False")
content, tool_calls, finish_reason, reasoning_content = await _request_codex(
content, tool_calls, finish_reason = await _request_codex(
DEFAULT_CODEX_URL, headers, body, verify=False,
on_content_delta=on_content_delta,
on_thinking_delta=on_thinking_delta,
on_tool_call_delta=on_tool_call_delta,
)
return LLMResponse(
content=content,
tool_calls=tool_calls,
finish_reason=finish_reason,
reasoning_content=reasoning_content,
)
return LLMResponse(content=content, tool_calls=tool_calls, finish_reason=finish_reason)
except Exception as e:
response = _codex_error_response(e)
exc_type = "CodexHTTPError" if isinstance(e, _CodexHTTPError) else type(e).__name__
logger.warning(
"Codex API request failed: type={} kind={} retryable={} status={} "
"error_type={} error_code={} retry_after={} summary={}",
exc_type,
response.error_kind,
response.error_should_retry,
response.error_status_code,
response.error_type,
response.error_code,
response.retry_after,
_codex_log_summary(exc_type, response),
)
return response
msg = f"Error calling Codex: {e}"
retry_after = getattr(e, "retry_after", None) or self._extract_retry_after(msg)
return LLMResponse(content=msg, finish_reason="error", retry_after=retry_after)
async def chat(
self, messages: list[dict[str, Any]], tools: list[dict[str, Any]] | None = None,
@@ -127,6 +105,7 @@ class OpenAICodexProvider(LLMProvider):
on_thinking_delta: Callable[[str], Awaitable[None]] | None = None,
on_tool_call_delta: Callable[[dict[str, Any]], Awaitable[None]] | None = None,
) -> LLMResponse:
_ = on_thinking_delta
return await self._call_codex(
messages,
tools,
@@ -134,7 +113,6 @@ class OpenAICodexProvider(LLMProvider):
reasoning_effort,
tool_choice,
on_content_delta,
on_thinking_delta,
on_tool_call_delta,
)
@@ -148,16 +126,6 @@ def _strip_model_prefix(model: str) -> str:
return model
def _build_reasoning_options(reasoning_effort: str | None) -> dict[str, str] | None:
"""Opt in to visible summaries without changing provider-default effort."""
if reasoning_effort and reasoning_effort.lower() == "none":
return {"effort": "none"}
options = {"summary": "auto"}
if reasoning_effort:
options["effort"] = reasoning_effort
return options
def _build_headers(account_id: str, token: str) -> dict[str, str]:
return {
"Authorization": f"Bearer {token}",
@@ -171,22 +139,9 @@ def _build_headers(account_id: str, token: str) -> dict[str, str]:
class _CodexHTTPError(RuntimeError):
def __init__(
self,
message: str,
*,
status_code: int | None = None,
retry_after: float | None = None,
error_type: str | None = None,
error_code: str | None = None,
should_retry: bool | None = None,
):
def __init__(self, message: str, retry_after: float | None = None):
super().__init__(message)
self.status_code = status_code
self.retry_after = retry_after
self.error_type = error_type
self.error_code = error_code
self.should_retry = should_retry
async def _request_codex(
@@ -195,31 +150,18 @@ async def _request_codex(
body: dict[str, Any],
verify: bool,
on_content_delta: Callable[[str], Awaitable[None]] | None = None,
on_thinking_delta: Callable[[str], Awaitable[None]] | None = None,
on_tool_call_delta: Callable[[dict[str, Any]], Awaitable[None]] | None = None,
) -> tuple[str, list[ToolCallRequest], str, str | None]:
idle_timeout_s = int(os.environ.get("NANOBOT_STREAM_IDLE_TIMEOUT_S", "90"))
async with httpx.AsyncClient(timeout=idle_timeout_s, verify=verify) as client:
) -> tuple[str, list[ToolCallRequest], str]:
async with httpx.AsyncClient(timeout=60.0, verify=verify) as client:
async with client.stream("POST", url, headers=headers, json=body) as response:
if response.status_code != 200:
text = await response.aread()
raw = text.decode("utf-8", "ignore")
retry_after = LLMProvider._extract_retry_after_from_headers(response.headers)
error_type, error_code = LLMProvider._extract_error_type_code(raw)
raise _CodexHTTPError(
_friendly_error(response.status_code, raw),
status_code=response.status_code,
_friendly_error(response.status_code, text.decode("utf-8", "ignore")),
retry_after=retry_after,
error_type=error_type,
error_code=error_code,
should_retry=_should_retry_status(response.status_code, error_type, error_code, raw),
)
return await consume_sse_with_reasoning(
response,
on_content_delta=on_content_delta,
on_tool_call_delta=on_tool_call_delta,
on_reasoning_delta=on_thinking_delta,
)
return await consume_sse(response, on_content_delta, on_tool_call_delta)
def _prompt_cache_key(messages: list[dict[str, Any]]) -> str:
@@ -228,94 +170,6 @@ def _prompt_cache_key(messages: list[dict[str, Any]]) -> str:
def _friendly_error(status_code: int, raw: str) -> str:
_ = raw
if status_code == 429:
return "ChatGPT usage quota exceeded or rate limit triggered. Please try again later."
return f"HTTP {status_code}: Codex API request failed"
def _codex_error_response(exc: Exception) -> LLMResponse:
"""Convert Codex transport/API failures into actionable, retryable metadata."""
exc_type = "CodexHTTPError" if isinstance(exc, _CodexHTTPError) else type(exc).__name__
detail = str(exc).strip()
status_code = getattr(exc, "status_code", None)
error_kind: str | None = None
default_detail: str | None = None
should_retry: bool | None = getattr(exc, "should_retry", None)
if isinstance(exc, (httpx.TimeoutException, asyncio.TimeoutError)):
error_kind = "timeout"
default_detail = "timed out waiting for response"
should_retry = True if should_retry is None else should_retry
elif isinstance(exc, httpx.RemoteProtocolError):
error_kind = "connection"
default_detail = "network protocol error while reading response"
should_retry = True if should_retry is None else should_retry
elif isinstance(exc, (httpx.NetworkError, httpx.TransportError)):
error_kind = "connection"
default_detail = "network connection failed"
should_retry = True if should_retry is None else should_retry
elif isinstance(exc, _CodexHTTPError):
error_kind = "http"
default_detail = "HTTP request failed"
if status_code is not None and should_retry is None:
retry_content = None if int(status_code) == 429 and isinstance(exc, _CodexHTTPError) else detail
should_retry = _should_retry_status(
int(status_code),
getattr(exc, "error_type", None),
getattr(exc, "error_code", None),
retry_content,
)
detail = detail or default_detail or "unexpected error"
message = f"Error calling Codex ({exc_type}): {detail}"
retry_after = getattr(exc, "retry_after", None) or LLMProvider._extract_retry_after(message)
return LLMResponse(
content=message,
finish_reason="error",
retry_after=retry_after,
error_status_code=int(status_code) if status_code is not None else None,
error_kind=error_kind,
error_type=getattr(exc, "error_type", None),
error_code=getattr(exc, "error_code", None),
error_retry_after_s=retry_after,
error_should_retry=should_retry,
)
def _codex_log_summary(exc_type: str, response: LLMResponse) -> str:
"""Return a bounded diagnostic summary without request body or raw upstream payload."""
if response.error_status_code is not None:
parts = [f"HTTP {response.error_status_code}"]
if response.error_type:
parts.append(f"type={response.error_type}")
if response.error_code:
parts.append(f"code={response.error_code}")
return " ".join(parts)
kind = (response.error_kind or "").strip()
if kind:
return f"{exc_type} {kind}"
return exc_type
def _should_retry_status(
status_code: int,
error_type: str | None,
error_code: str | None,
content: str | None,
) -> bool:
if status_code == 429:
return LLMProvider._is_retryable_429_response(
LLMResponse(
content=content or "",
finish_reason="error",
error_status_code=status_code,
error_type=error_type,
error_code=error_code,
)
)
return status_code in LLMProvider._RETRYABLE_STATUS_CODES or status_code >= 500
return f"HTTP {status_code}: {raw}"
+101 -237
View File
@@ -11,15 +11,25 @@ import secrets
import string
import time
import uuid
from collections import deque
from collections.abc import Awaitable, Callable
from ipaddress import ip_address
from typing import TYPE_CHECKING, Any
from urllib.parse import urlparse
import httpx
import json_repair
from loguru import logger
if os.environ.get("LANGFUSE_SECRET_KEY") and importlib.util.find_spec("langfuse"):
from langfuse.openai import AsyncOpenAI
else:
if os.environ.get("LANGFUSE_SECRET_KEY"):
logger.warning(
"LANGFUSE_SECRET_KEY is set but langfuse is not installed; "
"install with `pip install langfuse` to enable tracing"
)
from openai import AsyncOpenAI
from nanobot.providers.base import LLMProvider, LLMResponse, ToolCallRequest
from nanobot.providers.openai_responses import (
consume_sdk_stream,
@@ -29,15 +39,8 @@ from nanobot.providers.openai_responses import (
)
if TYPE_CHECKING:
from openai import AsyncOpenAI as AsyncOpenAIType
from nanobot.providers.registry import ProviderSpec
# Module-level placeholder — set lazily by _ensure_client on first real
# use, or replaced by tests via ``patch(...)``. Kept as a plain name so
# that ``unittest.mock.patch`` can find and replace it.
AsyncOpenAI: Any = None
_ALLOWED_MSG_KEYS = frozenset({
"role", "content", "tool_calls", "tool_call_id", "name",
"reasoning_content", "extra_content",
@@ -75,43 +78,41 @@ _THINKING_STYLE_MAP: dict[str, Any] = {
"enable_thinking": lambda on: {"enable_thinking": on},
"reasoning_split": lambda on: {"reasoning_split": on},
}
_GATEWAY_REASONING_STYLE_MAP: dict[str, Any] = {
"reasoning_effort": lambda effort: {"reasoning": {"effort": effort}},
}
_MODEL_THINKING_STYLES: dict[str, str] = {
**dict.fromkeys(_KIMI_THINKING_MODELS, "thinking_type"),
**dict.fromkeys(_MIMO_THINKING_MODELS, "thinking_type"),
}
def _model_slug(model_name: str) -> str:
return model_name.lower().rsplit("/", 1)[-1]
def _is_kimi_thinking_model(model_name: str) -> bool:
"""Return True if model_name refers to a Kimi thinking-capable model.
Supports two forms:
- Exact match: e.g. kimi-k2.5 / kimi-k2.6 in _KIMI_THINKING_MODELS
- Slug match: moonshotai/kimi-k2.5 -> the part after the last "/"
is checked against _KIMI_THINKING_MODELS
This covers both the native Moonshot provider (bare slug) and
OpenRouter-style names (``"publisher/slug"``).
"""
name = model_name.lower()
if name in _KIMI_THINKING_MODELS:
return True
if "/" in name and name.rsplit("/", 1)[1] in _KIMI_THINKING_MODELS:
return True
return False
def _model_thinking_style(model_name: str) -> str:
return _MODEL_THINKING_STYLES.get(_model_slug(model_name), "")
def _is_mimo_thinking_model(model_name: str) -> bool:
"""Return True if model_name refers to a MiMo thinking-capable model.
def _thinking_styles_for(spec: ProviderSpec | None, model_name: str) -> list[str]:
styles: list[str] = []
if spec and spec.thinking_style:
styles.append(spec.thinking_style)
model_style = _model_thinking_style(model_name)
if model_style and model_style not in styles:
styles.append(model_style)
return styles
def _thinking_extra_body(style: str, thinking_enabled: bool) -> dict[str, Any] | None:
builder = _THINKING_STYLE_MAP.get(style)
return builder(thinking_enabled) if builder else None
def _gateway_reasoning_extra_body(style: str, effort: str | None) -> dict[str, Any] | None:
if not effort:
return None
builder = _GATEWAY_REASONING_STYLE_MAP.get(style)
return builder(effort) if builder else None
Mirrors _is_kimi_thinking_model: gateway providers (e.g. OpenRouter
routing ``xiaomi/mimo-v2.5-pro``) have no ``thinking_style`` on their
spec, so the spec-driven branch in _build_kwargs misses them. The
model-name path catches those cases.
"""
name = model_name.lower()
if name in _MIMO_THINKING_MODELS:
return True
if "/" in name and name.rsplit("/", 1)[1] in _MIMO_THINKING_MODELS:
return True
return False
def _openai_compat_timeout_s() -> float:
@@ -274,47 +275,6 @@ def _deep_merge(base: dict[str, Any], override: dict[str, Any]) -> dict[str, Any
return merged
def _merge_unique_list(base: Any, override: Any) -> Any:
"""Append list values while preserving order and removing duplicates."""
if not isinstance(base, list) or not isinstance(override, list):
return override
result: list[Any] = []
seen: set[str] = set()
for value in [*base, *override]:
try:
key = json.dumps(value, sort_keys=True, ensure_ascii=False)
except Exception:
key = repr(value)
if key in seen:
continue
seen.add(key)
result.append(value)
return result
def _merge_responses_extra_body(
body: dict[str, Any],
extra_body: dict[str, Any],
) -> dict[str, Any]:
"""Merge configured Responses API body fields without clobbering tools."""
reserved = {"include", "tools"}
regular_extra = {key: value for key, value in extra_body.items() if key not in reserved}
merged = _deep_merge(body, regular_extra)
if "include" in extra_body:
merged["include"] = _merge_unique_list(body.get("include"), extra_body["include"])
if "tools" in extra_body:
current_tools = body.get("tools")
configured_tools = extra_body["tools"]
if isinstance(current_tools, list) and isinstance(configured_tools, list):
merged["tools"] = [*current_tools, *configured_tools]
else:
merged["tools"] = configured_tools
return merged
class OpenAICompatProvider(LLMProvider):
"""Unified provider for all OpenAI-compatible APIs.
@@ -330,89 +290,54 @@ class OpenAICompatProvider(LLMProvider):
extra_headers: dict[str, str] | None = None,
spec: ProviderSpec | None = None,
extra_body: dict[str, Any] | None = None,
api_type: str = "auto",
):
super().__init__(api_key, api_base)
self.default_model = default_model
self.extra_headers = extra_headers or {}
self._spec = spec
self._extra_body = extra_body or {}
self._api_type = api_type if spec and spec.name == "openai" else "auto"
if api_key and spec and spec.env_key:
self._setup_env(api_key, api_base)
effective_base = api_base or (spec.default_api_base if spec else None) or None
self._effective_base = effective_base
self._default_headers = {"x-session-affinity": uuid.uuid4().hex}
default_headers = {"x-session-affinity": uuid.uuid4().hex}
if _uses_openrouter_attribution(spec, effective_base):
self._default_headers.update(_DEFAULT_OPENROUTER_HEADERS)
default_headers.update(_DEFAULT_OPENROUTER_HEADERS)
if extra_headers:
self._default_headers.update(extra_headers)
self._api_key_for_client = api_key or "no-key"
self._is_local = _is_local_endpoint(spec, effective_base)
# Lazy-init: the OpenAI client and its httpx transport are expensive
# to create (~700 ms on Windows). Defer until first use.
self._client: AsyncOpenAIType | None = None
self._client_lock = asyncio.Lock()
# Responses API circuit breaker: skip after repeated failures,
# probe again after _RESPONSES_PROBE_INTERVAL_S seconds.
self._responses_failures: dict[str, int] = {}
self._responses_tripped_at: dict[str, float] = {}
def _build_client(self) -> None:
"""Create the OpenAI client using the current module-level AsyncOpenAI."""
import httpx
default_headers.update(extra_headers)
# Local model servers (Ollama, llama.cpp, vLLM) often close idle
# HTTP connections before the client-side keepalive expires. When
# two LLM calls happen seconds apart (e.g. heartbeat _decide then
# process_direct), the second call may grab a now-dead pooled
# connection, causing a transient APIConnectionError on every first
# attempt. Disabling keepalive for local endpoints avoids this by
# opening a fresh connection for each request, which is cheap on a
# LAN. Cloud providers benefit from keepalive, so we leave the
# default pool settings for them.
timeout_s = _openai_compat_timeout_s()
http_client: httpx.AsyncClient | None = None
if self._is_local:
# Local model servers (Ollama, llama.cpp, vLLM) often close idle
# HTTP connections before the client-side keepalive expires. When
# two LLM calls happen seconds apart (e.g. heartbeat _decide then
# process_direct), the second call may grab a now-dead pooled
# connection, causing a transient APIConnectionError on every first
# attempt. Disabling keepalive for local endpoints avoids this by
# opening a fresh connection for each request, which is cheap on a
# LAN. Cloud providers benefit from keepalive, so we leave the
# default pool settings for them.
if _is_local_endpoint(spec, effective_base):
http_client = httpx.AsyncClient(
limits=httpx.Limits(keepalive_expiry=0),
timeout=timeout_s,
)
self._client = AsyncOpenAI(
api_key=self._api_key_for_client,
base_url=self._effective_base,
default_headers=self._default_headers,
api_key=api_key or "no-key",
base_url=effective_base,
default_headers=default_headers,
max_retries=0,
timeout=timeout_s,
http_client=http_client,
)
async def _ensure_client(self):
"""Return the shared OpenAI client, creating it on first call."""
if self._client is not None:
return self._client
async with self._client_lock:
if self._client is not None:
return self._client
global AsyncOpenAI
if AsyncOpenAI is None:
if os.environ.get("LANGFUSE_SECRET_KEY") and importlib.util.find_spec("langfuse"):
from langfuse.openai import AsyncOpenAI as _AsyncOpenAI
else:
if os.environ.get("LANGFUSE_SECRET_KEY"):
logger.warning(
"LANGFUSE_SECRET_KEY is set but langfuse is not installed; "
"install with `pip install langfuse` to enable tracing"
)
from openai import AsyncOpenAI as _AsyncOpenAI
AsyncOpenAI = _AsyncOpenAI
self._build_client()
return self._client
# Responses API circuit breaker: skip after repeated failures,
# probe again after _RESPONSES_PROBE_INTERVAL_S seconds.
self._responses_failures: dict[str, int] = {}
self._responses_tripped_at: dict[str, float] = {}
def _setup_env(self, api_key: str, api_base: str | None) -> None:
"""Set environment variables based on provider spec."""
@@ -471,10 +396,6 @@ class OpenAICompatProvider(LLMProvider):
return tool_call_id
return hashlib.sha1(tool_call_id.encode()).hexdigest()[:9]
def _should_normalize_tool_call_ids(self) -> bool:
"""Return True for providers that reject normal OpenAI tool call IDs."""
return bool(self._spec and self._spec.name == "mistral")
@staticmethod
def _normalize_tool_call_arguments(arguments: Any) -> str:
"""Force function.arguments into a valid JSON object string."""
@@ -511,60 +432,22 @@ class OpenAICompatProvider(LLMProvider):
"""Strip non-standard keys, normalize tool_call IDs."""
sanitized = LLMProvider._sanitize_request_messages(messages, _ALLOWED_MSG_KEYS)
id_map: dict[str, str] = {}
pending_tool_ids: dict[str, deque[str]] = {}
force_string_content = bool(self._spec and self._spec.name == "deepseek")
normalize_tool_ids = self._should_normalize_tool_call_ids()
def map_id(value: Any) -> Any:
if not isinstance(value, str):
return value
if not normalize_tool_ids:
return value
return id_map.setdefault(value, self._normalize_tool_call_id(value))
def unique_tool_id(value: Any, used_ids: set[str], idx: int) -> str:
if isinstance(value, str) and value:
base = map_id(value)
else:
base = _short_tool_id()
if not isinstance(base, str) or not base:
base = _short_tool_id()
if base not in used_ids:
return base
seed = value if isinstance(value, str) and value else base
salt = 1
while True:
candidate = self._normalize_tool_call_id(f"{seed}:{idx}:{salt}")
if isinstance(candidate, str) and candidate not in used_ids:
return candidate
salt += 1
def map_tool_result_id(value: Any) -> Any:
if not isinstance(value, str):
return value
queue = pending_tool_ids.get(value)
if queue:
mapped = queue.popleft()
if not queue:
pending_tool_ids.pop(value, None)
return mapped
return map_id(value)
for clean in sanitized:
if isinstance(clean.get("tool_calls"), list):
normalized = []
used_ids: set[str] = set()
for idx, tc in enumerate(clean["tool_calls"]):
for tc in clean["tool_calls"]:
if not isinstance(tc, dict):
normalized.append(tc)
continue
tc_clean = dict(tc)
raw_id = tc_clean.get("id")
mapped_id = unique_tool_id(raw_id, used_ids, idx)
tc_clean["id"] = mapped_id
used_ids.add(mapped_id)
if isinstance(raw_id, str) and raw_id:
pending_tool_ids.setdefault(raw_id, deque()).append(mapped_id)
tc_clean["id"] = map_id(tc_clean.get("id"))
function = tc_clean.get("function")
if isinstance(function, dict):
function_clean = dict(function)
@@ -582,7 +465,7 @@ class OpenAICompatProvider(LLMProvider):
# that mix non-empty content with tool_calls.
clean["content"] = None
if "tool_call_id" in clean and clean["tool_call_id"]:
clean["tool_call_id"] = map_tool_result_id(clean["tool_call_id"])
clean["tool_call_id"] = map_id(clean["tool_call_id"])
if (
force_string_content
and not (clean.get("role") == "assistant" and clean.get("tool_calls"))
@@ -669,27 +552,39 @@ class OpenAICompatProvider(LLMProvider):
if wire_effort and semantic_effort != "none":
kwargs["reasoning_effort"] = wire_effort
# Only send thinking controls when reasoning_effort is explicit so
# omitting the config preserves each provider's default.
if reasoning_effort is not None:
# Provider-specific thinking parameters.
# Only sent when reasoning_effort is explicitly configured so that
# the provider default is preserved otherwise.
# The mapping is driven by ProviderSpec.thinking_style so that adding
# a new provider never requires touching this function.
if spec and spec.thinking_style and reasoning_effort is not None:
thinking_enabled = semantic_effort not in ("none", "minimal")
for thinking_style in _thinking_styles_for(spec, model_name):
extra = _thinking_extra_body(thinking_style, thinking_enabled)
if extra:
kwargs.setdefault("extra_body", {}).update(extra)
gateway_style = getattr(spec, "gateway_reasoning_style", "") if spec else ""
if gateway_style and _model_thinking_style(model_name):
extra = _gateway_reasoning_extra_body(gateway_style, semantic_effort)
if extra:
kwargs.setdefault("extra_body", {}).update(extra)
extra = _THINKING_STYLE_MAP.get(spec.thinking_style, lambda _: None)(thinking_enabled)
if extra:
kwargs.setdefault("extra_body", {}).update(extra)
# Moonshot rejects requests that carry both 'reasoning_effort'
# and the native 'thinking' param. We already expressed the
# user's intent via the provider-native shape, so drop the
# redundant wire-level kwarg. Only kimi models need this —
# Xiaomi's API accepts both params.
if _model_slug(model_name) in _KIMI_THINKING_MODELS:
kwargs.pop("reasoning_effort", None)
# Model-level thinking injection for Kimi thinking-capable models.
# Strip any provider prefix (e.g. "moonshotai/") before the set lookup
# so that OpenRouter-style names like "moonshotai/kimi-k2.5" are handled
# identically to bare names like "kimi-k2.5".
if reasoning_effort is not None and _is_kimi_thinking_model(model_name):
thinking_enabled = semantic_effort not in ("none", "minimal")
kwargs.setdefault("extra_body", {}).update(
{"thinking": {"type": "enabled" if thinking_enabled else "disabled"}}
)
# Model-level thinking injection for MiMo thinking-capable models.
# Same shape as Kimi: gateway providers (OpenRouter, etc.) lack the
# xiaomi_mimo spec's thinking_style, so the spec-driven branch above
# misses them — match by model name to catch "xiaomi/mimo-v2.5-pro"
# and friends. (Direct xiaomi_mimo requests are also covered here;
# both branches write the same payload, so the dict update is a
# safe no-op for already-handled cases.)
if reasoning_effort is not None and _is_mimo_thinking_model(model_name):
thinking_enabled = semantic_effort not in ("none", "minimal")
kwargs.setdefault("extra_body", {}).update(
{"thinking": {"type": "enabled" if thinking_enabled else "disabled"}}
)
if tools:
kwargs["tools"] = tools
@@ -704,7 +599,8 @@ class OpenAICompatProvider(LLMProvider):
and semantic_effort not in ("none", "minimal")
and (
(spec and spec.thinking_style)
or _model_thinking_style(model_name)
or _is_kimi_thinking_model(model_name)
or _is_mimo_thinking_model(model_name)
)
)
implicit_deepseek_thinking = (
@@ -735,14 +631,8 @@ class OpenAICompatProvider(LLMProvider):
reasoning_effort: str | None,
) -> bool:
"""Use Responses API only for direct OpenAI requests that benefit from it."""
if self._api_type == "chat_completions":
return False
if self._spec and self._spec.name not in ("openai", "github_copilot"):
return False
if self._api_type == "responses":
# Explicit configuration means Responses is mandatory; do not
# consult the circuit breaker or fall back to Chat Completions.
return True
if self._spec is None or self._spec.name != "github_copilot":
if not _is_direct_openai_base(self._effective_base):
return False
@@ -756,14 +646,7 @@ class OpenAICompatProvider(LLMProvider):
if not wants:
return False
return self._responses_circuit_allows_probe(model, reasoning_effort)
def _responses_circuit_allows_probe(
self,
model: str | None,
reasoning_effort: str | None,
) -> bool:
"""Return False when the Responses API circuit breaker is open."""
