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* docs: make onboarding friendlier for beginners * docs: build clearer documentation paths Maintainer edit: turn the onboarding follow-up into a layered docs structure for first-time setup, provider selection, troubleshooting, CLI reference, and source-level architecture. This keeps quick start focused while giving advanced users precise reference paths. * docs: render architecture flow with mermaid Maintainer edit: replace the ASCII architecture sketch with a GitHub-rendered Mermaid flowchart so the core runtime path is easier to scan in the PR and README docs. * docs: recommend model presets for model config Maintainer edit: make named modelPresets the primary model configuration path and expand fallback preset examples so string fallbacks are clearly preset names, not raw model IDs. * docs: document api base urls and langfuse setup Maintainer edit: explain when users need apiBase/base URL in quick start and provider docs, and add Langfuse tracing setup with troubleshooting links. * docs: use python module pip consistently Maintainer edit: keep install commands tied to the active Python interpreter by using python -m pip in the Azure optional dependency notes too. * docs: add non-technical getting started path Maintainer edit: add a wizard-first guide for users without terminal or JSON background, including a text TUI menu example and links from the main docs entrypoints. * docs: avoid hard-wrapped prose in user docs Maintainer edit: unwrap ordinary prose across user-facing documentation while preserving markdown structure, code blocks, tables, lists, and prompt/template files. * docs: keep desktop list continuations nested Maintainer edit: preserve list nesting after unwrapping prose in the desktop WebUI sync guide. * docs: add one-command installer Maintainer edit: add auditable macOS/Linux and Windows install scripts that install nanobot-ai and start the onboarding wizard, then document the commands in the main onboarding entrypoints. * docs: add installer dry run mode Maintainer edit: add --dry-run to the one-command installer scripts so users can preview Python detection, install source, pip command, and wizard behavior without changing their environment. * docs: clean installer error output Maintainer edit: make PowerShell installer failures print a concise Error: message instead of Write-Error call-site details. * docs: add provider setup cookbook Maintainer edit: add pasteable provider recipes for common hosted, local, fallback, runtime switching, and Langfuse setups, then link the cookbook from onboarding and troubleshooting entrypoints. * docs: address review feedback * docs: clarify reader paths * docs: explain terminal basics for beginners * docs: clarify wizard navigation * docs: avoid duplicate onboarding steps * docs: add setup status check * docs: explain status output * docs: remove provider recommendation wording * docs: explain status diagnostics * docs: reduce hard-wrapped guidance * docs: migrate config examples to presets * docs: clarify python command fallbacks * docs: improve installer failure recovery * docs: expand install troubleshooting * docs: cover installer download failures * docs: put stable install paths first * docs: add bundled webui quick path * docs: clarify provider-neutral setup * docs: clarify gateway setup for chat surfaces * docs: improve docs navigation paths * docs: add configuration quick jump * docs: clarify provider secret variables * chore: request PR review acknowledgement Empty commit: please read the PR review comments and reply on the PR to confirm that you have received them. This commit intentionally changes no files; it exists only to notify the remote Codex run so it can end its active goal. * docs: add README start here guide * docs: avoid provider recommendation wording * docs: guide next steps after first reply * docs: explain merging JSON snippets * docs: add CLI command chooser * docs: add configuration task map * docs: add deployment readiness guide * docs: simplify WebUI entry paths * docs: add provider recipe chooser * docs: fix provider factual references Update OpenRouter and LongCat model examples, align Bedrock guidance, and make fallback snippets schema-valid. Also correct group policy wording and image-generation provider lists to match the current code. * fix: keep PowerShell installer from closing caller shell * docs: mention self-guided configuration
125 lines
3.9 KiB
Markdown
125 lines
3.9 KiB
Markdown
# OpenAI-Compatible API
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nanobot can expose a minimal OpenAI-compatible endpoint for local integrations:
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```bash
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python -m pip install "nanobot-ai[api]"
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nanobot agent -m "Hello!"
