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Improve samples
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# Basic example of hosting an agent with the `invocations` API
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## Running the server locally
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### Environment setup
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Follow the instructions in the [Environment setup](../../README.md#environment-setup) section of the README in the parent directory to set up your environment and install dependencies.
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Run the following command to start the server:
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```bash
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python main.py
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```
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### Interacting with the agent
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Send a POST request to the server with a JSON body containing a "message" field to interact with the agent. For example:
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```bash
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curl -X POST http://localhost:8088/invocations -i -H "Content-Type: application/json" -d '{"message": "Hi"}'
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```
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The server will respond with a JSON object containing the response text. The `-i` flag in the `curl` command includes the HTTP response headers in the output, which includes the session ID that can be used for multi-turn conversations. Here is an example of the response:
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```
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HTTP/1.1 200
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content-length: 34
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content-type: application/json
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x-agent-invocation-id: ec04d020-a0e7-441e-ae83-db75635a9f83
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x-agent-session-id: 9370b9d4-cd13-4436-a57f-03b843ac0e17
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x-platform-server: azure-ai-agentserver-core/2.0.0a20260410006 (python/3.12)
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date: Fri, 17 Apr 2026 23:46:44 GMT
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server: hypercorn-h11
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{"response":"Hi! How can I help?"}
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```
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### Multi-turn conversation
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To have a multi-turn conversation with the agent, take the session ID from the response headers of the previous request and include it in URL parameters for the next request. For example:
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```bash
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curl -X POST http://localhost:8088/invocations?agent_session_id=9370b9d4-cd13-4436-a57f-03b843ac0e17 -i -H "Content-Type: application/json" -d '{"message": "How are you?"}'
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```
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