# Circuit breaker: skip after repeated failures, probe periodically.
key = _responses_circuit_key(model, self.default_model, reasoning_effort)
failures = self._responses_failures.get(key, 0)
if failures >= _RESPONSES_FAILURE_THRESHOLD:
@@ -855,10 +738,6 @@ class OpenAICompatProvider(LLMProvider):
body["tools"] = convert_tools(tools)
body["tool_choice"] = tool_choice or "auto"
extra_body = getattr(self, "_extra_body", {})
if extra_body:
body = _merge_responses_extra_body(body, extra_body)
return body
# ------------------------------------------------------------------
@@ -1023,7 +902,7 @@ class OpenAICompatProvider(LLMProvider):
args = json_repair.loads(args)
ec, prov, fn_prov = _extract_tc_extras(tc)
parsed_tool_calls.append(ToolCallRequest(
id=str(tc_map.get("id") or _short_tool_id()),
id=_short_tool_id(),
name=str(fn.get("name") or ""),
arguments=args if isinstance(args, dict) else {},
extra_content=ec,
@@ -1066,7 +945,7 @@ class OpenAICompatProvider(LLMProvider):
args = json_repair.loads(args)
ec, prov, fn_prov = _extract_tc_extras(tc)
tool_calls.append(ToolCallRequest(
id=str(getattr(tc, "id", None) or _short_tool_id()),
id=_short_tool_id(),
name=tc.function.name,
arguments=args,
extra_content=ec,
@@ -1189,15 +1068,6 @@ class OpenAICompatProvider(LLMProvider):
if delta:
_accum_legacy_function_call(getattr(delta, "function_call", None))
# Some providers (e.g. Zhipu/GLM) reuse the same tool_call id for
# parallel tool calls in streaming mode. Deduplicate before building
# the response so downstream tool messages don't collide.
_seen_tc_ids: set[str] = set()
for b in tc_bufs.values():
if not b["id"] or b["id"] in _seen_tc_ids:
b["id"] = _short_tool_id()
_seen_tc_ids.add(b["id"])
return LLMResponse(
content="".join(content_parts) or None,
tool_calls=[
@@ -1312,7 +1182,6 @@ class OpenAICompatProvider(LLMProvider):
reasoning_effort: str | None = None,
tool_choice: str | dict[str, Any] | None = None,
) -> LLMResponse:
await self._ensure_client()
try:
if self._should_use_responses_api(model, reasoning_effort):
try:
@@ -1329,8 +1198,6 @@ class OpenAICompatProvider(LLMProvider):
# falling back to /chat/completions cannot succeed and would
# hide the real error.
raise
if self._api_type == "responses":
raise
if not self._should_fallback_from_responses_error(responses_error):
raise
self._record_responses_failure(model, reasoning_effort)
@@ -1356,7 +1223,6 @@ class OpenAICompatProvider(LLMProvider):
on_thinking_delta: Callable[[str], Awaitable[None]] | None = None,
on_tool_call_delta: Callable[[dict[str, Any]], Awaitable[None]] | None = None,
) -> LLMResponse:
await self._ensure_client()
idle_timeout_s = int(os.environ.get("NANOBOT_STREAM_IDLE_TIMEOUT_S", "90"))
try:
if self._should_use_responses_api(model, reasoning_effort):
@@ -1404,8 +1270,6 @@ class OpenAICompatProvider(LLMProvider):
# falling back to /chat/completions cannot succeed and would
# hide the real error.
raise
if self._api_type == "responses":
raise
if not self._should_fallback_from_responses_error(responses_error):
raise
self._record_responses_failure(model, reasoning_effort)
@@ -10,7 +10,6 @@ from nanobot.providers.openai_responses.parsing import (
FINISH_REASON_MAP,
consume_sdk_stream,
consume_sse,
consume_sse_with_reasoning,
iter_sse,
map_finish_reason,
parse_response_output,
@@ -23,7 +22,6 @@ __all__ = [
"split_tool_call_id",
"iter_sse",
"consume_sse",
"consume_sse_with_reasoning",
"consume_sdk_stream",
"map_finish_reason",
"parse_response_output",
@@ -5,6 +5,8 @@ from __future__ import annotations
import json
from typing import Any
from nanobot.providers.base import LLMProvider
def convert_messages(messages: list[dict[str, Any]]) -> tuple[str, list[dict[str, Any]]]:
"""Convert Chat Completions messages to Responses API input items.
@@ -15,7 +17,6 @@ def convert_messages(messages: list[dict[str, Any]]) -> tuple[str, list[dict[str
"""
system_prompt = ""
input_items: list[dict[str, Any]] = []
used_item_ids: set[str] = set()
for idx, msg in enumerate(messages):
role = msg.get("role")
@@ -31,19 +32,17 @@ def convert_messages(messages: list[dict[str, Any]]) -> tuple[str, list[dict[str
if role == "assistant":
if isinstance(content, str) and content:
message_id = _unique_item_id(f"msg_{idx}", used_item_ids)
input_items.append({
"type": "message", "role": "assistant",
"content": [{"type": "output_text", "text": content}],
"status": "completed", "id": message_id,
"status": "completed", "id": f"msg_{idx}",
})
for tool_call in msg.get("tool_calls", []) or []:
fn = tool_call.get("function") or {}
call_id, item_id = split_tool_call_id(tool_call.get("id"))
response_item_id = _unique_item_id(item_id or f"fc_{idx}", used_item_ids)
input_items.append({
"type": "function_call",
"id": response_item_id,
"id": item_id or f"fc_{idx}",
"call_id": call_id or f"call_{idx}",
"name": fn.get("name"),
"arguments": fn.get("arguments") or "{}",
@@ -61,8 +60,10 @@ def convert_messages(messages: list[dict[str, Any]]) -> tuple[str, list[dict[str
def convert_user_message(content: Any) -> dict[str, Any]:
"""Convert a user message's content to Responses API format.
Handles plain strings, ``text`` blocks -> ``input_text``, and
``image_url`` blocks -> ``input_image``.
Handles plain strings, ``text`` blocks -> ``input_text``,
``image_url`` blocks -> ``input_image``, and ``input_audio`` blocks.
``video_url`` is downgraded to a text placeholder because Codex does
not support native video.
"""
if isinstance(content, str):
return {"role": "user", "content": [{"type": "input_text", "text": content}]}
@@ -77,6 +78,18 @@ def convert_user_message(content: Any) -> dict[str, Any]:
url = (item.get("image_url") or {}).get("url")
if url:
converted.append({"type": "input_image", "image_url": url, "detail": "auto"})
elif item.get("type") == "input_audio":
audio_info = item.get("input_audio") or {}
audio_data = audio_info.get("data")
if audio_data:
converted.append({
"type": "input_audio",
"input_audio": {"data": audio_data, "format": audio_info.get("format", "wav")},
})
elif item.get("type") == "video_url":
# Codex doesn't support native video → text placeholder
placeholder = LLMProvider._media_placeholder("video_url", item)
converted.append({"type": "input_text", "text": placeholder["text"]})
if converted:
return {"role": "user", "content": converted}
return {"role": "user", "content": [{"type": "input_text", "text": ""}]}
@@ -100,20 +113,6 @@ def convert_tools(tools: list[dict[str, Any]]) -> list[dict[str, Any]]:
return converted
def _unique_item_id(item_id: str, used: set[str]) -> str:
"""Return a Responses input item id that is unique within one request."""
if item_id not in used:
used.add(item_id)
return item_id
suffix = 2
while f"{item_id}_{suffix}" in used:
suffix += 1
unique = f"{item_id}_{suffix}"
used.add(unique)
return unique
def split_tool_call_id(tool_call_id: Any) -> tuple[str, str | None]:
"""Split a compound ``call_id|item_id`` string.
+4 -103
View File
@@ -65,28 +65,10 @@ async def consume_sse(
on_tool_call_delta: Callable[[dict[str, Any]], Awaitable[None]] | None = None,
) -> tuple[str, list[ToolCallRequest], str]:
"""Consume a Responses API SSE stream into ``(content, tool_calls, finish_reason)``."""
content, tool_calls, finish_reason, _ = await consume_sse_with_reasoning(
response,
on_content_delta=on_content_delta,
on_tool_call_delta=on_tool_call_delta,
)
return content, tool_calls, finish_reason
async def consume_sse_with_reasoning(
response: httpx.Response,
on_content_delta: Callable[[str], Awaitable[None]] | None = None,
on_tool_call_delta: Callable[[dict[str, Any]], Awaitable[None]] | None = None,
on_reasoning_delta: Callable[[str], Awaitable[None]] | None = None,
) -> tuple[str, list[ToolCallRequest], str, str | None]:
"""Consume a Responses API SSE stream, including visible reasoning summaries."""
content = ""
tool_calls: list[ToolCallRequest] = []
tool_call_buffers: dict[str, dict[str, Any]] = {}
tool_call_args_emitted: set[str] = set()
finish_reason = "stop"
reasoning_content: str | None = None
streamed_reasoning = False
async for event in iter_sse(response):
event_type = event.get("type")
@@ -112,26 +94,6 @@ async def consume_sse_with_reasoning(
content += delta_text
if on_content_delta and delta_text:
await on_content_delta(delta_text)
elif event_type == "response.reasoning_summary_text.delta":
delta_text = event.get("delta") or ""
if delta_text:
reasoning_content = (reasoning_content or "") + delta_text
streamed_reasoning = True
if on_reasoning_delta:
await on_reasoning_delta(delta_text)
elif event_type == "response.reasoning_summary_text.done":
text = event.get("text") or ""
if text and not streamed_reasoning and not reasoning_content:
reasoning_content = text
if on_reasoning_delta:
await on_reasoning_delta(text)
elif event_type == "response.reasoning_summary_part.done":
part = event.get("part") or {}
text = part.get("text") if part.get("type") == "summary_text" else None
if text and not streamed_reasoning and not reasoning_content:
reasoning_content = text
if on_reasoning_delta:
await on_reasoning_delta(text)
elif event_type == "response.function_call_arguments.delta":
call_id = event.get("call_id")
if call_id and call_id in tool_call_buffers:
@@ -146,15 +108,7 @@ async def consume_sse_with_reasoning(
elif event_type == "response.function_call_arguments.done":
call_id = event.get("call_id")
if call_id and call_id in tool_call_buffers:
arguments = event.get("arguments") or ""
tool_call_buffers[call_id]["arguments"] = arguments
if on_tool_call_delta:
tool_call_args_emitted.add(str(call_id))
await on_tool_call_delta({
"call_id": str(call_id),
"name": str(tool_call_buffers[call_id].get("name") or ""),
"arguments": str(arguments),
})
tool_call_buffers[call_id]["arguments"] = event.get("arguments") or ""
elif event_type == "response.output_item.done":
item = event.get("item") or {}
if item.get("type") == "function_call":
@@ -163,13 +117,6 @@ async def consume_sse_with_reasoning(
continue
buf = tool_call_buffers.get(call_id) or {}
args_raw = buf.get("arguments") or item.get("arguments") or "{}"
if on_tool_call_delta and str(call_id) not in tool_call_args_emitted:
tool_call_args_emitted.add(str(call_id))
await on_tool_call_delta({
"call_id": str(call_id),
"name": str(buf.get("name") or item.get("name") or ""),
"arguments": str(args_raw),
})
try:
args = json.loads(args_raw)
except Exception:
@@ -188,44 +135,14 @@ async def consume_sse_with_reasoning(
arguments=args,
)
)
elif item.get("type") == "reasoning" and not reasoning_content:
summary = _extract_reasoning_summary_from_output([item])
if summary:
reasoning_content = summary
if on_reasoning_delta:
await on_reasoning_delta(summary)
elif event_type == "response.completed":
response_obj = event.get("response") or {}
status = response_obj.get("status")
status = (event.get("response") or {}).get("status")
finish_reason = map_finish_reason(status)
if not reasoning_content:
summary = _extract_reasoning_summary_from_output(response_obj.get("output") or [])
if summary:
reasoning_content = summary
if on_reasoning_delta:
await on_reasoning_delta(summary)
elif event_type in {"error", "response.failed"}:
detail = event.get("error") or event.get("message") or event
raise RuntimeError(f"Response failed: {str(detail)[:500]}")
return content, tool_calls, finish_reason, reasoning_content
def _extract_reasoning_summary_from_output(output: Any) -> str | None:
parts: list[str] = []
for item in output or []:
if not isinstance(item, dict):
dump = getattr(item, "model_dump", None)
item = dump() if callable(dump) else vars(item)
if item.get("type") != "reasoning":
continue
for summary in item.get("summary") or []:
if not isinstance(summary, dict):
dump = getattr(summary, "model_dump", None)
summary = dump() if callable(dump) else vars(summary)
if summary.get("type") == "summary_text" and summary.get("text"):
parts.append(summary["text"])
return "".join(parts) or None
return content, tool_calls, finish_reason
def parse_response_output(response: Any) -> LLMResponse:
@@ -313,7 +230,6 @@ async def consume_sdk_stream(
content = ""
tool_calls: list[ToolCallRequest] = []
tool_call_buffers: dict[str, dict[str, Any]] = {}
tool_call_args_emitted: set[str] = set()
finish_reason = "stop"
usage: dict[str, int] = {}
reasoning_content: str | None = None
@@ -356,15 +272,7 @@ async def consume_sdk_stream(
elif event_type == "response.function_call_arguments.done":
call_id = getattr(event, "call_id", None)
if call_id and call_id in tool_call_buffers:
arguments = getattr(event, "arguments", "") or ""
tool_call_buffers[call_id]["arguments"] = arguments
if on_tool_call_delta:
tool_call_args_emitted.add(str(call_id))
await on_tool_call_delta({
"call_id": str(call_id),
"name": str(tool_call_buffers[call_id].get("name") or ""),
"arguments": str(arguments),
})
tool_call_buffers[call_id]["arguments"] = getattr(event, "arguments", "") or ""
elif event_type == "response.output_item.done":
item = getattr(event, "item", None)
if item and getattr(item, "type", None) == "function_call":
@@ -373,13 +281,6 @@ async def consume_sdk_stream(
continue
buf = tool_call_buffers.get(call_id) or {}
args_raw = buf.get("arguments") or getattr(item, "arguments", None) or "{}"
if on_tool_call_delta and str(call_id) not in tool_call_args_emitted:
tool_call_args_emitted.add(str(call_id))
await on_tool_call_delta({
"call_id": str(call_id),
"name": str(buf.get("name") or getattr(item, "name", None) or ""),
"arguments": str(args_raw),
})
try:
args = json.loads(args_raw)
except Exception:
+1 -19
View File
@@ -71,11 +71,6 @@ class ProviderSpec:
# "reasoning_split" — {"reasoning_split": true/false} (MiniMax)
thinking_style: str = ""
# Gateway-native reasoning control to pair with model-level thinking styles.
# "reasoning_effort" — {"reasoning": {"effort": <none|minimal|...>}}
# (OpenRouter)
gateway_reasoning_style: str = ""
# When True, treat the "reasoning" response field as formal content
# when "content" is empty. Only set this for providers (e.g. StepFun)
# whose API returns the actual answer in "reasoning" instead of "content".
@@ -147,7 +142,6 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
detect_by_base_keyword="openrouter",
default_api_base="https://openrouter.ai/api/v1",
supports_prompt_caching=True,
gateway_reasoning_style="reasoning_effort",
),
# Hugging Face Inference Providers: OpenAI-compatible router for chat models.
ProviderSpec(
@@ -171,7 +165,7 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
env_extras=(("APIFREE_API_KEY", "{api_key}"),),
is_gateway=True,
detect_by_base_keyword="apifree.ai",
default_api_base="https://api.apifree.ai/agent/v1",
default_api_base="https://api.apifree.ai/v1",
),
# AiHubMix: global gateway, OpenAI-compatible interface.
# strip_model_prefix=True: doesn't understand "anthropic/claude-3",
@@ -199,18 +193,6 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
default_api_base="https://api.siliconflow.cn/v1",
),
# Novita AI: OpenAI-compatible gateway for hosted model APIs.
ProviderSpec(
name="novita",
keywords=("novita",),
env_key="NOVITA_API_KEY",
display_name="Novita AI",
backend="openai_compat",
is_gateway=True,
detect_by_base_keyword="novita",
default_api_base="https://api.novita.ai/openai",
),
# VolcEngine (火山引擎): OpenAI-compatible gateway, pay-per-use models
ProviderSpec(
name="volcengine",
+8 -27
View File
@@ -7,25 +7,6 @@ from pathlib import Path
import httpx
from loguru import logger
_TRANSCRIPTIONS_PATH = "audio/transcriptions"
def _resolve_transcription_url(api_base: str | None, default_url: str) -> str:
"""Resolve the full transcription endpoint URL.
Accepts either a chat-style base (e.g. ``https://api.groq.com/openai/v1``)
or a complete URL already ending in ``/audio/transcriptions``. A chat-style
base the form users naturally copy from their LLM provider config gets
the path appended instead of being POSTed verbatim and 404ing (#3637).
"""
if not api_base:
return default_url
base = api_base.rstrip("/")
if base.endswith(_TRANSCRIPTIONS_PATH):
return base
return f"{base}/{_TRANSCRIPTIONS_PATH}"
# Up to 3 retries (4 attempts total) with exponential backoff on transient
# failures. Whisper endpoints occasionally return 502/503 under load, and
# mobile-network transcription callers hit sporadic connect/read errors.
@@ -146,12 +127,12 @@ class OpenAITranscriptionProvider:
language: str | None = None,
):
self.api_key = api_key or os.environ.get("OPENAI_API_KEY")
self.api_url = _resolve_transcription_url(
api_base or os.environ.get("OPENAI_TRANSCRIPTION_BASE_URL"),
"https://api.openai.com/v1/audio/transcriptions",
self.api_url = (
api_base
or os.environ.get("OPENAI_TRANSCRIPTION_BASE_URL")
or "https://api.openai.com/v1/audio/transcriptions"
)
self.language = language or None
logger.debug("OpenAI transcription endpoint: {}", self.api_url)
async def transcribe(self, file_path: str | Path) -> str:
if not self.api_key:
@@ -185,12 +166,12 @@ class GroqTranscriptionProvider:
language: str | None = None,
):
self.api_key = api_key or os.environ.get("GROQ_API_KEY")
self.api_url = _resolve_transcription_url(
api_base or os.environ.get("GROQ_BASE_URL"),
"https://api.groq.com/openai/v1/audio/transcriptions",
self.api_url = (
api_base
or os.environ.get("GROQ_BASE_URL")
or "https://api.groq.com/openai/v1/audio/transcriptions"
)
self.language = language or None
logger.debug("Groq transcription endpoint: {}", self.api_url)
async def transcribe(self, file_path: str | Path) -> str:
"""
+5 -45
View File
@@ -36,36 +36,15 @@ def configure_ssrf_whitelist(cidrs: list[str]) -> None:
_allowed_networks = nets
def _normalize_addr(
addr: ipaddress.IPv4Address | ipaddress.IPv6Address,
) -> ipaddress.IPv4Address | ipaddress.IPv6Address:
"""Normalize IPv6-mapped IPv4 addresses to their IPv4 form.
``::ffff:127.0.0.1`` is semantically identical to ``127.0.0.1`` but
Python's ipaddress treats it as an IPv6Address that matches neither
``127.0.0.0/8`` nor ``::1/128``. Converting it to IPv4 ensures
blocklist/allowlist checks work correctly.
"""
if isinstance(addr, ipaddress.IPv6Address) and addr.ipv4_mapped is not None:
return addr.ipv4_mapped
return addr
def _is_private(addr: ipaddress.IPv4Address | ipaddress.IPv6Address) -> bool:
normalized = _normalize_addr(addr)
if _allowed_networks and any(normalized in net for net in _allowed_networks):
if _allowed_networks and any(addr in net for net in _allowed_networks):
return False
return any(normalized in net for net in _BLOCKED_NETWORKS)
return any(addr in net for net in _BLOCKED_NETWORKS)
def validate_url_target(url: str, *, allow_loopback: bool = False) -> tuple[bool, str]:
def validate_url_target(url: str) -> tuple[bool, str]:
"""Validate a URL is safe to fetch: scheme, hostname, and resolved IPs.
``allow_loopback`` is intentionally narrow: it only permits literal
loopback hosts (localhost, 127.0.0.0/8, ::1) when every resolved address is
loopback. It does not allow RFC1918, link-local, metadata, or public DNS
names that happen to resolve to loopback.
Returns (ok, error_message). When ok is True, error_message is empty.
"""
try:
@@ -87,16 +66,11 @@ def validate_url_target(url: str, *, allow_loopback: bool = False) -> tuple[bool
except socket.gaierror:
return False, f"Cannot resolve hostname: {hostname}"
addrs: list[ipaddress.IPv4Address | ipaddress.IPv6Address] = []
for info in infos:
try:
addr = ipaddress.ip_address(info[4][0])
except ValueError:
continue
addrs.append(addr)
if allow_loopback and _is_allowed_loopback_target(hostname, addrs):
return True, ""
for addr in addrs:
if _is_private(addr):
return False, f"Blocked: {hostname} resolves to private/internal address {addr}"
@@ -135,25 +109,11 @@ def validate_resolved_url(url: str) -> tuple[bool, str]:
return True, ""
def contains_internal_url(command: str, *, allow_loopback: bool = False) -> bool:
def contains_internal_url(command: str) -> bool:
"""Return True if the command string contains a URL targeting an internal/private address."""
for m in _URL_RE.finditer(command):
url = m.group(0)
ok, _ = validate_url_target(url, allow_loopback=allow_loopback)
ok, _ = validate_url_target(url)
if not ok:
return True
return False
def _is_allowed_loopback_target(
hostname: str,
addrs: list[ipaddress.IPv4Address | ipaddress.IPv6Address],
) -> bool:
if not addrs or not all(_normalize_addr(addr).is_loopback for addr in addrs):
return False
normalized = hostname.rstrip(".").lower()
if normalized == "localhost":
return True
with suppress(ValueError):
return ipaddress.ip_address(hostname).is_loopback
return False
-430
View File
@@ -1,430 +0,0 @@
"""Workspace access scope and sandbox capability helpers."""
from __future__ import annotations
import os
from contextvars import ContextVar, Token
from dataclasses import dataclass
from pathlib import Path
from typing import Any, Literal
WorkspaceAccessMode = Literal["restricted", "full"]
WORKSPACE_SCOPE_METADATA_KEY = "workspace_scope"
_ACCESS_MODES = {"restricted", "full"}
_TRUE_VALUES = {"1", "true", "yes", "on", "enabled"}
_FALSE_VALUES = {"0", "false", "no", "off", "disabled", ""}
_PROVIDER_LABELS = {
"none": "None",
"unknown": "Unknown system sandbox",
"macos_app_sandbox": "macOS App Sandbox",
"bwrap": "Bubblewrap",
}
_CURRENT_WORKSPACE_SCOPE: ContextVar["WorkspaceScope | None"] = ContextVar(
"nanobot_workspace_scope",
default=None,
)
class WorkspaceScopeError(ValueError):
"""Raised when a requested WebUI workspace scope is invalid."""
status = 400
def __init__(self, message: str, *, status: int = 400) -> None:
super().__init__(message)
self.message = message
self.status = status
@dataclass(frozen=True)
class WorkspaceSandboxStatus:
"""Resolved workspace sandbox state for runtime display and tooling."""
restrict_to_workspace: bool
workspace_root: str
level: str
enforced: bool
provider: str
provider_label: str
summary: str
def as_dict(self) -> dict[str, object]:
return {
"restrict_to_workspace": self.restrict_to_workspace,
"workspace_root": self.workspace_root,
"level": self.level,
"enforced": self.enforced,
"provider": self.provider,
"provider_label": self.provider_label,
"summary": self.summary,
}
@dataclass(frozen=True)
class WorkspaceScope:
"""Effective project root and access mode for one agent turn."""
project_path: Path
access_mode: WorkspaceAccessMode
restrict_to_workspace: bool
sandbox_status: WorkspaceSandboxStatus
source_channel: str | None = None
@property
def project_name(self) -> str:
return self.project_path.name or str(self.project_path)
def metadata(self) -> dict[str, str]:
return {
"project_path": str(self.project_path),
"access_mode": self.access_mode,
}
def payload(self) -> dict[str, Any]:
return {
**self.metadata(),
"project_name": self.project_name,
"restrict_to_workspace": self.restrict_to_workspace,
"sandbox_status": self.sandbox_status.as_dict(),
}
@dataclass(frozen=True)
class ToolWorkspace:
"""Workspace policy resolved for a tool call."""
project_path: Path | None
restrict_to_workspace: bool
scope: WorkspaceScope | None = None
@property
def allowed_root(self) -> Path | None:
if self.restrict_to_workspace and self.project_path is not None:
return self.project_path
return None
@dataclass(frozen=True)
class WorkspaceScopeResolver:
"""Resolve the effective workspace scope at an agent turn boundary."""
