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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.
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*.egg-info
dist/
build/
nanobot/web/dist/
.git
.env
.assets
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@@ -6,8 +6,6 @@
.env
.web
.orion
nanobot-desktop/
desktop/
# Claude / AI assistant artifacts
docs/superpowers/
@@ -100,4 +98,3 @@ tmp/
temp/
*.tmp
exp/
.playwright-mcp/
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@@ -1,82 +0,0 @@
This file provides guidance to AI coding agents working with this repository.
## Project Overview
nanobot is a lightweight, open-source AI agent framework written in Python with a React/TypeScript WebUI. It centers around a small agent loop that receives messages from chat channels, invokes an LLM provider, executes tools, and manages session memory.
## Development Commands
```bash
# Python: run single test / lint
pytest tests/test_openai_api.py::test_function -v
ruff check nanobot/
# WebUI: dev server (proxies API/WS to gateway :8765), build, test
# Build outputs to ../nanobot/web/dist (bundled into the Python wheel)
cd webui && bun run dev # or NANOBOT_API_URL=... bun run dev
cd webui && bun run build
cd webui && bun run test
# Gateway
nanobot gateway
```
## High-Level Architecture
### Core Data Flow
Messages flow through an async `MessageBus` (`nanobot/bus/queue.py`) that decouples chat channels from the agent core:
1. **Channels** (`nanobot/channels/`) receive messages from external platforms and publish `InboundMessage` events to the bus.
2. **`AgentLoop`** (`nanobot/agent/loop.py`) consumes inbound messages, builds context, and coordinates the turn.
3. **`AgentRunner`** (`nanobot/agent/runner.py`) handles the actual LLM conversation loop: send messages to the provider, receive tool calls, execute tools, and stream responses.
4. Responses are published as `OutboundMessage` events back to the appropriate channel.
### Key Subsystems
- **Agent Loop** (`nanobot/agent/loop.py`, `runner.py`): The core processing engine. `AgentLoop` manages session keys, hooks, and context building. `AgentRunner` executes the multi-turn LLM conversation with tool execution.
- **LLM Providers** (`nanobot/providers/`): Provider implementations (Anthropic, OpenAI-compatible, OpenAI Responses API, Azure, Bedrock, GitHub Copilot, OpenAI Codex, etc.) built on a common base (`base.py`). Includes image generation (`image_generation.py`) and audio transcription (`transcription.py`). `factory.py` and `registry.py` handle instantiation and model discovery.
- **Channels** (`nanobot/channels/`): Platform integrations (Telegram, Discord, Slack, Feishu, Matrix, WhatsApp, QQ, WeChat, WeCom, DingTalk, Email, MoChat, MS Teams, WebSocket). `manager.py` discovers and coordinates them. Channels are auto-discovered via `pkgutil` scan + entry-point plugins.
- **Tools** (`nanobot/agent/tools/`): Agent capabilities exposed to the LLM: filesystem (read/write/edit/list), shell execution (with sandbox backends), web search/fetch, MCP servers, cron, notebook editing, subagent spawning, long-running tasks / sustained goals (`long_task.py`), image generation, and self-modification. Tools are auto-discovered via `pkgutil` scan + entry-point plugins.
- **Memory** (`nanobot/agent/memory.py`): Session history persistence with Dream two-phase memory consolidation. Uses atomic writes with fsync for durability.
- **Session Management** (`nanobot/session/`): Per-session history, context compaction, TTL-based auto-compaction (`manager.py`), and sustained goal state tracking (`goal_state.py`).
- **Config** (`nanobot/config/schema.py`, `loader.py`): Pydantic-based configuration loaded from `~/.nanobot/config.json`. Supports camelCase aliases for JSON compatibility.
- **Bridge** (`bridge/`): TypeScript services (e.g. WhatsApp bridge) bundled into the wheel via `pyproject.toml` `force-include`.
- **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).
- **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.
### Entry Points
- **CLI**: `nanobot/cli/commands.py`
- **Python SDK**: `nanobot/nanobot.py`
## Project-Specific Notes
- Architecture constraints: [`.agent/design.md`](.agent/design.md)
- Security boundaries: [`.agent/security.md`](.agent/security.md)
- Common gotchas: [`.agent/gotchas.md`](.agent/gotchas.md)
## Branching Strategy
See [`CONTRIBUTING.md`](./CONTRIBUTING.md) for the full two-branch model (`main` vs `nightly`) and PR guidelines.
## Code Style
- Python 3.11+, asyncio throughout.
- Line length: 100.
- Linting: `ruff` with rules E, F, I, N, W (E501 ignored).
- pytest with `asyncio_mode = "auto"`.
## Common File Locations
- Config schema: `nanobot/config/schema.py`
- Provider base / new provider template: `nanobot/providers/base.py`
- Channel base / new channel template: `nanobot/channels/base.py`
- Tool registry: `nanobot/agent/tools/registry.py`
- WebUI dev proxy config: `webui/vite.config.ts`
- Tests mirror the `nanobot/` package structure.
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@@ -1 +1,84 @@
@AGENTS.md
# CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
## Project Overview
nanobot is a lightweight, open-source AI agent framework written in Python with a React/TypeScript WebUI. It centers around a small agent loop that receives messages from chat channels, invokes an LLM provider, executes tools, and manages session memory.
## Development Commands
```bash
# Python: run single test / lint
pytest tests/test_openai_api.py::test_function -v
ruff check nanobot/
# WebUI: dev server (proxies API/WS to gateway :8765), build, test
# Build outputs to ../nanobot/web/dist (bundled into the Python wheel)
cd webui && bun run dev # or NANOBOT_API_URL=... bun run dev
cd webui && bun run build
cd webui && bun run test
# Gateway
nanobot gateway
```
## High-Level Architecture
### Core Data Flow
Messages flow through an async `MessageBus` (`nanobot/bus/queue.py`) that decouples chat channels from the agent core:
1. **Channels** (`nanobot/channels/`) receive messages from external platforms and publish `InboundMessage` events to the bus.
2. **`AgentLoop`** (`nanobot/agent/loop.py`) consumes inbound messages, builds context, and coordinates the turn.
3. **`AgentRunner`** (`nanobot/agent/runner.py`) handles the actual LLM conversation loop: send messages to the provider, receive tool calls, execute tools, and stream responses.
4. Responses are published as `OutboundMessage` events back to the appropriate channel.
### Key Subsystems
- **Agent Loop** (`nanobot/agent/loop.py`, `runner.py`): The core processing engine. `AgentLoop` manages session keys, hooks, and context building. `AgentRunner` executes the multi-turn LLM conversation with tool execution.
- **LLM Providers** (`nanobot/providers/`): Provider implementations (Anthropic, OpenAI-compatible, OpenAI Responses API, Azure, Bedrock, GitHub Copilot, OpenAI Codex, etc.) built on a common base (`base.py`). Includes image generation (`image_generation.py`) and audio transcription (`transcription.py`). `factory.py` and `registry.py` handle instantiation and model discovery.
- **Channels** (`nanobot/channels/`): Platform integrations (Telegram, Discord, Slack, Feishu, Matrix, WhatsApp, QQ, WeChat, WeCom, DingTalk, Email, MoChat, MS Teams, WebSocket). `manager.py` discovers and coordinates them. Channels are auto-discovered via `pkgutil` scan + entry-point plugins.
- **Tools** (`nanobot/agent/tools/`): Agent capabilities exposed to the LLM: filesystem (read/write/edit/list), shell execution (with sandbox backends), web search/fetch, MCP servers, cron, notebook editing, subagent spawning, long-running tasks / sustained goals (`long_task.py`), image generation, and self-modification. Tools are auto-discovered via `pkgutil` scan + entry-point plugins.
- **Memory** (`nanobot/agent/memory.py`): Session history persistence with Dream two-phase memory consolidation. Uses atomic writes with fsync for durability.
- **Session Management** (`nanobot/session/`): Per-session history, context compaction, TTL-based auto-compaction (`manager.py`), and sustained goal state tracking (`goal_state.py`).
- **Config** (`nanobot/config/schema.py`, `loader.py`): Pydantic-based configuration loaded from `~/.nanobot/config.json`. Supports camelCase aliases for JSON compatibility.
- **Bridge** (`bridge/`): TypeScript services (e.g. WhatsApp bridge) bundled into the wheel via `pyproject.toml` `force-include`.
- **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/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.
### Entry Points
- **CLI**: `nanobot/cli/commands.py`
- **Python SDK**: `nanobot/nanobot.py`
## Project-Specific Notes
- Architecture constraints: [`.agent/design.md`](.agent/design.md)
- Security boundaries: [`.agent/security.md`](.agent/security.md)
- Common gotchas: [`.agent/gotchas.md`](.agent/gotchas.md)
## Branching Strategy
See [`CONTRIBUTING.md`](./CONTRIBUTING.md) for the full two-branch model (`main` vs `nightly`) and PR guidelines.
## Code Style
- Python 3.11+, asyncio throughout.
- Line length: 100.
- Linting: `ruff` with rules E, F, I, N, W (E501 ignored).
- pytest with `asyncio_mode = "auto"`.
## Common File Locations
- Config schema: `nanobot/config/schema.py`
- Provider base / new provider template: `nanobot/providers/base.py`
- Channel base / new channel template: `nanobot/channels/base.py`
- Tool registry: `nanobot/agent/tools/registry.py`
- WebUI dev proxy config: `webui/vite.config.ts`
- Tests mirror the `nanobot/` package structure.
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@@ -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 |
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@@ -25,7 +25,7 @@ RUN mkdir -p nanobot bridge && touch nanobot/__init__.py && \
COPY nanobot/ nanobot/
COPY bridge/ bridge/
COPY webui/ webui/
RUN NANOBOT_FORCE_WEBUI_BUILD=1 uv pip install --system --no-cache .
RUN uv pip install --system --no-cache .
# Build the WhatsApp bridge
WORKDIR /app/bridge
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@@ -1,4 +1,4 @@
![nanobot README cover](./images/readme-cover.png)
![cover-v5-optimized](./images/GitHub_README.png)
<div align="center">
<p>
@@ -31,29 +31,10 @@
</p>
</div>
🐈 **nanobot** is an open-source, ultra-lightweight agent runtime for people who want to own their AI agent stack. It gives you a small, readable core plus the practical pieces for real long-running agents: WebUI, chat channels, tools, memory, MCP, model routing, and deployment.
🐈 **nanobot** is an open-source and ultra-lightweight AI agent in the spirit of [OpenClaw](https://github.com/openclaw/openclaw), [Claude Code](https://www.anthropic.com/claude-code), and [Codex](https://www.openai.com/codex/). It keeps the core agent loop small and readable while still supporting chat channels, memory, MCP and practical deployment paths, so you can go from local setup to a long-running personal agent with minimal overhead.
## 📢 News
- **2026-05-30** 🔐 Safer Matrix verification, bounded media downloads, clearer WebUI model timeline.
- **2026-05-29** 🧩 Extension registry, context-window tuning, document extraction controls.
- **2026-05-28** 🗂️ Project workspaces, access controls, steadier goals and streaming.
- **2026-05-27** ⏱️ Codex streams respect idle timeouts during long runs.
- **2026-05-26** 📡 Telegram webhooks, refreshed Kagi search, cleaner transport errors.
- **2026-05-25** 🔌 Unified CLI Apps and MCP, Step Plan support, steadier sustained goals.
- **2026-05-24** 🧰 MCP presets, richer slash actions, configurable OpenAI-compatible requests.
- **2026-05-23** 🖼️ Zhipu image generation, longer exec windows, cleaner transcription config.
- **2026-05-22** 🛠️ CLI Apps, more image providers, safer web redirects and edits.
- **2026-05-21** ⚡ Novita provider, faster sidebar, smoother coding tools and Weixin replies.
<details>
<summary>Earlier news</summary>
- **2026-05-20** 📶 Signal channel, faster gateway startup, multilingual README links.
- **2026-05-19** 🎨 Image provider registry, StepFun and Skywork, stronger WebUI controls.
- **2026-05-18** 🖌️ Gemini and MiniMax images, Ant Ling, live file-edit activity.
- **2026-05-17** 🌊 Smoother WebUI streaming, AutoCompact fixes, buffered CLI reasoning.
- **2026-05-16** 🧠 Atomic Chat provider, goal-aware timeouts, safer exec URL handling.
- **2026-05-15** 🚀 Released **v0.2.0****`/goal`** holds sustained objectives across turns, WebUI now ships inside the wheel, image generation end to end, 5 new providers with `fallback_models`, and a real agent-loop refactor. Please see [release notes](https://github.com/HKUDS/nanobot/releases/tag/v0.2.0) for details.
- **2026-05-14** 🎯 **`/goal`** for long-term objectives, visible multi-step progress, long-horizon missions in chat.
- **2026-05-13** 🧠 Streaming reasoning before answers, automatic backup models, smoother plug-in reconnects.
@@ -64,6 +45,10 @@
- **2026-05-07** 📜 Locale-aware slash palette in WebUI, LAN login, faithful HTTP streaming responses.
