78 lines
2.2 KiB
Markdown
78 lines
2.2 KiB
Markdown
# Web application
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A browser-based reference implementation of conversational RAG, built on a Starlette backend with pydantic-ai's `AGUIAdapter` and a Next.js / CopilotKit frontend. It lives in the `app/` directory of the haiku.rag repository.
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This is a starting point for your own deployments, not the canonical haiku.rag UX. For the day-to-day terminal experience see [Chat](chat.md).
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## Features
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- Streaming chat with real-time tool execution visibility.
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- Expandable citations with source documents, pages, and headings.
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- Visual grounding to view chunk source locations in documents.
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- Document filter to restrict searches to selected documents.
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- Session state view for inspecting citations and search results.
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## Quick start
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```bash
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cd app
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docker compose -f docker-compose.dev.yml up -d --build
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```
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- Frontend: `http://localhost:3000`
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- Backend: `http://localhost:8001`
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## Architecture
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- **Backend**: Starlette server with pydantic-ai `AGUIAdapter`.
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- **Frontend**: Next.js with CopilotKit.
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- **Protocol**: AG-UI for streaming chat.
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## Configuration
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Create a `.env` file in the `app/` directory:
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```bash
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# API Keys (at least one required)
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ANTHROPIC_API_KEY=your-anthropic-key
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OPENAI_API_KEY=your-openai-key
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# Database path
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DB_PATH=/path/to/your/haiku.rag.lancedb
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# Optional: Ollama base URL (if using local models)
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OLLAMA_BASE_URL=http://localhost:11434
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# Optional: Logfire for observability
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LOGFIRE_TOKEN=your-logfire-token
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```
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For full configuration, mount a `haiku.rag.yaml` file:
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```yaml
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# app/haiku.rag.yaml
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qa:
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model:
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provider: anthropic
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name: claude-sonnet-4-20250514
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```
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## API endpoints
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| Endpoint | Method | Description |
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|----------|--------|-------------|
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| `/v1/chat/stream` | POST | AG-UI chat streaming |
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| `/api/documents` | GET | List all documents |
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| `/api/info` | GET | Database statistics |
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| `/api/visualize/{chunk_id}` | GET | Visual grounding images (base64) |
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| `/health` | GET | Health check |
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## Development
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The backend reloads automatically on file changes. For frontend changes:
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```bash
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docker compose -f docker-compose.dev.yml up -d --build frontend
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```
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If `LOGFIRE_TOKEN` is set, LLM calls are traced and available in the Logfire dashboard.
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