default_workspace: str | Path
default_restrict_to_workspace: bool
scoped_channel: str = "websocket"
@property
def sandbox_status(self) -> WorkspaceSandboxStatus:
return self.default().sandbox_status
def default(self) -> WorkspaceScope:
return default_workspace_scope(
self.default_workspace,
self.default_restrict_to_workspace,
)
def for_message(
self,
msg: Any,
session_metadata: Any,
) -> WorkspaceScope:
return self.for_turn(
channel=getattr(msg, "channel", None),
message_metadata=getattr(msg, "metadata", None),
session_metadata=session_metadata,
)
def for_turn(
self,
*,
channel: str | None,
message_metadata: Any,
session_metadata: Any,
) -> WorkspaceScope:
if channel != self.scoped_channel:
return self.default()
return resolve_effective_workspace_scope(
message_metadata=message_metadata,
session_metadata=session_metadata,
default_workspace=self.default_workspace,
default_restrict_to_workspace=self.default_restrict_to_workspace,
source_channel=channel,
)
def persist_message_scope(self, session: Any, msg: Any) -> None:
if getattr(msg, "channel", None) != self.scoped_channel:
return
metadata = getattr(msg, "metadata", None)
if not isinstance(metadata, dict):
return
raw = metadata.get(WORKSPACE_SCOPE_METADATA_KEY)
if isinstance(raw, dict):
session.metadata[WORKSPACE_SCOPE_METADATA_KEY] = dict(raw)
def workspace_sandbox_status(
*,
restrict_to_workspace: bool,
workspace: str | Path,
environ: dict[str, str] | None = None,
) -> WorkspaceSandboxStatus:
"""Return how workspace restriction is enforced in the current host."""
workspace_root = str(Path(workspace).expanduser().resolve(strict=False))
provider = _env_system_provider(environ)
if not restrict_to_workspace:
return WorkspaceSandboxStatus(
restrict_to_workspace=False,
workspace_root=workspace_root,
level="off",
enforced=False,
provider="none",
provider_label=_provider_label("none"),
summary="Workspace restriction is disabled.",
)
if provider:
label = _provider_label(provider)
return WorkspaceSandboxStatus(
restrict_to_workspace=True,
workspace_root=workspace_root,
level="system",
enforced=True,
provider=provider,
provider_label=label,
summary=f"Workspace restriction is system-enforced by {label}.",
)
return WorkspaceSandboxStatus(
restrict_to_workspace=True,
workspace_root=workspace_root,
level="application",
enforced=False,
provider="none",
provider_label=_provider_label("none"),
summary="Workspace restriction uses nanobot application-level guards.",
)
def default_access_mode(restrict_to_workspace: bool) -> WorkspaceAccessMode:
return "restricted" if restrict_to_workspace else "full"
def build_workspace_scope(
project_path: str | Path,
access_mode: str,
*,
source_channel: str | None = None,
) -> WorkspaceScope:
mode = _normalize_access_mode(access_mode)
root = Path(project_path).expanduser().resolve(strict=False)
restrict = mode == "restricted"
return WorkspaceScope(
project_path=root,
access_mode=mode,
restrict_to_workspace=restrict,
sandbox_status=workspace_sandbox_status(
restrict_to_workspace=restrict,
workspace=root,
),
source_channel=source_channel,
)
def default_workspace_scope(
workspace: str | Path,
restrict_to_workspace: bool,
*,
source_channel: str | None = None,
) -> WorkspaceScope:
return build_workspace_scope(
workspace,
default_access_mode(restrict_to_workspace),
source_channel=source_channel,
)
def validate_workspace_scope_payload(
raw: Any,
*,
default_workspace: str | Path,
default_restrict_to_workspace: bool,
source_channel: str | None = None,
) -> WorkspaceScope:
"""Validate a client-requested workspace scope."""
if raw is None:
return default_workspace_scope(
default_workspace,
default_restrict_to_workspace,
source_channel=source_channel,
)
if not isinstance(raw, dict):
raise WorkspaceScopeError("workspace_scope must be an object")
raw_path = raw.get("project_path") or raw.get("path")
if raw_path is None or raw_path == "":
raw_path = str(Path(default_workspace).expanduser().resolve(strict=False))
if not isinstance(raw_path, str):
raise WorkspaceScopeError("project_path must be a string")
if "\0" in raw_path:
raise WorkspaceScopeError("project_path contains invalid characters")
project = Path(raw_path).expanduser()
if not project.is_absolute():
raise WorkspaceScopeError("project_path must be absolute")
project = project.resolve(strict=False)
if not project.is_dir():
raise WorkspaceScopeError("project_path must be an existing directory")
raw_mode = raw.get("access_mode")
if raw_mode is None:
raw_mode = default_access_mode(default_restrict_to_workspace)
if not isinstance(raw_mode, str):
raise WorkspaceScopeError("access_mode must be a string")
return build_workspace_scope(project, raw_mode, source_channel=source_channel)
def workspace_scope_from_metadata(
metadata: Any,
*,
default_workspace: str | Path,
default_restrict_to_workspace: bool,
source_channel: str | None = None,
) -> WorkspaceScope:
"""Resolve persisted metadata, falling back safely for old or stale sessions."""
if not isinstance(metadata, dict):
return default_workspace_scope(
default_workspace,
default_restrict_to_workspace,
source_channel=source_channel,
)
try:
return validate_workspace_scope_payload(
metadata.get(WORKSPACE_SCOPE_METADATA_KEY),
default_workspace=default_workspace,
default_restrict_to_workspace=default_restrict_to_workspace,
source_channel=source_channel,
)
except WorkspaceScopeError:
return default_workspace_scope(
default_workspace,
default_restrict_to_workspace,
source_channel=source_channel,
)
def resolve_effective_workspace_scope(
*,
message_metadata: Any,
session_metadata: Any,
default_workspace: str | Path,
default_restrict_to_workspace: bool,
source_channel: str | None = None,
) -> WorkspaceScope:
if isinstance(message_metadata, dict) and WORKSPACE_SCOPE_METADATA_KEY in message_metadata:
return workspace_scope_from_metadata(
message_metadata,
default_workspace=default_workspace,
default_restrict_to_workspace=default_restrict_to_workspace,
source_channel=source_channel,
)
return workspace_scope_from_metadata(
session_metadata,
default_workspace=default_workspace,
default_restrict_to_workspace=default_restrict_to_workspace,
source_channel=source_channel,
)
def bind_workspace_scope(scope: WorkspaceScope) -> Token[WorkspaceScope | None]:
return _CURRENT_WORKSPACE_SCOPE.set(scope)
def reset_workspace_scope(token: Token[WorkspaceScope | None]) -> None:
_CURRENT_WORKSPACE_SCOPE.reset(token)
def current_workspace_scope() -> WorkspaceScope | None:
return _CURRENT_WORKSPACE_SCOPE.get()
def current_tool_workspace(
default_workspace: str | Path | None,
*,
restrict_to_workspace: bool = False,
sandbox_restricts_workspace: bool = False,
) -> ToolWorkspace:
"""Return the workspace/access policy for the current tool call."""
scope = current_workspace_scope()
project_path = (
scope.project_path
if scope is not None
else Path(default_workspace).expanduser() if default_workspace is not None else None
)
restrict = (
scope.restrict_to_workspace
if scope is not None
else bool(restrict_to_workspace)
) or sandbox_restricts_workspace
return ToolWorkspace(
project_path=project_path,
restrict_to_workspace=restrict,
scope=scope,
)
def current_scope_allows_loopback(*, enabled: bool) -> bool:
"""Return True when the current WebUI Full Access turn may touch loopback URLs."""
scope = current_workspace_scope()
return bool(
enabled
and scope is not None
and scope.source_channel == "websocket"
and scope.access_mode == "full"
and not scope.restrict_to_workspace
)
def _env_system_provider(environ: dict[str, str] | None = None) -> str | None:
env = environ if environ is not None else os.environ
explicit_provider = env.get("NANOBOT_WORKSPACE_SANDBOX_PROVIDER")
enforced = env.get("NANOBOT_WORKSPACE_SANDBOX_ENFORCED")
compatibility = env.get("NANOBOT_SANDBOX_ENFORCED")
marker = enforced if enforced is not None else compatibility
if marker is None:
return None
normalized_marker = marker.strip().lower()
if normalized_marker in _FALSE_VALUES:
return None
if normalized_marker in _TRUE_VALUES:
return _normalize_provider(explicit_provider)
return _normalize_provider(marker)
def _normalize_provider(value: str | None) -> str:
if not value:
return "unknown"
normalized = value.strip().lower().replace("-", "_").replace(" ", "_")
return normalized or "unknown"
def _provider_label(provider: str) -> str:
if provider in _PROVIDER_LABELS:
return _PROVIDER_LABELS[provider]
return provider.replace("_", " ").title()
def _normalize_access_mode(value: str) -> WorkspaceAccessMode:
mode = value.strip().lower().replace("_", "-")
if mode == "restrict":
mode = "restricted"
if mode == "full-access":
mode = "full"
if mode not in _ACCESS_MODES:
raise WorkspaceScopeError("access_mode must be restricted or full")
return mode # type: ignore[return-value]
-85
View File
@@ -1,85 +0,0 @@
"""Workspace path boundary helpers.
These helpers are application-level guards. They make path decisions
consistent across tools, but they are not a replacement for an OS sandbox.
"""
from __future__ import annotations
from pathlib import Path
from typing import Iterable
WORKSPACE_BOUNDARY_NOTE = (
" (this is a hard policy boundary, not a transient failure; "
"do not retry with shell tricks or alternative tools, and ask "
"the user how to proceed if the resource is genuinely required)"
)
class WorkspaceBoundaryError(PermissionError):
"""Raised when a requested path escapes an allowed workspace boundary."""
def resolve_path(path: str | Path, workspace: str | Path | None = None, *, strict: bool = False) -> Path:
"""Resolve *path*, interpreting relative paths against *workspace* when set."""
candidate = Path(path).expanduser()
if not candidate.is_absolute() and workspace is not None:
candidate = Path(workspace).expanduser() / candidate
return candidate.resolve(strict=strict)
def is_path_within(path: str | Path, root: str | Path) -> bool:
"""Return True when *path* resolves to *root* or a descendant of *root*."""
try:
resolved_path = Path(path).expanduser().resolve(strict=False)
resolved_root = Path(root).expanduser().resolve(strict=False)
resolved_path.relative_to(resolved_root)
return True
except (OSError, RuntimeError, TypeError, ValueError):
return False
def is_path_allowed(path: str | Path, roots: Iterable[str | Path]) -> bool:
"""Return True when *path* is inside any allowed root."""
return any(is_path_within(path, root) for root in roots)
def require_path_within(
path: str | Path,
root: str | Path,
*,
message: str | None = None,
) -> Path:
"""Resolve *path* and require it to be inside *root*."""
resolved = Path(path).expanduser().resolve(strict=False)
if not is_path_within(resolved, root):
raise WorkspaceBoundaryError(
message
or f"Path {path} is outside allowed directory {Path(root).expanduser()}"
+ WORKSPACE_BOUNDARY_NOTE
)
return resolved
def resolve_allowed_path(
path: str | Path,
*,
workspace: str | Path | None = None,
allowed_root: str | Path | None = None,
extra_allowed_roots: Iterable[str | Path] | None = None,
strict: bool = False,
) -> Path:
"""Resolve a path and enforce containment in allowed roots when configured."""
resolved = resolve_path(path, workspace, strict=False)
if allowed_root is None:
return resolve_path(path, workspace, strict=strict) if strict else resolved
roots = [allowed_root, *(extra_allowed_roots or [])]
if not is_path_allowed(resolved, roots):
raise WorkspaceBoundaryError(
f"Path {path} is outside allowed directory {Path(allowed_root).expanduser()}"
+ WORKSPACE_BOUNDARY_NOTE
)
if strict:
return resolve_path(path, workspace, strict=True)
return resolved
+7 -65
View File
@@ -19,7 +19,6 @@ from nanobot.utils.helpers import (
find_legal_message_start,
image_placeholder_text,
safe_filename,
strip_think,
)
from nanobot.utils.subagent_channel_display import scrub_subagent_announce_body
@@ -28,8 +27,6 @@ _MESSAGE_TIME_PREFIX_RE = re.compile(r"^\[Message Time: [^\]]+\]\n?")
_LOCAL_IMAGE_BREADCRUMB_RE = re.compile(r"^\[image: (?:/|~)[^\]]+\]\s*$")
_TOOL_CALL_ECHO_RE = re.compile(r'^\s*(?:generate_image|message)\([^)]*\)\s*$')
_SESSION_PREVIEW_MAX_CHARS = 120
_SESSION_LIST_PREVIEW_MAX_RECORDS = 200
_SESSION_LIST_PREVIEW_MAX_CHARS = 1_000_000
def _sanitize_assistant_replay_text(content: str) -> str:
@@ -77,17 +74,6 @@ def _message_preview_text(message: dict[str, Any]) -> str:
return _text_preview(content)
def _metadata_title(metadata: Any) -> str:
if not isinstance(metadata, dict):
return ""
title = metadata.get("title")
if not isinstance(title, str):
return ""
if metadata.get("title_user_edited") is True:
return title
return strip_think(title)
@dataclass
class Session:
"""A conversation session."""
@@ -179,45 +165,6 @@ class Session:
image_placeholder_text(p) for p in media if isinstance(p, str) and p
)
content = f"{content}\n{breadcrumbs}" if content else breadcrumbs
cli_apps = message.get("cli_apps")
if role == "user" and isinstance(cli_apps, list) and cli_apps and isinstance(content, str):
cli_lines: list[str] = []
for item in cli_apps[:8]:
if not isinstance(item, dict):
continue
name = str(item.get("name") or "").strip().lower()
if not name:
continue
entry = str(item.get("entry_point") or "unknown").strip() or "unknown"
cli_lines.append(
f"[CLI App Attachment: @{name}; tool=run_cli_app; entry_point={entry}; "
f"skill=skills/cli-app-{name}/SKILL.md]"
)
if cli_lines:
breadcrumbs = "\n".join(cli_lines)
content = f"{content}\n{breadcrumbs}" if content else breadcrumbs
mcp_presets = message.get("mcp_presets")
if (
role == "user"
and isinstance(mcp_presets, list)
and mcp_presets
and isinstance(content, str)
):
mcp_lines: list[str] = []
for item in mcp_presets[:8]:
if not isinstance(item, dict):
continue
name = str(item.get("name") or "").strip().lower()
if not name:
continue
transport = str(item.get("transport") or "mcp").strip() or "mcp"
mcp_lines.append(
f"[MCP Preset Attachment: @{name}; tool_prefix=mcp_{name}_; "
f"transport={transport}]"
)
if mcp_lines:
breadcrumbs = "\n".join(mcp_lines)
content = f"{content}\n{breadcrumbs}" if content else breadcrumbs
if include_timestamps:
content = self._annotate_message_time(message, content)
if role == "assistant" and isinstance(content, str) and not content.strip():
@@ -654,21 +601,12 @@ class SessionManager:
if data.get("_type") == "metadata":
key = data.get("key") or path.stem.replace("_", ":", 1)
metadata = data.get("metadata", {})
title = _metadata_title(metadata)
title = metadata.get("title") if isinstance(metadata, dict) else None
preview = ""
fallback_preview = ""
scanned_records = 0
scanned_chars = 0
for line in f:
if not line.strip():
continue
scanned_records += 1
scanned_chars += len(line)
if (
scanned_records > _SESSION_LIST_PREVIEW_MAX_RECORDS
or scanned_chars > _SESSION_LIST_PREVIEW_MAX_CHARS
):
break
item = json.loads(line)
if item.get("_type") == "metadata":
continue
@@ -685,7 +623,7 @@ class SessionManager:
"key": key,
"created_at": data.get("created_at"),
"updated_at": data.get("updated_at"),
"title": title,
"title": title if isinstance(title, str) else "",
"preview": preview,
"path": str(path)
})
@@ -696,7 +634,11 @@ class SessionManager:
"key": repaired.key,
"created_at": repaired.created_at.isoformat(),
"updated_at": repaired.updated_at.isoformat(),
"title": _metadata_title(repaired.metadata),
"title": (
repaired.metadata.get("title")
if isinstance(repaired.metadata.get("title"), str)
else ""
),
"preview": next(
(
text
+2 -12
View File
@@ -19,7 +19,7 @@ from nanobot.bus.queue import MessageBus
from nanobot.providers.base import LLMProvider
from nanobot.session.goal_state import goal_state_ws_blob
from nanobot.session.manager import Session, SessionManager
from nanobot.utils.helpers import strip_think, truncate_text
from nanobot.utils.helpers import truncate_text
from nanobot.utils.llm_runtime import LLMRuntime
WEBUI_SESSION_METADATA_KEY = "webui"
@@ -48,7 +48,6 @@ def clean_generated_title(raw: str | None) -> str:
return ""
text = re.sub(r"^\s*(title|标题)\s*[:]\s*", "", text, flags=re.IGNORECASE)
text = text.strip().strip("\"'`“”‘’")
text = strip_think(text)
text = re.sub(r"\s+", " ", text).strip()
text = text.rstrip("。.!?,;:")
if len(text) > TITLE_MAX_CHARS:
@@ -66,9 +65,6 @@ def _title_inputs(session: Session) -> tuple[str, str]:
content = message.get("content")
if not isinstance(content, str) or not content.strip():
continue
content = strip_think(content)
if not content:
continue
if role == "user" and not user_text:
user_text = content.strip()
elif role == "assistant" and not assistant_text:
@@ -93,13 +89,7 @@ async def maybe_generate_webui_title(
return False
current_title = session.metadata.get(WEBUI_TITLE_METADATA_KEY)
if isinstance(current_title, str) and current_title.strip():
cleaned_current_title = clean_generated_title(current_title)
if cleaned_current_title:
if cleaned_current_title != current_title:
session.metadata[WEBUI_TITLE_METADATA_KEY] = cleaned_current_title
sessions.save(session)
return False
session.metadata.pop(WEBUI_TITLE_METADATA_KEY, None)
return False
user_text, assistant_text = _title_inputs(session)
if not user_text:
+5 -9
View File
@@ -1,9 +1,5 @@
# Agent Instructions
## Workspace Guidance
Use this file for project-specific preferences, recurring workflow conventions, and instructions you want the agent to remember for this workspace. Keep durable facts about the user in `USER.md`, personality/style guidance in `SOUL.md`, and long-term memory in `memory/MEMORY.md`.
## Scheduled Reminders
Before scheduling reminders, check available skills and follow skill guidance first.
@@ -14,10 +10,10 @@ Get USER_ID and CHANNEL from the current session (e.g., `8281248569` and `telegr
## Heartbeat Tasks
`HEARTBEAT.md` is checked periodically when registered as a cron job. Use the built-in `cron` tool to schedule it (e.g. `cron add --name heartbeat --schedule "every 30m" --message "Check HEARTBEAT.md"`).
`HEARTBEAT.md` is checked on the configured heartbeat interval. Use file tools to manage periodic tasks:
- Use `apply_patch` for normal task-list updates, especially when adding, removing, or changing multiple lines.
- Use `edit_file` only for small exact replacements copied from the current `HEARTBEAT.md`.
- Use `write_file` for first creation or intentional full-file rewrites.
- **Add**: `edit_file` to append new tasks
- **Remove**: `edit_file` to delete completed tasks
- **Rewrite**: `write_file` to replace all tasks
When the user asks for a recurring/periodic task, update `HEARTBEAT.md` and register it via `cron` instead of creating a one-time reminder.
When the user asks for a recurring/periodic task, update `HEARTBEAT.md` instead of creating a one-time cron reminder.
+3 -3
View File
@@ -1,9 +1,9 @@
# Heartbeat Tasks
This file is checked periodically by your nanobot agent.
Register it as a cron job (e.g. `cron add --name heartbeat --schedule "every 30m" --message "Check HEARTBEAT.md"`) to get the same behavior as the legacy heartbeat service.
This file is checked every 30 minutes by your nanobot agent.
Add tasks below that you want the agent to work on periodically.
If this file has no tasks (only headers and comments), the agent will skip it.
If this file has no tasks (only headers and comments), the agent will skip the heartbeat.
## Active Tasks
+28
View File
@@ -0,0 +1,28 @@
# Tool Usage Notes
Tool signatures are provided automatically via function calling.
This file documents non-obvious constraints and usage patterns.
## exec — Safety Limits
- Commands have a configurable timeout (default 60s)
- Dangerous commands are blocked (rm -rf, format, dd, shutdown, etc.)
- Output is truncated at 10,000 characters
- `restrictToWorkspace` config can limit file access to the workspace
## grep — Content Search
- Use `grep` to search file contents inside the workspace
- Default behavior returns only matching file paths (`output_mode="files_with_matches"`)
- Supports optional `glob` filtering (e.g. `glob="*.py"`) plus `context_before` / `context_after`
- Supports `type="py"`, `type="ts"`, `type="md"` and similar shorthand filters
- Use `fixed_strings=true` for literal keywords containing regex characters
- Use `output_mode="files_with_matches"` to get only matching file paths
- Use `output_mode="count"` to size a search before reading full matches
- Use `head_limit` and `offset` to page across results
- Prefer this over `exec` for code and history searches
- Binary or oversized files may be skipped to keep results readable
## cron — Scheduled Reminders
- Please refer to cron skill for usage.
-67
View File
@@ -1,67 +0,0 @@
# Tool Usage Notes
Tool signatures are provided automatically via function calling. This section
documents the general tool contract and non-obvious usage patterns.
## General Tool Contract
- Use the narrowest structured tool that directly matches the task.
- Use read-only discovery before writes when state is uncertain.
- Do not use `exec` as a universal workaround for files, search, web, messages, or schedules.
- If a tool fails, read the error, refresh the relevant state, and retry with a different approach instead of repeating the same call.
- After meaningful changes, verify with the smallest reliable check: re-read changed state, run targeted tests, or inspect command output.
- Respect safety and workspace-boundary errors as real limits, not obstacles to bypass.
## Discovery and Reading
- Use `find_files` or `list_dir` to locate workspace paths before `read_file` when a path is uncertain.
- Use `grep` for content search inside the workspace; prefer it over shell grep for ordinary searches.
- `grep` defaults to `output_mode="files_with_matches"`; use `output_mode="content"` for matching lines with context.
- Use `fixed_strings=true` for literal keywords containing regex characters.
- Use `output_mode="count"` to size a broad search before reading full matches.
- Use `head_limit` and `offset` to page across large result sets.
- Binary or oversized files may be skipped to keep results readable.
## File and Coding Workflows
- For code or config changes, the default loop is: locate (`find_files`/`grep`), inspect (`read_file`), edit (`apply_patch`), then verify (`exec` or re-read).
- Use `apply_patch` as the default code editing tool, especially for multi-file changes, structural edits, generated code, moves, adds, or deletes.
- Use `apply_patch dry_run=true` when the patch is uncertain and you want validation plus a change summary before writing.
- Use `edit_file` only for small exact replacements in one file, with `old_text` copied from `read_file`; add `occurrence`, `line_hint`, or `expected_replacements` when ambiguity matters.
- Use `write_file` for new files or intentional full-file rewrites, not routine partial edits.
- If `apply_patch` or `edit_file` fails, re-read with `force=true`, narrow the context, and try a smaller patch rather than switching to shell `sed` or `echo`.
## Process Execution
- Use `exec` for tests, builds, package commands, git commands, and other process execution.
- Prefer dedicated file/search tools over `cat`, shell `find`, shell `grep`, `sed`, or `echo` for ordinary workspace inspection and edits.
- Use non-interactive flags such as `-y` or `--yes` when available.
- Commands have a configurable timeout (default 60s), dangerous commands are blocked, and output is truncated.
- For long-running or interactive commands, pass `yield_time_ms`; if the process keeps running, continue with `write_stdin`.
- Use `write_stdin` to poll, provide stdin, close stdin, wait for expected output with `wait_for`, or terminate an existing exec session.
- Use `list_exec_sessions` to recover active session IDs after context shifts.
## CLI App Attachments
- When Runtime Context lists a `CLI App Attachment` or `CLI App Mention`, treat the `@name` as an app capability the user intentionally attached to the current turn.
- If the task may need app-specific behavior, read the listed skill first, then call `run_cli_app` with that `name`.
- Do not run an attached CLI app through shell or generic process tools unless the user explicitly asks for that lower-level path.
- If the app CLI is missing, lacks local desktop/app/API prerequisites, or cannot complete the requested action, explain that concrete blocker and what was attempted.
## Web and External Information
- Use web tools when the user asks for current information, a specific URL, or information likely to have changed.
- Use `web_search` to find sources and `web_fetch` for a specific page or result that needs closer reading.
- Do not invent freshness-sensitive facts when tools can verify them.
## Messaging and Media
- Use `message` to send content or local media to the user/channel.
- `read_file` only reads content for your analysis; it does not deliver a file to the user.
- When sending an existing local file, attach it through the message/media mechanism instead of pasting file contents unless the user asked for text.
## Scheduling and Background Work
- Use `cron` for scheduled reminders or recurring jobs; do not run `nanobot cron` through `exec`.
- For heartbeat tasks, register `HEARTBEAT.md` as a cron job according to the agent instructions.
- Do not write reminders only to memory files when the user expects an actual notification.
