Update app.py

app.py

@@ -825,56 +825,56 @@ def project_extraction(project_description):
 
 # steps = store_and_execute_task(task_description, reasoning_path)
 
-# def message_back(task_message, execution_status, doc_url, from_whatsapp):
-#     # Convert task steps to a simple numbered list
-#     task_steps_list = "\n".join(
-#         [f"{i + 1}. {step['action']} - {step.get('output', '')}" for i, step in enumerate(execution_status.to_dict(orient="records"))]
-#     )
-
-#     # Format the body message
-#     body_message = (
-#         f"*Task Message:*\n{task_message}\n\n"
-#         f"*Execution Status:*\n{task_steps_list}\n\n"
-#         f"*Doc URL:*\n{doc_url}\n\n"
-#     )
-
-#     # Send response back to WhatsApp
-#     try:
-#         twillo_client.messages.create(
-#             from_=twilio_phone_number,
-#             to=from_whatsapp,
-#             body=body_message
-#         )
-#     except Exception as e:
-#         logger.error(f"Twilio Error: {e}")
-#         raise HTTPException(status_code=500, detail=f"Error sending WhatsApp message: {str(e)}")
+def message_back(task_message, execution_status, doc_url, from_whatsapp):
+    # Convert task steps to a simple numbered list
+    task_steps_list = "\n".join(
+        [f"{i + 1}. {step['action']} - {step.get('output', '')}" for i, step in enumerate(execution_status.to_dict(orient="records"))]
+    )
 
-#     return {"status": "success"}
+    # Format the body message
+    body_message = (
+        f"*Task Message:*\n{task_message}\n\n"
+        f"*Execution Status:*\n{task_steps_list}\n\n"
+        f"*Doc URL:*\n{doc_url}\n\n"
+    )
 
-# # Initialize the Whisper pipeline
-# whisper_pipeline = pipeline("automatic-speech-recognition", model="openai/whisper-medium")
+    # Send response back to WhatsApp
+    try:
+        twillo_client.messages.create(
+            from_=twilio_phone_number,
+            to=from_whatsapp,
+            body=body_message
+        )
+    except Exception as e:
+        logger.error(f"Twilio Error: {e}")
+        raise HTTPException(status_code=500, detail=f"Error sending WhatsApp message: {str(e)}")
 
-# # Function to transcribe audio from a media URL
-# def transcribe_audio_from_media_url(media_url):
-#     try:
-#         media_response = requests.get(media_url, auth=HTTPBasicAuth(account_sid, auth_token))
-#         # Download the media file
-#         media_response.raise_for_status()
-#         audio_data = media_response.content
+    return {"status": "success"}
 
-#         # Save the audio data to a file for processing
-#         audio_file_path = "temp_audio_file.mp3"
-#         with open(audio_file_path, "wb") as audio_file:
-#             audio_file.write(audio_data)
+# Initialize the Whisper pipeline
+whisper_pipeline = pipeline("automatic-speech-recognition", model="openai/whisper-medium")
 
-#         # Transcribe the audio using Whisper
-#         transcription = whisper_pipeline(audio_file_path, return_timestamps=True)
-#         logger.debug(f"Transcription: {transcription['text']}")
-#         return transcription["text"]
+# Function to transcribe audio from a media URL
+def transcribe_audio_from_media_url(media_url):
+    try:
+        media_response = requests.get(media_url, auth=HTTPBasicAuth(account_sid, auth_token))
+        # Download the media file
+        media_response.raise_for_status()
+        audio_data = media_response.content
 
-#     except Exception as e:
-#         logger.error(f"An error occurred: {e}")
-#         return None
+        # Save the audio data to a file for processing
+        audio_file_path = "temp_audio_file.mp3"
+        with open(audio_file_path, "wb") as audio_file:
+            audio_file.write(audio_data)
+
+        # Transcribe the audio using Whisper
+        transcription = whisper_pipeline(audio_file_path, return_timestamps=True)
+        logger.debug(f"Transcription: {transcription['text']}")
+        return transcription["text"]
+
+    except Exception as e:
+        logger.error(f"An error occurred: {e}")
+        return None
 