- **2026-05-06** 🧩 Tunable tool hint, steadier voice and plug-in startups, schedules and reminders that stick.
- **2026-05-05** 🛡️ Quiet deny for unknown Telegram chats, Dream cleanup, fuller automation summaries.
<details>
<summary>Earlier news</summary>
- **2026-05-04** 🔐 Safer DingTalk outbound media links, durable cron persistence, DeepSeek polish.
- **2026-05-03** ⚙️ Predictable shell allow-list behavior, isolated chats mid-reply, cleaner interactive retries.
- **2026-05-02** 🐈 LongCat support, smarter token sizing hints, clearer bundled upgrade guidance.
@@ -160,13 +145,12 @@
</details>
## 💡 Why nanobot
## 💡 Key Features of nanobot
- **Persistent workflows**: goals, memory, tools, and chat context survive long-running work.
- **Chat-native reach**: WebUI, API, Telegram, Feishu, Slack, Discord, Teams, and email.
- **Model freedom**: OpenAI-compatible APIs, local LLMs, image generation, search, and fallbacks.
- **Small core**: readable internals with MCP, memory, deployment, and automation built in.
- **Own your stack**: inspect, customize, self-host, and extend without a giant platform.
- **Ultra-lightweight**: stable long-running agent behavior with a small, readable core.
- **Research-ready**: the codebase is intentionally simple enough to study, modify, and extend.
- **Practical**: chat channels, API, memory, MCP, and deployment paths are already built in.
- **Hackable**: you can start fast, then go deeper through repo docs instead of a monolithic landing page.
## 📦 Install
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@@ -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"
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@@ -51,43 +51,6 @@ 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>
@@ -244,7 +207,6 @@ for reliable encryption, password login is recommended instead. If the
"userId": "@nanobot:matrix.org",
"password": "mypasswordhere",
"e2eeEnabled": true,
"sasVerification": true,
"allowFrom": ["@your_user:matrix.org"],
"groupPolicy": "open",
"groupAllowFrom": [],
@@ -264,7 +226,6 @@ for reliable encryption, password login is recommended instead. If the
| `groupAllowFrom` | Room allowlist (used when policy is `allowlist`). |
| `allowRoomMentions` | Accept `@room` mentions in mention mode. |
| `e2eeEnabled` | E2EE support (default `true`). Set `false` for plaintext-only. |
| `sasVerification` | Auto-complete SAS device verification requests from allowed users (default `false`). Useful for Element X, which does not expose manual trust for third-party devices. |
| `maxMediaBytes` | Max attachment size (default `20MB`). Set `0` to block all media. |
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@@ -56,17 +56,17 @@ Preset names come from the top-level `modelPresets` config. Switching is runtime
## Periodic Tasks
The gateway wakes up every 30 minutes and checks `HEARTBEAT.md` in your workspace (`~/.nanobot/workspace/HEARTBEAT.md`). If the file has tasks under `## Active Tasks`, the agent executes them and delivers results to your most recently active chat channel. If there are no active tasks, the heartbeat is skipped silently.
The gateway wakes up every 30 minutes and checks `HEARTBEAT.md` in your workspace (`~/.nanobot/workspace/HEARTBEAT.md`). If the file has tasks, the agent executes them and delivers results to your most recently active chat channel.
**Setup:** edit `~/.nanobot/workspace/HEARTBEAT.md` (created automatically by `nanobot onboard`):
```markdown
## Active Tasks
## Periodic Tasks
- [ ] Check weather forecast and send a summary
- [ ] Scan inbox for urgent emails
```
The agent can also manage this file itself — ask it to "add a periodic task" and it will update `HEARTBEAT.md` for you. Completed tasks should be deleted from the file, not moved to another section.
The agent can also manage this file itself — ask it to "add a periodic task" and it will update `HEARTBEAT.md` for you.
> **Note:** The gateway must be running (`nanobot gateway`) and you must have chatted with the bot at least once so it knows which channel to deliver to.
+3 -107
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@@ -126,10 +126,8 @@ ANTHROPIC_API_KEY="$(bw get password api/anthropic)" nanobot agent
> - **VolcEngine / BytePlus Coding Plan**: Use dedicated providers `volcengineCodingPlan` or `byteplusCodingPlan` instead of the pay-per-use `volcengine` / `byteplus` providers.
> - **Zhipu Coding Plan**: If you're on Zhipu's coding plan, set `"apiBase": "https://open.bigmodel.cn/api/coding/paas/v4"` in your zhipu provider config.
> - **Alibaba Cloud BaiLian**: If you're using Alibaba Cloud BaiLian's OpenAI-compatible endpoint, set `"apiBase": "https://dashscope.aliyuncs.com/compatible-mode/v1"` in your dashscope provider config.
> - **StepFun Step Plan**: If you're on StepFun's Step Plan subscription, set `"apiBase": "https://api.stepfun.com/step_plan/v1"` in your stepfun provider config. Supported models include `step-3.5-flash`, `step-3.5-flash-2603`, and `step-router-v1`.
> - **Step Fun (Mainland China)**: If your API key is from Step Fun's mainland China platform (stepfun.com), set `"apiBase": "https://api.stepfun.com/v1"` in your stepfun provider config.
> - **Xiaomi MiMo thinking mode**: MiMo models (e.g. `mimo-v2.5-pro`) default to enabled thinking. Use `agents.defaults.reasoningEffort: "none"` to disable it, or `"low"` / `"medium"` / `"high"` to keep it on. Omitting the field preserves the provider's per-model default.
> - **Xiaomi MiMo Token Plan**: If you're on MiMo's token plan, set `"apiBase": "https://token-plan-sgp.xiaomimimo.com/v1"` in your xiaomi_mimo provider config.
| Provider | Purpose | Get API Key |
|----------|---------|-------------|
@@ -168,43 +166,6 @@ ANTHROPIC_API_KEY="$(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>
@@ -516,68 +477,6 @@ 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 +942,6 @@ 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 +955,8 @@ 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 +1195,7 @@ 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 +1288,6 @@ 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 +1430,7 @@ 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 -11
View File
@@ -11,23 +11,16 @@
> Official Docker usage currently means building from this repository with the included `Dockerfile`. Docker Hub images under third-party namespaces are not maintained or verified by HKUDS/nanobot; do not mount API keys or bot tokens into them unless you trust the publisher.
> [!IMPORTANT]
> The gateway and WebSocket channel default to `host: "127.0.0.1"` in `config.json` (set in `nanobot/config/schema.py`). Docker `-p` port forwarding cannot reach a container's loopback interface, so for the host or LAN to reach the exposed ports you must set both binds to `0.0.0.0` in `~/.nanobot/config.json` before starting the container. To serve the bundled WebUI from Docker, enable the WebSocket channel and protect bootstrap with a secret:
> The gateway and WebSocket channel default to `host: "127.0.0.1"` in `config.json` (set in `nanobot/config/schema.py`). Docker `-p` port forwarding cannot reach a container's loopback interface, so for the host or LAN to reach the exposed ports you must set both binds to `0.0.0.0` in `~/.nanobot/config.json` before starting the container:
>
> ```json
> {
> "gateway": { "host": "0.0.0.0" },
> "channels": {
> "websocket": {
> "enabled": true,
> "host": "0.0.0.0",
> "port": 8765,
> "tokenIssueSecret": "your-secret-here"
> }
> }
> "gateway": { "host": "0.0.0.0" },
> "channels": { "websocket": { "host": "0.0.0.0" } }
> }
> ```
>
> When the WebSocket `host` is `0.0.0.0`, the channel refuses to start unless `token` or `tokenIssueSecret` is also configured — see [`webui/README.md`](../webui/README.md) for details.
> When `host` is `0.0.0.0`, the gateway refuses to start unless `token` or `tokenIssueSecret` is also configured on the WebSocket channel — see [`webui/README.md`](../webui/README.md) for details.
### Docker Compose
+4 -28
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, Gemini, Ollama, and StepFun configuration examples.
> [!TIP]
> Prefer environment variables for API keys. nanobot resolves `${VAR_NAME}` values from the environment at startup.
@@ -46,7 +46,7 @@ The WebUI hides provider storage details from the user. The agent sees the saved
| Option | Type | Default | Description |
|--------|------|---------|-------------|
| `tools.imageGeneration.enabled` | boolean | `false` | Register the `generate_image` tool |
| `tools.imageGeneration.provider` | string | `"openrouter"` | Image provider name. Supported values: `openrouter`, `aihubmix`, `minimax`, `gemini`, `ollama`, `stepfun`, `zhipu` |
| `tools.imageGeneration.provider` | string | `"openrouter"` | Image provider name. Supported values: `openrouter`, `aihubmix`, `minimax`, `gemini`, `ollama`, `stepfun` |
| `tools.imageGeneration.model` | string | `"openai/gpt-5.4-image-2"` | Provider model name |
| `tools.imageGeneration.defaultAspectRatio` | string | `"1:1"` | Default ratio when the prompt/tool call does not specify one |
| `tools.imageGeneration.defaultImageSize` | string | `"1K"` | Default size hint, for example `1K`, `2K`, `4K`, or `1024x1024` |
@@ -245,31 +245,6 @@ StepPlan is StepFun's subscription tier and uses a different API base URL. The i
`apiBase` takes precedence over the registry default, so with the StepPlan base URL configured, image requests are sent to `https://api.stepfun.com/step_plan/v1/images/generations` — the same path prefix used for LLM calls. The API key is shared with the standard StepFun provider.
### Zhipu
Zhipu (智谱) `glm-image` model supports text-to-image generation. The API returns temporary image URLs (valid for 30 days); nanobot downloads and re-encodes them as base64 data URLs.
Supported aspect ratios: `1:1`, `16:9`, `9:16`, `3:4`, `4:3`. Sizes can be specified as `WIDTHxHEIGHT` (e.g. `1280x1280`, `1728x960`) or using aspect ratio presets.
```json
{
"providers": {
"zhipu": {
"apiKey": "${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 +299,8 @@ 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`, `ollama`, 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 |
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+1 -1
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@@ -22,7 +22,7 @@ def _resolve_version() -> str:
return _pkg_version("nanobot-ai")
except PackageNotFoundError:
# Source checkouts often import nanobot without installed dist-info.
return _read_pyproject_version() or "0.2.1"
return _read_pyproject_version() or "0.2.0"
__version__ = _resolve_version()
+13 -60
View File
@@ -3,51 +3,22 @@
import base64
import mimetypes
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.session.goal_state import goal_state_runtime_lines
from nanobot.utils.helpers import (
current_time_str,
detect_image_mime,
load_bundled_template,
truncate_text,
)
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."""
@@ -68,13 +39,11 @@ class ContextBuilder:
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)
@@ -108,10 +77,9 @@ 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 +123,12 @@ 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}")
@@ -171,9 +138,10 @@ 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
def build_messages(
@@ -189,18 +157,11 @@ class ContextBuilder:
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,
) -> 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)
runtime_ctx = self._build_runtime_context(
@@ -221,15 +182,7 @@ 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:
+75 -186
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
@@ -23,43 +22,32 @@ 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
from nanobot.agent.tools.self import MyTool
from nanobot.bus.events import InboundMessage, OutboundMessage
from nanobot.bus.queue import MessageBus
from nanobot.cli_apps import utils as cli_app_utils
from nanobot.command import CommandContext, CommandRouter, register_builtin_commands
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 import turn_continuation
from nanobot.session.webui_turns import (
WebuiTurnCoordinator,
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 (
@@ -113,7 +101,6 @@ class TurnContext:
save_skip: int = 0
outbound: OutboundMessage | None = None
suppress_response: bool = False
on_progress: Callable[..., Awaitable[None]] | None = None
on_stream: Callable[[str], Awaitable[None]] | None = None
@@ -122,8 +109,8 @@ class TurnContext:
pending_queue: asyncio.Queue | None = None
pending_summary: str | None = None
turn_wall_started_at: float = field(default_factory=time.time)
visible_run_started_at: float | None = None
turn_latency_ms: int | None = None
trace: list[StateTraceEntry] = field(default_factory=list)
@@ -177,7 +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,
@@ -249,10 +235,6 @@ 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] = {}
@@ -280,7 +262,6 @@ 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
@@ -366,7 +347,6 @@ 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,
@@ -482,7 +462,6 @@ 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)
@@ -497,8 +476,26 @@ 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,
@@ -506,7 +503,7 @@ 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
@@ -568,12 +565,10 @@ class AgentLoop:
Returns True if the message was persisted.