+5 -41
View File
@@ -7,6 +7,7 @@ from loguru import logger
from nanobot.utils.helpers import detect_image_mime
# Supported file extensions for text extraction
SUPPORTED_EXTENSIONS: set[str] = {
# Document formats
@@ -231,46 +232,6 @@ def _is_text_extension(ext: str) -> bool:
_MAX_EXTRACT_FILE_SIZE = 50 * 1024 * 1024 # 50 MB
def is_image_file(path: str) -> bool:
"""Check whether *path* looks like an image file.
Uses magic-byte detection (reads first 16 bytes) with a ``mimetypes``
extension-based fallback.
"""
p = Path(path)
mime: str | None = None
if p.is_file():
try:
with p.open("rb") as f:
mime = detect_image_mime(f.read(16))
except OSError:
mime = None
if not mime:
mime = mimetypes.guess_type(path)[0]
return bool(mime and mime.startswith("image/"))
def reference_non_image_attachments(
content: str, media: list[str],
) -> tuple[str, list[str]]:
"""Separate images from non-image attachments without reading file content.
Image paths are preserved for downstream vision-block construction.
Non-image paths are appended as ``[Attachment: path]`` references.
"""
image_paths: list[str] = []
attachment_refs: list[str] = []
for path in media:
if is_image_file(path):
image_paths.append(path)
else:
attachment_refs.append(f"[Attachment: {path}]")
if attachment_refs:
suffix = "\n".join(attachment_refs)
content = f"{content}\n\n{suffix}" if content else suffix
return content, image_paths
def extract_documents(
text: str,
media_paths: list[str],
@@ -306,7 +267,10 @@ def extract_documents(
)
continue
if is_image_file(path_str):
with open(p, "rb") as f:
header = f.read(16)
mime = detect_image_mime(header) or mimetypes.guess_type(path_str)[0]
if mime and mime.startswith("image/"):
image_paths.append(path_str)
else:
extracted = extract_text(p)
+9 -16
View File
@@ -44,15 +44,12 @@ async def evaluate_response(
task_context: str,
provider: LLMProvider,
model: str,
*,
default_notify: bool = True,
) -> bool:
"""Decide whether a background-task result should be delivered to the user.
Uses a lightweight tool-call LLM request. ``default_notify`` controls
the fallback path when the evaluator cannot produce a valid decision:
user-scheduled reminders stay fail-open, while internal checks such as
heartbeat can fail closed.
Uses a lightweight tool-call LLM request (same pattern as heartbeat
``_decide()``). Falls back to ``True`` (notify) on any failure so
that important messages are never silently dropped.
"""
try:
llm_response = await provider.chat_with_retry(
@@ -74,23 +71,19 @@ async def evaluate_response(
if not llm_response.should_execute_tools:
if llm_response.has_tool_calls:
logger.warning(
"evaluate_response: ignoring tool calls under finish_reason='{}', defaulting to notify={}",
"evaluate_response: ignoring tool calls under finish_reason='{}', defaulting to notify",
llm_response.finish_reason,
default_notify,
)
else:
logger.warning(
"evaluate_response: no tool call returned, defaulting to notify={}",
default_notify,
)
return default_notify
logger.warning("evaluate_response: no tool call returned, defaulting to notify")
return True
args = llm_response.tool_calls[0].arguments
should_notify = args.get("should_notify", default_notify)
should_notify = args.get("should_notify", True)
reason = args.get("reason", "")
logger.info("evaluate_response: should_notify={}, reason={}", should_notify, reason)
return bool(should_notify)
except Exception:
logger.exception("evaluate_response failed, defaulting to notify={}", default_notify)
return default_notify
logger.exception("evaluate_response failed, defaulting to notify")
return True
+88 -272
View File
@@ -3,13 +3,15 @@
from __future__ import annotations
import difflib
import json
import re
import time
from dataclasses import dataclass, field
from pathlib import Path
from typing import Any, Awaitable, Callable
TRACKED_FILE_EDIT_TOOLS = frozenset({"write_file", "edit_file", "apply_patch"})
TRACKED_FILE_EDIT_TOOLS = frozenset({"write_file", "edit_file", "notebook_edit"})
_MAX_SNAPSHOT_BYTES = 2 * 1024 * 1024
_LIVE_EMIT_INTERVAL_S = 0.18
_LIVE_EMIT_LINE_STEP = 24
@@ -152,108 +154,19 @@ def prepare_file_edit_tracker(
workspace: Path | None,
params: dict[str, Any] | None,
) -> FileEditTracker | None:
trackers = prepare_file_edit_trackers(
call_id=call_id,
tool_name=tool_name,
tool=tool,
workspace=workspace,
params=params,
)
return trackers[0] if trackers else None
def prepare_file_edit_trackers(
*,
call_id: str,
tool_name: str,
tool: Any,
workspace: Path | None,
params: dict[str, Any] | None,
) -> list[FileEditTracker]:
if not is_file_edit_tool(tool_name):
return []
paths = resolve_file_edit_paths(tool_name, tool, workspace, params)
trackers: list[FileEditTracker] = []
seen: set[Path] = set()
for path in paths:
try:
resolved = path.resolve()
except Exception:
resolved = path
if resolved in seen:
continue
seen.add(resolved)
before = read_file_snapshot(path)
trackers.append(FileEditTracker(
call_id=str(call_id or ""),
tool=tool_name,
path=path,
display_path=display_file_edit_path(path, workspace),
before=before,
))
return trackers
def resolve_file_edit_paths(
tool_name: str,
tool: Any,
workspace: Path | None,
params: dict[str, Any] | None,
) -> list[Path]:
if tool_name == "apply_patch":
return _resolve_apply_patch_paths(tool, workspace, params)
return None
path = resolve_file_edit_path(tool, workspace, params)
if path is None:
return []
return [path]
def _resolve_apply_patch_paths(
tool: Any,
workspace: Path | None,
params: dict[str, Any] | None,
) -> list[Path]:
if not isinstance(params, dict):
return []
edits = params.get("edits")
if not isinstance(edits, list) or not edits:
return []
if params.get("dry_run") is True:
return []
resolved: list[Path] = []
seen: set[Path] = set()
for edit in edits:
if not isinstance(edit, dict):
continue
raw_path = edit.get("path")
if not isinstance(raw_path, str) or not raw_path.strip():
continue
path = _resolve_raw_file_edit_path(tool, workspace, raw_path)
if path is not None and path not in seen:
seen.add(path)
resolved.append(path)
return resolved
def _resolve_raw_file_edit_path(
tool: Any,
workspace: Path | None,
raw_path: str,
) -> Path | None:
resolver = getattr(tool, "_resolve", None)
if callable(resolver):
try:
resolved = resolver(raw_path)
if isinstance(resolved, Path):
return resolved
if resolved:
return Path(resolved)
except Exception:
return None
if workspace is None:
return Path(raw_path).expanduser().resolve()
return (workspace / raw_path).expanduser().resolve()
return None
before = read_file_snapshot(path)
return FileEditTracker(
call_id=str(call_id or ""),
tool=tool_name,
path=path,
display_path=display_file_edit_path(path, workspace),
before=before,
)
def build_file_edit_start_event(
@@ -299,7 +212,6 @@ def build_file_edit_end_event(
deleted=deleted,
approximate=False,
binary=(after.binary or after.oversized or after.unreadable) and not counted,
operation="delete" if tracker.before.exists and not after.exists else None,
)
@@ -325,7 +237,6 @@ def build_file_edit_live_event(
*,
added: int,
deleted: int = 0,
operation: str | None = None,
) -> dict[str, Any]:
"""Build an approximate in-progress event while tool-call arguments stream."""
return _event_payload(
@@ -335,7 +246,6 @@ def build_file_edit_live_event(
added=added,
deleted=deleted,
approximate=True,
operation=operation,
)
@@ -394,9 +304,6 @@ class StreamingFileEditTracker:
self._states[key] = state
state.apply_delta(payload)
if state.name == "apply_patch":
await self._update_apply_patch(state)
return
if state.name not in {"write_file", "edit_file"}:
return
if state.path is None:
@@ -436,77 +343,10 @@ class StreamingFileEditTracker:
deleted=deleted,
)])
async def _update_apply_patch(self, state: _StreamingFileEditState) -> None:
if _json_bool_true(state.arguments, "dry_run"):
return
tool = self._tools.get("apply_patch") if hasattr(self._tools, "get") else None
events: list[dict[str, Any]] = []
now = time.monotonic()
path_matches = list(re.finditer(r'"path"\s*:\s*"([^"]+)"', state.arguments))
if not path_matches:
return
for i, m in enumerate(path_matches):
raw_path = m.group(1)
path = _resolve_raw_file_edit_path(tool, self._workspace, raw_path)
if path is None:
continue
segment_start = m.start()
segment_end = path_matches[i + 1].start() if i + 1 < len(path_matches) else len(state.arguments)
segment = state.arguments[segment_start:segment_end]
action_match = re.search(r'"action"\s*:\s*"(replace|add)"', segment)
action = action_match.group(1) if action_match else "replace"
old_text = _extract_json_string_prefix(segment, "old_text") or ""
new_text = _extract_json_string_prefix(segment, "new_text") or ""
added = _text_line_count(new_text) if action in ("replace", "add") else 0
deleted = _text_line_count(old_text) if action == "replace" else 0
file_state = state.patch_files.get(raw_path)
if file_state is None:
tracker = FileEditTracker(
call_id=state.call_id or state.key,
tool="apply_patch",
path=path,
display_path=display_file_edit_path(path, self._workspace),
before=read_file_snapshot(path),
)
file_state = _StreamingPatchFileState(tracker=tracker)
state.patch_files[raw_path] = file_state
if not file_state.should_emit(added, deleted, now):
continue
file_state.mark_emitted(added, deleted, now)
events.append(build_file_edit_live_event(
file_state.tracker,
added=added,
deleted=deleted,
))
if events:
await self._emit(events)
async def flush(self) -> None:
events: list[dict[str, Any]] = []
now = time.monotonic()
for state in self._states.values():
for file_state in state.patch_files.values():
added, deleted = file_state.last_added, file_state.last_deleted
if not file_state.emitted_once:
continue
if (
file_state.last_emitted_added == added
and file_state.last_emitted_deleted == deleted
):
continue
file_state.mark_emitted(added, deleted, now)
events.append(build_file_edit_live_event(
file_state.tracker,
added=added,
deleted=deleted,
))
if state.tracker is None:
continue
added, deleted = state.live_diff_counts()
@@ -527,14 +367,12 @@ class StreamingFileEditTracker:
def apply_final_call_ids(self, final_tool_calls: list[Any]) -> None:
"""Keep final start/end events keyed to any earlier streamed placeholder."""
used_canonicals: set[str] = set()
for tool_call in final_tool_calls:
canonical = self.canonical_call_id_for(tool_call)
if canonical and canonical not in used_canonicals:
if canonical:
try:
tool_call.id = canonical
used_canonicals.add(canonical)
except (AttributeError, TypeError):
except Exception:
pass
def canonical_call_id_for(self, tool_call: Any) -> str | None:
@@ -551,10 +389,6 @@ class StreamingFileEditTracker:
"""Mark streamed edits as failed when no final tool call will run."""
events: list[dict[str, Any]] = []
for state in self._states.values():
for file_state in state.patch_files.values():
if any(state.matches_final_tool_call(tool_call) for tool_call in final_tool_calls):
continue
events.append(build_file_edit_error_event(file_state.tracker, error))
if state.tracker is None:
continue
if any(state.matches_final_tool_call(tool_call) for tool_call in final_tool_calls):
@@ -658,39 +492,6 @@ class _StreamingJsonStringField:
self.last_char_cr = False
@dataclass(slots=True)
class _StreamingPatchFileState:
tracker: FileEditTracker
emitted_once: bool = False
last_emitted_added: int = -1
last_emitted_deleted: int = -1
last_emit_at: float = 0.0
last_added: int = 0
last_deleted: int = 0
def should_emit(self, added: int, deleted: int, now: float) -> bool:
self.last_added = added
self.last_deleted = deleted
if not self.emitted_once:
return True
if added == self.last_emitted_added and deleted == self.last_emitted_deleted:
return False
if max(
abs(added - self.last_emitted_added),
abs(deleted - self.last_emitted_deleted),
) >= _LIVE_EMIT_LINE_STEP:
return True
return now - self.last_emit_at >= _LIVE_EMIT_INTERVAL_S
def mark_emitted(self, added: int, deleted: int, now: float) -> None:
self.emitted_once = True
self.last_added = added
self.last_deleted = deleted
self.last_emitted_added = added
self.last_emitted_deleted = deleted
self.last_emit_at = now
@dataclass(slots=True)
class _StreamingFileEditState:
key: str
@@ -708,7 +509,6 @@ class _StreamingFileEditState:
new_text: _StreamingJsonStringField = field(
default_factory=lambda: _StreamingJsonStringField("new_text")
)
patch_files: dict[str, _StreamingPatchFileState] = field(default_factory=dict)
emitted_once: bool = False
last_emitted_added: int = -1
last_emitted_deleted: int = -1
@@ -731,7 +531,6 @@ class _StreamingFileEditState:
self.content.reset()
self.old_text.reset()
self.new_text.reset()
self.patch_files.clear()
return
delta = payload.get("arguments_delta")
if isinstance(delta, str) and delta:
@@ -791,14 +590,6 @@ class _StreamingFileEditState:
name = getattr(tool_call, "name", None)
if name != self.name:
return False
if self.name == "apply_patch":
arguments = getattr(tool_call, "arguments", None)
if not isinstance(arguments, dict):
return False
edits = arguments.get("edits")
if not isinstance(edits, list):
return False
return '"edits"' in self.arguments
arguments = getattr(tool_call, "arguments", None)
if not isinstance(arguments, dict):
return False
@@ -821,51 +612,6 @@ def _stream_key(payload: dict[str, Any]) -> str:
return ""
def _json_bool_true(source: str, key: str) -> bool:
return re.search(rf'"{re.escape(key)}"\s*:\s*true\b', source) is not None
def _extract_json_string_prefix(source: str, key: str) -> str | None:
match = re.search(rf'"{re.escape(key)}"\s*:\s*"', source)
if match is None:
return None
out: list[str] = []
i = match.end()
escape = False
while i < len(source):
ch = source[i]
if escape:
escape = False
if ch == "n":
out.append("\n")
elif ch == "r":
out.append("\r")
elif ch == "t":
out.append("\t")
elif ch == "u":
digits = source[i + 1:i + 5]
if len(digits) < 4:
break
try:
out.append(chr(int(digits, 16)))
except ValueError:
break
i += 4
else:
out.append(ch)
i += 1
continue
if ch == "\\":
escape = True
i += 1
continue
if ch == '"':
return "".join(out)
out.append(ch)
i += 1
return "".join(out)
def _extract_complete_json_string(source: str, key: str) -> str | None:
match = re.search(rf'"{re.escape(key)}"\s*:\s*"', source)
if match is None:
@@ -916,7 +662,6 @@ def _event_payload(
deleted: int,
approximate: bool,
binary: bool = False,
operation: str | None = None,
) -> dict[str, Any]:
payload: dict[str, Any] = {
"version": 1,
@@ -932,8 +677,6 @@ def _event_payload(
}
if binary:
payload["binary"] = True
if operation:
payload["operation"] = operation
return payload
@@ -961,4 +704,77 @@ def _predict_after_text(
return before_text.replace(old_text, new_text)
return before_text.replace(old_text, new_text, 1)
return None
if tool_name == "notebook_edit":
return _predict_notebook_after_text(params, before_text)
return None
def _predict_notebook_after_text(params: dict[str, Any], before_text: str) -> str | None:
try:
nb = json.loads(before_text) if before_text.strip() else _empty_notebook()
except Exception:
return None
cells = nb.get("cells")
if not isinstance(cells, list):
return None
try:
cell_index = int(params.get("cell_index", 0))
except (TypeError, ValueError):
return None
new_source = params.get("new_source")
source = new_source if isinstance(new_source, str) else ""
cell_type = (
params.get("cell_type") if params.get("cell_type") in ("code", "markdown") else "code"
)
mode = (
params.get("edit_mode")
if params.get("edit_mode") in ("replace", "insert", "delete")
else "replace"
)
if mode == "delete":
if 0 <= cell_index < len(cells):
cells.pop(cell_index)
else:
return None
elif mode == "insert":
insert_at = min(max(cell_index + 1, 0), len(cells))
cells.insert(insert_at, _new_notebook_cell(source, str(cell_type)))
else:
if not (0 <= cell_index < len(cells)):
return None
cell = cells[cell_index]
if not isinstance(cell, dict):
return None
cell["source"] = source
cell["cell_type"] = cell_type
if cell_type == "code":
cell.setdefault("outputs", [])
cell.setdefault("execution_count", None)
else:
cell.pop("outputs", None)
cell.pop("execution_count", None)
nb["cells"] = cells
try:
return json.dumps(nb, indent=1, ensure_ascii=False)
except Exception:
return None
def _empty_notebook() -> dict[str, Any]:
return {
"nbformat": 4,
"nbformat_minor": 5,
"metadata": {
"kernelspec": {"display_name": "Python 3", "language": "python", "name": "python3"},
"language_info": {"name": "python"},
},
"cells": [],
}
def _new_notebook_cell(source: str, cell_type: str) -> dict[str, Any]:
cell: dict[str, Any] = {"cell_type": cell_type, "source": source, "metadata": {}}
if cell_type == "code":
cell["outputs"] = []
cell["execution_count"] = None
return cell
+75 -14
View File
@@ -171,6 +171,79 @@ def detect_image_mime(data: bytes) -> str | None:
return None
# Audio formats supported by OpenAI input_audio block
_AUDIO_MIME_COMPAT = {"audio/wav", "audio/mpeg", "audio/mp3", "audio/aac",
"audio/ogg", "audio/flac", "audio/x-m4a", "audio/mp4"}
# Map MIME types to the format token expected by OpenAI-compatible input_audio APIs.
_AUDIO_FORMAT_MAP: dict[str, str] = {
"audio/wav": "wav",
"audio/x-wav": "wav",
"audio/mpeg": "mp3",
"audio/mp3": "mp3",
"audio/aac": "aac",
"audio/ogg": "ogg",
"audio/flac": "flac",
"audio/x-m4a": "m4a",
"audio/mp4": "m4a",
}
def detect_audio_mime(data: bytes, filename: str = "") -> str | None:
"""Detect audio MIME type from magic bytes; fallback to filename guess."""
if data[:4] == b"RIFF" and data[8:12] == b"WAVE":
return "audio/wav"
if data[:2] in (b"\xff\xfb", b"\xff\xf3", b"\xff\xf2", b"\xff\xfa"):
return "audio/mpeg"
if data[:4] == b"fLaC":
return "audio/flac"
if data[:4] == b"OggS":
return "audio/ogg"
if len(data) > 8 and data[4:8] == b"ftyp":
# Only claim audio for M4A-specific brands; avoid matching MP4 video.
brand = data[8:12]
if brand in (b"M4A ", b"M4AB", b"M4AC"):
return "audio/x-m4a"
if filename:
import mimetypes as _mt
guessed = _mt.guess_type(filename)[0]
if guessed and guessed.startswith("audio/"):
return guessed
return None
def audio_mime_compat(mime: str | None) -> bool:
"""Check if the audio MIME is compatible with OpenAI input_audio block."""
if not mime:
return False
return mime in _AUDIO_MIME_COMPAT
def audio_format_for_api(mime: str) -> str:
"""Convert an audio MIME type to the format token expected by the API.
Falls back to the subtype portion of the MIME (e.g. "x-m4a" from
"audio/x-m4a") when no explicit mapping exists.
"""
if not mime:
return "wav"
return _AUDIO_FORMAT_MAP.get(mime, mime.split("/")[-1])
# Video formats commonly supported by LLM APIs (data URI inline)
_VIDEO_MIME_COMPAT = {
"video/mp4", "video/quicktime", "video/x-m4v",
"video/webm", "video/x-matroska",
}
def video_mime_compat(mime: str | None) -> bool:
"""Check if the video MIME is in the commonly-supported set."""
if not mime:
return False
return mime in _VIDEO_MIME_COMPAT
def build_image_content_blocks(
raw: bytes, mime: str, path: str, label: str
) -> list[dict[str, Any]]:
@@ -576,7 +649,7 @@ def build_status_content(
def sync_workspace_templates(workspace: Path, silent: bool = False) -> list[str]:
"""Sync bundled templates to workspace. Creates missing files without overwriting user files."""
"""Sync bundled templates to workspace. Only creates missing files."""
from importlib.resources import files as pkg_files
try:
@@ -589,11 +662,10 @@ def sync_workspace_templates(workspace: Path, silent: bool = False) -> list[str]
added: list[str] = []
def _write(src, dest: Path):
content = src.read_text(encoding="utf-8") if src else ""
if dest.exists():
return
dest.parent.mkdir(parents=True, exist_ok=True)
dest.write_text(content, encoding="utf-8")
dest.write_text(src.read_text(encoding="utf-8") if src else "", encoding="utf-8")
added.append(str(dest.relative_to(workspace)))
for item in tpl.iterdir():
@@ -626,14 +698,3 @@ def sync_workspace_templates(workspace: Path, silent: bool = False) -> list[str]
logger.exception("Failed to initialize git store for {}", workspace)
return added
def load_bundled_template(template_name: str) -> str | None:
"""Read a bundled template file from the nanobot package."""
from importlib.resources import files as pkg_files
with suppress(Exception):
tpl = pkg_files("nanobot") / "templates" / template_name
if tpl.is_file():
return tpl.read_text(encoding="utf-8")
return None
-10
View File
@@ -29,11 +29,6 @@ LENGTH_RECOVERY_PROMPT = (
"— no recap, no apology. Break remaining work into smaller steps if needed."
)
SUSTAINED_GOAL_CONTINUE_PROMPT = (
"You have an active sustained goal. Please continue working toward the "
"objective using your tools, or call complete_goal if the work is truly finished."
)
def empty_tool_result_message(tool_name: str) -> str:
"""Short prompt-safe marker for tools that completed without visible output."""
