modified

app.py

@@ -5,11 +5,20 @@ import uuid
 import base64
 from io import BytesIO
 import os
+import logging
+
+# Set up logger
+logger = logging.getLogger(__name__)
+logger.setLevel(logging.DEBUG)
+console_handler = logging.StreamHandler()
+file_handler = logging.FileHandler('chatbot_log.log')
+formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
+console_handler.setFormatter(formatter)
+file_handler.setFormatter(formatter)
+logger.addHandler(console_handler)
+logger.addHandler(file_handler)
 
 # Initialize Groq Client
-# client = Groq(
-#     api_key="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",
-# )
 
 client = Groq(api_key=os.getenv("GROQ_API_KEY_2"))
 
@@ -19,35 +28,48 @@ client = Groq(api_key=os.getenv("GROQ_API_KEY_2"))
 
 # Function to encode the image
 def encode_image(uploaded_image):
-    buffered = BytesIO()
-    uploaded_image.save(buffered, format="PNG")  # Ensure the correct format
-    return base64.b64encode(buffered.getvalue()).decode("utf-8")
+    try:
+        logger.debug("Encoding image...")
+        buffered = BytesIO()
+        uploaded_image.save(buffered, format="PNG")  # Ensure the correct format
+        logger.debug("Image encoding complete.")
+        return base64.b64encode(buffered.getvalue()).decode("utf-8")
+    except Exception as e:
+        logger.error(f"Error encoding image: {e}")
+        raise
 
 # Function to handle text and image inputs
 def customLLMBot(user_input, uploaded_image):
     try:
+        logger.info("Processing input...")
+
         if uploaded_image is not None:
             # Encode the image to base64
             base64_image = encode_image(uploaded_image)
 
-            # Create a message specifically for image prompts (no system messages allowed)
+            # Log the image size and type
+            logger.debug(f"Image received, size: {len(base64_image)} bytes")
+
+            # Create a message specifically for image prompts
             messages = [
                 {
                     "role": "user",
                     "content": [
                         {"type": "text", "text": "What's in this image?"},
-                        {"type": "image_url", "image_url": {"url": f"data:image/png;base64,{base64_image}"}},
-                    ],
+                        {"type": "image_url", "image_url": {"url": f"data:image/png;base64,{base64_image}"}}]
                 }
             ]
 
+            logger.info("Sending image to Groq API for processing...")
             # Send the image message to the Groq API
             response = client.chat.completions.create(
                 model="llama-3.2-11b-vision-preview",
                 messages=messages,
             )
+            logger.info("Image processed successfully.")
         else:
-            # Process text input (system messages allowed here)
+            # Process text input
+            logger.info("Processing text input...")
             messages = [
                 {"role": "system", "content": "You are Dr. HealthBuddy, a professional virtual doctor chatbot."},
                 {"role": "user", "content": user_input},
@@ -56,21 +78,24 @@ def customLLMBot(user_input, uploaded_image):
                 model="llama-3.2-11b-vision-preview",
                 messages=messages,
             )
+            logger.info("Text processed successfully.")
 
         # Extract the reply
         LLM_reply = response.choices[0].message.content
+        logger.debug(f"LLM reply: {LLM_reply}")
 
         # Generate audio for response
         audio_file = f"response_{uuid.uuid4().hex}.mp3"
         tts = gTTS(LLM_reply, lang='en')
         tts.save(audio_file)
+        logger.info(f"Audio response saved as {audio_file}")
 
         return [(user_input or "Image uploaded", LLM_reply)], audio_file
 
     except Exception as e:
         # Handle errors gracefully
-        error_message = f"An error occurred: {e}"
-        return [(user_input or "Image uploaded", error_message)], None
+        logger.error(f"Error in customLLMBot function: {e}")
+        return [(user_input or "Image uploaded", f"An error occurred: {e}")], None
 
 
 # Gradio Interface
@@ -96,6 +121,7 @@ def chatbot_ui():
 
         # Define actions
         def handle_submit(user_query, image):
+            logger.info("User submitted a query.")
             response, audio = customLLMBot(user_query, image)
             return response, audio, ""
 

requirements.txt

@@ -1,3 +1,4 @@
 gtts
 gradio
 groq
+loguru