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AutoGen

1.1 Usage​

from autogen_ext.models.openai import OpenAIChatCompletionClient

client = OpenAIChatCompletionClient(
    model="minimax/minimax-m2.5",
    base_url="https://api.hpc-ai.com/inference/v1",
    api_key="your-hpc-ai-api-key",
    model_info={
        "vision": False,
        "function_calling": True,
        "json_output": True,
    }
)

# Use in Agent
from autogen_agentchat import AssistantAgent
agent = AssistantAgent(
    name="assistant",
    model_client=client,
)

Method 2: config_list (Legacy)​

import autogen

llm_config = {
    "config_list": [
        {
            "model": "minimax/minimax-m2.5",
            "api_base": "https://api.hpc-ai.com/inference/v1",
            "api_key": "your-hpc-ai-api-key",
            "api_type": "openai"
        }
    ]
}

assistant = autogen.AssistantAgent(
    name="assistant",
    llm_config=llm_config
)

Method 3: Custom Model Client (Advanced)​

from autogen_core.models import ChatCompletionClient, CreateResult, LLMMessage, ModelInfo

class CustomModelClient(ChatCompletionClient):
    def __init__(self, api_key, base_url, model, **kwargs):
        self.api_key = api_key
        self.base_url = base_url
        self.model = model
        self._model_info = ModelInfo(
            vision=False, function_calling=True, json_output=True
        )
    
    @property
    def model_info(self) -> ModelInfo:
        return self._model_info
    
    async def create(self, messages: List[LLMMessage], **kwargs) -> CreateResult:
        import requests
        
        headers = {"Authorization": f"Bearer {self.api_key}"}
        payload = {"model": self.model, "messages": [{"role": m.role, "content": m.content} for m in messages]}
        
        response = requests.post(f"{self.base_url}/chat/completions", headers=headers, json=payload)
        result = response.json()
        
        return CreateResult(
            content=result["choices"][0]["message"]["content"],
            finish_reason=result["choices"][0].get("finish_reason", "stop"),
            usage=result.get("usage", {})
        )

client = CustomModelClient(
    api_key="your-hpc-ai-api-key",
    base_url="https://api.hpc-ai.com/inference/v1",
    model="minimax/minimax-m2.5"
)

1.2 Troubleshooting​

Common IssueSolution
Version compatibilityAutoGen 0.2+ uses autogen_ext.models.openai
model_info errorsSet vision, function_calling, json_output per model capabilities
async/await errorsNew version uses async interface

1.3 References​