 
 # In[18]:
@@ -882,277 +882,264 @@ def project_extraction(project_description):
 
 app = FastAPI()
 
-# @app.get("/state")
-# async def fetch_state():
-#     return shared_state
+@app.get("/state")
+async def fetch_state():
+    return shared_state
 
-# @app.route("/whatsapp-webhook/", methods=["POST"])
-# async def whatsapp_webhook(request: Request):
-#     form_data = await request.form()
-#     # Log the form data to debug
-#     print("Received data:", form_data)
+@app.route("/whatsapp-webhook/", methods=["POST"])
+async def whatsapp_webhook(request: Request):
+    form_data = await request.form()
+    # Log the form data to debug
+    print("Received data:", form_data)
     
-#     # Extract message and user information
-#     incoming_msg = form_data.get("Body", "").strip()
-#     from_number = form_data.get("From", "")
-#     media_url = form_data.get("MediaUrl0", "")
-#     media_type = form_data.get("MediaContentType0", "")
-
-#     # Initialize response variables
-#     transcription = None
-
-#     if media_type.startswith("audio"):
-#         # If the media is an audio or video file, process it
-#         try:
-#             transcription = transcribe_audio_from_media_url(media_url)
-#         except Exception as e:
-#             return JSONResponse(
-#                 {"error": f"Failed to process voice input: {str(e)}"}, status_code=500
-#             )
-#     # Determine message content: use transcription if available, otherwise use text message
-#     processed_input = transcription if transcription else incoming_msg
+    # Extract message and user information
+    incoming_msg = form_data.get("Body", "").strip()
+    from_number = form_data.get("From", "")
+    media_url = form_data.get("MediaUrl0", "")
+    media_type = form_data.get("MediaContentType0", "")
 
-#     logger.debug(f"Processed input: {processed_input}")
-#     try:
-#         # Generate response
-#         project_desc_table, _ = fetch_updated_state()
-#         if not project_desc_table.empty:
-#             task_analysis_txt, execution_status, execution_results = fn_process_task(project_desc_table, processed_input)
-#             update_gradio_state(task_analysis_txt, execution_status, execution_results)
+    # Initialize response variables
+    transcription = None
+
+    if media_type.startswith("audio"):
+        # If the media is an audio or video file, process it
+        try:
+            transcription = transcribe_audio_from_media_url(media_url)
+        except Exception as e:
+            return JSONResponse(
+                {"error": f"Failed to process voice input: {str(e)}"}, status_code=500
+            )
+    # Determine message content: use transcription if available, otherwise use text message
+    processed_input = transcription if transcription else incoming_msg
+
+    logger.debug(f"Processed input: {processed_input}")
+    try:
+        # Generate response
+        project_desc_table, _ = fetch_updated_state()
+        if not project_desc_table.empty:
+            task_analysis_txt, execution_status, execution_results = fn_process_task(project_desc_table, processed_input)
+            update_gradio_state(task_analysis_txt, execution_status, execution_results)
             
-#             doc_url = 'Fail to generate doc'
-#             if 'doc_url' in execution_results:
-#                 doc_url = execution_results['doc_url']
+            doc_url = 'Fail to generate doc'
+            if 'doc_url' in execution_results:
+                doc_url = execution_results['doc_url']
 
-#             # Respond to the user on WhatsApp with the processed idea
-#             response = message_back(processed_input, execution_status, doc_url, from_number)
-#             logger.debug(response)
+            # Respond to the user on WhatsApp with the processed idea
+            response = message_back(processed_input, execution_status, doc_url, from_number)
+            logger.debug(response)
 
-#             return JSONResponse(content=str(response))
-#     except Exception as e:
-#         logger.error(f"Error during task processing: {e}")
-#         return {"error": str(e)}
+            return JSONResponse(content=str(response))
+    except Exception as e:
+        logger.error(f"Error during task processing: {e}")
+        return {"error": str(e)}
 
 
-# # In[19]:
+# In[19]:
 