"""
if not turn_continuation.should_persist_user_message(msg.metadata):
return False
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 {}) | cli_app_utils.session_extra(msg.metadata)
extra.update(kwargs)
text = msg.content if isinstance(msg.content, str) else ""
session.add_message("user", text, **extra)
@@ -590,7 +585,6 @@ 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),
@@ -599,10 +593,7 @@ class AgentLoop:
chat_id=self._runtime_chat_id(msg),
sender_id=msg.sender_id,
session_summary=pending_summary,
session_metadata=session.metadata,
workspace=scope.project_path,
runtime_state=self,
inbound_message=msg,
session_metadata=session.metadata, current_runtime_lines=cli_app_utils.runtime_lines(msg, self.context.workspace),
)
async def _dispatch_command_inline(
@@ -716,7 +707,7 @@ 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}
@@ -752,31 +743,7 @@ 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
session_metadata = session.metadata if session is not None else None
try:
result = await self.runner.run(AgentRunSpec(
initial_messages=initial_messages,
@@ -787,7 +754,7 @@ 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,
@@ -802,28 +769,17 @@ class AgentLoop:
llm_timeout_s=runner_wall_llm_timeout_s(
self.sessions,
session.key if session is not None else session_key,
metadata=session_metadata,
message_metadata=metadata,
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":
logger.warning("Max iterations ({}) reached", self.max_iterations)
should_stream = turn_continuation.should_stream_budget_response(
stop_reason=result.stop_reason,
pending_queue_available=pending_queue is not None and session is not None,
session_metadata=session_metadata,
message_metadata=metadata,
)
# Push final content through stream so streaming channels (e.g. Feishu)
# update the card instead of leaving it empty.
if on_stream and on_stream_end and should_stream:
if on_stream and on_stream_end:
await on_stream(result.final_content or "")
await on_stream_end(resuming=False)
elif result.stop_reason == "error":
@@ -856,15 +812,13 @@ 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.
@@ -915,13 +869,13 @@ 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"):
@@ -966,8 +920,7 @@ class AgentLoop:
channel=msg.channel, chat_id=msg.chat_id,
content="", metadata=msg.metadata or {},
))
continuing = turn_continuation.internal_continuation_pending(msg.metadata)
if msg.channel == "websocket" and not continuing:
if msg.channel == "websocket":
turn_lat = self._pending_turn_latency_ms.pop(session_key, None)
await self._webui_turns.handle_turn_end(
msg,
@@ -1006,40 +959,28 @@ 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,
)
if not turn_continuation.internal_continuation_pending(msg.metadata):
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."""
@@ -1108,7 +1049,6 @@ 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,
@@ -1118,11 +1058,7 @@ class AgentLoop:
current_role=current_role,
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,
session_metadata=session.metadata, current_runtime_lines=cli_app_utils.runtime_lines(msg, self.context.workspace, skip=is_subagent),
)
t_wall = time.time()
final_content, _, all_msgs, stop_reason, _ = await self._run_agent_loop(
@@ -1182,17 +1118,12 @@ class AgentLoop:
)
key = session_key or msg.session_key
t0 = time.time()
ctx = TurnContext(
msg=msg,
session=None,
session_key=key,
state=TurnState.RESTORE,
turn_id=f"{key}:{time.time_ns()}",
turn_wall_started_at=t0,
visible_run_started_at=turn_continuation.internal_continuation_run_started_at(
msg.metadata,
),
on_progress=on_progress,
on_stream=on_stream,
on_stream_end=on_stream_end,
@@ -1291,7 +1222,7 @@ 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
@@ -1303,7 +1234,6 @@ 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)
@@ -1312,16 +1242,6 @@ 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
@@ -1381,10 +1301,7 @@ 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
@@ -1398,13 +1315,7 @@ class AgentLoop:
return "ok"
async def _state_run(self, ctx: TurnContext) -> str:
if ctx.visible_run_started_at is None:
ctx.visible_run_started_at = time.time()
await self._webui_turns.publish_run_status(
ctx.msg,
"running",
started_at=ctx.visible_run_started_at,
)
await self._webui_turns.publish_run_status(ctx.msg, "running")
result = await self._run_agent_loop(
ctx.initial_messages,
on_progress=ctx.on_progress,
@@ -1425,25 +1336,15 @@ class AgentLoop:
ctx.all_messages = all_msgs
ctx.stop_reason = stop_reason
ctx.had_injections = had_injections
await turn_continuation.maybe_continue_turn(ctx)
return "ok"
async def _state_save(self, ctx: TurnContext) -> str:
turn_continuation.prepare_save_boundary(ctx)
if (
(ctx.final_content is None or not ctx.final_content.strip())
and not ctx.suppress_response
):
if ctx.final_content is None or not ctx.final_content.strip():
ctx.final_content = EMPTY_FINAL_RESPONSE_MESSAGE
latency_started_at = (
ctx.visible_run_started_at
if turn_continuation.internal_continuation_inbound(ctx.msg.metadata)
and ctx.visible_run_started_at is not None
else ctx.turn_wall_started_at
)
ctx.turn_latency_ms = max(0, int((time.time() - latency_started_at) * 1000))
ctx.save_skip = 1 + len(ctx.history) + (1 if ctx.user_persisted_early else 0)
ctx.turn_latency_ms = max(0, int((time.time() - ctx.turn_wall_started_at) * 1000))
self._save_turn(
ctx.session, ctx.all_messages, ctx.save_skip,
turn_latency_ms=ctx.turn_latency_ms,
@@ -1463,9 +1364,6 @@ class AgentLoop:
return "ok"
async def _state_respond(self, ctx: TurnContext) -> str:
if ctx.suppress_response:
ctx.outbound = None
return "ok"
ctx.outbound = self._assemble_outbound(
ctx.msg,
ctx.final_content,
@@ -1706,19 +1604,10 @@ 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,
)
+3 -2
View File
@@ -807,9 +807,10 @@ class Consolidator:
metadata={},
last_consolidated=0,
)
dropped, already_consolidated = probe.retain_recent_legal_suffix(max_suffix)
probe.retain_recent_legal_suffix(max_suffix)
kept = probe.messages
archive_msgs = dropped[already_consolidated:]
cut = len(tail) - len(kept)
archive_msgs = tail[:cut]
if not archive_msgs and not kept:
session.updated_at = datetime.now()
+13 -43
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 +16,12 @@ 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_trackers,
StreamingFileEditTracker,
)
from nanobot.utils.helpers import (
IncrementalThinkExtractor,
@@ -44,7 +42,6 @@ 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 +50,6 @@ 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
@@ -104,8 +97,6 @@ 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 +167,6 @@ 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 +175,12 @@ 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 +196,10 @@ 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 +475,6 @@ 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 +487,7 @@ 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)
@@ -1280,13 +1256,7 @@ 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 "",
)
+69 -7
View File
@@ -88,11 +88,11 @@ def _format_summary(summary: _PatchSummary) -> str:
items=ObjectSchema(
path=StringSchema("Relative path to the file to edit."),
action=StringSchema(
"Operation type: replace or add.",
enum=["replace", "add"],
"Operation type: replace (find and replace text), add (append new content or create file), delete (remove text).",
enum=["replace", "add", "delete"],
),
old_text=StringSchema(
"Exact text to search for in the file. Required for replace.",
"Exact text to search for in the file. Required for replace and delete.",
nullable=True,
),
new_text=StringSchema(
@@ -124,8 +124,7 @@ class ApplyPatchTool(_FsTool):
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. "
"Provide a list of structured edits, each specifying a file path, action (replace/add/delete), and the 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."
)
@@ -141,6 +140,7 @@ class ApplyPatchTool(_FsTool):
raise _PatchError("must provide edits")
writes: dict[Path, str] = {}
deletes: set[Path] = set()
summaries: list[_PatchSummary] = []
for edit in edits:
@@ -183,6 +183,7 @@ class ApplyPatchTool(_FsTool):
if uses_crlf:
new_norm = new_norm.replace("\n", "\r\n")
writes[source] = new_norm
deletes.discard(source)
added, deleted = _line_diff_stats(content, new_norm)
action_name = "update"
else:
@@ -190,6 +191,7 @@ class ApplyPatchTool(_FsTool):
if new_norm and not new_norm.endswith("\n"):
new_norm += "\n"
writes[source] = new_norm
deletes.discard(source)
added = _text_line_count(new_norm)
deleted = 0
action_name = "add"
@@ -244,6 +246,7 @@ class ApplyPatchTool(_FsTool):
new_norm = new_norm.replace("\n", "\r\n")
writes[source] = new_norm
deletes.discard(source)
added, deleted = _line_diff_stats(content, new_norm)
summaries.append(
_PatchSummary(
@@ -251,6 +254,62 @@ class ApplyPatchTool(_FsTool):
)
)
elif action == "delete":
old_text = edit.get("old_text") or ""
if not old_text:
raise _PatchError(f"old_text required for delete: {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}")
if norm_old == norm_content:
deletes.add(source)
writes.pop(source, None)
added, deleted = 0, _text_line_count(content)
summaries.append(
_PatchSummary(
action="delete", path=path, added=added, deleted=deleted
)
)
else:
new_norm = (
norm_content[:pos] + 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
deletes.discard(source)
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}")
@@ -260,10 +319,13 @@ class ApplyPatchTool(_FsTool):
)
backups: dict[Path, bytes | None] = {}
for path in writes:
for path in set(writes) | deletes:
backups[path] = path.read_bytes() if path.exists() else None
try:
for path in deletes:
if path.exists():
path.unlink()
for path, content in writes.items():
path.parent.mkdir(parents=True, exist_ok=True)
path.write_text(content, encoding="utf-8", newline="")
@@ -277,7 +339,7 @@ class ApplyPatchTool(_FsTool):
path.write_bytes(data)
raise
for path in writes:
for path in set(writes) | deletes:
self._file_states.record_write(path)
return "Patch applied:\n" + "\n".join(
_format_summary(summary) for summary in summaries
+3 -9
View File
@@ -9,8 +9,7 @@ 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.cli_apps import CliAppError, CliAppManager, CliAppsRuntimeConfig
from nanobot.config.schema import Base
@@ -114,12 +113,7 @@ class CliAppsTool(Tool):
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)
manager = CliAppManager(workspace=self.workspace, runtime=self.runtime)
try:
return manager.run(
name,
@@ -127,7 +121,7 @@ class CliAppsTool(Tool):
json_output=bool(json),
working_dir=working_dir,
timeout=timeout,
restrict_to_workspace=access.restrict_to_workspace,
restrict_to_workspace=self.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
+29 -36
View File
@@ -3,6 +3,7 @@
from __future__ import annotations
import asyncio
import shutil
import time
import uuid
from contextlib import suppress
@@ -10,13 +11,8 @@ 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,
)
from nanobot.agent.tools.schema import BooleanSchema, IntegerSchema, StringSchema, tool_parameters_schema
DEFAULT_YIELD_MS = 1000
MAX_YIELD_MS = 30_000
@@ -47,7 +43,6 @@ class ExecSessionInfo:
idle_s: float
remaining_s: float
returncode: int | None
owner_session_key: str | None = None
class _ExecSession:
@@ -58,17 +53,14 @@ class _ExecSession:
process: asyncio.subprocess.Process,
command: str,
cwd: str,
timeout: int | None,
owner_session_key: str | None = None,
timeout: int,
) -> 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.deadline = time.monotonic() + timeout
self.last_access = time.monotonic()
self._chunks: list[str] = []
self._lock = asyncio.Lock()
@@ -177,12 +169,11 @@ class ExecSessionManager:
command: str,
cwd: str,
env: dict[str, str],
timeout: int | None,
timeout: int,
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()
@@ -196,7 +187,6 @@ class ExecSessionManager:
command=command,
cwd=cwd,
timeout=timeout,
owner_session_key=owner_session_key,
)
self._sessions[session_id] = session
@@ -215,19 +205,12 @@ class ExecSessionManager:
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)
@@ -252,7 +235,7 @@ class ExecSessionManager:
self._sessions.pop(session_id, None)
return poll
async def list(self, *, owner_session_key: str | None = None) -> list[ExecSessionInfo]:
async def list(self) -> list[ExecSessionInfo]:
async with self._lock:
await self._cleanup_locked()
now = time.monotonic()
@@ -265,12 +248,8 @@ class ExecSessionManager:
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:
@@ -292,11 +271,29 @@ class ExecSessionManager:
shell_program: str | None,
login: bool,
) -> asyncio.subprocess.Process:
from nanobot.agent.tools.shell import ExecTool
from nanobot.agent.tools import shell
return await ExecTool._spawn(
command, cwd, env, shell_program, login,
if shell._IS_WINDOWS:
return await asyncio.create_subprocess_shell(
command,
stdin=asyncio.subprocess.PIPE,
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]
if login and shell_program.rsplit("/", 1)[-1] in {"bash", "zsh"}:
args.append("-l")
args.extend(["-c", command])
return await asyncio.create_subprocess_exec(
*args,
stdin=asyncio.subprocess.PIPE,
stdout=asyncio.subprocess.PIPE,
stderr=asyncio.subprocess.PIPE,
cwd=cwd,
env=env,
)
@@ -479,7 +476,6 @@ class WriteStdinTool(Tool):
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:
@@ -513,7 +509,6 @@ class WriteStdinTool(Tool):
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:
@@ -577,9 +572,7 @@ class ListExecSessionsTool(Tool):
async def execute(self, **kwargs: Any) -> str:
try:
sessions = await self._manager.list(
owner_session_key=current_request_session_key(),
)
sessions = await self._manager.list()
if not sessions:
return "No active exec sessions."
lines = []
+3 -23
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
+17 -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,
@@ -133,22 +131,18 @@ class ImageGenerationTool(Tool):
return cls(**kwargs)
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()
@@ -207,3 +201,11 @@ 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 -27
View File
@@ -4,13 +4,10 @@ from contextvars import ContextVar
from pathlib import Path
from typing import Any, Awaitable, Callable
from loguru import logger
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
@@ -85,10 +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:
@@ -127,14 +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):
"""Acknowledge but don't deliver tool sends (heartbeat internal check)."""
return self._suppress_delivery_var.set(active)
def reset_suppress_delivery(self, token) -> None:
"""Restore previous delivery-suppression state."""
self._suppress_delivery_var.reset(token)
@property
def _sent_in_turn(self) -> bool:
return self._sent_in_turn_var.get()
@@ -164,19 +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(
@@ -255,10 +236,6 @@ class MessageTool(Tool, ContextAware):
metadata=metadata,
)
if self._suppress_delivery_var.get():
logger.debug("MessageTool: delivery suppressed during internal check")
return f"Message acknowledged for {channel}:{chat_id} (not delivered)"
try:
await self._send_callback(msg)
if channel == default_channel and chat_id == default_chat_id:
+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: ...
