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Giles Odigwe
5affc9c333
* Reorganize A2A samples: client demos in 02-agents, use package A2AExecutor - Move client samples (agent_with_a2a, a2a_agent_as_function_tools) to samples/02-agents/a2a/ - Add new concept samples: polling, stream reconnection, protocol selection - Replace sample agent_executor.py with package-level A2AExecutor (stream=True) - Update 04-hosting/a2a to focus on server-side, point to 02-agents for clients - Add README.md for the new 02-agents/a2a/ sample collection Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix streaming artifact coalescing and address PR review feedback A2AExecutor fix: - Generate a stable artifact_id per stream in _run_stream so all streaming chunks share the same ID, enabling proper append=True coalescing per the A2A spec (TaskArtifactUpdateEvent with same artifactId). - Previously, item.message_id was None for OpenAI/Foundry streaming updates, causing the SDK to generate a new random UUID per token (100+ separate artifacts instead of 1 appended artifact). Sample improvements: - Replace join workaround with response.text now that coalescing works - Add background=True to stream reconnection resume call (required for continuation token emission on in-progress tasks) - Fix type ignore specificity in polling sample Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
82 lines
2.5 KiB
Markdown
82 lines
2.5 KiB
Markdown
# A2A Server Hosting Examples
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This sample demonstrates how to **host** Agent Framework agents as A2A-compliant servers using the [A2A (Agent2Agent) protocol](https://a2a-protocol.org/latest/).
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> **Looking for client samples?** See [`samples/02-agents/a2a/`](../../02-agents/a2a/) for consuming remote A2A agents.
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## Server Samples
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| Run this file | To... |
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|---------------|-------|
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| **[`a2a_server.py`](a2a_server.py)** | Host an Agent Framework agent as an A2A-compliant server (multi-agent). |
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| **[`agent_framework_to_a2a.py`](agent_framework_to_a2a.py)** | Minimal example: expose a single agent as an A2A server. |
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## Supporting Modules
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| File | Description |
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|------|-------------|
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| [`agent_definitions.py`](agent_definitions.py) | Agent and AgentCard factory definitions for invoice, policy, and logistics agents. |
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| [`invoice_data.py`](invoice_data.py) | Mock invoice data and tool functions for the invoice agent. |
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| [`a2a_server.http`](a2a_server.http) | REST Client requests for testing the server directly from VS Code. |
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## Environment Variables
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### Required (Server)
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- `FOUNDRY_PROJECT_ENDPOINT` — Your Azure AI Foundry project endpoint
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- `FOUNDRY_MODEL` — Model deployment name (e.g. `gpt-4o`)
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## Quick Start
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All commands below should be run from this directory:
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```powershell
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cd python/samples/04-hosting/a2a
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```
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### 0. Install Dependencies
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Copy `.env.example` to `.env` and fill in your values:
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```powershell
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copy .env.example .env
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```
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**Option A — pip (standard):**
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```powershell
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python -m venv .venv
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.venv\Scripts\Activate.ps1 # Windows
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# source .venv/bin/activate # macOS / Linux
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pip install -r requirements.txt
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```
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**Option B — uv:**
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```powershell
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uv run python a2a_server.py --agent-type policy
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```
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### 1. Start the A2A Server
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> **Note (Option A — pip users):** Replace `uv run python` with `python` in all `uv run` commands below. `uv` is not required once the virtual environment is activated.
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Pick an agent type and start the server (each in its own terminal):
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```powershell
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uv run python a2a_server.py --agent-type invoice --port 5000
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uv run python a2a_server.py --agent-type policy --port 5001
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uv run python a2a_server.py --agent-type logistics --port 5002
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```
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You can run one agent or all three — each listens on its own port.
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### 2. Run a Client
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Once a server is running, use any of the client samples in [`samples/02-agents/a2a/`](../../02-agents/a2a/):
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```powershell
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cd python/samples/02-agents/a2a
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$env:A2A_AGENT_HOST = "http://localhost:5001/"
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uv run python agent_with_a2a.py
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```
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