Castella A2a

Castella A2A Protocol Integration

A2A (Agent-to-Agent) is an open protocol for AI agent communication and discovery. Castella provides a client for connecting to A2A agents and displaying their information.

When to use: "connect to A2A agent", "A2AClient", "agent card", "send message to agent", "list agent skills", "A2A protocol", "stream agent response"

Quick Start

Connect to an A2A agent:

from castella.a2a import A2AClient

client = A2AClient("http://agent.example.com")
print(f"Connected to: {client.name}")
print(f"Skills: {[s.name for s in client.skills]}")

response = client.ask("What's the weather in Tokyo?")
print(response)

Installation

uv sync --extra agent   # A2A + A2UI support

A2AClient

The main class for A2A communication:

from castella.a2a import A2AClient

client = A2AClient(
    agent_url="http://localhost:8080",
    timeout=30.0,
)

Properties

Methods

# Synchronous ask
response = client.ask("Hello!")

# Asynchronous ask
response = await client.ask_async("Hello!")

# Streaming (async)
async for chunk in client.ask_stream("Tell me a story"):
    print(chunk, end="", flush=True)

# Send structured message
from castella.a2a import Message
response = client.send_message(Message(role="user", content="Hello"))

# Check skills
if client.has_skill("get_weather"):
    skill = client.get_skill("get_weather")
    print(f"Skill: {skill.name} - {skill.description}")

Agent Card

Access agent metadata via the agent card:

from castella.a2a import A2AClient

client = A2AClient("http://agent.example.com")
card = client.agent_card

print(f"Name: {card.name}")
print(f"Description: {card.description}")
print(f"Version: {card.version}")
print(f"URL: {card.url}")

# List skills
for skill in card.skills:
    print(f"  - {skill.name}: {skill.description}")
    print(f"    Tags: {skill.tags}")

AgentSkill

Skills define agent capabilities:

skill = client.get_skill("get_weather")

print(skill.name)          # "get_weather"
print(skill.description)   # "Get current weather"
print(skill.tags)          # ["weather", "api"]
print(skill.examples)      # ["What's the weather in Tokyo?"]

Error Handling

from castella.a2a import A2AClient, A2AConnectionError, A2AResponseError

try:
    client = A2AClient("http://agent.example.com")
    response = client.ask("Hello")
except A2AConnectionError as e:
    print(f"Connection failed: {e}")
except A2AResponseError as e:
    print(f"Agent error: {e}")

Streaming Responses

For long-running responses:

async def stream_story():
    client = A2AClient("http://agent.example.com")

    if client.supports_streaming:
        async for chunk in client.ask_stream("Tell me a story"):
            print(chunk, end="", flush=True)
    else:
        # Fallback to non-streaming
        response = await client.ask_async("Tell me a story")
        print(response)

AgentCardView Widget

Display agent card in Castella UI:

from castella import App, Column
from castella.agent import AgentCardView
from castella.a2a import A2AClient
from castella.frame import Frame

client = A2AClient("http://agent.example.com")

card_view = AgentCardView(
    client.agent_card,
    show_skills=True,
    compact=False,
)

App(Frame("Agent Info", 400, 300), card_view).run()

Integration with AgentChat

Use A2AClient with high-level chat components:

from castella.agent import AgentChat

# Automatic connection and chat UI
chat = AgentChat.from_a2a("http://localhost:8080")
chat.run()

See the castella-agent-ui skill for more chat options.

Creating A2A Servers

For creating A2A servers, use python-a2a directly:

from python_a2a import A2AServer, skill, run_server

class WeatherAgent(A2AServer):
    @skill(name="get_weather", description="Get current weather")
    def get_weather(self, location: str) -> str:
        return f"Weather in {location}: Sunny, 22°C"

agent = WeatherAgent(
    name="Weather Agent",
    description="Provides weather information",
    version="1.0.0",
    url="http://localhost:8080",
)

run_server(agent, port=8080)

Best Practices

1. Check capabilities before using features:

   if client.supports_streaming:
       async for chunk in client.ask_stream(msg):
           ...
   

2. Handle errors gracefully:

   try:
       response = client.ask(msg)
   except A2AConnectionError:
       # Retry or show offline message
   

3. Use async for UI responsiveness:

   response = await client.ask_async(msg)
   

4. Inspect skills for routing:

   if client.has_skill("search"):
       # Route search queries to this agent
   

Reference

• references/types.md - AgentCard, AgentSkill, Message types
• references/streaming.md - Streaming response handling
• scripts/ - Executable examples (a2a_connect.py, a2a_async.py)
• A2A Protocol: https://a2a-protocol.org/
• python-a2a: https://github.com/themanojdesai/python-a2a

Converted and distributed by TomeVault — claim your Tome and manage your conversions.