+2 -3
View File
@@ -101,10 +101,9 @@ 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]:
+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
+25 -81
View File
@@ -16,27 +16,19 @@ 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,
DEFAULT_EXEC_SESSION_MANAGER,
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 BooleanSchema, 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 +46,7 @@ _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)
@@ -67,7 +59,7 @@ class _PreparedCommand:
command: str
cwd: str
env: dict[str, str]
timeout: int | None
timeout: int
shell_program: str | None
login: bool
@@ -148,7 +140,6 @@ 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,
@@ -163,8 +154,6 @@ 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,
@@ -194,9 +183,6 @@ 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
@@ -327,7 +313,6 @@ class ExecTool(Tool):
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,
@@ -339,20 +324,6 @@ class ExecTool(Tool):
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,
@@ -361,39 +332,29 @@ class ExecTool(Tool):
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()
cwd = working_dir or self.working_dir 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:
if self.restrict_to_workspace and self.working_dir:
try:
requested = Path(cwd).expanduser().resolve()
resolved_root = Path(workspace_root).expanduser().resolve()
workspace_root = Path(self.working_dir).expanduser().resolve()
except Exception:
return (
"Error: working_dir could not be resolved"
+ _WORKSPACE_BOUNDARY_NOTE
)
if not is_path_within(requested, resolved_root):
if requested != workspace_root and workspace_root not in requested.parents:
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,
)
guard_error = self._guard_command(command, cwd)
if guard_error:
return guard_error
@@ -404,11 +365,11 @@ class ExecTool(Tool):
self.sandbox,
)
else:
workspace = workspace_root or cwd
workspace = self.working_dir or cwd
command = wrap_command(self.sandbox, command, workspace, cwd)
cwd = str(Path(workspace).resolve())
effective_timeout = self._resolve_timeout(timeout)
effective_timeout = min(timeout or self.timeout, self._MAX_TIMEOUT)
env = self._build_env()
if self.path_append:
@@ -436,23 +397,16 @@ class ExecTool(Tool):
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,
stdin=asyncio.subprocess.DEVNULL,
stdout=asyncio.subprocess.PIPE,
stderr=asyncio.subprocess.PIPE,
cwd=cwd,
@@ -466,7 +420,7 @@ class ExecTool(Tool):
args.extend(["-c", command])
return await asyncio.create_subprocess_exec(
*args,
stdin=stdin,
stdin=asyncio.subprocess.DEVNULL,
stdout=asyncio.subprocess.PIPE,
stderr=asyncio.subprocess.PIPE,
cwd=cwd,
@@ -560,13 +514,7 @@ 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 +534,11 @@ 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 +563,11 @@ 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)"
+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(),
)
+6 -5
View File
@@ -455,16 +455,17 @@ 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:
-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"]
-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)
+1 -10
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] = {}
@@ -113,15 +107,12 @@ class ChannelManager:
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 -134
View File
@@ -8,28 +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,
KeyVerificationCancel,
KeyVerificationEvent,
KeyVerificationKey,
KeyVerificationMac,
KeyVerificationStart,
LoginResponse,
MatrixRoom,
MemoryDownloadResponse,
RoomEncryptedMedia,
RoomMessage,
RoomMessageMedia,
@@ -38,7 +31,6 @@ try:
RoomSendResponse,
RoomTypingError,
SyncError,
ToDeviceError,
UploadError,
)
from nio.crypto.attachments import decrypt_attachment
@@ -70,10 +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"],
@@ -200,10 +188,8 @@ class MatrixConfig(Base):
access_token: str = ""
device_id: str = ""
e2ee_enabled: bool = Field(default=True, alias="e2eeEnabled")
sas_verification: bool = Field(default=False, alias="sasVerification")
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)
@@ -245,9 +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:
@@ -275,7 +258,6 @@ class MatrixChannel(BaseChannel):
)
self._register_event_callbacks()
self._register_to_device_callbacks()
self._register_response_callbacks()
if not self.config.e2ee_enabled:
@@ -362,7 +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."""
@@ -580,77 +566,11 @@ class MatrixChannel(BaseChannel):
self.client.add_event_callback(self._on_media_message, MATRIX_MEDIA_EVENT_FILTER)
self.client.add_event_callback(self._on_room_invite, InviteEvent)
def _register_to_device_callbacks(self) -> None:
if self.config.e2ee_enabled and self.config.sas_verification:
self.client.add_to_device_callback(
self._on_key_verification_event,
(KeyVerificationEvent,),
)
def _register_response_callbacks(self) -> None:
self.client.add_response_callback(self._on_sync_error, SyncError)
self.client.add_response_callback(self._on_join_error, JoinError)
self.client.add_response_callback(self._on_send_error, RoomSendError)
def _is_sas_sender_allowed(self, sender: str) -> bool:
return bool(sender and self.is_allowed(sender))
async def _on_key_verification_event(self, event: KeyVerificationEvent) -> None:
try:
await self._handle_key_verification_event(event)
except asyncio.CancelledError:
raise
except Exception:
self.logger.exception("Matrix SAS verification handling failed")
async def _handle_key_verification_event(self, event: KeyVerificationEvent) -> None:
if not (self.config.e2ee_enabled and self.config.sas_verification):
return
if not self.client:
return
sender = str(getattr(event, "sender", "") or "")
transaction_id = str(getattr(event, "transaction_id", "") or "")
if not transaction_id or not self._is_sas_sender_allowed(sender):
return
if isinstance(event, KeyVerificationStart):
if "emoji" not in (getattr(event, "short_authentication_string", None) or []):
self.logger.info(
"Ignoring Matrix SAS verification from {} without emoji support",
sender,
)
return
response = await self.client.accept_key_verification(transaction_id)
if isinstance(response, ToDeviceError):
self.logger.warning("Matrix SAS accept failed for {}: {}", sender, response)
return
if isinstance(event, KeyVerificationKey):
responses = await self.client.send_to_device_messages()
if any(isinstance(response, ToDeviceError) for response in responses):
self.logger.warning("Matrix SAS key share failed for {}", sender)
return
response = await self.client.confirm_short_auth_string(transaction_id)
if isinstance(response, ToDeviceError):
self.logger.warning("Matrix SAS confirm failed for {}: {}", sender, response)
return
if isinstance(event, KeyVerificationMac):
sas = getattr(self.client, "key_verifications", {}).get(transaction_id)
if sas is not None and getattr(sas, "verified", False):
self.logger.info("Matrix SAS verification completed for {}", sender)
return
if isinstance(event, KeyVerificationCancel):
self.logger.info(
"Matrix SAS verification cancelled by {}: {}",
sender,
getattr(event, "reason", ""),
)
def _is_fatal_auth_response(self, response: Any) -> bool:
code = getattr(response, "status_code", None)
is_auth = code in {"M_UNKNOWN_TOKEN", "M_FORBIDDEN", "M_UNAUTHORIZED"}
@@ -823,7 +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")
@@ -852,48 +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)
@@ -922,14 +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
+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
File diff suppressed because it is too large Load Diff
+81 -266
View File
@@ -75,7 +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,
@@ -95,39 +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 just "
"'All clear.' and nothing else.]\n\n"
)
def _heartbeat_has_active_tasks(content: str) -> bool:
"""True if HEARTBEAT.md has task lines, ignoring headers, blanks and comments."""
in_comment = False
in_active_section: bool = False
for line in content.splitlines():
stripped = line.strip()
if in_comment:
if "-->" in stripped:
in_comment = False
continue
if not stripped or stripped.startswith("#"):
if stripped.startswith("##") and not stripped.startswith("###"):
heading = stripped.lstrip("#").strip().lower()
in_active_section = heading.startswith("active tasks")
continue
if stripped.startswith("<!--"):
if "-->" not in stripped[4:]:
in_comment = True
continue
if in_active_section is False:
continue
return True
return False
# ---------------------------------------------------------------------------
# CLI input: prompt_toolkit for editing, paste, history, and display
# ---------------------------------------------------------------------------
@@ -738,144 +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
@@ -885,6 +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
@@ -976,9 +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:
@@ -988,67 +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 _heartbeat_has_active_tasks(content):
logger.debug("Heartbeat: HEARTBEAT.md has no active tasks")
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}"
)
# Internal check: funnel all output through the post-run gate so the
# turn can't deliver directly via the message tool and skip it.
suppress_token = None
if isinstance(message_tool, MessageTool):
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 suppress_token is not None:
message_tool.reset_suppress_delivery(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
# Fail closed: stay silent on evaluator failure instead of notifying.
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, "
@@ -1063,6 +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)
@@ -1119,14 +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:
@@ -1136,8 +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:
@@ -1147,11 +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."""
@@ -1195,37 +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."""
@@ -1253,12 +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)
@@ -1271,6 +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"}),
}
@@ -1,6 +1,6 @@
"""CLI app adapter for the unified Apps domain."""
"""CLI Apps integration helpers."""
from nanobot.apps.cli.service import (
from nanobot.cli_apps.service import (
CliAppError,
CliAppManager,
CliAppsRuntimeConfig,
@@ -11,36 +11,25 @@ import subprocess
import sys
import time
from dataclasses import dataclass
from importlib import metadata as importlib_metadata
from pathlib import Path
from typing import Any
from urllib.parse import urlparse
import httpx
from nanobot.apps.protocol import app_manifest, compact_dict
from nanobot.config.paths import get_runtime_subdir
from nanobot.security.workspace_policy import is_path_within
CLI_ANYTHING_REGISTRY_URL = "https://hkuds.github.io/CLI-Anything/registry.json"
CLI_ANYTHING_PUBLIC_REGISTRY_URL = "https://hkuds.github.io/CLI-Anything/public_registry.json"
CLI_ANYTHING_RAW_BASE = "https://raw.githubusercontent.com/HKUDS/CLI-Anything/main"
NANOBOT_EXTENSION_REGISTRY_URL = "https://raw.githubusercontent.com/Re-bin/nanobot-extension/main/registry.json"
NANOBOT_EXTENSION_RAW_BASE = "https://raw.githubusercontent.com/Re-bin/nanobot-extension/main"
_CATALOG_SOURCES = (
("harness", CLI_ANYTHING_REGISTRY_URL, CLI_ANYTHING_RAW_BASE, True),
("public", CLI_ANYTHING_PUBLIC_REGISTRY_URL, CLI_ANYTHING_RAW_BASE, True),
("extensions", NANOBOT_EXTENSION_REGISTRY_URL, NANOBOT_EXTENSION_RAW_BASE, False),
)
CLI_ANYTHING_RAW_SKILLS_BASE = f"{CLI_ANYTHING_RAW_BASE}/skills/"
_MAX_TOOL_OUTPUT_CHARS = 12_000
_MAX_ARTIFACT_SCAN_PATHS = 4_000
_MAX_ARTIFACT_REPORT = 12
_SAFE_NAME_RE = re.compile(r"[^a-z0-9_-]+")
_SAFE_NPM_DIR_RE = re.compile(r"^[a-z0-9._-]+$", re.IGNORECASE)
_MENTION_RE = re.compile(r"(^|[\s([{])@([a-z0-9_-]+)\b", re.IGNORECASE)
_SHELL_META_CHARS = ("|", "&&", "||", ";", "$(", "`", ">", "<")
_ENDORSEMENT_WORD_RE = re.compile(r"\bofficial\s+", re.IGNORECASE)
_ARTIFACT_EXTENSIONS = frozenset({
".csv",
".drawio",
@@ -150,7 +139,7 @@ _BRANDS: dict[str, tuple[str, str]] = {
_BRAND_DOMAINS: dict[str, tuple[str, str]] = {
"3mf": ("3mf.io", "#00A1DE"),
"anygen": ("anygen.io", "#111827"),
"anygen": ("anygen.com", "#111827"),
"clibrowser": ("github.com/allthingssecurity/clibrowser", "#24292F"),
"cloudanalyzer": ("github.com/rsasaki0109/CloudAnalyzer", "#2563EB"),
"cloudcompare": ("cloudcompare.org", "#4D83C3"),
@@ -255,29 +244,6 @@ def _pip_uninstall_args_from_command(command: str) -> list[str] | None:
return packages
def _console_script_distribution(entry_point: str) -> str | None:
if not entry_point:
return None
try:
distributions = importlib_metadata.distributions()
except Exception:
return None
for distribution in distributions:
try:
entry_points = distribution.entry_points
except Exception:
continue
for item in entry_points:
if item.group != "console_scripts" or item.name != entry_point:
continue
try:
name = distribution.metadata.get("Name")
except Exception:
name = None
return str(name or getattr(distribution, "name", "") or "").strip() or None
return None
def _brand_key(value: str) -> str:
return _SAFE_NAME_RE.sub("-", value.lower()).replace("_", "-").strip("-")
@@ -303,11 +269,6 @@ def _brand_candidates(app: dict[str, Any]) -> list[str]:
def _brand_payload(app: dict[str, Any]) -> tuple[str | None, str | None]:
declared_logo = str(app.get("logo_url") or "").strip()
if declared_logo.startswith(("https://", "/")):
declared_color = str(app.get("brand_color") or "").strip()
return declared_logo, declared_color or None
brand = None
domain_brand = None
for candidate in _brand_candidates(app):
@@ -356,17 +317,16 @@ def _safe_skill_path(value: str) -> str | None:
return value if parts[-1] == "SKILL.md" else None
def _skill_content_url(skill_md: str, *, raw_base: str = CLI_ANYTHING_RAW_BASE) -> str | None:
def _skill_content_url(skill_md: str) -> str | None:
safe_path = _safe_skill_path(skill_md)
if safe_path:
return f"{raw_base.rstrip('/')}/{safe_path}"
return f"{CLI_ANYTHING_RAW_BASE}/{safe_path}"
parsed = urlparse(skill_md)
if parsed.scheme != "https" or parsed.netloc != "raw.githubusercontent.com":
return None
raw_prefix = raw_base.rstrip("/") + "/"
if not skill_md.startswith(raw_prefix):
if not skill_md.startswith(CLI_ANYTHING_RAW_SKILLS_BASE):
return None
suffix = skill_md.removeprefix(raw_prefix)
suffix = skill_md.removeprefix(f"{CLI_ANYTHING_RAW_BASE}/")
return skill_md if _safe_skill_path(suffix) else None
@@ -377,12 +337,6 @@ def _truncate(text: str, limit: int = _MAX_TOOL_OUTPUT_CHARS) -> str:
return text[:limit] + f"\n\n... truncated {omitted} characters ..."
