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:
Shiwen Cheng
2025-07-13 09:27:57 +08:00
committed by GitHub
parent 86a89acac3
commit 0c46f8361b
2 changed files with 21 additions and 16 deletions

View File

@@ -105,16 +105,18 @@ BASIC_MODEL:
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).
### How to use Azure models?
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`:
### How to use Azure OpenAI chat models?
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`:
```yaml
BASIC_MODEL:
model: "azure/gpt-4o-2024-08-06"
api_base: $AZURE_API_BASE
api_version: $AZURE_API_VERSION
api_key: $AZURE_API_KEY
azure_endpoint: $AZURE_OPENAI_ENDPOINT
api_version: $OPENAI_API_VERSION
api_key: $AZURE_OPENAI_API_KEY
```
## About Search Engine
### How to control search domains for Tavily?
@@ -136,4 +138,5 @@ SEARCH_ENGINE:
# Exclude results from these domains (blacklist)
exclude_domains:
- unreliable-site.com
- spam-domain.net
- spam-domain.net

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@@ -6,7 +6,8 @@ from typing import Any, Dict
import os
import httpx
from langchain_openai import ChatOpenAI
from langchain_core.language_models import BaseChatModel
from langchain_openai import ChatOpenAI, AzureChatOpenAI
from langchain_deepseek import ChatDeepSeek
from typing import get_args
@@ -14,7 +15,7 @@ from src.config import load_yaml_config
from src.config.agents import LLMType
# Cache for LLM instances
_llm_cache: dict[LLMType, ChatOpenAI] = {}
_llm_cache: dict[LLMType, BaseChatModel] = {}
def _get_config_file_path() -> str:
@@ -48,7 +49,7 @@ def _get_env_llm_conf(llm_type: str) -> Dict[str, Any]:
def _create_llm_use_conf(
llm_type: LLMType, conf: Dict[str, Any]
) -> ChatOpenAI | ChatDeepSeek:
) -> BaseChatModel :
"""Create LLM instance using configuration."""
llm_type_config_keys = _get_llm_type_config_keys()
config_key = llm_type_config_keys.get(llm_type)
@@ -86,16 +87,17 @@ def _create_llm_use_conf(
merged_conf["http_client"] = http_client
merged_conf["http_async_client"] = http_async_client
return (
ChatOpenAI(**merged_conf)
if llm_type != "reasoning"
else ChatDeepSeek(**merged_conf)
)
if "azure_endpoint" in merged_conf or os.getenv("AZURE_OPENAI_ENDPOINT"):
return AzureChatOpenAI(**merged_conf)
if llm_type == "reasoning":
return ChatDeepSeek(**merged_conf)
else
return ChatOpenAI(**merged_conf)
def get_llm_by_type(
llm_type: LLMType,
) -> ChatOpenAI:
) -> BaseChatModel:
"""
Get LLM instance by type. Returns cached instance if available.
"""