@@ -70,11 +65,6 @@ def build_length_recovery_message() -> dict[str, str]:
return {"role": "user", "content": LENGTH_RECOVERY_PROMPT}
def build_goal_continue_message(custom: str | None = None) -> dict[str, str]:
"""Prompt the model to continue when a sustained goal is still active."""
return {"role": "user", "content": custom or SUSTAINED_GOAL_CONTINUE_PROMPT}
def external_lookup_signature(tool_name: str, arguments: dict[str, Any]) -> str | None:
"""Stable signature for repeated external lookups we want to throttle."""
if tool_name == "web_fetch":
-4
View File
@@ -11,10 +11,8 @@ _TOOL_FORMATS: dict[str, tuple[list[str], str, bool, bool]] = {
"read_file": (["path", "file_path"], "read {}", True, False),
"write_file": (["path", "file_path"], "write {}", True, False),
"edit": (["file_path", "path"], "edit {}", True, False),
"find_files": (["query", "glob", "path"], "find {}", False, False),
"grep": (["pattern"], 'grep "{}"', False, False),
"exec": (["command"], "$ {}", False, True),
"list_exec_sessions": ([], "exec sessions", False, False),
"web_search": (["query"], 'search "{}"', False, False),
"web_fetch": (["url"], "fetch {}", True, False),
"list_dir": (["path"], "ls {}", True, False),
@@ -83,8 +81,6 @@ def _extract_arg(tc, key_args: list[str]) -> str | None:
def _fmt_known(tc, fmt: tuple, max_length: int = 40) -> str:
"""Format a registered tool using its template."""
if not fmt[0] and "{}" not in fmt[1]:
return fmt[1]
val = _extract_arg(tc, fmt[0])
if val is None:
return tc.name
-93
View File
@@ -1,93 +0,0 @@
"""CLI Apps helpers for the WebUI HTTP and message surfaces."""
from __future__ import annotations
import re
from typing import Any
from nanobot.apps.cli import CliAppError, CliAppManager, CliAppsRuntimeConfig
from nanobot.config.loader import load_config
QueryParams = dict[str, list[str]]
_CLI_APP_NAME_RE = re.compile(r"^[a-z0-9][a-z0-9_-]{0,63}$", re.IGNORECASE)
_CLI_APP_ATTACHMENT_KEYS = (
"name",
"display_name",
"category",
"entry_point",
"logo_url",
"brand_color",
)
def _clip_ws_string(value: Any, limit: int = 240) -> str | None:
if not isinstance(value, str):
return None
text = value.strip()
if not text:
return None
return text[:limit]
def normalize_cli_app_mentions(raw: Any) -> list[dict[str, str]]:
"""Sanitize structured CLI app mentions sent by the WebUI."""
if not isinstance(raw, list):
return []
out: list[dict[str, str]] = []
seen: set[str] = set()
for item in raw[:8]:
if not isinstance(item, dict):
continue
name = _clip_ws_string(item.get("name"), 64)
if not name or _CLI_APP_NAME_RE.match(name) is None:
continue
key = name.lower()
if key in seen:
continue
seen.add(key)
row: dict[str, str] = {"name": key}
for field in _CLI_APP_ATTACHMENT_KEYS[1:]:
value = _clip_ws_string(item.get(field), 512 if field == "logo_url" else 160)
if value:
row[field] = value
out.append(row)
return out
def _query_first(query: QueryParams, key: str) -> str | None:
values = query.get(key)
return values[0] if values else None
def _manager() -> CliAppManager:
config = load_config()
cli_cfg = config.tools.cli_apps
return CliAppManager(
workspace=config.workspace_path,
runtime=CliAppsRuntimeConfig(
install_timeout=cli_cfg.install_timeout,
run_timeout=cli_cfg.run_timeout,
catalog_ttl_seconds=cli_cfg.catalog_ttl_seconds,
),
)
def cli_apps_payload() -> dict[str, Any]:
return _manager().payload()
def cli_apps_action(action: str, query: QueryParams) -> dict[str, Any]:
name = (_query_first(query, "name") or "").strip()
if not name:
raise CliAppError("missing CLI app name")
manager = _manager()
if action == "install":
return manager.install(name)
if action == "update":
return manager.update(name)
if action == "uninstall":
return manager.uninstall(name)
if action == "test":
return manager.test(name)
raise CliAppError(f"unknown CLI app action '{action}'", status=404)
File diff suppressed because it is too large Load Diff
-5
View File
@@ -1,5 +0,0 @@
"""Compatibility exports for WebUI-attached MCP preset annotations."""
from nanobot.agent.tools.mcp import runtime_lines, session_extra
__all__ = ["runtime_lines", "session_extra"]
-255
View File
@@ -1,255 +0,0 @@
"""Signed media helpers for the WebUI HTTP surface."""
from __future__ import annotations
import base64
import binascii
import email.utils
import hashlib
import hmac
import http
import mimetypes
import re
import shutil
import uuid
from collections.abc import Callable
from pathlib import Path
from typing import Any
from websockets.datastructures import Headers
from websockets.http11 import Request as WsRequest
from websockets.http11 import Response
from nanobot.config.paths import get_media_dir
from nanobot.utils.helpers import safe_filename
MediaDirProvider = Callable[[str | None], Path]
def b64url_encode(data: bytes) -> str:
"""URL-safe base64 without padding."""
return base64.urlsafe_b64encode(data).rstrip(b"=").decode("ascii")
def b64url_decode(value: str) -> bytes:
"""Reverse of :func:`b64url_encode`; caller handles decode errors."""
pad = "=" * (-len(value) % 4)
return base64.urlsafe_b64decode(value + pad)
def _default_media_dir(channel: str | None = None) -> Path:
return get_media_dir(channel)
# Allowed MIME types we actually serve from the media endpoint. Anything
# outside this set is degraded to ``application/octet-stream`` so an
# attacker who somehow gets a signed URL for an unexpected file type can't
# trick the browser into sniffing executable content.
_MEDIA_ALLOWED_MIMES: frozenset[str] = frozenset({
"image/png",
"image/jpeg",
"image/webp",
"image/gif",
"image/svg+xml",
"video/mp4",
"video/webm",
"video/quicktime",
})
_SVG_MEDIA_HEADERS: tuple[tuple[str, str], ...] = (
(
"Content-Security-Policy",
"default-src 'none'; img-src 'self' data:; style-src 'unsafe-inline'; sandbox",
),
)
_BYTE_RANGE_RE = re.compile(r"^bytes=(\d*)-(\d*)$")
def _http_response(
body: bytes,
*,
status: int = 200,
content_type: str = "text/plain; charset=utf-8",
extra_headers: list[tuple[str, str]] | None = None,
) -> Response:
headers = [
("Date", email.utils.formatdate(usegmt=True)),
("Connection", "close"),
("Content-Length", str(len(body))),
("Content-Type", content_type),
]
if extra_headers:
headers.extend(extra_headers)
reason = http.HTTPStatus(status).phrase
return Response(status, reason, Headers(headers), body)
def _http_error(status: int, message: str | None = None) -> Response:
body = (message or http.HTTPStatus(status).phrase).encode("utf-8")
return _http_response(body, status=status)
def _case_insensitive_header(headers: Any, key: str) -> str:
try:
value = headers.get(key)
except Exception:
value = None
if value is None:
try:
value = headers.get(key.lower())
except Exception:
value = None
return str(value or "").strip()
def _parse_single_byte_range(range_header: str, size: int) -> tuple[int, int]:
"""Parse a single HTTP byte range for signed media responses."""
if size <= 0 or "," in range_header:
raise ValueError("invalid byte range")
m = _BYTE_RANGE_RE.fullmatch(range_header.strip())
if m is None:
raise ValueError("invalid byte range")
start_text, end_text = m.groups()
if not start_text and not end_text:
raise ValueError("invalid byte range")
if not start_text:
suffix_length = int(end_text)
if suffix_length <= 0:
raise ValueError("invalid byte range")
start = max(size - suffix_length, 0)
end = size - 1
else:
start = int(start_text)
end = int(end_text) if end_text else size - 1
if start >= size or start > end:
raise ValueError("invalid byte range")
end = min(end, size - 1)
return start, end
def sign_media_path(
abs_path: Path,
*,
secret: bytes,
media_dir: MediaDirProvider = _default_media_dir,
) -> str | None:
"""Return a signed ``/api/media/<sig>/<payload>`` URL for a media-root path."""
try:
media_root = media_dir(None).resolve()
rel = abs_path.resolve().relative_to(media_root)
except (OSError, ValueError):
return None
payload = b64url_encode(rel.as_posix().encode("utf-8"))
mac = hmac.new(secret, payload.encode("ascii"), hashlib.sha256).digest()[:16]
return f"/api/media/{b64url_encode(mac)}/{payload}"
def sign_or_stage_media_path(
path: Path,
*,
secret: bytes,
media_dir: MediaDirProvider = _default_media_dir,
logger: Any | None = None,
) -> dict[str, str] | None:
"""Sign an existing media-root path, or stage an arbitrary file before signing."""
signed = sign_media_path(path, secret=secret, media_dir=media_dir)
if signed is not None:
return {"url": signed, "name": path.name}
try:
if not path.is_file():
return None
target_dir = media_dir("websocket")
safe_name = safe_filename(path.name) or "attachment"
staged = target_dir / f"{uuid.uuid4().hex[:12]}-{safe_name}"
shutil.copyfile(path, staged)
except OSError as exc:
if logger is not None:
logger.warning("failed to stage outbound media {}: {}", path, exc)
return None
signed = sign_media_path(staged, secret=secret, media_dir=media_dir)
if signed is None:
return None
return {"url": signed, "name": path.name}
def serve_signed_media(
sig: str,
payload: str,
*,
secret: bytes,
request: WsRequest | None = None,
media_dir: MediaDirProvider = _default_media_dir,
) -> Response:
"""Serve a signed media URL, including browser-friendly byte ranges."""
try:
provided_mac = b64url_decode(sig)
except (ValueError, binascii.Error):
return _http_error(401, "invalid signature")
expected_mac = hmac.new(secret, payload.encode("ascii"), hashlib.sha256).digest()[:16]
if not hmac.compare_digest(expected_mac, provided_mac):
return _http_error(401, "invalid signature")
try:
rel_bytes = b64url_decode(payload)
rel_str = rel_bytes.decode("utf-8")
except (ValueError, binascii.Error, UnicodeDecodeError):
return _http_error(400, "invalid payload")
try:
media_root = media_dir(None).resolve()
candidate = (media_root / rel_str).resolve()
candidate.relative_to(media_root)
except (OSError, ValueError):
return _http_error(404, "not found")
if not candidate.is_file():
return _http_error(404, "not found")
mime, _ = mimetypes.guess_type(candidate.name)
if mime not in _MEDIA_ALLOWED_MIMES:
mime = "application/octet-stream"
common_headers = [
("Accept-Ranges", "bytes"),
("Cache-Control", "private, max-age=31536000, immutable"),
("X-Content-Type-Options", "nosniff"),
]
if mime == "image/svg+xml":
common_headers.extend(_SVG_MEDIA_HEADERS)
try:
size = candidate.stat().st_size
except OSError:
return _http_error(500, "read error")
range_header = _case_insensitive_header(request.headers, "Range") if request else ""
if range_header:
try:
start, end = _parse_single_byte_range(range_header, size)
except ValueError:
return _http_response(
b"range not satisfiable",
status=416,
extra_headers=[
("Accept-Ranges", "bytes"),
("Content-Range", f"bytes */{size}"),
("X-Content-Type-Options", "nosniff"),
],
)
try:
length = end - start + 1
with candidate.open("rb") as fh:
fh.seek(start)
body = fh.read(length)
except OSError:
return _http_error(500, "read error")
return _http_response(
body,
status=206,
content_type=mime,
extra_headers=[
*common_headers,
("Content-Range", f"bytes {start}-{end}/{size}"),
],
)
try:
body = candidate.read_bytes()
except OSError:
return _http_error(500, "read error")
return _http_response(body, content_type=mime, extra_headers=common_headers)
+25 -721
View File
@@ -6,64 +6,17 @@ settings payload shape and the allowlisted config mutations exposed to WebUI.
from __future__ import annotations
import os
import re
import time
from contextlib import suppress
from typing import Any, Literal
from typing import Any
from zoneinfo import ZoneInfo
import httpx
from nanobot.config.loader import get_config_path, load_config, save_config
from nanobot.config.schema import ModelPresetConfig
from nanobot.providers.image_generation import (
get_image_gen_provider,
image_gen_provider_names,
)
from nanobot.providers.registry import PROVIDERS, find_by_name
from nanobot.security.workspace_access import workspace_sandbox_status
from nanobot.webui.workspaces import (
read_webui_default_access_mode,
write_webui_default_access_mode,
)
QueryParams = dict[str, list[str]]
RuntimeSurface = Literal["browser", "native"]
_RUNTIME_CAPABILITIES = {
"can_restart_engine": False,
"can_pick_folder": False,
"can_open_logs": False,
"can_export_diagnostics": False,
}
_NATIVE_RUNTIME_CAPABILITIES = {
**_RUNTIME_CAPABILITIES,
"can_restart_engine": True,
"can_pick_folder": True,
"can_open_logs": True,
"can_export_diagnostics": True,
}
_BROWSER_RESTART_BEHAVIOR_BY_SECTION = {
"appearance": "none",
"models": "none",
"providers": "none",
"runtime": "engineRestart",
"browser": "engineRestart",
"image": "engineRestart",
"apps": "engineRestart",
"advanced": "appRestart",
}
_NATIVE_RESTART_BEHAVIOR_BY_SECTION = {
**_BROWSER_RESTART_BEHAVIOR_BY_SECTION,
"runtime": "engineRestart",
"browser": "engineRestart",
"image": "engineRestart",
"apps": "engineRestart",
}
_WEB_SEARCH_PROVIDER_OPTIONS: tuple[dict[str, str], ...] = (
{"name": "duckduckgo", "label": "DuckDuckGo", "credential": "none"},
@@ -88,49 +41,6 @@ _IMAGE_GENERATION_ASPECT_RATIOS = {
"2:3",
"21:9",
}
_CONTEXT_WINDOW_TOKEN_OPTIONS = {65_536, 262_144}
_MODEL_CONFIGURATION_SLUG_RE = re.compile(r"[^a-z0-9_-]+")
_ENV_REF_RE = re.compile(r"\$\{([A-Za-z_][A-Za-z0-9_]*)\}")
_MODEL_LIST_UNSUPPORTED_BACKENDS = {
"anthropic",
"azure_openai",
"bedrock",
"github_copilot",
"openai_codex",
}
_MODEL_LIST_CATALOG_PROVIDERS = {
"aihubmix",
"byteplus",
"byteplus_coding_plan",
"huggingface",
"novita",
"openrouter",
"siliconflow",
"volcengine",
"volcengine_coding_plan",
}
_MODEL_LIST_OFFICIAL_PROVIDERS = {
"ant_ling",
"dashscope",
"deepseek",
"gemini",
"groq",
"longcat",
"minimax",
"minimax_anthropic",
"mistral",
"moonshot",
"nvidia",
"openai",
"qianfan",
"skywork",
"stepfun",
"xiaomi_mimo",
"zhipu",
}
class WebUISettingsError(ValueError):
@@ -142,70 +52,6 @@ class WebUISettingsError(ValueError):
self.status = status
def _normalize_surface(surface: str | None) -> RuntimeSurface:
return "native" if surface in {"native", "desktop"} else "browser"
def runtime_capabilities(
surface: str | None = "browser",
overrides: dict[str, Any] | None = None,
) -> dict[str, bool]:
"""Return the capability flags exposed to the WebUI runtime."""
base = (
_NATIVE_RUNTIME_CAPABILITIES
if _normalize_surface(surface) == "native"
else _RUNTIME_CAPABILITIES
)
result = dict(base)
for key, value in (overrides or {}).items():
if key in result:
result[key] = bool(value)
return result
def restart_behavior_by_section(surface: str | None = "browser") -> dict[str, str]:
return dict(
_NATIVE_RESTART_BEHAVIOR_BY_SECTION
if _normalize_surface(surface) == "native"
else _BROWSER_RESTART_BEHAVIOR_BY_SECTION
)
def decorate_settings_payload(
payload: dict[str, Any],
*,
surface: str | None = "browser",
runtime_capability_overrides: dict[str, Any] | None = None,
restart_required_sections: list[str] | None = None,
apply_state: dict[str, Any] | None = None,
) -> dict[str, Any]:
"""Attach runtime-surface metadata without changing the core settings shape."""
surface_value = _normalize_surface(surface)
sections = restart_required_sections
if sections is None:
raw_sections = payload.get("restart_required_sections") or []
sections = [str(section) for section in raw_sections if isinstance(section, str)]
sections = sorted(dict.fromkeys(sections))
result = dict(payload)
result["surface"] = surface_value
result["runtime_surface"] = surface_value
result["runtime_capabilities"] = runtime_capabilities(
surface_value,
runtime_capability_overrides,
)
result["restart_behavior_by_section"] = restart_behavior_by_section(surface_value)
result["restart_required_sections"] = sections
if sections:
result["requires_restart"] = True
else:
result["requires_restart"] = bool(result.get("requires_restart", False))
result["apply_state"] = apply_state or {
"status": "pending" if result["requires_restart"] else "idle",
"sections": sections,
}
return result
def _query_first(query: QueryParams, key: str) -> str | None:
values = query.get(key)
return values[0] if values else None
@@ -224,86 +70,15 @@ def _mask_secret_hint(secret: str | None) -> str | None:
return f"{secret[:4]}••••{secret[-4:]}"
def _resolve_env_placeholders(value: str | None) -> str | None:
if not value:
return None
missing = False
def replace(match: re.Match[str]) -> str:
nonlocal missing
env_value = os.environ.get(match.group(1))
if env_value is None:
missing = True
return ""
return env_value
resolved = _ENV_REF_RE.sub(replace, value).strip()
if missing and not resolved:
return None
return resolved or None
def _provider_requires_api_key(spec: Any) -> bool:
if spec.backend == "azure_openai":
return True
if spec.is_oauth:
return False
if spec.is_local or spec.is_direct:
return False
return True
def _oauth_provider_status(spec: Any) -> dict[str, Any]:
if not getattr(spec, "is_oauth", False):
return {"configured": False, "account": None, "expires_at": None, "login_supported": False}
if spec.name == "openai_codex":
try:
from oauth_cli_kit import get_token as get_codex_token
except Exception:
return {
"configured": False,
"account": None,
"expires_at": None,
"login_supported": False,
}
token = None
with suppress(Exception):
token = get_codex_token()
expires_at = getattr(token, "expires", None) if token else None
return {
"configured": bool(token and token.access),
"account": getattr(token, "account_id", None) if token else None,
"expires_at": expires_at,
"login_supported": True,
}
if spec.name == "github_copilot":
try:
from nanobot.providers.github_copilot_provider import get_github_copilot_login_status
except Exception:
return {
"configured": False,
"account": None,
"expires_at": None,
"login_supported": False,
}
token = None
with suppress(Exception):
token = get_github_copilot_login_status()
return {
"configured": bool(token and token.access and token.expires > int(time.time() * 1000)),
"account": getattr(token, "account_id", None) if token else None,
"expires_at": getattr(token, "expires", None) if token else None,
"login_supported": True,
}
return {"configured": False, "account": None, "expires_at": None, "login_supported": False}
def _provider_configured_for_settings(spec: Any, provider_config: Any) -> bool:
if spec.is_oauth:
return bool(_oauth_provider_status(spec)["configured"])
if _provider_requires_api_key(spec):
return bool(provider_config.api_key)
return bool(
@@ -314,191 +89,6 @@ def _provider_configured_for_settings(spec: Any, provider_config: Any) -> bool:
)
def _model_catalog_kind(spec: Any) -> str:
if spec.name in _MODEL_LIST_CATALOG_PROVIDERS:
return "catalog"
if spec.name in _MODEL_LIST_OFFICIAL_PROVIDERS:
return "official"
if spec.is_local:
return "local"
if spec.is_direct:
return "custom"
if spec.is_gateway:
return "catalog"
return "official"
def _model_id_from_row(row: Any) -> str | None:
if isinstance(row, str):
return row.strip() or None
if not isinstance(row, dict):
return None
for key in ("id", "name", "model"):
value = row.get(key)
if isinstance(value, str) and value.strip():
return value.strip()
return None
def _model_context_window(row: Any) -> int | None:
if not isinstance(row, dict):
return None
for key in (
"context_window",
"context_length",
"max_context_length",
"max_model_len",
"max_input_tokens",
):
value = row.get(key)
if isinstance(value, int) and value > 0:
return value
if isinstance(value, float) and value > 0:
return int(value)
return None
def _model_row_payload(row: Any) -> dict[str, Any] | None:
model_id = _model_id_from_row(row)
if not model_id:
return None
label: str | None = None
owned_by: str | None = None
if isinstance(row, dict):
raw_label = row.get("display_name") or row.get("label") or row.get("name")
if isinstance(raw_label, str) and raw_label.strip() and raw_label.strip() != model_id:
label = raw_label.strip()
raw_owner = row.get("owned_by") or row.get("owner") or row.get("organization")
if isinstance(raw_owner, str) and raw_owner.strip():
owned_by = raw_owner.strip()
return {
"id": model_id,
"label": label,
"owned_by": owned_by,
"context_window": _model_context_window(row),
}
def _extract_model_rows(body: Any) -> list[dict[str, Any]]:
raw_rows = body.get("data") if isinstance(body, dict) else body
if not isinstance(raw_rows, list):
return []
rows: list[dict[str, Any]] = []
seen: set[str] = set()
for raw_row in raw_rows:
row = _model_row_payload(raw_row)
if row is None or row["id"] in seen:
continue
seen.add(row["id"])
rows.append(row)
return rows
def provider_models_payload(query: QueryParams) -> dict[str, Any]:
"""Fetch an OpenAI-compatible provider's model list for Settings.
The result is advisory only: users can always type a custom model id. This
helper deliberately avoids mutating config so probing model lists never
changes runtime behavior.