def _catalog_description(app: dict[str, Any]) -> str:
"""Return catalog copy without implying vendor endorsement."""
description = str(app.get("description") or "")
return _ENDORSEMENT_WORD_RE.sub("", description).strip()
class CliAppManager:
"""Manage CLI-Anything registry entries and local install state."""
@@ -448,22 +402,27 @@ class CliAppManager:
return data
def catalog(self, *, force_refresh: bool = False) -> tuple[list[dict[str, Any]], str | None]:
registries: list[tuple[str, str, dict[str, Any]]] = []
for source, url, raw_base, required in _CATALOG_SOURCES:
try:
registry = self._fetch_registry(
url,
self._cache_path(source),
registries = [
(
"harness",
self._fetch_registry(
CLI_ANYTHING_REGISTRY_URL,
self._cache_path("harness"),
force_refresh=force_refresh,
)
except Exception:
if required:
raise
continue
registries.append((source, raw_base, registry))
),
),
(
"public",
self._fetch_registry(
CLI_ANYTHING_PUBLIC_REGISTRY_URL,
self._cache_path("public"),
force_refresh=force_refresh,
),
),
]
apps_by_name: dict[str, dict[str, Any]] = {}
updated_values: list[str] = []
for source, raw_base, registry in registries:
for source, registry in registries:
meta = registry.get("meta")
if isinstance(meta, dict) and isinstance(meta.get("updated"), str):
updated_values.append(meta["updated"])
@@ -472,7 +431,6 @@ class CliAppManager:
continue
entry = dict(row)
entry["_source"] = source
entry["_raw_base"] = raw_base
key = str(entry["name"]).lower()
previous = apps_by_name.get(key)
if previous:
@@ -485,15 +443,6 @@ class CliAppManager:
apps_by_name[key] = entry
return list(apps_by_name.values()), max(updated_values) if updated_values else None
def _manifest_source(self, app: dict[str, Any]) -> str:
source = str(app.get("_source") or "harness")
if source == "extensions":
return "nanobot-extension"
return f"cli-anything:{source}"
def _trust_registry(self, app: dict[str, Any]) -> str:
return "nanobot-extension" if str(app.get("_source") or "") == "extensions" else "cli-anything"
def get_app(self, name: str, *, force_refresh: bool = False) -> dict[str, Any]:
wanted = name.lower()
for app in self.catalog(force_refresh=force_refresh)[0]:
@@ -580,7 +529,7 @@ class CliAppManager:
"name": name,
"display_name": app.get("display_name") or name,
"category": app.get("category") or "uncategorized",
"description": _catalog_description(app),
"description": app.get("description") or "",
"requires": app.get("requires") or "",
"source": app.get("_source") or "harness",
"entry_point": entry_point,
@@ -591,86 +540,8 @@ class CliAppManager:
"logo_url": logo_url,
"brand_color": brand_color,
"skill_installed": self._skill_path(name).is_file(),
"manifest": self._manifest_payload(app, logo_url=logo_url, brand_color=brand_color),
}
def _package_ref(self, app: dict[str, Any]) -> dict[str, Any] | None:
strategy = self._strategy(app)
name = ""
if strategy == "pip":
try:
uninstall = self._pip_uninstall_argv(app)
except CliAppError:
uninstall = None
name = uninstall[-1] if uninstall else ""
elif strategy == "npm":
name = str(app.get("npm_package") or "").strip()
elif strategy in {"brew", "uv"}:
try:
uninstall = self._argv_for_action(app, "uninstall")
except CliAppError:
uninstall = None
if uninstall:
name = uninstall[-1]
if not strategy or strategy in {"unsupported", "bundled"}:
return None
return compact_dict({"manager": strategy, "name": name})
def _manifest_payload(
self,
app: dict[str, Any],
*,
logo_url: str | None,
brand_color: str | None,
) -> dict[str, Any]:
name = str(app["name"])
entry_point = str(app.get("entry_point") or "")
strategy = self._strategy(app)
skill_path = f"skills/{_safe_skill_name(name)}/SKILL.md"
capabilities = [
compact_dict({
"type": "cli",
"entry_point": entry_point,
"package": self._package_ref(app),
}),
{"type": "skill", "path": skill_path},
]
install_supported = self._install_supported(app)
install = compact_dict({
"supported": install_supported,
"strategy": strategy,
"managed_paths": [skill_path],
"verification": ["entry_point_available"] if entry_point else [],
})
remove = compact_dict({
"supported": strategy != "unsupported",
"strategy": strategy,
"managed_paths": [skill_path],
"verification": (
["package_manager_ok", "entry_point_absent", "managed_paths_absent"]
if strategy not in {"bundled", "unsupported"}
else ["nanobot_state_absent", "managed_paths_absent"]
),
})
return app_manifest(
app_id=name,
display_name=str(app.get("display_name") or name),
version=str(app.get("version") or ""),
description=_catalog_description(app),
category=str(app.get("category") or "uncategorized"),
source=self._manifest_source(app),
logo_url=logo_url,
brand_color=brand_color,
capabilities=capabilities,
install=install,
remove=remove,
trust={
"registry": self._trust_registry(app),
"level": "catalog",
"review_status": "catalog_entry",
},
)
def payload(self, *, force_refresh: bool = False) -> dict[str, Any]:
apps, updated = self.catalog(force_refresh=force_refresh)
installed = self._load_installed()
@@ -710,14 +581,7 @@ class CliAppManager:
prefix.extend(["--upgrade", "--force-reinstall"])
return prefix + args
def _pip_uninstall_argv(
self,
app: dict[str, Any],
installed_entry: dict[str, Any] | None = None,
) -> list[str]:
distribution = str((installed_entry or {}).get("pip_distribution") or "").strip()
if distribution:
return [sys.executable, "-m", "pip", "uninstall", "-y", distribution]
def _pip_uninstall_argv(self, app: dict[str, Any]) -> list[str]:
uninstall_cmd = str(app.get("uninstall_cmd") or "")
packages = _pip_uninstall_args_from_command(uninstall_cmd)
if packages:
@@ -741,45 +605,6 @@ class CliAppManager:
return [npm, "install", "-g", package + "@latest"]
return [npm, "uninstall", "-g", package]
def _cleanup_stale_npm_install(self, app: dict[str, Any]) -> bool:
npm = shutil.which("npm")
package = str(app.get("npm_package") or "").strip()
if not npm or not package or "/" in package or _SAFE_NPM_DIR_RE.match(package) is None:
return False
result = self._run_argv([npm, "root", "-g"], timeout=min(self.runtime.install_timeout, 30))
if result.returncode != 0:
return False
root = Path(result.stdout.strip()).expanduser()
try:
root = root.resolve(strict=True)
except OSError:
return False
targets = [root / package, *root.glob(f".{package}-*")]
removed = False
for target in targets:
try:
resolved = target.resolve(strict=False)
if not is_path_within(resolved, root) or not target.is_dir():
continue
shutil.rmtree(target)
removed = True
except OSError:
continue
return removed
def _retry_stale_npm_install(
self,
app: dict[str, Any],
argv: list[str],
result: subprocess.CompletedProcess[str],
) -> subprocess.CompletedProcess[str]:
output = f"{result.stderr}\n{result.stdout}"
if "ENOTEMPTY" not in output or "rename" not in output:
return result
if not self._cleanup_stale_npm_install(app):
return result
return self._run_argv(argv, timeout=self.runtime.install_timeout)
def _split_safe_command(self, app: dict[str, Any], key: str, expected: str) -> list[str]:
command = str(app.get(key) or "")
if not command:
@@ -794,19 +619,14 @@ class CliAppManager:
raise CliAppError(f"unsupported {expected} command")
return argv
def _argv_for_action(
self,
app: dict[str, Any],
action: str,
installed_entry: dict[str, Any] | None = None,
) -> list[str] | None:
def _argv_for_action(self, app: dict[str, Any], action: str) -> list[str] | None:
strategy = self._strategy(app)
if strategy == "pip":
if action == "install":
return self._pip_install_argv(app)
if action == "update":
return self._pip_install_argv(app, update=True)
return self._pip_uninstall_argv(app, installed_entry=installed_entry)
return self._pip_uninstall_argv(app)
if strategy == "npm":
return self._npm_argv(app, action)
if strategy == "brew":
@@ -828,29 +648,19 @@ class CliAppManager:
)
def _installed_entry(self, app: dict[str, Any]) -> dict[str, Any]:
entry_point = str(app.get("entry_point") or "")
strategy = self._strategy(app)
entry: dict[str, Any] = {
return {
"version": app.get("version") or "unknown",
"entry_point": entry_point,
"entry_point": app.get("entry_point") or "",
"source": app.get("_source") or "harness",
"strategy": strategy,
"strategy": self._strategy(app),
"installed_at": int(_now()),
}
resolved = shutil.which(entry_point) if entry_point else None
if resolved:
entry["entry_point_path"] = resolved
if strategy == "pip":
distribution = _console_script_distribution(entry_point)
if distribution:
entry["pip_distribution"] = distribution
return entry
def _fetch_skill_content(self, app: dict[str, Any]) -> str | None:
skill_md = str(app.get("skill_md") or "").strip()
if not skill_md:
return None
url = _skill_content_url(skill_md, raw_base=str(app.get("_raw_base") or CLI_ANYTHING_RAW_BASE))
url = _skill_content_url(skill_md)
if not url:
return None
try:
@@ -867,7 +677,7 @@ class CliAppManager:
name = str(app.get("name") or "unknown")
display = str(app.get("display_name") or name)
entry = str(app.get("entry_point") or f"cli-anything-{name}")
description = _catalog_description(app) or f"Use {display} from nanobot."
description = str(app.get("description") or f"Use {display} from nanobot.")
