Merge pull request #178 from ks6088ts-labs/feature/issue-177_convert-code-from-string

add structured output example script

Author: ks6088ts

apps/1_call_azure_openai_chat/convert_code.py

@@ -0,0 +1,79 @@
+import argparse
+import logging
+from os import getenv
+
+from dotenv import load_dotenv
+from openai import AzureOpenAI
+from pydantic import BaseModel
+
+
+def init_args() -> argparse.Namespace:
+    parser = argparse.ArgumentParser(
+        prog="convert_code",
+        description="Convert code to a structured format",
+    )
+    parser.add_argument("-s", "--system", default="Extract the event information.")
+    parser.add_argument("-u", "--user", default="Alice and Bob are going to a science fair on Friday.")
+    parser.add_argument("-v", "--verbose", action="store_true")
+    return parser.parse_args()
+
+
+class ResponseFormat(BaseModel):
+    # FIXME: Update the ResponseFormat class to match your actual response format
+    name: str
+    date: str
+    participants: list[str]
+
+
+def print_structured_output(
+    system: str,
+    user: str,
+):
+    """
+    How to use:
+        Support for structured outputs was first added in API version 2024-08-01-preview.
+        It is available in the latest preview APIs as well as the latest GA API: 2024-10-21.
+
+    Install dependencies:
+        $ pip install openai python-dotenv pydantic
+
+    References:
+        - https://learn.microsoft.com/ja-jp/azure/ai-services/openai/how-to/structured-outputs?tabs=python
+    """
+
+    client = AzureOpenAI(
+        azure_endpoint=getenv("AZURE_OPENAI_ENDPOINT"),
+        api_key=getenv("AZURE_OPENAI_API_KEY"),
+        api_version=getenv("AZURE_OPENAI_API_VERSION"),
+    )
+
+    completion = client.beta.chat.completions.parse(
+        model=getenv("AZURE_OPENAI_GPT_MODEL"),
+        messages=[
+            {"role": "system", "content": system},
+            {"role": "user", "content": user},
+        ],
+        response_format=ResponseFormat,
+    )
+
+    print(completion.choices[0].message.parsed)
+    print(completion.model_dump_json(indent=2))
+
+
+if __name__ == "__main__":
+    args = init_args()
+
+    # Set verbose mode
+    if args.verbose:
+        logging.basicConfig(level=logging.DEBUG)
+
+    # Parse .env file and set environment variables
+    load_dotenv()
+
+    try:
+        print_structured_output(
+            system=args.system,
+            user=args.user,
+        )
+    except Exception as e:
+        logging.error(e)