 
-# # Mock Gmail Login Function
-# def mock_login(email):
-#     if email.endswith("@gmail.com"):
-#         return f"✅ Logged in as {email}", gr.update(visible=False), gr.update(visible=True)
-#     else:
-#         return "❌ Invalid Gmail address. Please try again.", gr.update(), gr.update()
+# Mock Gmail Login Function
+def mock_login(email):
+    if email.endswith("@gmail.com"):
+        return f"✅ Logged in as {email}", gr.update(visible=False), gr.update(visible=True)
+    else:
+        return "❌ Invalid Gmail address. Please try again.", gr.update(), gr.update()
 
-# # User Onboarding Function
-# def onboarding_survey(role, industry, project_description):
-#     return (project_extraction(project_description),
-#             gr.update(visible=False), gr.update(visible=True))
+# User Onboarding Function
+def onboarding_survey(role, industry, project_description):
+    return (project_extraction(project_description),
+            gr.update(visible=False), gr.update(visible=True))
 
-# # Mock Integration Functions
-# def integrate_todoist():
-#     return "✅ Successfully connected to Todoist!"
+# Mock Integration Functions
+def integrate_todoist():
+    return "✅ Successfully connected to Todoist!"
 
-# def integrate_evernote():
-#     return "✅ Successfully connected to Evernote!"
+def integrate_evernote():
+    return "✅ Successfully connected to Evernote!"
 
-# def integrate_calendar():
-#     return "✅ Successfully connected to Google Calendar!"
+def integrate_calendar():
+    return "✅ Successfully connected to Google Calendar!"
 
-# def load_svg_with_size(file_path, width="600px", height="400px"):
-#     # Read the SVG content from the file
-#     with open(file_path, "r", encoding="utf-8") as file:
-#         svg_content = file.read()
+def load_svg_with_size(file_path, width="600px", height="400px"):
+    # Read the SVG content from the file
+    with open(file_path, "r", encoding="utf-8") as file:
+        svg_content = file.read()
     