return f"""---
name: {_safe_skill_name(name)}
description: >-
@@ -920,60 +730,31 @@ Use the `run_cli_app` tool with `name="{name}"` for command execution. Do not in
if skill_dir.is_dir():
shutil.rmtree(skill_dir)
def _record_installed(self, app: dict[str, Any]) -> dict[str, Any]:
def _record_installed(self, app: dict[str, Any]) -> None:
installed = self._load_installed()
entry = self._installed_entry(app)
installed[str(app["name"])] = entry
installed[str(app["name"])] = self._installed_entry(app)
self._save_installed(installed)
self.install_skill(app)
return entry
def install(self, name: str) -> dict[str, Any]:
app = self.get_app(name)
if not self._install_supported(app):
raise CliAppError("this CLI app uses an unsupported install strategy")
strategy = self._strategy(app)
entry_point = str(app.get("entry_point") or "")
if entry_point and shutil.which(entry_point):
self._record_installed(app)
return self.payload() | {
"last_action": {
"ok": True,
"message": f"CLI for {app['display_name']} is already available.",
"installed": True,
"verification": ["entry_point_available", "state_recorded", "managed_paths_present"],
}
}
if strategy == "bundled":
detect_cmd = str(app.get("detect_cmd") or app.get("entry_point") or "")
if detect_cmd and _command_exists(detect_cmd):
self._record_installed(app)
return self.payload() | {
"last_action": {
"ok": True,
"message": f"CLI for {app['display_name']} is available.",
"installed": True,
"verification": ["entry_point_available", "state_recorded"],
}
}
return self.payload() | {"last_action": {"ok": True, "message": f"CLI for {app['display_name']} is available."}}
note = app.get("install_notes") or f"{app['display_name']} is bundled with its parent app."
raise CliAppError(str(note))
argv = self._argv_for_action(app, "install")
assert argv is not None
result = self._run_argv(argv, timeout=self.runtime.install_timeout)
if strategy == "npm" and result.returncode != 0:
result = self._retry_stale_npm_install(app, argv, result)
if result.returncode != 0:
raise CliAppError(_truncate(result.stderr or result.stdout or "install failed"), status=500)
self._record_installed(app)
return self.payload() | {
"last_action": {
"ok": True,
"message": f"Installed CLI for {app['display_name']}.",
"installed": True,
"verification": ["package_manager_ok", "state_recorded", "managed_paths_present"],
}
}
return self.payload() | {"last_action": {"ok": True, "message": f"Installed CLI for {app['display_name']}."}}
def update(self, name: str) -> dict[str, Any]:
app = self.get_app(name, force_refresh=True)
@@ -981,94 +762,30 @@ Use the `run_cli_app` tool with `name="{name}"` for command execution. Do not in
raise CliAppError("CLI app is not installed")
if self._strategy(app) == "bundled":
self._record_installed(app)
return self.payload() | {
"last_action": {
"ok": True,
"message": f"Checked {app['display_name']}.",
"installed": True,
"verification": ["state_recorded"],
}
}
return self.payload() | {"last_action": {"ok": True, "message": f"Checked {app['display_name']}."}}
argv = self._argv_for_action(app, "update")
assert argv is not None
result = self._run_argv(argv, timeout=self.runtime.install_timeout)
if result.returncode != 0:
raise CliAppError(_truncate(result.stderr or result.stdout or "update failed"), status=500)
self._record_installed(app)
return self.payload() | {
"last_action": {
"ok": True,
"message": f"Updated CLI for {app['display_name']}.",
"installed": True,
"verification": ["package_manager_ok", "state_recorded", "managed_paths_present"],
}
}
return self.payload() | {"last_action": {"ok": True, "message": f"Updated CLI for {app['display_name']}."}}
def uninstall(self, name: str) -> dict[str, Any]:
app = self.get_app(name)
installed = self._load_installed()
if str(app["name"]) not in installed:
raise CliAppError("CLI app is not installed")
raw_installed_entry = installed.get(str(app["name"]))
installed_entry = raw_installed_entry if isinstance(raw_installed_entry, dict) else {}
strategy = self._strategy(app)
entry_point = str(app.get("entry_point") or "").strip()
managed_entry_path = str(installed_entry.get("entry_point_path") or "").strip()
if strategy != "bundled":
argv = self._argv_for_action(app, "uninstall", installed_entry=installed_entry)
if self._strategy(app) != "bundled":
argv = self._argv_for_action(app, "uninstall")
assert argv is not None
result = self._run_argv(argv, timeout=self.runtime.install_timeout)
if result.returncode != 0:
raise CliAppError(_truncate(result.stderr or result.stdout or "uninstall failed"), status=500)
still_managed = bool(managed_entry_path and Path(managed_entry_path).exists())
still_available = bool(entry_point and shutil.which(entry_point))
if still_managed or (not managed_entry_path and still_available):
reason = (
f"the recorded entry point at {managed_entry_path} still exists"
if still_managed
else f"{entry_point} is still available on PATH"
)
message = (
f"Uninstall for {app['display_name']} completed, but {reason}, "
"so nanobot kept it installed."
)
return self.payload() | {
"last_action": {
"ok": False,
"message": message,
"removed": False,
"still_available": True,
"verification_failed": ["entry_point_absent"],
}
}
else:
still_available = bool(entry_point and shutil.which(entry_point))
installed.pop(str(app["name"]), None)
self._save_installed(installed)
self.remove_skill(str(app["name"]))
if strategy == "bundled" and still_available:
message = (
f"Removed {app['display_name']} from nanobot. {entry_point} "
"is still available because it is managed outside nanobot."
)
elif still_available:
message = (
f"Uninstalled CLI for {app['display_name']}, but another {entry_point} "
"is still available on PATH."
)
else:
message = f"Uninstalled CLI for {app['display_name']}."
return self.payload() | {
"last_action": {
"ok": True,
"message": message,
"removed": True,
"still_available": still_available,
"verification": ["state_absent", "managed_paths_absent"]
if still_available
else ["entry_point_absent", "state_absent", "managed_paths_absent"],
}
}
return self.payload() | {"last_action": {"ok": True, "message": f"Uninstalled CLI for {app['display_name']}."}}
def test(self, name: str) -> dict[str, Any]:
app = self.get_app(name)
@@ -1096,7 +813,7 @@ Use the `run_cli_app` tool with `name="{name}"` for command execution. Do not in
cwd = Path(working_dir).expanduser() if working_dir else self.workspace
cwd = cwd.resolve(strict=False)
workspace = self.workspace.resolve(strict=False)
if restrict_to_workspace and not is_path_within(cwd, workspace):
if restrict_to_workspace and cwd != workspace and not cwd.is_relative_to(workspace):
raise CliAppError("working_dir is outside the configured workspace")
return cwd
@@ -46,7 +46,7 @@ def _cli_app_runtime_lines(
if "@" not in text:
return []
try:
from nanobot.apps.cli import CliAppManager
from nanobot.cli_apps import CliAppManager
mentions = CliAppManager(workspace=workspace).mentioned_installed_apps(text)
except Exception:
+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()
+3 -32
View File
@@ -37,7 +37,6 @@ 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 +47,6 @@ 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 +92,6 @@ 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
@@ -173,9 +170,8 @@ 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):
@@ -226,19 +222,9 @@ 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
@@ -268,7 +254,6 @@ 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
@@ -297,16 +282,7 @@ class ToolsConfig(Base):
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
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 +301,6 @@ 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:
+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)
+1 -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)
@@ -236,13 +228,6 @@ 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)})
continue
result.append(item)
return result or "(empty)"
+1 -40
View File
@@ -315,29 +315,6 @@ 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:
@@ -580,20 +557,11 @@ 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 +571,6 @@ 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 +717,6 @@ 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 +730,6 @@ 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
-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,
-144
View File
@@ -1445,149 +1445,6 @@ 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
# ---------------------------------------------------------------------------
@@ -1600,4 +1457,3 @@ register_image_gen_provider(MiniMaxImageGenerationClient)
register_image_gen_provider(OpenAIImageGenerationClient)
register_image_gen_provider(OpenRouterImageGenerationClient)
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}"
+3 -74
View File
@@ -274,47 +274,6 @@ 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.
@@ -330,14 +289,12 @@ 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)
@@ -471,10 +428,6 @@ 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."""
@@ -513,13 +466,10 @@ class OpenAICompatProvider(LLMProvider):
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:
@@ -735,14 +685,8 @@ 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 +700,7 @@ 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 +792,6 @@ 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 +956,7 @@ 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 +999,7 @@ 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,
@@ -1329,8 +1262,6 @@ 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)
@@ -1404,8 +1335,6 @@ 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",
+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:
+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
+4 -19
View File
@@ -43,19 +43,6 @@ def sustained_goal_active(metadata: Mapping[str, Any] | None) -> bool:
return isinstance(goal, dict) and goal.get("status") == "active"
def sustained_goal_turn(
metadata: Mapping[str, Any] | None,
*,
message_metadata: Mapping[str, Any] | None = None,
) -> bool:
"""True when this turn should use sustained-goal runtime limits."""
if sustained_goal_active(metadata):
return True
if not message_metadata:
return False
return str(message_metadata.get("original_command") or "").strip() == "/goal"
def parse_goal_state(blob: Any) -> dict[str, Any] | None:
if blob is None:
return None
@@ -111,16 +98,14 @@ def runner_wall_llm_timeout_s(
session_key: str | None,
*,
metadata: Mapping[str, Any] | None = None,
message_metadata: Mapping[str, Any] | None = None,
) -> float | None:
"""Wall-clock cap for :class:`~nanobot.agent.runner.AgentRunner` when streaming an LLM.
Returns ``0.0`` to disable ``asyncio.wait_for`` around the request when this is a
sustained-goal turn; ``None`` means use ``NANOBOT_LLM_TIMEOUT_S``. Pass in-memory
``metadata`` when the caller already holds :attr:`~nanobot.session.manager.Session.metadata`
for this turn.
Returns ``0.0`` to disable ``asyncio.wait_for`` around the request when a sustained goal is
active; ``None`` means use ``NANOBOT_LLM_TIMEOUT_S``. Pass in-memory ``metadata`` when the
caller already holds :attr:`~nanobot.session.manager.Session.metadata` for this turn.
"""
meta: Mapping[str, Any] | None = metadata
if meta is None and session_key:
meta = sessions.get_or_create(session_key).metadata
return 0.0 if sustained_goal_turn(meta, message_metadata=message_metadata) else None
return 0.0 if sustained_goal_active(meta) else None
+22 -91
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."""
@@ -196,28 +182,6 @@ class Session:
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():
@@ -269,25 +233,13 @@ class Session:
self.updated_at = datetime.now()
self.metadata.pop("_last_summary", None)
def retain_recent_legal_suffix(self, max_messages: int) -> tuple[list[dict], int]:
"""Keep a legal recent suffix constrained by a hard message cap.
Returns ``(dropped, already_consolidated_count)`` where *dropped* is
the list of removed messages (in original order) and
*already_consolidated_count* is how many of those were inside the
pre-existing ``last_consolidated`` prefix and therefore do not need
raw archiving.
"""
def retain_recent_legal_suffix(self, max_messages: int) -> None:
"""Keep a legal recent suffix constrained by a hard message cap."""
if max_messages <= 0:
dropped = list(self.messages)
lc = self.last_consolidated
self.clear()
return dropped, min(lc, len(dropped))
return
if len(self.messages) <= max_messages:
return [], 0
original = list(self.messages)
before_lc = self.last_consolidated
return
retained = list(self.messages[-max_messages:])
@@ -318,32 +270,10 @@ class Session:
if start:
retained = retained[start:]
# Compute actually-dropped messages using identity comparison so that
# even when retained is a non-contiguous slice of original (the else
# branch above), we never duplicate or lose messages.
retained_ids = set(id(m) for m in retained)
dropped = [m for m in original if id(m) not in retained_ids]
# Count how many dropped messages were in the already-consolidated
# prefix of the original list. This cannot be a simple min() because
# dropped may include messages from *after* the consolidated prefix
# (e.g. in the else branch).
already_consolidated = sum(
1 for i, m in enumerate(original)
if i < before_lc and id(m) not in retained_ids
)
# New last_consolidated = count of retained messages that were inside
# the old consolidated prefix.
new_lc = sum(
1 for i, m in enumerate(original)
if i < before_lc and id(m) in retained_ids
)
dropped = len(self.messages) - len(retained)
self.messages = retained
self.last_consolidated = new_lc
self.last_consolidated = max(0, self.last_consolidated - dropped)
self.updated_at = datetime.now()
return dropped, already_consolidated
def enforce_file_cap(
self,
@@ -354,17 +284,23 @@ class Session:
if limit <= 0 or len(self.messages) <= limit:
return
dropped, already_consolidated = self.retain_recent_legal_suffix(limit)
if not dropped:
before = list(self.messages)
before_last_consolidated = self.last_consolidated
before_count = len(before)
self.retain_recent_legal_suffix(limit)
dropped_count = before_count - len(self.messages)
if dropped_count <= 0:
return
dropped = before[:dropped_count]
already_consolidated = min(before_last_consolidated, dropped_count)
archive_chunk = dropped[already_consolidated:]
if archive_chunk and on_archive:
on_archive(archive_chunk)
logger.info(
"Session file cap hit for {}: dropped {}, raw-archived {}, kept {}",
self.key,
len(dropped),
dropped_count,
len(archive_chunk),
len(self.messages),
)
@@ -682,21 +618,12 @@ 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
@@ -713,7 +640,7 @@ 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)
})
@@ -724,7 +651,11 @@ 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
-240
View File
@@ -1,240 +0,0 @@
"""Internal turn continuation helpers.
This module keeps budget-boundary continuation policy out of ``AgentLoop``.
The loop calls a small set of helpers; those helpers decide whether an internal
continuation is allowed and, when it is, queue the next turn directly.