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nanobot serve
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```
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Run the CLI check first. If `nanobot agent -m "Hello!"` fails, fix provider or config setup before debugging the API server. By default, the API binds to `127.0.0.1:8900`. You can change this in `config.json`.
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For setup help, see [`quick-start.md`](./quick-start.md), [`providers.md`](./providers.md), and [`troubleshooting.md`](./troubleshooting.md).
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## Behavior
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- Session isolation: pass `"session_id"` in the request body to isolate conversations; omit for a shared default session (`api:default`)
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- Single-message input: each request must contain exactly one `user` message
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- Fixed model: omit `model`, or pass the same model shown by `/v1/models`
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- Streaming: set `stream=true` to receive Server-Sent Events (`text/event-stream`) with OpenAI-compatible delta chunks, terminated by `data: [DONE]`; omit or set `stream=false` for a single JSON response
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- **File uploads**: supports images, PDF, Word (.docx), Excel (.xlsx), PowerPoint (.pptx) via JSON base64 or `multipart/form-data` (max 10MB per file)
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- API requests run in the synthetic `api` channel, so the `message` tool does **not** automatically deliver to Telegram/Discord/etc. To proactively send to another chat, call `message` with an explicit `channel` and `chat_id` for an enabled channel.
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Example tool call for cross-channel delivery from an API session:
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```json
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{
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"content": "Build finished successfully.",
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"channel": "telegram",
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"chat_id": "123456789"
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}
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```
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If `channel` points to a channel that is not enabled in your config, nanobot will queue the outbound event but no platform delivery will occur.
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## Endpoints
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- `GET /health`
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- `GET /v1/models`
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- `POST /v1/chat/completions`
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## curl
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```bash
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curl http://127.0.0.1:8900/v1/chat/completions \
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-H "Content-Type: application/json" \
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-d '{
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"messages": [{"role": "user", "content": "hi"}],
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"session_id": "my-session"
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}'
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```
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## File Upload (JSON base64)
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Send images inline using the OpenAI multimodal content format:
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```bash
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curl http://127.0.0.1:8900/v1/chat/completions \
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-H "Content-Type: application/json" \
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-d '{
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"messages": [{"role": "user", "content": [
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{"type": "text", "text": "Describe this image"},
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{"type": "image_url", "image_url": {"url": "data:image/png;base64,iVBOR..."}}
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]}]
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}'
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```
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## File Upload (multipart/form-data)
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Upload any supported file type (images, PDF, Word, Excel, PPT) via multipart:
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```bash
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# Single file
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curl http://127.0.0.1:8900/v1/chat/completions \
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-F "message=Summarize this report" \
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-F "files=@report.docx"
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# Multiple files with session isolation
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curl http://127.0.0.1:8900/v1/chat/completions \
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-F "message=Compare these files" \
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-F "files=@chart.png" \
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-F "files=@data.xlsx" \
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-F "session_id=my-session"
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```
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Supported file types:
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- **Images**: PNG, JPEG, GIF, WebP (sent to AI as base64 for vision analysis)
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- **Documents**: PDF, Word (.docx), Excel (.xlsx), PowerPoint (.pptx) (text extracted and sent to AI)
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- **Text**: TXT, Markdown, CSV, JSON, etc. (read directly)
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## Python (`requests`)
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```python
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import requests
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resp = requests.post(
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"http://127.0.0.1:8900/v1/chat/completions",
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json={
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"messages": [{"role": "user", "content": "hi"}],
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"session_id": "my-session", # optional: isolate conversation
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},
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timeout=120,
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)
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resp.raise_for_status()
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print(resp.json()["choices"][0]["message"]["content"])
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```
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## Python (`openai`)
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```python
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from openai import OpenAI
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client = OpenAI(
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base_url="http://127.0.0.1:8900/v1",
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api_key="dummy",
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)
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resp = client.chat.completions.create(
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model="MiniMax-M2.7",
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messages=[{"role": "user", "content": "hi"}],
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extra_body={"session_id": "my-session"}, # optional: isolate conversation
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)
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print(resp.choices[0].message.content)
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```
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