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https://github.com/farcasclaudiu/TradingAgents.git
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feat: add DeepSeek, Qwen, GLM, and Azure OpenAI provider support
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import os
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from typing import Any, Optional
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from langchain_openai import AzureChatOpenAI
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from .base_client import BaseLLMClient, normalize_content
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from .validators import validate_model
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_PASSTHROUGH_KWARGS = (
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"timeout", "max_retries", "api_key", "reasoning_effort",
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"callbacks", "http_client", "http_async_client",
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)
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class NormalizedAzureChatOpenAI(AzureChatOpenAI):
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"""AzureChatOpenAI with normalized content output."""
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def invoke(self, input, config=None, **kwargs):
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return normalize_content(super().invoke(input, config, **kwargs))
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class AzureOpenAIClient(BaseLLMClient):
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"""Client for Azure OpenAI deployments.
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Requires environment variables:
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AZURE_OPENAI_API_KEY: API key
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AZURE_OPENAI_ENDPOINT: Endpoint URL (e.g. https://<resource>.openai.azure.com/)
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AZURE_OPENAI_DEPLOYMENT_NAME: Deployment name
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OPENAI_API_VERSION: API version (e.g. 2025-03-01-preview)
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"""
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def __init__(self, model: str, base_url: Optional[str] = None, **kwargs):
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super().__init__(model, base_url, **kwargs)
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def get_llm(self) -> Any:
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"""Return configured AzureChatOpenAI instance."""
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self.warn_if_unknown_model()
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llm_kwargs = {
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"model": self.model,
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"azure_deployment": os.environ.get("AZURE_OPENAI_DEPLOYMENT_NAME", self.model),
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}
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for key in _PASSTHROUGH_KWARGS:
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if key in self.kwargs:
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llm_kwargs[key] = self.kwargs[key]
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return NormalizedAzureChatOpenAI(**llm_kwargs)
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def validate_model(self) -> bool:
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"""Azure accepts any deployed model name."""
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return True
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