"""
from __future__ import annotations
import dataclasses
from typing import Any, Mapping, MutableMapping
from loguru import logger
from nanobot.session.goal_state import (
goal_state_runtime_lines,
sustained_goal_active,
sustained_goal_turn,
)
INTERNAL_CONTINUATION_META = "_internal_continuation"
INTERNAL_CONTINUATION_KIND_META = "_internal_continuation_kind"
INTERNAL_CONTINUATION_PENDING_META = "_internal_continuation_pending"
INTERNAL_CONTINUATION_RUN_STARTED_AT_META = "_internal_continuation_run_started_at"
_GOAL_CONTINUATION_KIND = "sustained_goal"
_GOAL_CONTINUATION_SENDER = "system:continuation"
_GOAL_CONTINUATION_ROUNDS_KEY = "_sustained_goal_continuation_rounds"
_MAX_GOAL_CONTINUATION_ROUNDS = 12
_STRIPPED_INBOUND_META_KEYS = {
"_stream_id",
"_stream_delta",
"_stream_end",
"_resuming",
INTERNAL_CONTINUATION_PENDING_META,
}
def internal_continuation_inbound(metadata: Mapping[str, Any] | None) -> bool:
"""True for an inbound message created by an internal continuation policy."""
return bool(metadata and metadata.get(INTERNAL_CONTINUATION_META) is True)
def internal_continuation_pending(metadata: Mapping[str, Any] | None) -> bool:
"""True when the current turn scheduled an invisible continuation slice."""
return bool(metadata and metadata.get(INTERNAL_CONTINUATION_PENDING_META) is True)
def internal_continuation_run_started_at(metadata: Mapping[str, Any] | None) -> float | None:
"""Return the user-visible run start propagated across continuation slices."""
if not metadata:
return None
value = metadata.get(INTERNAL_CONTINUATION_RUN_STARTED_AT_META)
if not isinstance(value, int | float):
return None
started_at = float(value)
return started_at if started_at > 0 else None
def should_persist_user_message(metadata: Mapping[str, Any] | None) -> bool:
"""Return whether this inbound message should be persisted as user input."""
return not internal_continuation_inbound(metadata)
def should_stream_budget_response(
*,
stop_reason: str,
pending_queue_available: bool,
session_metadata: Mapping[str, Any] | None,
message_metadata: Mapping[str, Any] | None = None,
) -> bool:
"""Return whether the budget-boundary response should be sent to the user."""
return not _continuation_available(
stop_reason=stop_reason,
pending_queue_available=pending_queue_available,
session_metadata=session_metadata,
message_metadata=message_metadata,
)
async def maybe_continue_turn(ctx: Any) -> bool:
"""Queue an internal continuation for *ctx* when policy allows it."""
if ctx.session is None or ctx.pending_queue is None:
return False
if not _continuation_available(
stop_reason=ctx.stop_reason,
pending_queue_available=True,
session_metadata=ctx.session.metadata,
message_metadata=ctx.msg.metadata,
):
return False
metadata = _internal_continuation_metadata(
ctx.msg.metadata,
run_started_at=getattr(ctx, "visible_run_started_at", None),
)
content = _goal_continuation_prompt(ctx.session.metadata)
messages = _strip_terminal_assistant(ctx.all_messages, ctx.final_content)
_increment_goal_continuation_round(ctx.session.metadata)
logger.info("Turn budget reached; scheduling internal continuation")
ctx.msg.metadata[INTERNAL_CONTINUATION_PENDING_META] = True
ctx.final_content = ""
ctx.all_messages = messages
ctx.suppress_response = True
await ctx.pending_queue.put(
dataclasses.replace(
ctx.msg,
sender_id=_GOAL_CONTINUATION_SENDER,
content=content,
media=[],
metadata=metadata,
session_key_override=ctx.session_key,
)
)
return True
def prepare_save_boundary(ctx: Any) -> None:
"""Prepare continuation bookkeeping and the history append boundary."""
if ctx.session is not None:
clear_internal_continuation_state(ctx.session.metadata)
ctx.save_skip = _save_skip_for_turn(
message_metadata=ctx.msg.metadata,
initial_message_count=len(ctx.initial_messages),
history_count=len(ctx.history),
user_persisted_early=ctx.user_persisted_early,
)
def _continuation_available(
*,
stop_reason: str,
pending_queue_available: bool,
session_metadata: Mapping[str, Any] | None,
message_metadata: Mapping[str, Any] | None = None,
) -> bool:
if stop_reason != "max_iterations" or not pending_queue_available:
return False
return _goal_continuation_available(
session_metadata,
message_metadata=message_metadata,
)
def clear_internal_continuation_state(metadata: MutableMapping[str, Any]) -> None:
"""Reset policy bookkeeping once its owning runtime mode is inactive."""
if not sustained_goal_active(metadata):
metadata.pop(_GOAL_CONTINUATION_ROUNDS_KEY, None)
def _save_skip_for_turn(
*,
message_metadata: Mapping[str, Any] | None,
initial_message_count: int,
history_count: int,
user_persisted_early: bool,
) -> int:
"""Return the persisted-message append boundary for this turn."""
if internal_continuation_inbound(message_metadata):
return initial_message_count
return 1 + history_count + (1 if user_persisted_early else 0)
def _goal_continuation_available(
session_metadata: Mapping[str, Any] | None,
*,
message_metadata: Mapping[str, Any] | None = None,
max_rounds: int = _MAX_GOAL_CONTINUATION_ROUNDS,
) -> bool:
if not sustained_goal_turn(session_metadata, message_metadata=message_metadata):
return False
if not sustained_goal_active(session_metadata):
return False
try:
rounds = int((session_metadata or {}).get(_GOAL_CONTINUATION_ROUNDS_KEY) or 0)
except (TypeError, ValueError):
rounds = 0
return rounds < max(0, max_rounds)
def _increment_goal_continuation_round(session_metadata: MutableMapping[str, Any]) -> None:
try:
rounds = int(session_metadata.get(_GOAL_CONTINUATION_ROUNDS_KEY) or 0)
except (TypeError, ValueError):
rounds = 0
session_metadata[_GOAL_CONTINUATION_ROUNDS_KEY] = rounds + 1
def _internal_continuation_metadata(
message_metadata: Mapping[str, Any] | None,
*,
run_started_at: float | None = None,
) -> dict[str, Any]:
metadata = dict(message_metadata or {})
metadata[INTERNAL_CONTINUATION_META] = True
metadata[INTERNAL_CONTINUATION_KIND_META] = _GOAL_CONTINUATION_KIND
if run_started_at is not None:
metadata[INTERNAL_CONTINUATION_RUN_STARTED_AT_META] = float(run_started_at)
for key in _STRIPPED_INBOUND_META_KEYS:
metadata.pop(key, None)
return metadata
def _goal_continuation_prompt(metadata: Mapping[str, Any] | None) -> str:
lines = goal_state_runtime_lines(metadata)
if lines:
goal = "\n".join(lines)
return (
"Continue the active sustained goal after the previous turn reached "
"its tool-call budget.\n\n"
f"{goal}\n\n"
"Continue from the saved context. Do not mention the continuation "
"boundary to the user. Use tools as needed, and call complete_goal "
"when the objective is truly finished."
)
return (
"Continue the active sustained goal after the previous turn reached "
"its tool-call budget. Continue from the saved context. Do not mention "
"the continuation boundary to the user. Use tools as needed, and call "
"complete_goal when the objective is truly finished."
)
def _strip_terminal_assistant(
messages: list[dict[str, Any]],
final_content: str | None,
) -> list[dict[str, Any]]:
"""Drop the synthetic max-iteration assistant message before saving history."""
if not messages:
return messages
last = messages[-1]
if last.get("role") != "assistant":
return messages
if final_content is None or last.get("content") != final_content:
return messages
if last.get("tool_calls"):
return messages
return messages[:-1]
+6 -31
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:
@@ -178,13 +168,7 @@ def websocket_turn_wall_started_at(chat_id: str) -> float | None:
return _WEBSOCKET_TURN_WALL_STARTED_AT.get(chat_id)
async def publish_turn_run_status(
bus: MessageBus,
msg: InboundMessage,
status: str,
*,
started_at: float | None = None,
) -> None:
async def publish_turn_run_status(bus: MessageBus, msg: InboundMessage, status: str) -> None:
"""Notify WebSocket clients while a user turn is executing (timing strip)."""
if msg.channel != "websocket":
return
@@ -195,10 +179,7 @@ async def publish_turn_run_status(
"goal_status": status,
}
if status == "running":
if isinstance(started_at, int | float) and started_at > 0:
t0 = float(started_at)
else:
t0 = time.time()
t0 = time.time()
meta["started_at"] = t0
_WEBSOCKET_TURN_WALL_STARTED_AT[cid] = t0
else:
@@ -309,14 +290,8 @@ class WebuiTurnCoordinator:
def discard(self, session_key: str) -> None:
self._title_contexts.pop(session_key, None)
async def publish_run_status(
self,
msg: InboundMessage,
status: str,
*,
started_at: float | None = None,
) -> None:
await publish_turn_run_status(self.bus, msg, status, started_at=started_at)
async def publish_run_status(self, msg: InboundMessage, status: str) -> None:
await publish_turn_run_status(self.bus, msg, status)
async def handle_turn_end(
self,
+2 -2
View File
@@ -14,10 +14,10 @@ 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.
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.
+8 -6
View File
@@ -1,14 +1,16 @@
# 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.
Completed tasks should be deleted, not kept — heartbeat only reads "Active Tasks".
-->
If this file has no tasks (only headers and comments), the agent will skip the heartbeat.
## Active Tasks
<!-- Add your periodic tasks below this line -->
## Completed
<!-- Move completed tasks here or delete them -->
+1 -1
View File
@@ -63,5 +63,5 @@ documents the general tool contract and non-obvious usage patterns.
## 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.
- For heartbeat tasks, update `HEARTBEAT.md` 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 -14
View File
@@ -44,12 +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.
On any failure, falls back to ``default_notify`` (cron reminders fail open;
heartbeat passes ``False`` to 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(
@@ -71,24 +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
+5 -8
View File
@@ -299,7 +299,6 @@ 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 +324,6 @@ 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 +333,6 @@ def build_file_edit_live_event(
added=added,
deleted=deleted,
approximate=True,
operation=operation,
)
@@ -457,14 +454,15 @@ class StreamingFileEditTracker:
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_match = re.search(r'"action"\s*:\s*"(replace|add|delete)"', 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
deleted = _text_line_count(old_text) if action in ("replace", "delete") else 0
delete_file = action == "delete"
file_state = state.patch_files.get(raw_path)
if file_state is None:
@@ -477,6 +475,8 @@ class StreamingFileEditTracker:
)
file_state = _StreamingPatchFileState(tracker=tracker)
state.patch_files[raw_path] = file_state
if delete_file and added == 0 and deleted == 0 and file_state.tracker.before.countable:
deleted = _text_line_count(file_state.tracker.before.text or "")
if not file_state.should_emit(added, deleted, now):
continue
file_state.mark_emitted(added, deleted, now)
@@ -916,7 +916,6 @@ 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 +931,6 @@ def _event_payload(
}
if binary:
payload["binary"] = True
if operation:
payload["operation"] = operation
return payload
-11
View File
@@ -626,14 +626,3 @@ 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":
+1 -1
View File
@@ -5,7 +5,7 @@ from __future__ import annotations
import re
from typing import Any
from nanobot.apps.cli import CliAppError, CliAppManager, CliAppsRuntimeConfig
from nanobot.cli_apps import CliAppError, CliAppManager, CliAppsRuntimeConfig
from nanobot.config.loader import load_config
QueryParams = dict[str, list[str]]
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)
+26 -718
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
@@ -224,25 +70,6 @@ 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
@@ -253,57 +80,9 @@ def _provider_requires_api_key(spec: Any) -> bool:
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"])
return True
if _provider_requires_api_key(spec):
return bool(provider_config.api_key)
return bool(
@@ -314,191 +93,6 @@ 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 +100,6 @@ 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 +115,6 @@ 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 +127,7 @@ 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 +150,19 @@ 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 +198,7 @@ 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 +211,7 @@ 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 +282,6 @@ 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 +290,6 @@ 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 +321,19 @@ 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 +388,6 @@ 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 +416,6 @@ 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 +428,6 @@ 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
+22 -248
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:
@@ -221,19 +143,6 @@ def _tool_event_key(event: dict[str, Any]) -> str:
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
@@ -256,87 +165,6 @@ def _merge_tool_events(previous: Any, incoming: list[dict[str, Any]]) -> list[di
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],
@@ -458,40 +286,6 @@ 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 +347,13 @@ 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 +363,16 @@ 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 +380,11 @@ 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)
@@ -669,11 +458,6 @@ def replay_transcript_to_ui_messages(
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
@@ -774,21 +558,12 @@ def replay_transcript_to_ui_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 +574,7 @@ 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 and not structured_events:
continue
else:
merged_traces = prev_traces + trace_lines
@@ -807,8 +582,8 @@ 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
"toolEvents": _merge_tool_events(last.get("toolEvents"), structured_events)
if structured_events
else last.get("toolEvents"),
"activitySegmentId": last.get("activitySegmentId") or segment,
}
@@ -821,7 +596,7 @@ def replay_transcript_to_ui_messages(
"kind": "trace",
"content": trace_lines[-1],
"traces": trace_lines,
**({"toolEvents": visible_structured_events} if visible_structured_events else {}),
**({"toolEvents": structured_events} if structured_events else {}),
"activitySegmentId": segment,
"createdAt": _ts_base + idx,
},
@@ -837,12 +612,11 @@ 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}
-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)
+2 -3
View File
@@ -1,6 +1,6 @@
[project]
name = "nanobot-ai"
version = "0.2.1"
version = "0.2.0"
description = "A lightweight personal AI assistant framework"
readme = { file = "README.md", content-type = "text/markdown" }
requires-python = ">=3.11"
@@ -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",
]
+3 -2
View File
@@ -76,9 +76,10 @@ def _make_fake_compact(
metadata={},
last_consolidated=0,
)
dropped, already_consolidated = probe.retain_recent_legal_suffix(max_suffix)
probe.retain_recent_legal_suffix(max_suffix)
kept = probe.messages
archive_msgs = dropped[already_consolidated:]
cut = len(tail) - len(kept)
archive_msgs = tail[:cut]
if not archive_msgs and not kept:
session.updated_at = datetime.now()
-38
View File
@@ -440,44 +440,6 @@ class TestCompactIdleSession:
assert "u0" not in user_content
assert "u25" in user_content or "a25" in user_content
@pytest.mark.asyncio
async def test_non_contiguous_suffix_archives_actual_dropped_messages(
self,
real_consolidator,
mock_provider,
):
"""Assistant-only tails retain a non-contiguous slice, so archive the
actual dropped messages rather than a computed prefix."""
