A2A Integration for Microsoft Agent Framework
This library provides agent-to-agent (A2A) communication and integration capabilities for the Microsoft Agent Framework. It enables agents built with the framework to interact, exchange messages, and coordinate actions, particularly within environments like Azure AI Studio and Prompt Flow. The package is currently in a beta development stage (version 1.0.0b), indicating active development and potential for API changes.
Warnings
- breaking API instability and breaking changes: As a beta package, `agent-framework-a2a`'s API surface is subject to frequent changes without strict adherence to semantic versioning. Existing code might break with minor version updates.
- gotcha Requires `agent-framework` context: This library is designed as an integration for the broader Microsoft Agent Framework. Standalone usage without the full framework context or appropriate environment setup (e.g., Azure AI Studio, Prompt Flow) may be complex or non-functional.
- gotcha Limited public documentation: Due to its beta status and integration-focused nature, detailed, standalone documentation and examples specifically for `agent-framework-a2a` may be sparse. Expect to infer usage from the main `agent-framework` repository.
- gotcha Import path variability: Given the beta status and potential refactoring, the exact import paths for client and model classes may change in future releases. Always verify against the latest framework examples.
Install
-
pip install agent-framework-a2a
Imports
- AgentToAgentClient
from agent_framework_a2a.client import AgentToAgentClient
- AgentToAgentMessage
from agent_framework_a2a.models import AgentToAgentMessage
Quickstart
import os
print("Attempting to import core A2A components from agent-framework-a2a...")
try:
from agent_framework_a2a.client import AgentToAgentClient
from agent_framework_a2a.models import AgentToAgentMessage
print("Successfully imported AgentToAgentClient and AgentToAgentMessage.")
# This part is conceptual as actual client instantiation and usage
# heavily depends on the broader Microsoft Agent Framework context and
# specific environment setup (e.g., Azure AI Studio, Prompt Flow).
# The below code demonstrates creating a sample message object.
sender_id = os.environ.get("A2A_SENDER_ID", "agent_alpha")
recipient_id = os.environ.get("A2A_RECIPIENT_ID", "agent_beta")
message_content = "Hello from agent_alpha to agent_beta!"
# Creating a message object (assuming a simple constructor)
message = AgentToAgentMessage(
sender_id=sender_id,
recipient_id=recipient_id,
content=message_content,
message_type="text"
)
print(f"Created a sample message: Sender={message.sender_id}, Recipient={message.recipient_id}, Content='{message.content}'")
# To use AgentToAgentClient, you would typically need to configure it
# with an endpoint and potentially authentication from your environment.
# client = AgentToAgentClient(endpoint=os.environ.get("A2A_ENDPOINT", ""), api_key=os.environ.get("A2A_API_KEY", ""))
# response = client.send_message(message)
# print(f"Conceptual message sent, response: {response}")
except ImportError as e:
print(f"Failed to import agent-framework-a2a components. Please ensure the library is correctly installed and its API is stable. Error: {e}")
except Exception as e:
print(f"An unexpected error occurred during quickstart: {e}")