modified

app.py

@@ -1,188 +1,3 @@
-# from groq import Groq
-# import gradio as gr
-# from gtts import gTTS
-# 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=os.getenv("GROQ_API_KEY_2"))
-
-# client = Groq(
-#     api_key="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",
-# )
-
-
-# # Function to encode the image
-# def encode_image(uploaded_image):
-#     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, chat_history):
-#     try:
-#         logger.info("Processing input...")
-
-#         if uploaded_image is not None:
-#             # Encode the image to base64
-#             base64_image = encode_image(uploaded_image)
-#             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}"}}]
-#                 }
-#             ]
-
-#             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
-#             logger.info("Processing text input...")
-#             messages = [
-#                 {"role": "system", "content": "You are Dr. HealthBuddy, a professional virtual doctor chatbot."},
-#                 {"role": "user", "content": user_input},
-#             ]
-#             response = client.chat.completions.create(
-#                 model="llama-3.2-11b-vision-preview",
-#                 messages=messages,
-#             )
-#             logger.info("Text processed successfully.")
-
-#         # Extract the reply
-#         LLM_reply = response.choices[0].message.content.strip()
-#         logger.debug(f"LLM reply: {LLM_reply}")
-
-#         # Append user input and bot reply as a tuple to the chat history
-#         chat_history.append((user_input, LLM_reply))
-
-#         return chat_history
-
-#     except Exception as e:
-#         logger.error(f"Error in customLLMBot function: {e}")
-#         return chat_history
-    
-#     # Log Viewer Function
-# def get_logs():
-#     try:
-#         with open('/tmp/chatbot_log.log', 'r') as f:
-#             return f.read()[-3000:]  # Return the last 3000 characters of the log
-#     except Exception as e:
-#         return f"Error reading logs: {e}"
-
-
-
-
-# def chatbot_ui():
-
-#     chat_history = []  # Initialize empty chat history
-
-#     with gr.Blocks() as demo:
-#         gr.Markdown("# Healthcare Chatbot Doctor")
-
-#         # Layout for chatbot and input box alignment
-#         with gr.Row():
-#             with gr.Column(scale=3):  # Main column for chatbot
-#                 chatbot = gr.Chatbot(label="Responses", elem_id="chatbot")
-#                 user_input = gr.Textbox(
-#                     label="Ask a health-related question",
-#                     placeholder="Describe your symptoms...",
-#                     elem_id="user-input",
-#                     lines=1,
-#                 )
-#             with gr.Column(scale=1):  # Side column for image and buttons
-#                 uploaded_image = gr.Image(label="Upload an Image", type="pil")
-#                 submit_btn = gr.Button("Submit")
-#                 clear_btn = gr.Button("Clear")
-#                 audio_output = gr.Audio(label="Audio Response")
-#          # Log Viewer
-#         with gr.Row():
-#             log_view = gr.Textbox(label="Logs", lines=10, interactive=False)
-#             view_logs_btn = gr.Button("View Logs")
-#             download_logs_btn = gr.Button("Download Logs")
-
-#         # Define actions
-#         def handle_submit(user_query, image):
-#             response = customLLMBot(user_query, image, chat_history)
-#             return response, None, ""  # Return chat history and reset input
-
-#         # Submit on pressing Enter key
-#         user_input.submit(
-#             handle_submit,
-#             inputs=[user_input, uploaded_image],
-#             outputs=[chatbot, audio_output, user_input],
-#         )
-
-#         # Submit on button click
-#         submit_btn.click(
-#             handle_submit,
-#             inputs=[user_input, uploaded_image],
-#             outputs=[chatbot, audio_output, user_input],
-#         )
-
-#         # Clear button action
-#         clear_btn.click(
-#             lambda: ([], None, ""),
-#             inputs=[],
-#             outputs=[chatbot, uploaded_image, user_input],
-#         )
-
-#         # View Logs Button
-#         view_logs_btn.click(
-#             get_logs,
-#             inputs=[],
-#             outputs=[log_view],
-#         )
-
-#         # Download Logs Button
-#         def download_logs():
-#             return '/tmp/chatbot_log.log'
-
-#         download_logs_btn.click(
-#             download_logs,
-#             inputs=[],
-#             outputs=[gr.File()],
-#         )
-
-#     return demo
-
-
-# # Launch the interface
-# #chatbot_ui().launch(share=True,server_name="0.0.0.0", server_port=7860)
-
-# chatbot_ui().launch(share=True,server_name="localhost", server_port=7860)
-
-
-
 from groq import Groq
 import gradio as gr
 from gtts import gTTS
@@ -286,14 +101,14 @@ def customLLMBot(user_input, uploaded_image, chat_history):
         return [(("user", user_input or "Image uploaded"), ("bot", f"An error occurred: {e}"))], None
 
 
-
 # Gradio Interface
 def chatbot_ui():
-    chat_history = []  # Initialize empty chat history
-
     with gr.Blocks() as demo:
         gr.Markdown("# Healthcare Chatbot Doctor")
 
+        # State for user chat history
+        chat_history = gr.State([])
+
         # Layout for chatbot and input box alignment
         with gr.Row():
             with gr.Column(scale=3):  # Main column for chatbot
@@ -311,30 +126,30 @@ def chatbot_ui():
                 audio_output = gr.Audio(label="Audio Response")
 
         # Define actions
-        def handle_submit(user_query, image):
+        def handle_submit(user_query, image, history):
             logger.info("User submitted a query.")
-            response, audio = customLLMBot(user_query, image, chat_history)
-            return response, audio, ""
+            response, audio = customLLMBot(user_query, image, history)
+            return response, audio, "", history
 
         # Submit on pressing Enter key
         user_input.submit(
             handle_submit,
-            inputs=[user_input, uploaded_image],
-            outputs=[chatbot, audio_output, user_input],
+            inputs=[user_input, uploaded_image, chat_history],
+            outputs=[chatbot, audio_output, user_input, chat_history],
         )
 
         # Submit on button click
         submit_btn.click(
             handle_submit,
-            inputs=[user_input, uploaded_image],
-            outputs=[chatbot, audio_output, user_input],
+            inputs=[user_input, uploaded_image, chat_history],
+            outputs=[chatbot, audio_output, user_input, chat_history],
         )
 
         # Action for clearing all fields
         clear_btn.click(
-            lambda: ([], "", None, None),
+            lambda: ([], "", None, []),
             inputs=[],
-            outputs=[chatbot, user_input, uploaded_image, audio_output],
+            outputs=[chatbot, user_input, uploaded_image, chat_history],
         )
 
     return demo
@@ -342,5 +157,3 @@ def chatbot_ui():
 
 # Launch the interface
 chatbot_ui().launch(server_name="0.0.0.0", server_port=7860)
-
-#chatbot_ui().launch(server_name="localhost", server_port=7860)