|
| 1 | +--- |
| 2 | +title: AutoGen |
| 3 | +--- |
| 4 | +[](){ #deployment-autogen } |
| 5 | + |
| 6 | +[AutoGen](https://github.com/microsoft/autogen) is a framework for creating multi-agent AI applications that can act autonomously or work alongside humans. |
| 7 | + |
| 8 | +## Prerequisites |
| 9 | + |
| 10 | +- Setup vLLM environment |
| 11 | + |
| 12 | +- Setup [AutoGen](https://microsoft.github.io/autogen/0.2/docs/installation/) environment |
| 13 | + |
| 14 | +```console |
| 15 | +pip install vllm |
| 16 | + |
| 17 | +# Install AgentChat and OpenAI client from Extensions |
| 18 | +# AutoGen requires Python 3.10 or later. |
| 19 | +pip install -U "autogen-agentchat" "autogen-ext[openai]" |
| 20 | +``` |
| 21 | + |
| 22 | +## Deploy |
| 23 | + |
| 24 | +- Start the vLLM server with the supported chat completion model, e.g. |
| 25 | + |
| 26 | +```console |
| 27 | +python -m vllm.entrypoints.openai.api_server \ |
| 28 | + --model mistralai/Mistral-7B-Instruct-v0.2 |
| 29 | +``` |
| 30 | + |
| 31 | +- Call it with AutoGen: |
| 32 | + |
| 33 | +```python |
| 34 | +import asyncio |
| 35 | +from autogen_core.models import UserMessage |
| 36 | +from autogen_ext.models.openai import OpenAIChatCompletionClient |
| 37 | +from autogen_core.models import ModelFamily |
| 38 | + |
| 39 | + |
| 40 | +async def main() -> None: |
| 41 | + # Create a model client |
| 42 | + model_client = OpenAIChatCompletionClient( |
| 43 | + model="mistralai/Mistral-7B-Instruct-v0.2", |
| 44 | + base_url="http://{your-vllm-host-ip}:{your-vllm-host-port}/v1", |
| 45 | + api_key="EMPTY", |
| 46 | + model_info={ |
| 47 | + "vision": False, |
| 48 | + "function_calling": False, |
| 49 | + "json_output": False, |
| 50 | + "family": ModelFamily.MISTRAL, |
| 51 | + "structured_output": True, |
| 52 | + }, |
| 53 | + ) |
| 54 | + |
| 55 | + messages = [UserMessage(content="Write a very short story about a dragon.", source="user")] |
| 56 | + |
| 57 | + # Create a stream. |
| 58 | + stream = model_client.create_stream(messages=messages) |
| 59 | + |
| 60 | + # Iterate over the stream and print the responses. |
| 61 | + print("Streamed responses:") |
| 62 | + async for response in stream: |
| 63 | + if isinstance(response, str): |
| 64 | + # A partial response is a string. |
| 65 | + print(response, flush=True, end="") |
| 66 | + else: |
| 67 | + # The last response is a CreateResult object with the complete message. |
| 68 | + print("\n\n------------\n") |
| 69 | + print("The complete response:", flush=True) |
| 70 | + print(response.content, flush=True) |
| 71 | + |
| 72 | + # Close the client when done. |
| 73 | + await model_client.close() |
| 74 | + |
| 75 | + |
| 76 | +asyncio.run(main()) |
| 77 | +``` |
| 78 | + |
| 79 | +For details, see the tutorial: |
| 80 | + |
| 81 | +- [Using vLLM in AutoGen](https://microsoft.github.io/autogen/0.2/docs/topics/non-openai-models/local-vllm/) |
| 82 | + |
| 83 | +- [OpenAI-compatible API examples](https://microsoft.github.io/autogen/stable/reference/python/autogen_ext.models.openai.html#autogen_ext.models.openai.OpenAIChatCompletionClient) |
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