"""
provider_name = (_query_first(query, "provider") or "").strip()
if not provider_name:
raise WebUISettingsError("provider is required")
spec = find_by_name(provider_name)
if spec is None:
raise WebUISettingsError("unknown provider")
base_payload: dict[str, Any] = {
"provider": spec.name,
"label": spec.label,
"catalog_kind": _model_catalog_kind(spec),
"models": [],
"model_count": 0,
"message": None,
"fetched_at": time.time(),
}
if (
spec.backend in _MODEL_LIST_UNSUPPORTED_BACKENDS
and spec.name != "minimax_anthropic"
) or spec.is_oauth:
return {
**base_payload,
"status": "unsupported",
"catalog_kind": "unsupported",
"message": "Model list is not available for this provider. Type a model ID manually.",
}
config = load_config()
provider_config = getattr(config.providers, spec.name, None)
if provider_config is None:
raise WebUISettingsError("unknown provider")
api_base = _resolve_env_placeholders(provider_config.api_base) or spec.default_api_base
if spec.name == "openai" and not api_base:
api_base = "https://api.openai.com/v1"
if not api_base:
return {
**base_payload,
"status": "missing_api_base",
"message": "Configure an API base URL to load models.",
}
api_key = _resolve_env_placeholders(provider_config.api_key)
if _provider_requires_api_key(spec) and not api_key:
return {
**base_payload,
"status": "not_configured",
"message": "Configure this provider before loading models.",
}
headers = {"Accept": "application/json"}
if api_key:
if spec.name == "minimax_anthropic":
headers["X-Api-Key"] = api_key
else:
headers["Authorization"] = f"Bearer {api_key}"
models_url = f"{api_base.rstrip('/')}/models"
if spec.name == "minimax_anthropic" and not api_base.rstrip("/").endswith("/v1"):
models_url = f"{api_base.rstrip('/')}/v1/models"
try:
response = httpx.get(
models_url,
headers=headers,
timeout=10.0,
follow_redirects=False,
)
response.raise_for_status()
rows = _extract_model_rows(response.json())
except httpx.HTTPStatusError as exc:
status = exc.response.status_code
if status in {401, 403}:
return {
**base_payload,
"status": "not_configured",
"message": "The provider rejected the configured credential.",
}
return {
**base_payload,
"status": "error",
"message": f"Model list request failed with HTTP {status}.",
}
except (httpx.HTTPError, ValueError) as exc:
return {
**base_payload,
"status": "error",
"message": f"Could not load models: {exc}",
}
return {
**base_payload,
"status": "available",
"models": rows,
"model_count": len(rows),
}
def _parse_bool(value: str, field: str) -> bool:
normalized = value.strip().lower()
if normalized not in {"1", "0", "true", "false", "yes", "no"}:
@@ -506,44 +96,6 @@ def _parse_bool(value: str, field: str) -> bool:
return normalized in {"1", "true", "yes"}
def _parse_context_window_tokens(value: str | None) -> int | None:
if value is None:
return None
try:
parsed = int(value)
except ValueError:
raise WebUISettingsError("context_window_tokens must be an integer") from None
if parsed not in _CONTEXT_WINDOW_TOKEN_OPTIONS:
raise WebUISettingsError("context_window_tokens must be 65536 or 262144")
return parsed
def _model_configuration_slug(label: str) -> str:
normalized = _MODEL_CONFIGURATION_SLUG_RE.sub("-", label.strip().lower())
normalized = normalized.strip("-_")
if not normalized:
raise WebUISettingsError("configuration name is required")
if normalized == "default":
raise WebUISettingsError("configuration name is reserved")
if len(normalized) > 48:
normalized = normalized[:48].rstrip("-_")
return normalized
def _validate_configured_provider(config: Any, provider: str) -> None:
if provider == "auto":
return
spec = find_by_name(provider)
if spec is None:
raise WebUISettingsError("unknown provider")
provider_config = getattr(config.providers, provider, None)
if (
provider_config is None
or not _provider_configured_for_settings(spec, provider_config)
):
raise WebUISettingsError("provider is not configured")
def _image_generation_provider_rows(config: Any) -> list[dict[str, Any]]:
rows: list[dict[str, Any]] = []
for name in image_gen_provider_names():
@@ -559,7 +111,6 @@ def _image_generation_provider_rows(config: Any) -> list[dict[str, Any]]:
"name": name,
"label": spec.label if spec is not None else name,
"configured": configured,
"auth_type": "oauth" if spec is not None and spec.is_oauth else "api_key",
"api_key_hint": _mask_secret_hint(
getattr(provider_config, "api_key", None)
),
@@ -572,14 +123,7 @@ def _image_generation_provider_rows(config: Any) -> list[dict[str, Any]]:
return rows
def settings_payload(
*,
requires_restart: bool = False,
surface: str | None = "browser",
runtime_capability_overrides: dict[str, Any] | None = None,
restart_required_sections: list[str] | None = None,
apply_state: dict[str, Any] | None = None,
) -> dict[str, Any]:
def settings_payload(*, requires_restart: bool = False) -> dict[str, Any]:
config = load_config()
defaults = config.agents.defaults
active_preset_name = defaults.model_preset or "default"
@@ -602,30 +146,19 @@ def settings_payload(
providers = []
for spec in PROVIDERS:
provider_config = getattr(config.providers, spec.name, None)
if provider_config is None:
if provider_config is None or spec.is_oauth:
continue
oauth_status = _oauth_provider_status(spec) if spec.is_oauth else None
row = {
"name": spec.name,
"label": spec.label,
"configured": (
bool(oauth_status["configured"])
if oauth_status is not None
else _provider_configured_for_settings(spec, provider_config)
),
"auth_type": "oauth" if spec.is_oauth else "api_key",
"api_key_required": _provider_requires_api_key(spec),
"api_key_hint": _mask_secret_hint(provider_config.api_key),
"api_base": provider_config.api_base,
"default_api_base": spec.default_api_base or None,
}
if oauth_status is not None:
row["oauth_account"] = oauth_status["account"]
row["oauth_expires_at"] = oauth_status["expires_at"]
row["oauth_login_supported"] = oauth_status["login_supported"]
if spec.name == "openai":
row["api_type"] = provider_config.api_type
providers.append(row)
providers.append(
{
"name": spec.name,
"label": spec.label,
"configured": _provider_configured_for_settings(spec, provider_config),
"api_key_required": _provider_requires_api_key(spec),
"api_key_hint": _mask_secret_hint(provider_config.api_key),
"api_base": provider_config.api_base,
"default_api_base": spec.default_api_base or None,
}
)
search_config = config.tools.web.search
image_config = config.tools.image_generation
@@ -661,7 +194,7 @@ def settings_payload(
model_presets.append(
{
"name": name,
"label": preset.label or name,
"label": name,
"active": active_preset_name == name,
"is_default": False,
"model": preset.model,
@@ -674,11 +207,7 @@ def settings_payload(
)
exec_config = config.tools.exec
sandbox_status = workspace_sandbox_status(
restrict_to_workspace=config.tools.restrict_to_workspace,
workspace=config.workspace_path,
)
payload = {
return {
"agent": {
"model": effective_preset.model,
"provider": selected_provider,
@@ -749,11 +278,6 @@ def settings_payload(
},
"advanced": {
"restrict_to_workspace": config.tools.restrict_to_workspace,
"workspace_sandbox": sandbox_status.as_dict(),
"webui_allow_local_service_access": config.tools.webui_allow_local_service_access,
"allow_local_preview_access": config.tools.webui_allow_local_service_access,
"webui_default_access_mode": read_webui_default_access_mode(),
"private_service_protection_enabled": True,
"ssrf_whitelist_count": len(config.tools.ssrf_whitelist),
"mcp_server_count": len(config.tools.mcp_servers),
"exec_enabled": exec_config.enable,
@@ -762,13 +286,6 @@ def settings_payload(
},
"requires_restart": requires_restart,
}
return decorate_settings_payload(
payload,
surface=surface,
runtime_capability_overrides=runtime_capability_overrides,
restart_required_sections=restart_required_sections,
apply_state=apply_state,
)
def update_agent_settings(query: QueryParams) -> dict[str, Any]:
@@ -800,21 +317,19 @@ def update_agent_settings(query: QueryParams) -> dict[str, Any]:
provider = provider.strip()
if not provider:
raise WebUISettingsError("provider is required")
_validate_configured_provider(config, provider)
spec = find_by_name(provider)
if spec is None:
raise WebUISettingsError("unknown provider")
provider_config = getattr(config.providers, provider, None)
if (
provider_config is None
or not _provider_configured_for_settings(spec, provider_config)
):
raise WebUISettingsError("provider is not configured")
if defaults.provider != provider:
defaults.provider = provider
changed = True
context_window_tokens = _parse_context_window_tokens(
_query_first_alias(query, "context_window_tokens", "contextWindowTokens")
)
if (
context_window_tokens is not None
and defaults.context_window_tokens != context_window_tokens
):
defaults.context_window_tokens = context_window_tokens
changed = True
timezone = _query_first(query, "timezone")
if timezone is not None:
timezone = timezone.strip()
@@ -869,98 +384,6 @@ def update_agent_settings(query: QueryParams) -> dict[str, Any]:
return settings_payload(requires_restart=restart_required)
def create_model_configuration(query: QueryParams) -> dict[str, Any]:
label = (_query_first_alias(query, "label", "displayName") or "").strip()
raw_name = (_query_first(query, "name") or label).strip()
model = (_query_first(query, "model") or "").strip()
provider = (_query_first(query, "provider") or "").strip()
if not label:
label = raw_name
if not model:
raise WebUISettingsError("model is required")
if not provider:
raise WebUISettingsError("provider is required")
name = _model_configuration_slug(raw_name or label)
config = load_config()
if name in config.model_presets:
raise WebUISettingsError("configuration already exists", status=409)
_validate_configured_provider(config, provider)
base = config.resolve_default_preset()
config.model_presets[name] = ModelPresetConfig(
label=label,
model=model,
provider=provider,
max_tokens=base.max_tokens,
context_window_tokens=base.context_window_tokens,
temperature=base.temperature,
reasoning_effort=base.reasoning_effort,
)
config.agents.defaults.model_preset = name
save_config(config)
return settings_payload()
def update_model_configuration(query: QueryParams) -> dict[str, Any]:
name = (_query_first(query, "name") or "").strip()
if not name or name == "default":
raise WebUISettingsError("model configuration is required")
config = load_config()
preset = config.model_presets.get(name)
if preset is None:
raise WebUISettingsError("unknown model configuration")
changed = False
label = _query_first_alias(query, "label", "displayName")
if label is not None:
label = label.strip()
if not label:
raise WebUISettingsError("label is required")
if preset.label != label:
preset.label = label
changed = True
model = _query_first(query, "model")
if model is not None:
model = model.strip()
if not model:
raise WebUISettingsError("model is required")
if preset.model != model:
preset.model = model
changed = True
provider = _query_first(query, "provider")
if provider is not None:
provider = provider.strip()
if not provider:
raise WebUISettingsError("provider is required")
_validate_configured_provider(config, provider)
if preset.provider != provider:
preset.provider = provider
changed = True
context_window_tokens = _parse_context_window_tokens(
_query_first_alias(query, "context_window_tokens", "contextWindowTokens")
)
if (
context_window_tokens is not None
and preset.context_window_tokens != context_window_tokens
):
preset.context_window_tokens = context_window_tokens
changed = True
if config.agents.defaults.model_preset != name:
config.agents.defaults.model_preset = name
changed = True
if changed:
save_config(config)
return settings_payload()
def update_provider_settings(query: QueryParams) -> dict[str, Any]:
provider_name = (_query_first(query, "provider") or "").strip()
if not provider_name:
@@ -989,17 +412,6 @@ def update_provider_settings(query: QueryParams) -> dict[str, Any]:
provider_config.api_base = api_base
changed = True
if "api_type" in query:
if spec.name == "openai":
api_type = (_query_first(query, "api_type") or "").strip()
try:
parsed_api_type = type(provider_config)(api_type=api_type).api_type
except Exception:
raise WebUISettingsError("api_type must be auto, chat_completions, or responses") from None
if provider_config.api_type != parsed_api_type:
provider_config.api_type = parsed_api_type
changed = True
if changed:
save_config(config)
image_config = config.tools.image_generation
@@ -1012,114 +424,6 @@ def update_provider_settings(query: QueryParams) -> dict[str, Any]:
return settings_payload(requires_restart=restart_required)
def login_oauth_provider(query: QueryParams) -> dict[str, Any]:
provider_name = (_query_first(query, "provider") or "").strip()
if not provider_name:
raise WebUISettingsError("provider is required")
spec = find_by_name(provider_name)
if spec is None or not spec.is_oauth:
raise WebUISettingsError("unknown OAuth provider")
if spec.name == "openai_codex":
try:
from oauth_cli_kit import get_token, login_oauth_interactive
except ImportError:
raise WebUISettingsError("oauth_cli_kit is not installed", status=500) from None
token = None
with suppress(Exception):
token = get_token()
if not (token and token.access):
messages: list[str] = []
token = login_oauth_interactive(
print_fn=lambda message: messages.append(str(message)),
prompt_fn=lambda _prompt: "",
)
if not (token and token.access):
raise WebUISettingsError("OAuth login failed", status=401)
return settings_payload()
if spec.name == "github_copilot":
try:
from nanobot.providers.github_copilot_provider import (
get_github_copilot_login_status,
login_github_copilot,
)
except ImportError:
raise WebUISettingsError("GitHub Copilot OAuth support is unavailable", status=500) from None
token = get_github_copilot_login_status()
if not token:
token = login_github_copilot(print_fn=lambda _message: None)
if not (token and token.access):
raise WebUISettingsError("OAuth login failed", status=401)
return settings_payload()
raise WebUISettingsError("OAuth login is not supported for this provider")
def logout_oauth_provider(query: QueryParams) -> dict[str, Any]:
provider_name = (_query_first(query, "provider") or "").strip()
if not provider_name:
raise WebUISettingsError("provider is required")
spec = find_by_name(provider_name)
if spec is None or not spec.is_oauth:
raise WebUISettingsError("unknown OAuth provider")
if spec.name == "openai_codex":
try:
from oauth_cli_kit.providers import OPENAI_CODEX_PROVIDER
from oauth_cli_kit.storage import FileTokenStorage
except ImportError:
raise WebUISettingsError("oauth_cli_kit is not installed", status=500) from None
token_path = FileTokenStorage(token_filename=OPENAI_CODEX_PROVIDER.token_filename).get_token_path()
elif spec.name == "github_copilot":
try:
from nanobot.providers.github_copilot_provider import get_storage
except ImportError:
raise WebUISettingsError("GitHub Copilot OAuth support is unavailable", status=500) from None
token_path = get_storage().get_token_path()
else:
raise WebUISettingsError("OAuth logout is not supported for this provider")
for path in (token_path, token_path.with_suffix(".lock")):
with suppress(FileNotFoundError):
path.unlink()
return settings_payload()
def update_network_safety_settings(query: QueryParams) -> dict[str, Any]:
raw_allow = (
_query_first_alias(query, "webui_allow_local_service_access", "webuiAllowLocalServiceAccess")
or _query_first_alias(query, "allow_local_preview_access", "allowLocalPreviewAccess")
)
raw_default_access_mode = _query_first_alias(query, "webui_default_access_mode", "webuiDefaultAccessMode")
if raw_allow is None and raw_default_access_mode is None:
raise WebUISettingsError("webui_allow_local_service_access or webui_default_access_mode is required")
config = load_config()
changed = False
if raw_allow is not None:
webui_allow_local_service_access = _parse_bool(raw_allow, "webui_allow_local_service_access")
if config.tools.webui_allow_local_service_access != webui_allow_local_service_access:
config.tools.webui_allow_local_service_access = webui_allow_local_service_access
changed = True
if changed:
save_config(config)
if raw_default_access_mode is not None:
default_access_mode = raw_default_access_mode.strip().lower()
if default_access_mode == "restricted":
default_access_mode = "default"
if default_access_mode not in {"default", "full"}:
raise WebUISettingsError("webui_default_access_mode must be default or full")
try:
write_webui_default_access_mode(default_access_mode)
except ValueError as exc:
raise WebUISettingsError(str(exc)) from exc
return settings_payload(requires_restart=changed)
def update_web_search_settings(query: QueryParams) -> dict[str, Any]:
provider_name = (_query_first(query, "provider") or "").strip().lower()
provider_option = _WEB_SEARCH_PROVIDER_BY_NAME.get(provider_name)
-329
View File
@@ -1,329 +0,0 @@
"""HTTP route adapter for WebUI Settings APIs.
Keep WebUI Settings route handlers here, not in ``channels/websocket.py``.
The websocket channel owns transport concerns; this module owns WebUI Settings
request mapping and response shaping.
"""
from __future__ import annotations
import asyncio
import json
from collections.abc import Callable
from typing import Any
from websockets.http11 import Request as WsRequest
from websockets.http11 import Response
from nanobot.agent.tools.mcp import request_mcp_reload
from nanobot.bus.queue import MessageBus
from nanobot.webui.cli_apps_api import cli_apps_action, cli_apps_payload
from nanobot.webui.mcp_presets_api import mcp_presets_settings_action
from nanobot.webui.settings_api import (
WebUISettingsError,
create_model_configuration,
decorate_settings_payload,
login_oauth_provider,
logout_oauth_provider,
provider_models_payload,
settings_payload,
update_agent_settings,
update_image_generation_settings,
update_model_configuration,
update_network_safety_settings,
update_provider_settings,
update_web_search_settings,
)
QueryParams = dict[str, list[str]]
_MCP_VALUES_HEADER = "X-Nanobot-MCP-Values"
_MCP_VALUES_HEADER_MAX_BYTES = 64 * 1024
_MCP_PRESET_ACTIONS_BY_PATH = {
"/api/settings/mcp-presets/enable": "enable",
"/api/settings/mcp-presets/remove": "remove",
"/api/settings/mcp-presets/test": "test",
"/api/settings/mcp-presets/custom": "custom",
"/api/settings/mcp-presets/import": "import",
"/api/settings/mcp-presets/import-cursor": "import-cursor",
"/api/settings/mcp-presets/tools": "tools",
}
class WebUISettingsRouter:
"""Route WebUI Settings HTTP requests behind a transport-neutral boundary."""
def __init__(
self,
*,
bus: MessageBus,
logger: Any,
check_api_token: Callable[[WsRequest], bool],
parse_query: Callable[[str], QueryParams],
json_response: Callable[[dict[str, Any]], Response],
error_response: Callable[[int, str | None], Response],
runtime_surface: str,
runtime_capabilities: dict[str, Any],
) -> None:
self.bus = bus
self.logger = logger
self._check_api_token = check_api_token
self._parse_query = parse_query
self._json_response = json_response
self._error_response = error_response
self._runtime_surface = runtime_surface
self._runtime_capabilities = runtime_capabilities
self._restart_sections: set[str] = set()
async def dispatch(self, request: WsRequest, path: str) -> Response | None:
if path == "/api/settings":
return self._handle_settings(request)
if path == "/api/settings/update":
return self._handle_settings_update(request)
if path == "/api/settings/model-configurations/create":
return self._handle_settings_model_configuration_create(request)
if path == "/api/settings/model-configurations/update":
return self._handle_settings_model_configuration_update(request)
if path == "/api/settings/provider/update":
return self._handle_settings_provider_update(request)
if path == "/api/settings/provider-models":
return await self._handle_settings_provider_models(request)
if path == "/api/settings/provider/oauth-login":
return await self._handle_settings_provider_oauth(request, "login")
if path == "/api/settings/provider/oauth-logout":
return await self._handle_settings_provider_oauth(request, "logout")
if path == "/api/settings/web-search/update":
return self._handle_settings_web_search_update(request)
if path == "/api/settings/image-generation/update":
return self._handle_settings_image_generation_update(request)
if path == "/api/settings/network-safety/update":
return self._handle_settings_network_safety_update(request)
if path == "/api/settings/cli-apps":
return self._handle_settings_cli_apps(request)
if path == "/api/settings/cli-apps/install":
return await self._handle_settings_cli_apps_action(request, "install")
if path == "/api/settings/cli-apps/update":
return await self._handle_settings_cli_apps_action(request, "update")
if path == "/api/settings/cli-apps/uninstall":
return await self._handle_settings_cli_apps_action(request, "uninstall")
if path == "/api/settings/cli-apps/test":
return await self._handle_settings_cli_apps_action(request, "test")
if path == "/api/settings/mcp-presets":
return await self._handle_settings_mcp_presets(request)
mcp_action = _MCP_PRESET_ACTIONS_BY_PATH.get(path)
if mcp_action is not None:
return await self._handle_settings_mcp_presets(request, mcp_action)
return None
def _query(self, request: WsRequest) -> QueryParams:
return self._parse_query(request.path)
def _authorized(self, request: WsRequest) -> bool:
return self._check_api_token(request)
def _unauthorized(self) -> Response:
return self._error_response(401, "Unauthorized")
def _with_restart_state(
self,
payload: dict[str, Any],
*,
section: str | None = None,
) -> dict[str, Any]:
"""Keep restart-required state alive for this gateway process."""
if section and payload.get("requires_restart"):
self._restart_sections.add(section)
sections = sorted(self._restart_sections)
payload = dict(payload)
if sections:
payload["requires_restart"] = True
return decorate_settings_payload(
payload,
surface=self._runtime_surface,
runtime_capability_overrides=self._runtime_capabilities,
restart_required_sections=sections,
)
def _parse_mcp_settings_query(self, request: WsRequest) -> QueryParams:
query = self._query(request)
raw = request.headers.get(_MCP_VALUES_HEADER)
if not raw:
return query
if len(raw.encode("utf-8")) > _MCP_VALUES_HEADER_MAX_BYTES:
raise WebUISettingsError("MCP settings payload is too large")
try:
payload = json.loads(raw)
except json.JSONDecodeError as exc:
raise WebUISettingsError("invalid MCP settings payload") from exc
if not isinstance(payload, dict):
raise WebUISettingsError("MCP settings payload must be a JSON object")
merged = {key: list(values) for key, values in query.items()}
for key, value in payload.items():
if not isinstance(key, str) or not key:
raise WebUISettingsError("MCP settings payload contains an invalid key")
if value is None:
continue
if isinstance(value, str):
text = value.strip()
else:
text = json.dumps(value, ensure_ascii=False, separators=(",", ":"))
if text:
merged[key] = [text]
return merged
def _handle_settings(self, request: WsRequest) -> Response:
if not self._authorized(request):
return self._unauthorized()
return self._json_response(
self._with_restart_state(
settings_payload(
surface=self._runtime_surface,
runtime_capability_overrides=self._runtime_capabilities,
)
)
)
def _handle_settings_update(self, request: WsRequest) -> Response:
if not self._authorized(request):
return self._unauthorized()
try:
payload = update_agent_settings(self._query(request))
except WebUISettingsError as e:
return self._error_response(e.status, e.message)
return self._json_response(self._with_restart_state(payload, section="runtime"))
def _handle_settings_model_configuration_create(self, request: WsRequest) -> Response:
if not self._authorized(request):
return self._unauthorized()
try:
payload = create_model_configuration(self._query(request))
except WebUISettingsError as e:
return self._error_response(e.status, e.message)
return self._json_response(self._with_restart_state(payload))
def _handle_settings_model_configuration_update(self, request: WsRequest) -> Response:
if not self._authorized(request):
return self._unauthorized()
try:
payload = update_model_configuration(self._query(request))
except WebUISettingsError as e:
return self._error_response(e.status, e.message)
return self._json_response(self._with_restart_state(payload))
def _handle_settings_provider_update(self, request: WsRequest) -> Response:
if not self._authorized(request):
return self._unauthorized()
try:
payload = update_provider_settings(self._query(request))
except WebUISettingsError as e:
return self._error_response(e.status, e.message)
return self._json_response(self._with_restart_state(payload, section="image"))
async def _handle_settings_provider_models(self, request: WsRequest) -> Response:
if not self._authorized(request):
return self._unauthorized()
try:
payload = await asyncio.to_thread(provider_models_payload, self._query(request))
except WebUISettingsError as e:
return self._error_response(e.status, e.message)
except Exception:
self.logger.exception("failed to load provider model list")
return self._error_response(500, "failed to load provider model list")
return self._json_response(payload)
async def _handle_settings_provider_oauth(
self,
request: WsRequest,
action: str,
) -> Response:
if not self._authorized(request):
return self._unauthorized()
query = self._query(request)
try:
if action == "login":
payload = await asyncio.to_thread(login_oauth_provider, query)
else:
payload = await asyncio.to_thread(logout_oauth_provider, query)
except WebUISettingsError as e:
return self._error_response(e.status, e.message)
return self._json_response(self._with_restart_state(payload))
def _handle_settings_web_search_update(self, request: WsRequest) -> Response:
if not self._authorized(request):
return self._unauthorized()
try:
payload = update_web_search_settings(self._query(request))
except WebUISettingsError as e:
return self._error_response(e.status, e.message)
return self._json_response(self._with_restart_state(payload, section="browser"))
def _handle_settings_image_generation_update(self, request: WsRequest) -> Response:
if not self._authorized(request):
return self._unauthorized()
try:
payload = update_image_generation_settings(self._query(request))
except WebUISettingsError as e:
return self._error_response(e.status, e.message)
return self._json_response(self._with_restart_state(payload, section="image"))
def _handle_settings_network_safety_update(self, request: WsRequest) -> Response:
if not self._authorized(request):
return self._unauthorized()
try:
payload = update_network_safety_settings(self._query(request))
except WebUISettingsError as e:
return self._error_response(e.status, e.message)
return self._json_response(self._with_restart_state(payload, section="runtime"))
def _handle_settings_cli_apps(self, request: WsRequest) -> Response:
if not self._authorized(request):
return self._unauthorized()
try:
payload = cli_apps_payload()
except Exception:
self.logger.exception("failed to load CLI Apps payload")
return self._error_response(500, "failed to load CLI Apps")
return self._json_response(payload)
async def _handle_settings_cli_apps_action(
self,
request: WsRequest,
action: str,
) -> Response:
if not self._authorized(request):
return self._unauthorized()
try:
payload = await asyncio.to_thread(cli_apps_action, action, self._query(request))
except WebUISettingsError as e:
return self._error_response(e.status, e.message)
except Exception as e:
status = getattr(e, "status", 500)
message = getattr(e, "message", str(e))
if status >= 500:
self.logger.exception("CLI Apps action '{}' failed", action)
return self._error_response(status, message)
return self._json_response(payload)
async def _handle_settings_mcp_presets(
self,
request: WsRequest,
action: str | None = None,
) -> Response:
if not self._authorized(request):
return self._unauthorized()
try:
payload = await mcp_presets_settings_action(
action,
self._parse_mcp_settings_query(request),
reload_mcp=lambda: request_mcp_reload(self.bus),
)
except Exception as e:
status = getattr(e, "status", 500)
message = getattr(e, "message", str(e))
if status >= 500:
self.logger.exception("MCP preset action '{}' failed", action or "list")
return self._error_response(status, message)
if action is None:
return self._json_response(payload)
return self._json_response(self._with_restart_state(payload, section="runtime"))
+1 -4
View File
@@ -38,7 +38,6 @@ def default_webui_sidebar_state() -> dict[str, Any]:
"pinned_keys": [],
"archived_keys": [],
"title_overrides": {},
"project_name_overrides": {},
"tags_by_key": {},
"collapsed_groups": {},
"view": {
@@ -137,9 +136,6 @@ def normalize_webui_sidebar_state(raw: Any) -> dict[str, Any]:
state["pinned_keys"] = _clean_string_list(raw.get("pinned_keys"))
state["archived_keys"] = _clean_string_list(raw.get("archived_keys"))
state["title_overrides"] = _clean_title_overrides(raw.get("title_overrides"))
state["project_name_overrides"] = _clean_title_overrides(
raw.get("project_name_overrides")
)
state["tags_by_key"] = _clean_tags_by_key(raw.get("tags_by_key"))
state["collapsed_groups"] = _clean_bool_map(raw.get("collapsed_groups"))
state["view"] = _clean_view(raw.get("view"))
@@ -194,3 +190,4 @@ def write_webui_sidebar_state(raw: dict[str, Any]) -> dict[str, Any]:
finally:
os.close(dir_fd)
return state
+21 -335
View File
@@ -4,12 +4,10 @@ from __future__ import annotations
import json
import os
import re
import time
import uuid
from pathlib import Path
from typing import Any, Callable, Mapping
from urllib.parse import unquote, urlparse
from typing import Any, Callable
from loguru import logger
@@ -18,82 +16,6 @@ from nanobot.session.manager import SessionManager
WEBUI_TRANSCRIPT_SCHEMA_VERSION = 3
_MAX_TRANSCRIPT_FILE_BYTES = 8 * 1024 * 1024
_MARKDOWN_LOCAL_IMAGE_RE = re.compile(
r"!\[([^\]]*)\]\((<[^>]+>|[^)\s]+)(\s+(?:\"[^\"]*\"|'[^']*'))?\)"
)
_INLINE_MARKDOWN_IMAGE_EXTS: frozenset[str] = frozenset({
".png",
".jpg",
".jpeg",
".webp",
".gif",
".svg",
})
_INLINE_MARKDOWN_VIDEO_EXTS: frozenset[str] = frozenset({
".mp4",
".mov",
".webm",
})
_INLINE_MARKDOWN_MEDIA_EXTS = _INLINE_MARKDOWN_IMAGE_EXTS | _INLINE_MARKDOWN_VIDEO_EXTS
_FILE_EDIT_TOOL_NAMES: frozenset[str] = frozenset({
"write_file",
"edit_file",
"apply_patch",
})
def rewrite_local_markdown_images(
text: str,
*,
workspace_path: Path,
sign_path: Callable[[Path], Mapping[str, Any] | None],
) -> str:
"""Rewrite markdown media paths inside the workspace to signed WebUI media URLs."""
