haiku.rag/examples/a2a-server

haiku-rag-a2a

A2A (Agent-to-Agent) protocol server for haiku.rag. This package provides a conversational agent interface that maintains conversation history and context across multiple turns.

Features

• Conversational Context: Maintains full conversation history including tool calls and results
• Multi-turn Dialogue: Supports follow-up questions with pronoun resolution ("he", "it", "that document")
• Intelligent Search: Performs single or multiple searches depending on question complexity
• Source Citations: Always includes sources with both titles and URIs
• Full Document Retrieval: Can fetch complete documents on request
• Multiple Skills: Exposes three distinct skills with appropriate artifacts:
  • document-qa: Conversational question answering (default)
  • document-search: Semantic search with structured results
  • document-retrieve: Fetch complete documents by URI

Installation

This package is not published to PyPI. Install it locally from the haiku.rag repository:

cd examples/a2a-server
uv sync

This will install the package and all its dependencies, including haiku.rag.

Quick Start

Starting the A2A Server

# Start server with default database location (uses the same default as haiku-rag)
uv run haiku-rag-a2a serve

# Or specify a custom database path
uv run haiku-rag-a2a serve --db /path/to/database

# Start on custom host/port
uv run haiku-rag-a2a serve --host 0.0.0.0 --port 8080

By default, the server uses the same database location as haiku-rag:

• Linux: ~/.local/share/haiku.rag/haiku.rag.lancedb
• macOS: ~/Library/Application Support/haiku.rag/haiku.rag.lancedb
• Windows: C:/Users/<USER>/AppData/Roaming/haiku.rag/haiku.rag.lancedb

Interactive Client

Test and interact with the A2A server using the built-in interactive client:

# Connect to local server
uv run haiku-rag-a2a client

# Connect to remote server
uv run haiku-rag-a2a client --url https://example.com:8000

The interactive client provides:

• Rich markdown rendering of agent responses
• Conversation context across multiple turns
• Agent card discovery and display
• Compact artifact summaries

Python Usage

from pathlib import Path
from haiku_rag_a2a.a2a import create_a2a_app
import uvicorn

# Create A2A app
app = create_a2a_app(Path("/path/to/database"))

# Run with uvicorn
uvicorn.run(app, host="127.0.0.1", port=8000)

Security Examples

The security_examples/ directory contains examples for securing the A2A server:

• apikey_example.py - Simple API key authentication
• oauth2_github.py - GitHub Personal Access Token authentication
• oauth2_example.py - Full OAuth2 with JWT verification

Architecture

The A2A agent uses:

• FastA2A: Python framework implementing the A2A protocol
• Pydantic AI: Agent framework with tool support
• In-Memory Storage: Context and message history storage (persists during server lifetime)
• Conversation State: Full pydantic-ai message history serialized in A2A context

Configuration

The server uses the same configuration as haiku.rag. You can specify a config file:

uv run haiku-rag-a2a serve --db /path/to/database --config haiku.rag.yaml

You can also control the maximum number of conversation contexts via the --max-contexts parameter (defaults to 1000).

Documentation

See a2a.md for detailed documentation including:

• API examples
• Security configuration
• Docker deployment
• Artifact specification

License

MIT