-#     # Add inline styles to control width and height
-#     styled_svg = f"""
-#     <div style="width: {width}; height: {height}; overflow: auto;">
-#         {svg_content}
-#     </div>
-#     """
-#     return styled_svg
-
-
-# # In[20]:
-
-
-# # Gradio Demo
-# def create_gradio_interface(state=None):
-#     with gr.Blocks(
-#         css="""
-#         .gradio-table td {
-#             white-space: normal !important;
-#             word-wrap: break-word !important;
-#         }
-#         .gradio-table {
-#             width: 100% !important;  /* Adjust to 100% to fit the container */
-#             table-layout: fixed !important;  /* Fixed column widths */
-#             overflow-x: hidden !important;  /* Disable horizontal scrolling */
-#         }
-#         .gradio-container {
-#             overflow-x: hidden !important;  /* Disable horizontal scroll for entire container */
-#             padding: 0 !important;  /* Remove any default padding */
-#         }
-#         .gradio-column {
-#             max-width: 100% !important;  /* Ensure columns take up full width */
-#             overflow: hidden !important;  /* Hide overflow to prevent horizontal scroll */
-#         }
-#         .gradio-row {
-#             overflow-x: hidden !important;  /* Prevent horizontal scroll on rows */
-#         }
-#     """) as demo:
-
-#     # Page 1: Mock Gmail Login
-#         with gr.Group(visible=True) as login_page:
-#             gr.Markdown("### **1️⃣ Login with Gmail**")
-#             email_input = gr.Textbox(label="Enter your Gmail Address", placeholder="[email protected]")
-#             login_button = gr.Button("Login")
-#             login_result = gr.Textbox(label="Login Status", interactive=False, visible=False)
-#         # Page 2: User Onboarding
-#         with gr.Group(visible=False) as onboarding_page:
-#             gr.Markdown("### **2️⃣ Tell Us About Yourself**")
-#             role = gr.Textbox(label="What is your role?", placeholder="e.g. Developer, Designer")
-#             industry = gr.Textbox(label="Which industry are you in?", placeholder="e.g. Software, Finance")
-#             project_description = gr.Textbox(label="Describe your project", placeholder="e.g. A task management app")
-#             submit_survey = gr.Button("Submit")
-
-#         # Page 3: Mock Integrations with Separate Buttons
-#         with gr.Group(visible=False) as integrations_page:
-#             gr.Markdown("### **3️⃣ Connect Integrations**")
-#             gr.Markdown("Click on the buttons below to connect each tool:")
-
-#             # Separate Buttons and Results for Each Integration
-#             todoist_button = gr.Button("Connect to Todoist")
-#             todoist_result = gr.Textbox(label="Todoist Status", interactive=False, visible=False)
+    # Add inline styles to control width and height
+    styled_svg = f"""
+    <div style="width: {width}; height: {height}; overflow: auto;">
+        {svg_content}
+    </div>
+    """
+    return styled_svg
+
+
+# In[20]:
+
+
+# Gradio Demo
+def create_gradio_interface(state=None):
+    with gr.Blocks(
+        css="""
+        .gradio-table td {
+            white-space: normal !important;
+            word-wrap: break-word !important;
+        }
+        .gradio-table {
+            width: 100% !important;  /* Adjust to 100% to fit the container */
+            table-layout: fixed !important;  /* Fixed column widths */
+            overflow-x: hidden !important;  /* Disable horizontal scrolling */
+        }
+        .gradio-container {
+            overflow-x: hidden !important;  /* Disable horizontal scroll for entire container */
+            padding: 0 !important;  /* Remove any default padding */
+        }
+        .gradio-column {
+            max-width: 100% !important;  /* Ensure columns take up full width */
+            overflow: hidden !important;  /* Hide overflow to prevent horizontal scroll */
+        }
+        .gradio-row {
+            overflow-x: hidden !important;  /* Prevent horizontal scroll on rows */
+        }
+    """) as demo:
+
+    # Page 1: Mock Gmail Login
+        with gr.Group(visible=True) as login_page:
+            gr.Markdown("### **1️⃣ Login with Gmail**")
+            email_input = gr.Textbox(label="Enter your Gmail Address", placeholder="[email protected]")
+            login_button = gr.Button("Login")
+            login_result = gr.Textbox(label="Login Status", interactive=False, visible=False)
+        # Page 2: User Onboarding
+        with gr.Group(visible=False) as onboarding_page:
+            gr.Markdown("### **2️⃣ Tell Us About Yourself**")
+            role = gr.Textbox(label="What is your role?", placeholder="e.g. Developer, Designer")
+            industry = gr.Textbox(label="Which industry are you in?", placeholder="e.g. Software, Finance")
+            project_description = gr.Textbox(label="Describe your project", placeholder="e.g. A task management app")
+            submit_survey = gr.Button("Submit")
+
+        # Page 3: Mock Integrations with Separate Buttons
+        with gr.Group(visible=False) as integrations_page:
+            gr.Markdown("### **3️⃣ Connect Integrations**")
+            gr.Markdown("Click on the buttons below to connect each tool:")
+
+            # Separate Buttons and Results for Each Integration
+            todoist_button = gr.Button("Connect to Todoist")
+            todoist_result = gr.Textbox(label="Todoist Status", interactive=False, visible=False)
             
-#             evernote_button = gr.Button("Connect to Evernote")
-#             evernote_result = gr.Textbox(label="Evernote Status", interactive=False, visible=False)
+            evernote_button = gr.Button("Connect to Evernote")
+            evernote_result = gr.Textbox(label="Evernote Status", interactive=False, visible=False)
             
-#             calendar_button = gr.Button("Connect to Google Calendar")
-#             calendar_result = gr.Textbox(label="Google Calendar Status", interactive=False, visible=False)
+            calendar_button = gr.Button("Connect to Google Calendar")
+            calendar_result = gr.Textbox(label="Google Calendar Status", interactive=False, visible=False)
 
-#             # Skip Button to proceed directly to next page
-#             skip_integrations = gr.Button("Skip ➡️")
-#             next_button = gr.Button("Proceed to QR Code")
+            # Skip Button to proceed directly to next page
+            skip_integrations = gr.Button("Skip ➡️")
+            next_button = gr.Button("Proceed to QR Code")
 
-#         with gr.Group(visible=False) as qr_code_page:
-#             # Page 4: QR Code and Curify Ideas
-#             gr.Markdown("## Curify: Unified AI Tools for Productivity")
+        with gr.Group(visible=False) as qr_code_page:
+            # Page 4: QR Code and Curify Ideas
+            gr.Markdown("## Curify: Unified AI Tools for Productivity")
             