mock_provider.chat_with_retry.return_value = MagicMock(
content="Tail summary.", finish_reason="stop"
)
sessions = real_consolidator.sessions
session = sessions.get_or_create("cli:noncontiguous")
for i in range(15):
session.add_message("user", f"user-{i:02d}")
for i in range(10):
session.add_message("assistant", f"assistant-{i:02d}")
sessions.save(session)
result = await real_consolidator.compact_idle_session("cli:noncontiguous", max_suffix=6)
assert result == "Tail summary."
reloaded = sessions.get_or_create("cli:noncontiguous")
assert [m["content"] for m in reloaded.messages] == [
"user-14",
"assistant-00",
"assistant-01",
"assistant-02",
"assistant-03",
"assistant-04",
]
archived_call = mock_provider.chat_with_retry.call_args
user_content = archived_call.kwargs["messages"][1]["content"]
assert "user-14" not in user_content
assert "assistant-00" not in user_content
assert "assistant-09" in user_content
@pytest.mark.asyncio
async def test_acquires_consolidation_lock(self, real_consolidator, mock_provider):
"""Verify lock is held during execution."""
@@ -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
-18
View File
@@ -61,21 +61,3 @@ 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_fail_closed_on_error() -> None:
class FailingProvider(DummyProvider):
async def chat(self, *args, **kwargs) -> LLMResponse:
raise RuntimeError("provider down")
provider = FailingProvider([])
result = await evaluate_response("some", "task", provider, "m", default_notify=False)
assert result is False
@pytest.mark.asyncio
async def test_fail_closed_on_no_tool_call() -> None:
provider = DummyProvider([LLMResponse(content="text only", tool_calls=[])])
result = await evaluate_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
+1 -24
View File
@@ -2,6 +2,7 @@
from __future__ import annotations
import asyncio
import time
from unittest.mock import AsyncMock, MagicMock, patch
@@ -47,30 +48,6 @@ async def test_loop_max_iterations_message_stays_stable(tmp_path):
)
@pytest.mark.asyncio
async def test_loop_goal_turn_uses_standard_iteration_budget(tmp_path):
loop = _make_loop(tmp_path)
loop.provider.chat_with_retry = AsyncMock(return_value=LLMResponse(
content="working",
tool_calls=[ToolCallRequest(id="call_1", name="list_dir", arguments={})],
))
loop.tools.get_definitions = MagicMock(return_value=[])
loop.tools.execute = AsyncMock(return_value="ok")
loop.max_iterations = 2
final_content, _, _, stop_reason, _ = await loop._run_agent_loop(
[],
metadata={"original_command": "/goal"},
)
assert stop_reason == "max_iterations"
assert loop.provider.chat_with_retry.await_count == 2
assert final_content == (
"I reached the maximum number of tool call iterations (2) "
"without completing the task. You can try breaking the task into smaller steps."
)
@pytest.mark.asyncio
async def test_loop_stream_filter_handles_think_only_prefix_without_crashing(tmp_path):
loop = _make_loop(tmp_path)
+7 -237
View File
@@ -11,17 +11,12 @@ from nanobot.bus.queue import MessageBus
from nanobot.providers.base import LLMResponse
from nanobot.session.goal_state import GOAL_STATE_KEY
from nanobot.session.manager import Session, SessionManager
from nanobot.session.turn_continuation import (
INTERNAL_CONTINUATION_META,
INTERNAL_CONTINUATION_RUN_STARTED_AT_META,
)
from nanobot.session.webui_turns import (
TITLE_GENERATION_MAX_TOKENS,
TITLE_GENERATION_REASONING_EFFORT,
WEBUI_SESSION_METADATA_KEY,
WEBUI_TITLE_METADATA_KEY,
WebuiTurnCoordinator,
clean_generated_title,
maybe_generate_webui_title,
)
from nanobot.utils.llm_runtime import LLMRuntime
@@ -58,11 +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)
@@ -564,226 +554,6 @@ async def test_process_message_does_not_duplicate_early_persisted_user_message(t
assert AgentLoop._PENDING_USER_TURN_KEY not in session.metadata
@pytest.mark.asyncio
async def test_internal_continuation_queues_turn_without_fake_user_history(
tmp_path: Path,
) -> None:
loop = _make_full_loop(tmp_path)
loop.consolidator.maybe_consolidate_by_tokens = AsyncMock(return_value=False) # type: ignore[method-assign]
session = loop.sessions.get_or_create("feishu:c-auto")
session.metadata[GOAL_STATE_KEY] = {
"status": "active",
"objective": "Finish the long goal.",
}
loop.sessions.save(session)
calls: list[dict] = []
async def fake_run_agent_loop(initial_messages, *, metadata=None, **_kwargs):
calls.append({"initial_messages": initial_messages, "metadata": metadata})
if len(calls) == 1:
return (
"paused",
[],
[*initial_messages, {"role": "assistant", "content": "paused"}],
"max_iterations",
False,
)
return (
"done",
[],
[*initial_messages, {"role": "assistant", "content": "done"}],
"completed",
False,
)
loop._run_agent_loop = fake_run_agent_loop # type: ignore[method-assign]
pending: asyncio.Queue[InboundMessage] = asyncio.Queue()
first = await loop._process_message(
InboundMessage(
channel="feishu",
sender_id="u1",
chat_id="c-auto",
content="start the goal",
),
pending_queue=pending,
)
assert first is None
queued = pending.get_nowait()
assert queued.sender_id == "system:continuation"
assert queued.metadata[INTERNAL_CONTINUATION_META] is True
assert "Finish the long goal." in queued.content
session = loop.sessions.get_or_create("feishu:c-auto")
assert [
{k: v for k, v in m.items() if k in {"role", "content"}}
for m in session.messages
] == [{"role": "user", "content": "start the goal"}]
second = await loop._process_message(queued, pending_queue=asyncio.Queue())
assert second is not None
assert second.content == "done"
session = loop.sessions.get_or_create("feishu:c-auto")
assert [
{k: v for k, v in m.items() if k in {"role", "content"}}
for m in session.messages
] == [
{"role": "user", "content": "start the goal"},
{"role": "assistant", "content": "done"},
]
@pytest.mark.asyncio
async def test_internal_continuation_preserves_streaming_route_metadata(
tmp_path: Path,
) -> None:
loop = _make_full_loop(tmp_path)
loop.consolidator.maybe_consolidate_by_tokens = AsyncMock(return_value=False) # type: ignore[method-assign]
session = loop.sessions.get_or_create("feishu:c-stream")
session.metadata[GOAL_STATE_KEY] = {
"status": "active",
"objective": "Finish the streamed long goal.",
}
loop.sessions.save(session)
calls = 0
async def fake_run_agent_loop(initial_messages, *, on_stream=None, on_stream_end=None, **_kwargs):
nonlocal calls
calls += 1
if calls == 1:
return (
"paused",
[],
[*initial_messages, {"role": "assistant", "content": "paused"}],
"max_iterations",
False,
)
assert on_stream is not None
assert on_stream_end is not None
await on_stream("done")
await on_stream_end(resuming=False)
return (
"done",
[],
[*initial_messages, {"role": "assistant", "content": "done"}],
"completed",
False,
)
loop._run_agent_loop = fake_run_agent_loop # type: ignore[method-assign]
await loop._dispatch(InboundMessage(
channel="feishu",
sender_id="u1",
chat_id="c-stream",
content="start the goal",
metadata={
"_wants_stream": True,
"message_id": "om_001",
"origin_message_id": "root_001",
"_stream_id": "old-stream",
},
))
assert loop.bus.outbound_size == 0
queued = await asyncio.wait_for(loop.bus.consume_inbound(), timeout=0.5)
assert queued.metadata[INTERNAL_CONTINUATION_META] is True
assert queued.metadata["_wants_stream"] is True
assert queued.metadata["message_id"] == "om_001"
assert queued.metadata["origin_message_id"] == "root_001"
assert "_stream_id" not in queued.metadata
await loop._dispatch(queued)
outbound = []
while loop.bus.outbound_size:
outbound.append(await loop.bus.consume_outbound())
deltas = [m for m in outbound if m.metadata.get("_stream_delta")]
ends = [m for m in outbound if m.metadata.get("_stream_end")]
streamed_markers = [m for m in outbound if m.metadata.get("_streamed")]
assert [m.content for m in deltas] == ["done"]
assert len(ends) == 1
assert ends[0].metadata["_resuming"] is False
assert ends[0].metadata["message_id"] == "om_001"
assert ends[0].metadata["origin_message_id"] == "root_001"
assert isinstance(ends[0].metadata.get("_stream_id"), str)
assert streamed_markers and streamed_markers[-1].content == "done"
@pytest.mark.asyncio
async def test_websocket_internal_continuation_keeps_single_visible_run(
tmp_path: Path,
) -> None:
loop = _make_full_loop(tmp_path)
loop.consolidator.maybe_consolidate_by_tokens = AsyncMock(return_value=False) # type: ignore[method-assign]
session = loop.sessions.get_or_create("websocket:c-auto")
session.metadata[GOAL_STATE_KEY] = {
"status": "active",
"objective": "Finish the long goal.",
}
loop.sessions.save(session)
calls = 0
async def fake_run_agent_loop(initial_messages, **_kwargs):
nonlocal calls
calls += 1
if calls == 1:
return (
"paused",
[],
[*initial_messages, {"role": "assistant", "content": "paused"}],
"max_iterations",
False,
)
return (
"done",
[],
[*initial_messages, {"role": "assistant", "content": "done"}],
"completed",
False,
)
loop._run_agent_loop = fake_run_agent_loop # type: ignore[method-assign]
await loop._dispatch(InboundMessage(
channel="websocket",
sender_id="u1",
chat_id="c-auto",
content="start the goal",
metadata={"webui": True},
))
first_outbound = []
while loop.bus.outbound_size:
first_outbound.append(await loop.bus.consume_outbound())
first_statuses = [m.metadata for m in first_outbound if m.metadata.get("_goal_status")]
assert [m["goal_status"] for m in first_statuses] == ["running"]
assert not [m for m in first_outbound if m.metadata.get("_turn_end")]
started_at = first_statuses[0]["started_at"]
queued = await asyncio.wait_for(loop.bus.consume_inbound(), timeout=0.5)
assert queued.metadata[INTERNAL_CONTINUATION_META] is True
assert queued.metadata[INTERNAL_CONTINUATION_RUN_STARTED_AT_META] == started_at
await loop._dispatch(queued)
second_outbound = []
while loop.bus.outbound_size:
second_outbound.append(await loop.bus.consume_outbound())
second_statuses = [m.metadata for m in second_outbound if m.metadata.get("_goal_status")]
assert [m["goal_status"] for m in second_statuses] == ["running", "idle"]
assert second_statuses[0]["started_at"] == started_at
turn_end = [m for m in second_outbound if m.metadata.get("_turn_end")]
assert len(turn_end) == 1
assert isinstance(turn_end[0].metadata.get("latency_ms"), int)
@pytest.mark.asyncio
async def test_process_message_uses_context_chat_id_for_runtime_prompt(tmp_path: Path) -> None:
loop = _make_full_loop(tmp_path)
@@ -832,17 +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]
@@ -850,7 +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",
@@ -860,11 +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

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