Update app.py

app.py

@@ -11,8 +11,8 @@ from google.genai import types
 # --- Configuration and Client Initialization ---
 load_dotenv()
 
-# Initializing the client exactly as in your code
-try:
+try
+    # Initializing the client exactly as in your code
     client = genai.Client(api_key=os.environ["GEMINI_API_KEY"])
 except KeyError:
     raise gr.Error("FATAL: GEMINI_API_KEY not found. Please set it in your Hugging Face Space secrets.")
@@ -24,50 +24,52 @@ def analyze_device_condition(video_file_path):
         return "Please upload video", "", ""
 
     try:
-        print(f"Log: Starting analysis for video: {video_file_path}")
-
-        # 1. Prepare video file for the client API
+        # 1. Prepare video file
         mime_type, _ = mimetypes.guess_type(video_file_path)
         if not mime_type or not mime_type.startswith("video"):
-            raise ValueError("Unsupported file type. Please upload a valid video.")
+            raise ValueError("Unsupported file type.")
         
         with open(video_file_path, "rb") as video:
             video_part = types.Part(
                 inline_data=types.Blob(mime_type=mime_type, data=video.read())
             )
         
-        # 2. Prepare the prompt and model settings from your code
+        # 2. Prepare the prompt
         prompt = """
-        Analyze the provided video of a device. Respond ONLY with a valid JSON object.
-        The JSON object must have the following three keys and nothing else:
+        Analyze the provided video. Respond ONLY with a valid JSON object with three keys:
         1. "device_type": A short string identifying the device.
-        2. "condition": A single word describing its condition. Choose from: "Mint", "Excellent", "Good", "Fair", "Poor".
-        3. "reason": A brief string explaining the condition rating.
+        2. "condition": A single word: "Mint", "Excellent", "Good", "Fair", or "Poor".
+        3. "reason": A brief string explaining the condition.
         """
+        prompt_part = types.Part.from_text(prompt)
+
+        # 3. --- THIS IS THE KEY CORRECTION ---
+        #    Wrapping the parts inside types.Content, exactly like your reference code.
+        contents = [
+            types.Content(parts=[prompt_part, video_part])
+        ]
+        # --- END OF CORRECTION ---
         
-        # USING YOUR EXACT REQUESTED MODEL NAME
+        # 4. Use gemini-2.5-flash and the specified config
         model_name = "gemini-2.5-flash"
-        
         generate_content_config = types.GenerateContentConfig(
             temperature=0.2,
             response_mime_type="application/json"
         )
         
-        # The contents list must contain both the text prompt and the video part
-        contents = [prompt, video_part]
-
-        # 3. Call the Gemini API using the client.generate_content method
+        # 5. Call the API using the streaming method from your code
         print(f"Log: Sending request to model: {model_name}...")
-        response = client.generate_content(
+        stream = client.models.generate_content_stream(
             model=f"models/{model_name}",
             contents=contents,
             generation_config=generate_content_config,
         )
 
-        print("Log: Analysis received.")
+        # 6. Handle the streamed response to build the complete JSON string
+        response_text = "".join(chunk.text for chunk in stream)
 
-        # 4. Parse the JSON response
-        parsed_json = json.loads(response.text)
+        # 7. Parse the final JSON response
+        parsed_json = json.loads(response_text)
         device_type = parsed_json.get("device_type", "N/A")
         condition = parsed_json.get("condition", "N/A")
         reason = parsed_json.get("reason", "N/A")
@@ -75,8 +77,8 @@ def analyze_device_condition(video_file_path):
         return device_type, condition, reason
 
     except Exception as e:
-        print(f"!!!!!!!! AN ERROR OCCURRED !!!!!!!!\n{e}")
         error_message = f"An error occurred: {e}"
+        print(f"ERROR: {error_message}")
         return error_message, "", ""
 
 # --- Gradio Interface ---