-#             with gr.Tab("Curify Idea"):
-#                 with gr.Row():
-#                     with gr.Column():
-#                         gr.Markdown("#### ** QR Code**")
-#                         # Path to your local SVG file
-#                         svg_file_path = "qr.svg"
-#                         # Load the SVG content
-#                         svg_content = load_svg_with_size(svg_file_path, width="200px", height="200px")
-#                         gr.HTML(svg_content)
-
-#                     # Column 1: Webpage rendering
-#                     with gr.Column():
+            with gr.Tab("Curify Idea"):
+                with gr.Row():
+                    with gr.Column():
+                        gr.Markdown("#### ** QR Code**")
+                        # Path to your local SVG file
+                        svg_file_path = "qr.svg"
+                        # Load the SVG content
+                        svg_content = load_svg_with_size(svg_file_path, width="200px", height="200px")
+                        gr.HTML(svg_content)
+
+                    # Column 1: Webpage rendering
+                    with gr.Column():
                         
-#                         gr.Markdown("## Projects Overview")
-#                         project_desc_table = gr.DataFrame(
-#                             type="pandas"
-#                         )
-
-#                         gr.Markdown("## Enter task message.")
-#                         idea_input = gr.Textbox(
-#                             label=None,
-#                             placeholder="Describe the task you want to execute (e.g., Research Paper Review)")
+                        gr.Markdown("## Projects Overview")
+                        project_desc_table = gr.DataFrame(
+                            type="pandas"
+                        )
+
+                        gr.Markdown("## Enter task message.")
+                        idea_input = gr.Textbox(
+                            label=None,
+                            placeholder="Describe the task you want to execute (e.g., Research Paper Review)")
             
