Web application

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.

This is a starting point for your own deployments, not the canonical haiku.rag UX. For the day-to-day terminal experience see Chat.

Features

• Streaming chat with real-time tool execution visibility.
• Expandable citations with source documents, pages, and headings.
• Visual grounding to view chunk source locations in documents.
• Document filter to restrict searches to selected documents.
• Session state view for inspecting citations and search results.

Quick start

cd app
docker compose -f docker-compose.dev.yml up -d --build

• Frontend: http://localhost:3000
• Backend: http://localhost:8001

Architecture

• Backend: Starlette server with pydantic-ai AGUIAdapter.
• Frontend: Next.js with CopilotKit.
• Protocol: AG-UI for streaming chat.

Configuration

Create a .env file in the app/ directory:

# API Keys (at least one required)
ANTHROPIC_API_KEY=your-anthropic-key
OPENAI_API_KEY=your-openai-key

# Database path
DB_PATH=/path/to/your/haiku.rag.lancedb

# Optional: Ollama base URL (if using local models)
OLLAMA_BASE_URL=http://localhost:11434

# Optional: Logfire for observability
LOGFIRE_TOKEN=your-logfire-token

For full configuration, mount a haiku.rag.yaml file:

# app/haiku.rag.yaml
qa:
  model:
    provider: anthropic
    name: claude-sonnet-4-20250514

API endpoints

Development

The backend reloads automatically on file changes. For frontend changes:

docker compose -f docker-compose.dev.yml up -d --build frontend

If LOGFIRE_TOKEN is set, LLM calls are traced and available in the Logfire dashboard.