if "![" not in text:
return text
def resolve_url(raw_url: str) -> str | None:
url = raw_url.strip()
if url.startswith("<") and url.endswith(">"):
url = url[1:-1].strip()
if not url or url.startswith(("/api/media/", "#")):
return None
parsed = urlparse(url)
if parsed.scheme or parsed.netloc or parsed.query or parsed.fragment:
return None
path_text = unquote(url)
if Path(path_text).suffix.lower() not in _INLINE_MARKDOWN_MEDIA_EXTS:
return None
candidate = Path(path_text).expanduser()
if not candidate.is_absolute():
candidate = workspace_path / candidate
try:
resolved = candidate.resolve(strict=False)
resolved.relative_to(workspace_path)
except (OSError, ValueError):
return None
if not resolved.is_file():
return None
signed = sign_path(resolved)
return str(signed.get("url")) if signed and signed.get("url") else None
def replace(match: re.Match[str]) -> str:
signed_url = resolve_url(match.group(2))
if not signed_url:
return match.group(0)
title = match.group(3) or ""
return f"![{match.group(1)}]({signed_url}{title})"
return _MARKDOWN_LOCAL_IMAGE_RE.sub(replace, text)
def _media_kind_from_name(name: str) -> str:
ext = Path(name).suffix.lower()
if ext in _INLINE_MARKDOWN_IMAGE_EXTS:
return "image"
if ext in _INLINE_MARKDOWN_VIDEO_EXTS:
return "video"
return "file"
def webui_transcript_path(session_key: str) -> Path:
@@ -194,149 +116,6 @@ def tool_trace_lines_from_events(events: Any) -> list[str]:
return lines
_PHASE_RANK = {"start": 1, "end": 2, "error": 3}
def _normalize_tool_events(events: Any) -> list[dict[str, Any]]:
if not isinstance(events, list):
return []
out: list[dict[str, Any]] = []
for event in events:
if not event or not isinstance(event, dict):
continue
if event.get("phase") not in {"start", "end", "error"}:
continue
if not isinstance(event.get("name"), str):
fn = event.get("function")
if not (isinstance(fn, dict) and isinstance(fn.get("name"), str)):
continue
out.append(dict(event))
return out
def _tool_event_key(event: dict[str, Any]) -> str:
call_id = event.get("call_id")
if isinstance(call_id, str) and call_id:
return f"call:{call_id}"
return _format_tool_call_trace(event) or json.dumps(event, sort_keys=True, ensure_ascii=False)
def _tool_event_file_edit_key(event: dict[str, Any]) -> str | None:
call_id = event.get("call_id")
if not isinstance(call_id, str) or not call_id:
return None
name = event.get("name")
if not isinstance(name, str) or not name:
fn = event.get("function")
name = fn.get("name") if isinstance(fn, dict) else ""
if not isinstance(name, str) or name not in _FILE_EDIT_TOOL_NAMES:
return None
return f"{call_id}|{name}"
def _merge_tool_events(previous: Any, incoming: list[dict[str, Any]]) -> list[dict[str, Any]]:
if not isinstance(previous, list) or not previous:
return incoming
if not incoming:
return [dict(event) for event in previous if isinstance(event, dict)]
merged = [dict(event) for event in previous if isinstance(event, dict)]
index_by_key = {_tool_event_key(event): idx for idx, event in enumerate(merged)}
for event in incoming:
key = _tool_event_key(event)
existing_index = index_by_key.get(key)
if existing_index is None:
index_by_key[key] = len(merged)
merged.append(event)
continue
existing = merged[existing_index]
incoming_rank = _PHASE_RANK.get(str(event.get("phase")), 0)
existing_rank = _PHASE_RANK.get(str(existing.get("phase")), 0)
if incoming_rank >= existing_rank:
merged[existing_index] = {**existing, **event}
return merged
def _file_edit_key(edit: dict[str, Any]) -> str:
call_id = str(edit.get("call_id") or "")
tool = str(edit.get("tool") or "")
if call_id:
return f"{call_id}|{tool}"
return f"{tool}|{edit.get('path') or ''}"
def _message_has_file_edit_for_tool_event(
message: dict[str, Any],
event: dict[str, Any],
) -> bool:
key = _tool_event_file_edit_key(event)
if not key:
return False
edits = message.get("fileEdits")
if not isinstance(edits, list):
return False
return any(isinstance(edit, dict) and _file_edit_key(edit) == key for edit in edits)
def _filter_covered_file_edit_tool_events(
messages: list[dict[str, Any]],
events: list[dict[str, Any]],
) -> list[dict[str, Any]]:
if not events:
return events
return [
event
for event in events
if not any(_message_has_file_edit_for_tool_event(message, event) for message in messages)
]
def _strip_covered_file_edit_tool_hints(
message: dict[str, Any],
edits: list[dict[str, Any]],
) -> dict[str, Any]:
incoming_keys = {
_file_edit_key(edit)
for edit in edits
if isinstance(edit, dict)
}
events = message.get("toolEvents")
if not incoming_keys or not isinstance(events, list):
return message
kept_events: list[dict[str, Any]] = []
removed_trace_lines: set[str] = set()
changed = False
for event in events:
if not isinstance(event, dict):
continue
key = _tool_event_file_edit_key(event)
if key and key in incoming_keys:
changed = True
removed_trace_lines.update(tool_trace_lines_from_events([event]))
continue
kept_events.append(event)
if not changed:
return message
raw_traces = message.get("traces")
if isinstance(raw_traces, list):
previous_traces = [trace for trace in raw_traces if isinstance(trace, str)]
else:
content = message.get("content")
previous_traces = [content] if isinstance(content, str) and content else []
next_traces = [trace for trace in previous_traces if trace not in removed_trace_lines]
next_message = {
**message,
"traces": next_traces,
"content": next_traces[-1] if next_traces else "",
}
if kept_events:
next_message["toolEvents"] = kept_events
else:
next_message.pop("toolEvents", None)
return next_message
def _merge_unique_tool_trace_lines(
previous_traces: list[str],
lines: list[str],
@@ -357,7 +136,6 @@ def replay_transcript_to_ui_messages(
lines: list[dict[str, Any]],
*,
augment_user_media: Callable[[list[str]], list[dict[str, Any]]] | None = None,
augment_assistant_text: Callable[[str], str] | None = None,
) -> list[dict[str, Any]]:
"""Fold JSONL records into ``UIMessage``-shaped dicts for the WebUI.
@@ -458,40 +236,6 @@ def replay_transcript_to_ui_messages(
return None
return str(last.get("id"))
def demote_interrupted_assistant(segment: str) -> None:
nonlocal buffer_message_id, buffer_parts
for i in range(len(messages) - 1, -1, -1):
candidate = messages[i]
if candidate.get("role") == "user":
break
content = candidate.get("content")
if (
candidate.get("role") != "assistant"
or candidate.get("kind") == "trace"
or not candidate.get("isStreaming")
or not isinstance(content, str)
or not content.strip()
or candidate.get("media")
):
continue
reasoning_parts = [
part
for part in (candidate.get("reasoning"), content)
if isinstance(part, str) and part.strip()
]
messages[i] = {
**candidate,
"content": "",
"reasoning": "\n\n".join(reasoning_parts),
"reasoningStreaming": False,
"isStreaming": False,
"activitySegmentId": candidate.get("activitySegmentId") or segment,
}
if buffer_message_id == candidate.get("id"):
buffer_message_id = None
buffer_parts = []
return
def close_reasoning(prev: list[dict[str, Any]]) -> None:
for i in range(len(prev) - 1, -1, -1):
if prev[i].get("reasoningStreaming"):
@@ -553,6 +297,13 @@ def replay_transcript_to_ui_messages(
active_activity_segment_id = None
active_file_edit_segment_id = None
def _file_edit_key(edit: dict[str, Any]) -> str:
call_id = str(edit.get("call_id") or "")
tool = str(edit.get("tool") or "")
if call_id:
return f"{call_id}|{tool}"
return f"{tool}|{edit.get('path') or ''}"
def find_file_edit_trace_index(
segment: str | None,
edits: list[dict[str, Any]],
@@ -562,23 +313,16 @@ def replay_transcript_to_ui_messages(
candidate = messages[i]
if candidate.get("role") == "user":
break
if candidate.get("kind") != "trace":
if candidate.get("kind") != "trace" or not candidate.get("fileEdits"):
continue
if segment and candidate.get("activitySegmentId") == segment:
return i
existing_edits = candidate.get("fileEdits")
if isinstance(existing_edits, list):
for existing in existing_edits:
if isinstance(existing, dict) and _file_edit_key(existing) in incoming_keys:
return i
existing_tool_events = candidate.get("toolEvents")
if isinstance(existing_tool_events, list):
for event in existing_tool_events:
if not isinstance(event, dict):
continue
key = _tool_event_file_edit_key(event)
if key and key in incoming_keys:
return i
if not isinstance(existing_edits, list):
continue
for existing in existing_edits:
if isinstance(existing, dict) and _file_edit_key(existing) in incoming_keys:
return i
return None
def upsert_file_edits(edits: list[dict[str, Any]], idx: int) -> None:
@@ -586,16 +330,11 @@ def replay_transcript_to_ui_messages(
if not edits:
return
segment = active_file_edit_segment_id
if not segment:
segment = _new_activity_segment(activate=False)
active_file_edit_segment_id = segment
demote_interrupted_assistant(segment)
target_index = find_file_edit_trace_index(segment, edits)
if target_index is not None:
last = messages[target_index]
segment = str(last.get("activitySegmentId") or segment or _new_activity_segment(activate=False))
active_file_edit_segment_id = segment
last = _strip_covered_file_edit_tool_hints(last, edits)
else:
if not segment:
segment = _new_activity_segment(activate=False)
@@ -666,14 +405,6 @@ def replay_transcript_to_ui_messages(
row["media"] = media_att
if all(m.get("kind") == "image" for m in media_att):
row["images"] = [{"url": m.get("url"), "name": m.get("name")} for m in media_att]
cli_apps = rec.get("cli_apps")
if isinstance(cli_apps, list) and cli_apps:
row["cliApps"] = [dict(app) for app in cli_apps if isinstance(app, dict)]
mcp_presets = rec.get("mcp_presets")
if isinstance(mcp_presets, list) and mcp_presets:
row["mcpPresets"] = [
dict(preset) for preset in mcp_presets if isinstance(preset, dict)
]
messages.append(row)
continue
@@ -718,24 +449,6 @@ def replay_transcript_to_ui_messages(
buffer_message_id = None
buffer_parts = []
continue
final_text = rec.get("text")
if isinstance(final_text, str):
if buffer_message_id is None:
buffer_message_id = _new_id("buf", idx)
messages.append(
{
"id": buffer_message_id,
"role": "assistant",
"content": final_text,
"isStreaming": True,
"createdAt": _ts_base + idx,
},
)
else:
for i, m in enumerate(messages):
if m.get("id") == buffer_message_id:
messages[i] = {**m, "content": final_text, "isStreaming": True}
break
buffer_message_id = None
buffer_parts = []
continue
@@ -773,22 +486,12 @@ def replay_transcript_to_ui_messages(
close_reasoning(messages)
continue
if kind in ("tool_hint", "progress"):
structured_events = _normalize_tool_events(rec.get("tool_events"))
visible_structured_events = _filter_covered_file_edit_tool_events(messages, structured_events)
structured = tool_trace_lines_from_events(visible_structured_events)
structured = tool_trace_lines_from_events(rec.get("tool_events"))
text = rec.get("text")
if structured:
trace_lines = structured
elif structured_events:
trace_lines = []
elif isinstance(text, str) and text:
trace_lines = [text]
else:
trace_lines = []
trace_lines = structured if structured else ([text] if isinstance(text, str) and text else [])
if not trace_lines:
continue
segment = _ensure_activity_segment()
demote_interrupted_assistant(segment)
last = messages[-1] if messages else None
if (
last
@@ -799,7 +502,7 @@ def replay_transcript_to_ui_messages(
prev_traces = list(last.get("traces") or [last.get("content")])
if structured:
merged_traces, added = _merge_unique_tool_trace_lines(prev_traces, structured)
if not added and not visible_structured_events:
if not added:
continue
else:
merged_traces = prev_traces + trace_lines
@@ -807,9 +510,6 @@ def replay_transcript_to_ui_messages(
**last,
"traces": merged_traces,
"content": merged_traces[-1],
"toolEvents": _merge_tool_events(last.get("toolEvents"), visible_structured_events)
if visible_structured_events
else last.get("toolEvents"),
"activitySegmentId": last.get("activitySegmentId") or segment,
}
messages[-1] = merged
@@ -821,7 +521,6 @@ def replay_transcript_to_ui_messages(
"kind": "trace",
"content": trace_lines[-1],
"traces": trace_lines,
**({"toolEvents": visible_structured_events} if visible_structured_events else {}),
"activitySegmentId": segment,
"createdAt": _ts_base + idx,
},
@@ -837,12 +536,11 @@ def replay_transcript_to_ui_messages(
if isinstance(media_urls, list):
for m in media_urls:
if isinstance(m, dict) and m.get("url"):
name = str(m.get("name") or "")
media.append(
{
"kind": _media_kind_from_name(name),
"kind": "image",
"url": str(m["url"]),
"name": name,
"name": str(m.get("name") or ""),
},
)
extra: dict[str, Any] = {"content": content_s}
@@ -871,14 +569,7 @@ def replay_transcript_to_ui_messages(
buffer_parts = []
continue
for i, m in enumerate(messages):
if (
augment_assistant_text is not None
and m.get("role") == "assistant"
and m.get("kind") != "trace"
and isinstance(m.get("content"), str)
):
messages[i] = {**m, "content": augment_assistant_text(m["content"])}
for m in messages:
m.pop("isStreaming", None)
m.pop("reasoningStreaming", None)
return messages
@@ -888,17 +579,12 @@ def build_webui_thread_response(
session_key: str,
*,
augment_user_media: Callable[[list[str]], list[dict[str, Any]]] | None = None,
augment_assistant_text: Callable[[str], str] | None = None,
) -> dict[str, Any] | None:
"""Return a payload compatible with ``WebuiThreadPersistedPayload``."""
lines = read_transcript_lines(session_key)
if not lines:
return None
msgs = replay_transcript_to_ui_messages(
lines,
augment_user_media=augment_user_media,
augment_assistant_text=augment_assistant_text,
)
msgs = replay_transcript_to_ui_messages(lines, augment_user_media=augment_user_media)
return {
"schemaVersion": WEBUI_TRANSCRIPT_SCHEMA_VERSION,
"sessionKey": session_key,
-283
View File
@@ -1,283 +0,0 @@
"""Persisted WebUI project workspace state."""
from __future__ import annotations
import json
import os
import time
from pathlib import Path
from typing import Any
from loguru import logger
from nanobot.config.paths import get_webui_dir
from nanobot.security.workspace_access import (
WORKSPACE_SCOPE_METADATA_KEY,
WorkspaceScope,
WorkspaceScopeError,
build_workspace_scope,
default_workspace_scope,
validate_workspace_scope_payload,
)
WEBUI_WORKSPACE_STATE_SCHEMA_VERSION = 1
_MAX_STATE_FILE_BYTES = 128 * 1024
_DEFAULT_ACCESS_MODES = {"default", "full"}
_LEGACY_RESTRICTED_DEFAULT_ACCESS_MODE = "restricted"
_WEBUI_SCOPE_CHANNEL = "websocket"
def webui_workspace_state_path() -> Path:
return get_webui_dir() / "workspace-state.json"
def default_webui_workspace_state() -> dict[str, Any]:
return {
"schema_version": WEBUI_WORKSPACE_STATE_SCHEMA_VERSION,
"default_access_mode": "default",
"updated_at": None,
}
def normalize_webui_workspace_state(raw: Any) -> dict[str, Any]:
if not isinstance(raw, dict):
raw = {}
state = default_webui_workspace_state()
updated_at = raw.get("updated_at")
state["updated_at"] = updated_at if isinstance(updated_at, str) else None
default_access_mode = raw.get("default_access_mode")
if default_access_mode in _DEFAULT_ACCESS_MODES:
state["default_access_mode"] = default_access_mode
return state
def read_webui_workspace_state() -> dict[str, Any]:
path = webui_workspace_state_path()
if not path.is_file():
return default_webui_workspace_state()
try:
if path.stat().st_size > _MAX_STATE_FILE_BYTES:
logger.warning("webui workspace state too large, ignoring: {}", path)
return default_webui_workspace_state()
with open(path, encoding="utf-8") as f:
raw = json.load(f)
except (OSError, json.JSONDecodeError) as e:
logger.warning("read webui workspace state failed {}: {}", path, e)
return default_webui_workspace_state()
return normalize_webui_workspace_state(raw)
def write_webui_workspace_state(raw: dict[str, Any]) -> dict[str, Any]:
state = normalize_webui_workspace_state(raw)
state["updated_at"] = time.strftime("%Y-%m-%dT%H:%M:%SZ", time.gmtime())
encoded = json.dumps(
state,
ensure_ascii=False,
indent=2,
sort_keys=True,
).encode("utf-8")
if len(encoded) > _MAX_STATE_FILE_BYTES:
raise ValueError("workspace state is too large")
path = webui_workspace_state_path()
path.parent.mkdir(parents=True, exist_ok=True)
tmp = path.with_suffix(".json.tmp")
with open(tmp, "wb") as f:
f.write(encoded)
f.write(b"\n")
f.flush()
os.fsync(f.fileno())
os.replace(tmp, path)
try:
dir_fd = os.open(path.parent, os.O_RDONLY)
except OSError:
return state
try:
os.fsync(dir_fd)
finally:
os.close(dir_fd)
return state
def read_webui_default_access_mode() -> str:
state = read_webui_workspace_state()
mode = state.get("default_access_mode")
return mode if mode in _DEFAULT_ACCESS_MODES else "default"
def write_webui_default_access_mode(mode: str) -> bool:
if mode == _LEGACY_RESTRICTED_DEFAULT_ACCESS_MODE:
mode = "default"
if mode not in _DEFAULT_ACCESS_MODES:
raise ValueError("default access mode must be default or full")
state = read_webui_workspace_state()
changed = state.get("default_access_mode") != mode
if changed:
state["default_access_mode"] = mode
write_webui_workspace_state(state)
return changed
def default_scope_for_webui(
default_workspace: Path,
default_restrict_to_workspace: bool,
) -> WorkspaceScope:
mode = read_webui_default_access_mode()
if mode == "default":
return default_workspace_scope(
default_workspace,
default_restrict_to_workspace,
source_channel=_WEBUI_SCOPE_CHANNEL,
)
return build_workspace_scope(default_workspace, mode, source_channel=_WEBUI_SCOPE_CHANNEL)
def workspaces_payload(
*,
default_workspace: Path,
default_restrict_to_workspace: bool,
controls_available: bool,
) -> dict[str, Any]:
default_access_mode = read_webui_default_access_mode()
default_scope = (
default_workspace_scope(
default_workspace,
default_restrict_to_workspace,
source_channel=_WEBUI_SCOPE_CHANNEL,
)
if default_access_mode == "default"
else build_workspace_scope(default_workspace, default_access_mode, source_channel=_WEBUI_SCOPE_CHANNEL)
)
return {
"schema_version": WEBUI_WORKSPACE_STATE_SCHEMA_VERSION,
"default_access_mode": default_access_mode,
"default_scope": default_scope.payload(),
"controls": {
"can_change_project": controls_available,
"can_use_full_access": controls_available,
},
}
class WebUIWorkspaceController:
"""Own WebUI project scope persistence and validation."""