-#                         task_btn = gr.Button("Generate Task Steps")
-#                         fetch_state_btn = gr.Button("Fetch Updated State")
-
-#                     with gr.Column():
-#                         gr.Markdown("## Task analysis")
-#                         task_analysis_txt = gr.Textbox(
-#                             label=None,
-#                             placeholder="Here is the execution status of your task...")
-
-#                         gr.Markdown("## Execution status")
-#                         execution_status = gr.DataFrame(
-#                             type="pandas"
-#                         )
-#                         gr.Markdown("## Execution output")
-#                         execution_results = gr.JSON(
-#                             label=None
-#                         )
-#                         state_output = gr.State()  # Add a state output to hold the state
-
-#                 task_btn.click(
-#                     fn_process_task, 
-#                     inputs=[project_desc_table, idea_input], 
-#                     outputs=[task_analysis_txt, execution_status, execution_results]
-#                 )
-
-#                 fetch_state_btn.click(
-#                     fetch_updated_state, 
-#                     inputs=None, 
-#                     outputs=[project_desc_table, task_analysis_txt, execution_status, execution_results]
-#                 )
-
-#                 # Page 1 -> Page 2 Transition
-#                 login_button.click(
-#                     mock_login, 
-#                     inputs=email_input, 
-#                     outputs=[login_result, login_page, onboarding_page]
-#                 )
-
-#                 # Page 2 -> Page 3 Transition (Submit and Skip)
-#                 submit_survey.click(
-#                     onboarding_survey, 
-#                     inputs=[role, industry, project_description], 
-#                     outputs=[project_desc_table, onboarding_page, integrations_page]
-#                 )
-
-#                 # Integration Buttons
-#                 todoist_button.click(integrate_todoist, outputs=todoist_result)
-#                 evernote_button.click(integrate_evernote, outputs=evernote_result)
-#                 calendar_button.click(integrate_calendar, outputs=calendar_result)
-
-#                 # Skip Integrations and Proceed
-#                 skip_integrations.click(
-#                     lambda: (gr.update(visible=False), gr.update(visible=True)),
-#                     outputs=[integrations_page, qr_code_page]
-#                 )
-
-#         # # Set the load_fn to initialize the state when the page is loaded
-#         # demo.load(
-#         #     curify_ideas, 
-#         #     inputs=[project_input, idea_input], 
-#         #     outputs=[task_steps, task_analysis_txt, state_output]
-#         # )
-#     return demo
-#     # Load function to initialize the state
-#     # demo.load(load_fn, inputs=None, outputs=[state])  # Initialize the state when the page is loaded
-
-@app.on_event("startup")
-async def startup_event():
-    logger.debug("Application startup initiated")
-    # Simulate heavy operation
-    # from transformers import pipeline
-    # global model
-    # model = pipeline("automatic-speech-recognition", model="openai/whisper-medium")
-    logger.debug("Application startup complete")
+                        task_btn = gr.Button("Generate Task Steps")
+                        fetch_state_btn = gr.Button("Fetch Updated State")
+
+                    with gr.Column():
+                        gr.Markdown("## Task analysis")
+                        task_analysis_txt = gr.Textbox(
+                            label=None,
+                            placeholder="Here is the execution status of your task...")
+
+                        gr.Markdown("## Execution status")
+                        execution_status = gr.DataFrame(
+                            type="pandas"
+                        )
+                        gr.Markdown("## Execution output")
+                        execution_results = gr.JSON(
+                            label=None
+                        )
+                        state_output = gr.State()  # Add a state output to hold the state
+
+                task_btn.click(
+                    fn_process_task, 
+                    inputs=[project_desc_table, idea_input], 
+                    outputs=[task_analysis_txt, execution_status, execution_results]
+                )
+
+                fetch_state_btn.click(
+                    fetch_updated_state, 
+                    inputs=None, 
+                    outputs=[project_desc_table, task_analysis_txt, execution_status, execution_results]
+                )
+
+                # Page 1 -> Page 2 Transition
+                login_button.click(
+                    mock_login, 
+                    inputs=email_input, 
+                    outputs=[login_result, login_page, onboarding_page]
+                )
+
+                # Page 2 -> Page 3 Transition (Submit and Skip)
+                submit_survey.click(
+                    onboarding_survey, 
+                    inputs=[role, industry, project_description], 
+                    outputs=[project_desc_table, onboarding_page, integrations_page]
+                )
+
+                # Integration Buttons
+                todoist_button.click(integrate_todoist, outputs=todoist_result)
+                evernote_button.click(integrate_evernote, outputs=evernote_result)
+                calendar_button.click(integrate_calendar, outputs=calendar_result)
+
+                # Skip Integrations and Proceed
+                skip_integrations.click(
+                    lambda: (gr.update(visible=False), gr.update(visible=True)),
+                    outputs=[integrations_page, qr_code_page]
+                )
+
+        # # Set the load_fn to initialize the state when the page is loaded
+        # demo.load(
+        #     curify_ideas, 
+        #     inputs=[project_input, idea_input], 
+        #     outputs=[task_steps, task_analysis_txt, state_output]
+        # )
+    return demo
+    # Load function to initialize the state
+    # demo.load(load_fn, inputs=None, outputs=[state])  # Initialize the state when the page is loaded
 
 # In[21]:
-@app.get("/", response_class=JSONResponse)
-async def index():
-    return {"status": "FastAPI is running!"}
-
-# demo = create_gradio_interface()
-# # Use Gradio's `server_app` to get an ASGI app for Blocks
-# gradio_asgi_app = gr.routes.App.create_app(demo)
+demo = create_gradio_interface()
+# Use Gradio's `server_app` to get an ASGI app for Blocks
+gradio_asgi_app = gr.routes.App.create_app(demo)
 
-# # Mount the Gradio ASGI app at "/gradio"
-# app.mount("/gradio", gradio_asgi_app)
+# Mount the Gradio ASGI app at "/gradio"
+app.mount("/gradio", gradio_asgi_app)
 
-# # Redirect from the root endpoint to the Gradio app
-# @app.get("/", response_class=RedirectResponse)
-# async def index():
-#     return RedirectResponse(url="/gradio", status_code=307)
+# Redirect from the root endpoint to the Gradio app
+@app.get("/", response_class=RedirectResponse)
+async def index():
+    return RedirectResponse(url="/gradio", status_code=307)
 
 # Run the FastAPI server using uvicorn
 if __name__ == "__main__":