Merge pull request #50 from ks6088ts-labs/feature/issue-47_support-reasoning-model

support reasoning model

Author: ks6088ts

.env.template

@@ -15,9 +15,10 @@ LANGSMITH_API_KEY="lsv2_xxx"
 ## Azure OpenAI Service
 AZURE_OPENAI_ENDPOINT="https://xxx.openai.azure.com/"
 AZURE_OPENAI_API_KEY="xxx"
-AZURE_OPENAI_API_VERSION="2024-10-21"
+AZURE_OPENAI_API_VERSION="2025-04-01-preview"
 AZURE_OPENAI_MODEL_CHAT="gpt-4o"
 AZURE_OPENAI_MODEL_EMBEDDING="text-embedding-3-small"
+AZURE_OPENAI_MODEL_REASONING="o4-mini"
 
 # ---------
 # Tools

scripts/azure_openai_operator.py

@@ -0,0 +1,88 @@
+import logging
+
+import typer
+from dotenv import load_dotenv
+
+from template_langgraph.llms.azure_openais import AzureOpenAiWrapper
+from template_langgraph.loggers import get_logger
+
+# Initialize the Typer application
+app = typer.Typer(
+    add_completion=False,
+    help="Azure OpenAI operator CLI",
+)
+
+# Set up logging
+logger = get_logger(__name__)
+
+
+@app.command()
+def chat(
+    query: str = typer.Option(
+        "What is the weather like today?",
+        "--query",
+        "-q",
+        help="Query to run with the Azure OpenAI chat model",
+    ),
+    verbose: bool = typer.Option(
+        False,
+        "--verbose",
+        "-v",
+        help="Enable verbose output",
+    ),
+):
+    # Set up logging
+    if verbose:
+        logger.setLevel(logging.DEBUG)
+
+    logger.info("Running...")
+    response = AzureOpenAiWrapper().chat_model.invoke(
+        input=query,
+    )
+    logger.debug(
+        response.model_dump_json(
+            indent=2,
+            exclude_none=True,
+        )
+    )
+    logger.info(f"Output: {response.content}")
+
+
+@app.command()
+def reasoning(
+    query: str = typer.Option(
+        "患者のデータから考えられる病名を診断してください。年齢： 55歳, 性別： 男性, 主訴： 激しい胸の痛み、息切れ, 検査データ： 心電図異常、トロポニン値上昇, 病歴： 高血圧、喫煙歴あり",  # noqa: E501
+        "--query",
+        "-q",
+        help="Query to run with the Azure OpenAI reasoning model",
+    ),
+    verbose: bool = typer.Option(
+        False,
+        "--verbose",
+        "-v",
+        help="Enable verbose output",
+    ),
+):
+    # Set up logging
+    if verbose:
+        logger.setLevel(logging.DEBUG)
+
+    logger.info("Running...")
+    response = AzureOpenAiWrapper().reasoning_model.invoke(
+        input=query,
+    )
+    logger.debug(
+        response.model_dump_json(
+            indent=2,
+            exclude_none=True,
+        )
+    )
+    logger.info(f"Output: {response.content}")
+
+
+if __name__ == "__main__":
+    load_dotenv(
+        override=True,
+        verbose=True,
+    )
+    app()

template_langgraph/llms/azure_openais.py

@@ -10,6 +10,7 @@ class Settings(BaseSettings):
     azure_openai_api_version: str = "2024-10-21"
     azure_openai_model_chat: str = "gpt-4o"
     azure_openai_model_embedding: str = "text-embedding-3-small"
+    azure_openai_model_reasoning: str = "o4-mini"
 
     model_config = SettingsConfigDict(
         env_file=".env",
@@ -42,6 +43,12 @@ def __init__(self, settings: Settings = None):
             api_version=settings.azure_openai_api_version,
             azure_deployment=settings.azure_openai_model_embedding,
         )
+        self.reasoning_model = AzureChatOpenAI(
+            azure_endpoint=settings.azure_openai_endpoint,
+            api_key=settings.azure_openai_api_key,
+            api_version=settings.azure_openai_api_version,
+            azure_deployment=settings.azure_openai_model_reasoning,
+        )
 
     def create_embedding(self, text: str):
         """Create an embedding for the given text."""