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https://gitee.com/wanwujie/deer-flow
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feat: support AzureChatOpenAI under configuring azure_endpoint or AZURE_OPENAI_ENDPOINT (#237)
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
This commit is contained in:
@@ -105,16 +105,18 @@ BASIC_MODEL:
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Note: The available models and their exact names may change over time. Please verify the currently available models and their correct identifiers in [OpenRouter's official documentation](https://openrouter.ai/docs).
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### How to use Azure models?
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DeerFlow supports the integration of Azure models. You can refer to [litellm Azure](https://docs.litellm.ai/docs/providers/azure). Configuration example of `conf.yaml`:
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### How to use Azure OpenAI chat models?
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DeerFlow supports the integration of Azure OpenAI chat models. You can refer to [AzureChatOpenAI](https://python.langchain.com/api_reference/openai/chat_models/langchain_openai.chat_models.azure.AzureChatOpenAI.html). Configuration example of `conf.yaml`:
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```yaml
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BASIC_MODEL:
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model: "azure/gpt-4o-2024-08-06"
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api_base: $AZURE_API_BASE
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api_version: $AZURE_API_VERSION
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api_key: $AZURE_API_KEY
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azure_endpoint: $AZURE_OPENAI_ENDPOINT
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api_version: $OPENAI_API_VERSION
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api_key: $AZURE_OPENAI_API_KEY
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```
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## About Search Engine
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### How to control search domains for Tavily?
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@@ -136,4 +138,5 @@ SEARCH_ENGINE:
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# Exclude results from these domains (blacklist)
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exclude_domains:
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- unreliable-site.com
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- spam-domain.net
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- spam-domain.net
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@@ -6,7 +6,8 @@ from typing import Any, Dict
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import os
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import httpx
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from langchain_openai import ChatOpenAI
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from langchain_core.language_models import BaseChatModel
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from langchain_openai import ChatOpenAI, AzureChatOpenAI
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from langchain_deepseek import ChatDeepSeek
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from typing import get_args
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@@ -14,7 +15,7 @@ from src.config import load_yaml_config
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from src.config.agents import LLMType
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# Cache for LLM instances
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_llm_cache: dict[LLMType, ChatOpenAI] = {}
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_llm_cache: dict[LLMType, BaseChatModel] = {}
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def _get_config_file_path() -> str:
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@@ -48,7 +49,7 @@ def _get_env_llm_conf(llm_type: str) -> Dict[str, Any]:
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def _create_llm_use_conf(
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llm_type: LLMType, conf: Dict[str, Any]
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) -> ChatOpenAI | ChatDeepSeek:
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) -> BaseChatModel :
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"""Create LLM instance using configuration."""
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llm_type_config_keys = _get_llm_type_config_keys()
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config_key = llm_type_config_keys.get(llm_type)
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@@ -86,16 +87,17 @@ def _create_llm_use_conf(
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merged_conf["http_client"] = http_client
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merged_conf["http_async_client"] = http_async_client
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return (
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ChatOpenAI(**merged_conf)
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if llm_type != "reasoning"
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else ChatDeepSeek(**merged_conf)
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)
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if "azure_endpoint" in merged_conf or os.getenv("AZURE_OPENAI_ENDPOINT"):
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return AzureChatOpenAI(**merged_conf)
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if llm_type == "reasoning":
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return ChatDeepSeek(**merged_conf)
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else
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return ChatOpenAI(**merged_conf)
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def get_llm_by_type(
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llm_type: LLMType,
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) -> ChatOpenAI:
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) -> BaseChatModel:
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"""
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Get LLM instance by type. Returns cached instance if available.
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"""
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