add query image script

Author: ks6088ts

.gitignore

@@ -164,3 +164,5 @@ cython_debug/
 generated/
 *.mp3
 *.pt
+*.jpg
+*.jpeg

apps/1_call_azure_openai_chat/query_image.py

@@ -0,0 +1,68 @@
+import argparse
+import base64
+from os import getenv
+
+from dotenv import load_dotenv
+from openai import AzureOpenAI
+
+
+def init_args() -> argparse.Namespace:
+    parser = argparse.ArgumentParser(
+        prog="ProgramName",
+        description="What the program does",
+        epilog="Text at the bottom of help",
+    )
+    parser.add_argument("-f", "--file")
+    parser.add_argument("-s", "--system", default="You are a professional image analyst. Describe the image.")
+    parser.add_argument("-p", "--prompt", default="Please describe the content of the image")
+    return parser.parse_args()
+
+
+if __name__ == "__main__":
+    # Parse .env file and set environment variables
+    load_dotenv()
+
+    # Initialize AzureOpenAI client
+    client = AzureOpenAI(
+        api_key=getenv("AZURE_OPENAI_API_KEY"),
+        api_version=getenv("AZURE_OPENAI_API_VERSION"),
+        azure_endpoint=getenv("AZURE_OPENAI_ENDPOINT"),
+    )
+
+    args = init_args()
+
+    # Read image file and encode it to base64
+    try:
+        with open(args.file, "rb") as f:
+            encoded_image = base64.b64encode(f.read()).decode()
+    except Exception as e:
+        print(e)
+        exit(1)
+
+    # Call completion API and get a response to user input
+    response = client.chat.completions.create(
+        model=getenv("AZURE_OPENAI_GPT_MODEL"),
+        messages=[
+            {
+                "role": "system",
+                "content": args.system,
+            },
+            {
+                "role": "user",
+                "content": [
+                    {
+                        "type": "image_url",
+                        "image_url": {"url": f"data:image/jpeg;base64,{encoded_image}"},
+                    },
+                    {
+                        "type": "text",
+                        "content": args.prompt,
+                    },
+                ],
+            },
+        ],
+    )
+
+    # Print response to console
+    # print(response.model_dump_json(indent=2))
+    print(response.choices[0].message.content)