def __init__(
self,
*,
session_manager: Any | None,
default_workspace: Path,
default_restrict_to_workspace: bool,
) -> None:
self._sessions = session_manager
self._default_workspace = default_workspace
self._default_restrict_to_workspace = default_restrict_to_workspace
def default_scope(self) -> WorkspaceScope:
return default_scope_for_webui(
self._default_workspace,
self._default_restrict_to_workspace,
)
def scope_for_session_key(self, session_key: str) -> WorkspaceScope:
if self._sessions is None:
return self.default_scope()
data = self._sessions.read_session_file(session_key)
metadata = data.get("metadata", {}) if isinstance(data, dict) else {}
if not isinstance(metadata, dict) or WORKSPACE_SCOPE_METADATA_KEY not in metadata:
return self.default_scope()
try:
return validate_workspace_scope_payload(
metadata.get(WORKSPACE_SCOPE_METADATA_KEY),
default_workspace=self._default_workspace,
default_restrict_to_workspace=self._default_restrict_to_workspace,
source_channel=_WEBUI_SCOPE_CHANNEL,
)
except WorkspaceScopeError:
return self.default_scope()
def payload(self, *, controls_available: bool) -> dict[str, Any]:
return workspaces_payload(
default_workspace=self._default_workspace,
default_restrict_to_workspace=self._default_restrict_to_workspace,
controls_available=controls_available,
)
def scope_from_envelope(
self,
envelope: dict[str, Any],
*,
session_key: str | None,
controls_available: bool,
) -> WorkspaceScope:
raw = envelope.get(WORKSPACE_SCOPE_METADATA_KEY)
if raw is None and session_key:
scope = self.scope_for_session_key(session_key)
elif raw is None:
scope = self.default_scope()
else:
scope = validate_workspace_scope_payload(
raw,
default_workspace=self._default_workspace,
default_restrict_to_workspace=self._default_restrict_to_workspace,
source_channel=_WEBUI_SCOPE_CHANNEL,
)
if not controls_available and scope.metadata() != self.default_scope().metadata():
raise WorkspaceScopeError("workspace controls are localhost-only", status=403)
return scope
def scope_for_new_chat(
self,
envelope: dict[str, Any],
*,
controls_available: bool,
) -> WorkspaceScope:
return self.scope_from_envelope(
envelope,
session_key=None,
controls_available=controls_available,
)
def scope_for_set_request(
self,
envelope: dict[str, Any],
*,
chat_id: str,
chat_running: bool,
controls_available: bool,
) -> WorkspaceScope:
if chat_running:
raise WorkspaceScopeError("chat_running", status=409)
return self.scope_from_envelope(
envelope,
session_key=f"websocket:{chat_id}",
controls_available=controls_available,
)
def scope_for_message(
self,
envelope: dict[str, Any],
*,
chat_id: str,
chat_running: bool,
controls_available: bool,
) -> WorkspaceScope:
scope = self.scope_from_envelope(
envelope,
session_key=f"websocket:{chat_id}",
controls_available=controls_available,
)
if (
WORKSPACE_SCOPE_METADATA_KEY in envelope
and chat_running
and scope.metadata() != self.scope_for_session_key(f"websocket:{chat_id}").metadata()
):
raise WorkspaceScopeError("chat_running", status=409)
return scope
def persist_scope(self, chat_id: str, scope: WorkspaceScope) -> None:
if self._sessions is not None:
session = self._sessions.get_or_create(f"websocket:{chat_id}")
session.metadata["webui"] = True
session.metadata[WORKSPACE_SCOPE_METADATA_KEY] = scope.metadata()
self._sessions.save(session)
+1 -2
View File
@@ -37,7 +37,7 @@ dependencies = [
"rich>=14.0.0,<15.0.0",
"croniter>=6.0.0,<7.0.0",
"dingtalk-stream>=0.24.0,<1.0.0",
"python-telegram-bot[socks,webhooks]>=22.6,<23.0",
"python-telegram-bot[socks]>=22.6,<23.0",
"lark-oapi>=1.5.0,<2.0.0",
"socksio>=1.0.0,<2.0.0",
"python-socketio>=5.16.0,<6.0.0",
@@ -82,7 +82,6 @@ msteams = [
matrix = [
"matrix-nio[e2e]>=0.25.2; sys_platform != 'win32'",
"aiohttp>=3.9.0,<4.0.0",
"mistune>=3.0.0,<4.0.0",
"nh3>=0.2.17,<1.0.0",
]
-53
View File
@@ -139,13 +139,6 @@ class TestLoadBootstrapFiles:
for name in ContextBuilder.BOOTSTRAP_FILES:
assert f"## {name}" in result
def test_legacy_tools_md_is_not_bootstrapped(self, tmp_path):
(tmp_path / "TOOLS.md").write_text("workspace tool notes", encoding="utf-8")
builder = _builder(tmp_path)
result = builder._load_bootstrap_files()
assert "TOOLS.md" not in result
assert "workspace tool notes" not in result
def test_utf8_content(self, tmp_path):
(tmp_path / "AGENTS.md").write_text("用中文回复", encoding="utf-8")
builder = _builder(tmp_path)
@@ -178,37 +171,6 @@ class TestIsTemplateContent:
assert ContextBuilder._is_template_content("totally different", "memory/MEMORY.md") is False
# ---------------------------------------------------------------------------
# Bundled bootstrap templates
# ---------------------------------------------------------------------------
class TestBundledToolContract:
def test_tool_contract_balances_general_and_coding_workflows(self):
from importlib.resources import files as pkg_files
tpl = pkg_files("nanobot") / "templates" / "agent" / "tool_contract.md"
content = tpl.read_text(encoding="utf-8")
assert "## General Tool Contract" in content
assert "Use the narrowest structured tool" in content
assert "Do not use `exec` as a universal workaround" in content
assert "## File and Coding Workflows" in content
assert "apply_patch" in content
assert "## Web and External Information" in content
assert "## Messaging and Media" in content
assert "## Scheduling and Background Work" in content
assert "pure coding" not in content.lower()
def test_tool_contract_is_injected_without_workspace_file(self, tmp_path):
builder = _builder(tmp_path)
prompt = builder.build_system_prompt()
assert "# Tool Usage Notes" in prompt
assert "## General Tool Contract" in prompt
assert "Do not use `exec` as a universal workaround" in prompt
# ---------------------------------------------------------------------------
# _build_user_content
# ---------------------------------------------------------------------------
@@ -362,21 +324,6 @@ class TestBuildMessages:
assert "Other chat goal." not in str(without_goal[-1]["content"])
assert "Goal (active):" not in str(without_goal[-1]["content"])
def test_current_runtime_lines_are_injected(self, tmp_path):
builder = _builder(tmp_path)
messages = builder.build_messages(
[],
"please use @zoom tonight",
current_runtime_lines=[
"CLI App Attachment: @zoom (installed; tool=run_cli_app; entry_point=cli-anything-zoom).",
],
)
user_msg = str(messages[-1]["content"])
assert "CLI App Attachment: @zoom" in user_msg
assert "tool=run_cli_app" in user_msg
assert "entry_point=cli-anything-zoom" in user_msg
def test_consecutive_same_role_merged(self, tmp_path):
builder = _builder(tmp_path)
history = [{"role": "user", "content": "previous user message"}]
@@ -1,169 +0,0 @@
import asyncio
import base64
from pathlib import Path
from unittest.mock import AsyncMock, MagicMock
import pytest
from nanobot.agent.loop import AgentLoop, TurnContext, TurnState
from nanobot.bus.events import InboundMessage
from nanobot.bus.queue import MessageBus
from nanobot.config.schema import ChannelsConfig
from nanobot.providers.base import LLMResponse
from nanobot.utils.document import reference_non_image_attachments
def _make_loop(tmp_path: Path, channels_config: ChannelsConfig | None = None) -> AgentLoop:
provider = MagicMock()
provider.get_default_model.return_value = "test-model"
provider.chat_with_retry = AsyncMock(return_value=LLMResponse(content="ok"))
return AgentLoop(
bus=MessageBus(),
provider=provider,
workspace=tmp_path,
model="test-model",
channels_config=channels_config,
)
@pytest.mark.asyncio
async def test_state_restore_extracts_documents_by_default(
tmp_path: Path,
monkeypatch: pytest.MonkeyPatch,
) -> None:
loop = _make_loop(tmp_path)
doc_path = tmp_path / "report.txt"
doc_path.write_text("Quarterly revenue is $5M", encoding="utf-8")
calls: list[tuple[str, list[str]]] = []
def fake_extract_documents(content: str, media: list[str]) -> tuple[str, list[str]]:
calls.append((content, media))
return f"{content}\n\n[File: report.txt]\nQuarterly revenue is $5M", []
monkeypatch.setattr("nanobot.agent.loop.extract_documents", fake_extract_documents)
ctx = TurnContext(
msg=InboundMessage(
channel="cli",
sender_id="u",
chat_id="c",
content="summarize",
media=[str(doc_path)],
),
session_key="cli:c",
state=TurnState.RESTORE,
turn_id="turn-1",
)
assert await loop._state_restore(ctx) == "ok"
assert calls == [("summarize", [str(doc_path)])]
assert "Quarterly revenue" in ctx.msg.content
assert ctx.msg.media == []
@pytest.mark.asyncio
async def test_state_restore_references_documents_when_extraction_disabled(
tmp_path: Path,
monkeypatch: pytest.MonkeyPatch,
) -> None:
loop = _make_loop(tmp_path, ChannelsConfig(extract_document_text=False))
doc_path = tmp_path / "report.txt"
doc_path.write_text("Quarterly revenue is $5M", encoding="utf-8")
def fail_extract_documents(content: str, media: list[str]) -> tuple[str, list[str]]:
raise AssertionError("document extraction should be disabled")
monkeypatch.setattr("nanobot.agent.loop.extract_documents", fail_extract_documents)
ctx = TurnContext(
msg=InboundMessage(
channel="cli",
sender_id="u",
chat_id="c",
content="summarize",
media=[str(doc_path)],
),
session_key="cli:c",
state=TurnState.RESTORE,
turn_id="turn-1",
)
assert await loop._state_restore(ctx) == "ok"
assert "Quarterly revenue" not in ctx.msg.content
assert f"[Attachment: {doc_path}]" in ctx.msg.content
assert ctx.msg.media == []
@pytest.mark.asyncio
async def test_pending_followup_references_documents_when_extraction_disabled(
tmp_path: Path,
monkeypatch: pytest.MonkeyPatch,
) -> None:
doc_path = tmp_path / "followup.txt"
doc_path.write_text("Do not inject this file body", encoding="utf-8")
captured_messages: list[list[dict]] = []
call_count = {"n": 0}
async def chat_with_retry(*, messages: list[dict], **kwargs: object) -> LLMResponse:
call_count["n"] += 1
captured_messages.append([dict(message) for message in messages])
return LLMResponse(content=f"answer-{call_count['n']}", tool_calls=[], usage={})
loop = _make_loop(tmp_path, ChannelsConfig(extract_document_text=False))
loop.provider.chat_with_retry = chat_with_retry
loop.tools.get_definitions = MagicMock(return_value=[])
def fail_extract_documents(content: str, media: list[str]) -> tuple[str, list[str]]:
raise AssertionError("document extraction should be disabled")
monkeypatch.setattr("nanobot.agent.loop.extract_documents", fail_extract_documents)
pending_queue: asyncio.Queue[InboundMessage] = asyncio.Queue()
await pending_queue.put(
InboundMessage(
channel="cli",
sender_id="u",
chat_id="c",
content="check this",
media=[str(doc_path)],
)
)
final_content, _, _, _, had_injections = await loop._run_agent_loop(
[{"role": "user", "content": "hello"}],
channel="cli",
chat_id="c",
pending_queue=pending_queue,
)
assert final_content == "answer-2"
assert had_injections is True
injected_user_content = [
message["content"]
for message in captured_messages[-1]
if message.get("role") == "user" and isinstance(message.get("content"), str)
][-1]
assert "check this" in injected_user_content
assert f"[Attachment: {doc_path}]" in injected_user_content
assert "Do not inject this file body" not in injected_user_content
def test_document_extraction_disabled_still_preserves_images(tmp_path: Path) -> None:
image_path = tmp_path / "chart.png"
image_path.write_bytes(
base64.b64decode(
"iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mP8/x8AAwMCAO+yF9kAAAAASUVORK5CYII="
)
)
doc_path = tmp_path / "report.txt"
doc_path.write_text("manual extraction target", encoding="utf-8")
content, media = reference_non_image_attachments(
"review these",
[str(image_path), str(doc_path)],
)
assert media == [str(image_path)]
assert f"[Attachment: {doc_path}]" in content
-30
View File
@@ -56,38 +56,8 @@ async def test_fallback_on_error() -> None:
assert result is True
@pytest.mark.asyncio
async def test_fallback_can_fail_closed() -> None:
class FailingProvider(DummyProvider):
async def chat(self, *args, **kwargs) -> LLMResponse:
raise RuntimeError("provider down")
provider = FailingProvider([])
result = await evaluate_response(
"some response",
"some task",
provider,
"m",
default_notify=False,
)
assert result is False
@pytest.mark.asyncio
async def test_no_tool_call_fallback() -> None:
provider = DummyProvider([LLMResponse(content="I think you should notify", tool_calls=[])])
result = await evaluate_response("some response", "some task", provider, "m")
assert result is True
@pytest.mark.asyncio
async def test_no_tool_call_can_fail_closed() -> None:
provider = DummyProvider([LLMResponse(content="I think you should notify", tool_calls=[])])
result = await evaluate_response(
"some response",
"some task",
provider,
"m",
default_notify=False,
)
assert result is False
+336
View File
@@ -0,0 +1,336 @@
import asyncio
import pytest
from nanobot.heartbeat.service import HeartbeatService
from nanobot.providers.base import LLMProvider, LLMResponse, ToolCallRequest
from nanobot.utils.llm_runtime import LLMRuntime
class DummyProvider(LLMProvider):
def __init__(self, responses: list[LLMResponse]):
super().__init__()
self._responses = list(responses)
self.calls = 0
self.models: list[str | None] = []
async def chat(self, *args, **kwargs) -> LLMResponse:
self.calls += 1
self.models.append(kwargs.get("model"))
if self._responses:
return self._responses.pop(0)
return LLMResponse(content="", tool_calls=[])
def get_default_model(self) -> str:
return "test-model"
@pytest.mark.asyncio
async def test_start_is_idempotent(tmp_path) -> None:
provider = DummyProvider([])
service = HeartbeatService(
workspace=tmp_path,
provider=provider,
model="openai/gpt-4o-mini",
interval_s=9999,
enabled=True,
)
await service.start()
first_task = service._task
await service.start()
assert service._task is first_task
service.stop()
await asyncio.sleep(0)
@pytest.mark.asyncio
async def test_decide_returns_skip_when_no_tool_call(tmp_path) -> None:
provider = DummyProvider([LLMResponse(content="no tool call", tool_calls=[])])
service = HeartbeatService(
workspace=tmp_path,
provider=provider,
model="openai/gpt-4o-mini",
)
action, tasks = await service._decide("heartbeat content")
assert action == "skip"
assert tasks == ""
@pytest.mark.asyncio
async def test_trigger_now_executes_when_decision_is_run(tmp_path) -> None:
(tmp_path / "HEARTBEAT.md").write_text("- [ ] do thing", encoding="utf-8")
provider = DummyProvider([
LLMResponse(
content="",
tool_calls=[
ToolCallRequest(
id="hb_1",
name="heartbeat",
arguments={"action": "run", "tasks": "check open tasks"},
)
],
)
])
called_with: list[str] = []
async def _on_execute(tasks: str) -> str:
called_with.append(tasks)
return "done"
service = HeartbeatService(
workspace=tmp_path,
provider=provider,
model="openai/gpt-4o-mini",
on_execute=_on_execute,
)
result = await service.trigger_now()
assert result == "done"
assert called_with == ["check open tasks"]
@pytest.mark.asyncio
async def test_trigger_now_returns_none_when_decision_is_skip(tmp_path) -> None:
(tmp_path / "HEARTBEAT.md").write_text("- [ ] do thing", encoding="utf-8")
provider = DummyProvider([
LLMResponse(
content="",
tool_calls=[
ToolCallRequest(
id="hb_1",
name="heartbeat",
arguments={"action": "skip"},
)
],
)
])
async def _on_execute(tasks: str) -> str:
return tasks
service = HeartbeatService(
workspace=tmp_path,
provider=provider,
model="openai/gpt-4o-mini",
on_execute=_on_execute,
)
assert await service.trigger_now() is None
@pytest.mark.asyncio
async def test_tick_notifies_when_evaluator_says_yes(tmp_path, monkeypatch) -> None:
"""Phase 1 run -> Phase 2 execute -> Phase 3 evaluate=notify -> on_notify called."""
(tmp_path / "HEARTBEAT.md").write_text("- [ ] check deployments", encoding="utf-8")
provider = DummyProvider([
LLMResponse(
content="",
tool_calls=[
ToolCallRequest(
id="hb_1",
name="heartbeat",
arguments={"action": "run", "tasks": "check deployments"},
)
],
),
])
executed: list[str] = []
notified: list[str] = []
async def _on_execute(tasks: str) -> str:
executed.append(tasks)
return "deployment failed on staging"
async def _on_notify(response: str) -> None:
notified.append(response)
service = HeartbeatService(
workspace=tmp_path,
provider=provider,
model="openai/gpt-4o-mini",
on_execute=_on_execute,
on_notify=_on_notify,
)
async def _eval_notify(*a, **kw):
return True
monkeypatch.setattr("nanobot.utils.evaluator.evaluate_response", _eval_notify)
await service._tick()
assert executed == ["check deployments"]
assert notified == ["deployment failed on staging"]
@pytest.mark.asyncio
async def test_tick_suppresses_when_evaluator_says_no(tmp_path, monkeypatch) -> None:
"""Phase 1 run -> Phase 2 execute -> Phase 3 evaluate=silent -> on_notify NOT called."""
(tmp_path / "HEARTBEAT.md").write_text("- [ ] check status", encoding="utf-8")
provider = DummyProvider([
LLMResponse(
content="",
tool_calls=[
ToolCallRequest(
id="hb_1",
name="heartbeat",
arguments={"action": "run", "tasks": "check status"},
)
],
),
])
executed: list[str] = []
notified: list[str] = []
async def _on_execute(tasks: str) -> str:
executed.append(tasks)
return "everything is fine, no issues"
async def _on_notify(response: str) -> None:
notified.append(response)
service = HeartbeatService(
workspace=tmp_path,
provider=provider,
model="openai/gpt-4o-mini",
on_execute=_on_execute,
on_notify=_on_notify,
)
async def _eval_silent(*a, **kw):
return False
monkeypatch.setattr("nanobot.utils.evaluator.evaluate_response", _eval_silent)
await service._tick()
assert executed == ["check status"]
assert notified == []
def test_tick_uses_runtime_provider_and_model(tmp_path, monkeypatch) -> None:
"""Preset changes must apply to heartbeat decision and post-run evaluation."""
(tmp_path / "HEARTBEAT.md").write_text("- [ ] check runtime model", encoding="utf-8")
runtime_provider = DummyProvider([
LLMResponse(
content="",
tool_calls=[
ToolCallRequest(
id="hb_1",
name="heartbeat",
arguments={"action": "run", "tasks": "check runtime model"},
)
],
),
])
runtime_model = "openai/gpt-4.1"
executed: list[str] = []
evaluated: list[tuple[LLMProvider, str]] = []
async def _on_execute(tasks: str) -> str:
executed.append(tasks)
return "runtime model produced a user-facing update"
async def _eval_capture(response, tasks, provider, model):
evaluated.append((provider, model))
return False
service = HeartbeatService(
workspace=tmp_path,
llm_runtime=lambda: LLMRuntime(runtime_provider, runtime_model),
on_execute=_on_execute,
)
monkeypatch.setattr("nanobot.utils.evaluator.evaluate_response", _eval_capture)
asyncio.run(service._tick())
assert runtime_provider.calls == 1
assert runtime_provider.models == [runtime_model]
assert executed == ["check runtime model"]
assert evaluated == [(runtime_provider, runtime_model)]
@pytest.mark.asyncio
async def test_decide_retries_transient_error_then_succeeds(tmp_path, monkeypatch) -> None:
provider = DummyProvider([
LLMResponse(content="429 rate limit", finish_reason="error"),
LLMResponse(
content="",
tool_calls=[
ToolCallRequest(
id="hb_1",
name="heartbeat",
arguments={"action": "run", "tasks": "check open tasks"},
)
],
),
])
delays: list[int] = []
async def _fake_sleep(delay: int) -> None:
delays.append(delay)
monkeypatch.setattr(asyncio, "sleep", _fake_sleep)
service = HeartbeatService(
workspace=tmp_path,
provider=provider,
model="openai/gpt-4o-mini",
)
action, tasks = await service._decide("heartbeat content")
assert action == "run"
assert tasks == "check open tasks"
assert provider.calls == 2
assert delays == [1]
@pytest.mark.asyncio
async def test_decide_prompt_includes_current_time(tmp_path) -> None:
"""Phase 1 user prompt must contain current time so the LLM can judge task urgency."""
captured_messages: list[dict] = []
class CapturingProvider(LLMProvider):
async def chat(self, *, messages=None, **kwargs) -> LLMResponse:
if messages:
captured_messages.extend(messages)
return LLMResponse(
content="",
tool_calls=[
ToolCallRequest(
id="hb_1", name="heartbeat",
arguments={"action": "skip"},
)
],
)
def get_default_model(self) -> str:
return "test-model"
service = HeartbeatService(
workspace=tmp_path,
provider=CapturingProvider(),
model="test-model",
)
await service._decide("- [ ] check servers at 10:00 UTC")
user_msg = captured_messages[1]
assert user_msg["role"] == "user"
assert "Current Time:" in user_msg["content"]
@@ -1,91 +0,0 @@
import asyncio
from unittest.mock import AsyncMock, MagicMock
import pytest
from nanobot.agent.loop import AgentLoop
from nanobot.bus.events import OutboundMessage
from nanobot.bus.queue import MessageBus
from nanobot.providers.base import GenerationSettings, LLMResponse
def _make_loop(tmp_path):
bus = MessageBus()
provider = MagicMock()
provider.get_default_model.return_value = "test-model"
provider.generation = GenerationSettings(max_tokens=0)
provider.estimate_prompt_tokens.return_value = (0, "test-counter")
response = LLMResponse(content="done", tool_calls=[])
provider.chat_with_retry = AsyncMock(return_value=response)
provider.chat_stream_with_retry = AsyncMock(return_value=response)
loop = AgentLoop(
bus=bus,
provider=provider,
workspace=tmp_path,
model="test-model",
)
loop.tools.get_definitions = MagicMock(return_value=[])
return loop
@pytest.mark.asyncio
async def test_process_direct_websocket_clears_run_status(tmp_path) -> None:
loop = _make_loop(tmp_path)
response = await loop.process_direct(
"deliver reminder",
session_key="cron:reminder-1",
channel="websocket",
chat_id="chat-1",
)
assert response is not None
assert response.content == "done"
events = []
while loop.bus.outbound_size:
events.append(await loop.bus.consume_outbound())
statuses = [
event.metadata
for event in events
if event.metadata.get("_goal_status") is True
]
assert [status["goal_status"] for status in statuses] == ["running", "idle"]
assert isinstance(statuses[0].get("started_at"), float)
assert "started_at" not in statuses[1]
@pytest.mark.asyncio
async def test_process_direct_reuses_existing_session_lock(tmp_path) -> None:
loop = _make_loop(tmp_path)
loop._connect_mcp = AsyncMock()
session_key = "api:fixed"
lock = loop._session_locks.setdefault(session_key, asyncio.Lock())
await lock.acquire()
entered = asyncio.Event()
async def _process_message(msg, **_kwargs):
entered.set()
return OutboundMessage(channel=msg.channel, chat_id=msg.chat_id, content=msg.content)
loop._process_message = _process_message
task = asyncio.create_task(loop.process_direct("direct", session_key=session_key))
try:
await asyncio.sleep(0)
assert not entered.is_set()
lock.release()
response = await asyncio.wait_for(task, timeout=1.0)
assert entered.is_set()
assert response is not None
assert response.content == "direct"
finally:
if lock.locked():
lock.release()
if not task.done():
task.cancel()
with pytest.raises(asyncio.CancelledError):
await task
+7 -13
View File
@@ -17,7 +17,6 @@ from nanobot.session.webui_turns import (
WEBUI_SESSION_METADATA_KEY,
WEBUI_TITLE_METADATA_KEY,
WebuiTurnCoordinator,
clean_generated_title,
maybe_generate_webui_title,
)
from nanobot.utils.llm_runtime import LLMRuntime
@@ -54,11 +53,6 @@ def test_agent_loop_llm_runtime_reflects_current_provider_and_model(tmp_path: Pa
assert runtime.model == "next-model"
def test_clean_generated_title_strips_reasoning_tags() -> None:
assert clean_generated_title("<think>reasoning</think> WebUI polish") == "WebUI polish"
assert clean_generated_title("Title: <think> The user said hello") == ""
@pytest.mark.asyncio
async def test_generate_webui_title_only_for_marked_webui_sessions(tmp_path: Path) -> None:
loop = _make_full_loop(tmp_path)
@@ -608,17 +602,17 @@ async def test_process_message_uses_explicit_session_metadata_for_goal_context(
chat_session = loop.sessions.get_or_create("websocket:chat-with-goal")
chat_session.metadata[GOAL_STATE_KEY] = {
"status": "active",
"objective": "This chat goal must not leak into system.",
"objective": "This chat goal must not leak into heartbeat.",
}
loop.sessions.save(chat_session)
system_session = loop.sessions.get_or_create("system")
system_session = loop.sessions.get_or_create("heartbeat")
system_session.metadata = {}
loop.sessions.save(system_session)
loop.context.build_messages = MagicMock( # type: ignore[method-assign]
return_value=[
{"role": "system", "content": "system"},
{"role": "user", "content": "runtime + system"},
{"role": "user", "content": "runtime + heartbeat"},
]
)
loop._run_agent_loop = AsyncMock(return_value=( # type: ignore[method-assign]
@@ -626,7 +620,7 @@ async def test_process_message_uses_explicit_session_metadata_for_goal_context(
[],
[
{"role": "system", "content": "system"},
{"role": "user", "content": "runtime + system"},
{"role": "user", "content": "runtime + heartbeat"},
{"role": "assistant", "content": "ok"},
],
"stop",
@@ -636,11 +630,11 @@ async def test_process_message_uses_explicit_session_metadata_for_goal_context(
result = await loop._process_message(
InboundMessage(
channel="websocket",
sender_id="system",
sender_id="heartbeat",
chat_id="chat-with-goal",
content="system work",
content="heartbeat work",
),
session_key="system",
session_key="heartbeat",
)
assert result is not None
-176
View File
@@ -2,39 +2,12 @@
from __future__ import annotations
import asyncio
from contextlib import AsyncExitStack
from typing import Any
from unittest.mock import MagicMock
import pytest
from nanobot.agent.loop import AgentLoop
from nanobot.agent.tools import mcp as mcp_runtime
from nanobot.agent.tools.base import Tool
from nanobot.bus.queue import MessageBus
from nanobot.config.loader import load_config, save_config
from nanobot.config.schema import MCPServerConfig
class _FakeMcpTool(Tool):
def __init__(self, name: str) -> None:
self._name = name
@property
def name(self) -> str:
return self._name
@property
def description(self) -> str:
return "fake MCP tool"
@property
def parameters(self) -> dict[str, Any]:
return {"type": "object", "properties": {}}
async def execute(self, **_kwargs: Any) -> str:
return "ok"
def _make_loop(tmp_path, *, mcp_servers: dict | None = None) -> AgentLoop:
@@ -69,152 +42,3 @@ async def test_connect_mcp_retries_when_no_servers_connect(tmp_path, monkeypatch
assert attempts == 2
assert loop._mcp_connected is False
assert loop._mcp_stacks == {}
@pytest.mark.asyncio
async def test_reload_mcp_servers_adds_and_removes_tools_without_restart(
tmp_path,
monkeypatch: pytest.MonkeyPatch,
):
config_path = tmp_path / "config.json"
monkeypatch.setattr("nanobot.config.loader._current_config_path", config_path)
config = load_config()
config.tools.mcp_servers["browserbase"] = MCPServerConfig(
type="stdio",
command="browserbase-mcp",
)
save_config(config)
closed: list[str] = []
async def _mark_closed(name: str) -> None:
closed.append(name)
async def _fake_connect(servers, registry):
stacks = {}
for name in servers:
registry.register(_FakeMcpTool(f"mcp_{name}_navigate"))
stack = AsyncExitStack()
await stack.__aenter__()
stack.push_async_callback(_mark_closed, name)
stacks[name] = stack
return stacks
monkeypatch.setattr("nanobot.agent.tools.mcp.connect_mcp_servers", _fake_connect)
loop = _make_loop(tmp_path, mcp_servers={})
added = await mcp_runtime.reload_servers(loop, loop.tools)
assert added["ok"] is True
assert added["added"] == ["browserbase"]
assert loop.tools.has("mcp_browserbase_navigate")
assert "browserbase" in loop._mcp_stacks
config = load_config()
del config.tools.mcp_servers["browserbase"]
save_config(config)
removed = await mcp_runtime.reload_servers(loop, loop.tools)
assert removed["ok"] is True
assert removed["removed"] == ["browserbase"]
assert not loop.tools.has("mcp_browserbase_navigate")
assert "browserbase" not in loop._mcp_stacks
assert closed == ["browserbase"]
@pytest.mark.asyncio
async def test_request_mcp_reload_reaches_runtime_control_without_restart(
tmp_path,
monkeypatch: pytest.MonkeyPatch,
):
config_path = tmp_path / "config.json"
monkeypatch.setattr("nanobot.config.loader._current_config_path", config_path)
config = load_config()
config.tools.mcp_servers["browserbase"] = MCPServerConfig(
type="stdio",
command="browserbase-mcp",
)
save_config(config)
closed: list[str] = []
async def _mark_closed(name: str) -> None:
closed.append(name)
async def _fake_connect(servers, registry):
stacks = {}
for name in servers:
registry.register(_FakeMcpTool(f"mcp_{name}_navigate"))
stack = AsyncExitStack()
await stack.__aenter__()
stack.push_async_callback(_mark_closed, name)
stacks[name] = stack
return stacks
monkeypatch.setattr("nanobot.agent.tools.mcp.connect_mcp_servers", _fake_connect)
loop = _make_loop(tmp_path, mcp_servers={})
async def _handle_one_runtime_control() -> None:
msg = await loop.bus.consume_inbound()
handled = await mcp_runtime.handle_runtime_control(loop, msg, loop.tools)
assert handled is True
consumer = asyncio.create_task(_handle_one_runtime_control())
result = await mcp_runtime.request_mcp_reload(loop.bus, timeout=2.0)
await consumer
assert result["ok"] is True
assert result["added"] == ["browserbase"]
assert result["requires_restart"] is False
assert loop.tools.has("mcp_browserbase_navigate")
config = load_config()
del config.tools.mcp_servers["browserbase"]
save_config(config)
consumer = asyncio.create_task(_handle_one_runtime_control())
result = await mcp_runtime.request_mcp_reload(loop.bus, timeout=2.0)
await consumer
assert result["ok"] is True
assert result["removed"] == ["browserbase"]
assert result["requires_restart"] is False
assert not loop.tools.has("mcp_browserbase_navigate")
assert closed == ["browserbase"]
@pytest.mark.asyncio
async def test_reload_mcp_servers_retries_configured_server_without_live_stack(
tmp_path,
monkeypatch: pytest.MonkeyPatch,
):
config_path = tmp_path / "config.json"
monkeypatch.setattr("nanobot.config.loader._current_config_path", config_path)
config = load_config()
config.tools.mcp_servers["browserbase"] = MCPServerConfig(
type="stdio",
command="browserbase-mcp",
)
save_config(config)
async def _fake_connect(servers, registry):
stacks = {}
for name in servers:
registry.register(_FakeMcpTool(f"mcp_{name}_navigate"))
stack = AsyncExitStack()
await stack.__aenter__()
stacks[name] = stack
return stacks
monkeypatch.setattr("nanobot.agent.tools.mcp.connect_mcp_servers", _fake_connect)
loop = _make_loop(tmp_path, mcp_servers={"browserbase": config.tools.mcp_servers["browserbase"]})
result = await mcp_runtime.reload_servers(loop, loop.tools)
assert result["ok"] is True
assert result["added"] == []
assert result["changed"] == []
assert result["retried"] == ["browserbase"]
assert loop.tools.has("mcp_browserbase_navigate")
await loop.close_mcp()

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