# PrepGenie/app.py """Main Gradio application file.""" import gradio as gr import os import json import google.generativeai as genai from dotenv import load_dotenv import datetime # --- Import Logic Modules --- import interview_logic import interview_history # import auth_logic # If you move auth logic # import chat_logic # If chat logic is moved # --- Environment and Configuration --- load_dotenv() # --- Firebase Admin SDK Setup (in app.py or auth_logic) --- import firebase_admin from firebase_admin import credentials, auth, firestore # Added firestore def initialize_firebase(): """Attempts to initialize Firebase Admin SDK.""" if firebase_admin._apps: print("Firebase app already initialized in app.py.") return firebase_admin.get_app() cred = None try: firebase_credentials_path = os.getenv("FIREBASE_CREDENTIALS_PATH", "prepgenie-64134-firebase-adminsdk-fbsvc-3370ac4ab9.json") if firebase_credentials_path and os.path.exists(firebase_credentials_path): print(f"Initializing Firebase with credentials file in app.py: {firebase_credentials_path}") cred = credentials.Certificate(firebase_credentials_path) firebase_app = firebase_admin.initialize_app(cred) print("Firebase Admin initialized successfully using credentials file in app.py.") return firebase_app elif not firebase_credentials_path: print("FIREBASE_CREDENTIALS_PATH is not set or is None in app.py.") else: print(f"Firebase credentials file not found at {firebase_credentials_path} in app.py.") except Exception as e: print(f"Failed to initialize Firebase using credentials file in app.py: {e}") try: firebase_credentials_json = os.getenv("FIREBASE_CREDENTIALS_JSON") if firebase_credentials_json: print("Initializing Firebase with credentials from FIREBASE_CREDENTIALS_JSON environment variable in app.py.") cred_dict = json.loads(firebase_credentials_json) cred = credentials.Certificate(cred_dict) firebase_app = firebase_admin.initialize_app(cred) print("Firebase Admin initialized successfully using FIREBASE_CREDENTIALS_JSON in app.py.") return firebase_app else: print("FIREBASE_CREDENTIALS_JSON environment variable not set in app.py.") except (json.JSONDecodeError, ValueError) as e: print(f"Error parsing FIREBASE_CREDENTIALS_JSON in app.py: {e}") except Exception as e: print(f"Failed to initialize Firebase using FIREBASE_CREDENTIALS_JSON in app.py: {e}") print("Warning: Firebase Admin SDK could not be initialized in app.py. Authentication features will not work.") return None FIREBASE_APP = initialize_firebase() FIREBASE_AVAILABLE = FIREBASE_APP is not None # --- Generative AI Setup --- genai.configure(api_key=os.getenv("GOOGLE_API_KEY") or "YOUR_DEFAULT_API_KEY_HERE") TEXT_MODEL = genai.GenerativeModel("gemini-1.5-flash") # Global model instance print("Using Generative AI model: gemini-1.5-flash in app.py") # --- Import Chat Module Functions --- try: from login_module import chat as chat_module # Assuming this is external CHAT_MODULE_AVAILABLE = True print("Chat module imported successfully in app.py.") except ImportError as e: print(f"Warning: Could not import chat module in app.py: {e}") CHAT_MODULE_AVAILABLE = False chat_module = None # --- Helper Functions for UI Updates --- def apply_ui_updates(updates_dict): """Converts logic function UI update instructions to Gradio updates.""" gr_updates = {} for component_name, instruction in updates_dict.items(): if instruction == "gr_hide": gr_updates[component_name] = gr.update(visible=False) elif instruction == "gr_show": gr_updates[component_name] = gr.update(visible=True) elif instruction == "gr_show_and_update": # This needs specific handling in the calling function # Placeholder, logic should set value in calling function gr_updates[component_name] = gr.update(visible=True) elif instruction == "gr_show_and_update_error": gr_updates[component_name] = gr.update(visible=True) elif instruction == "gr_clear": gr_updates[component_name] = "" # For textboxes elif instruction == "gr_clear_dict": gr_updates[component_name] = {} # For JSON # Add more instructions as needed else: # Default or pass through gr_updates[component_name] = gr.update() return gr_updates # --- Navigation Functions --- def navigate_to_interview(): return (gr.update(visible=True), gr.update(visible=False), gr.update(visible=False)) def navigate_to_chat(): return (gr.update(visible=False), gr.update(visible=True), gr.update(visible=False)) def navigate_to_history(): return (gr.update(visible=False), gr.update(visible=False), gr.update(visible=True)) # --- Event Handler Functions (Orchestrators) --- def process_resume_handler(file_obj): """Handles resume processing event.""" result = interview_logic.process_resume_logic(file_obj) ui_updates = apply_ui_updates(result["ui_updates"]) # Unpack ui_updates in the correct order for outputs return ( result["status"], ui_updates.get("role_selection", gr.update()), ui_updates.get("start_interview_btn", gr.update()), ui_updates.get("question_display", gr.update()), ui_updates.get("answer_instructions", gr.update()), ui_updates.get("audio_input", gr.update()), ui_updates.get("submit_answer_btn", gr.update()), ui_updates.get("next_question_btn", gr.update()), ui_updates.get("submit_interview_btn", gr.update()), ui_updates.get("answer_display", gr.update()), ui_updates.get("feedback_display", gr.update()), ui_updates.get("metrics_display", gr.update()), result["processed_data"] # Pass processed data ) def start_interview_handler(roles, processed_resume_data): """Handles interview start event.""" # First, format the resume data using the AI model formatted_resume_data = interview_logic.getallinfo(processed_resume_data, TEXT_MODEL) result = interview_logic.start_interview_logic(roles, formatted_resume_data, TEXT_MODEL) ui_updates = apply_ui_updates(result["ui_updates"]) return ( result["status"], result["initial_question"], ui_updates.get("audio_input", gr.update()), ui_updates.get("submit_answer_btn", gr.update()), ui_updates.get("next_question_btn", gr.update()), ui_updates.get("submit_interview_btn", gr.update()), ui_updates.get("feedback_display", gr.update()), ui_updates.get("metrics_display", gr.update()), ui_updates.get("question_display", gr.update()), ui_updates.get("answer_instructions", gr.update()), result["interview_state"] ) def submit_answer_handler(audio, interview_state): """Handles answer submission event.""" result = interview_logic.submit_answer_logic(audio, interview_state, TEXT_MODEL) ui_updates = apply_ui_updates(result["ui_updates"]) # Handle special updates for feedback and metrics that need value setting feedback_update = ui_updates.get("feedback_display", gr.update()) if "gr_show_and_update" in result["ui_updates"].values(): feedback_update = gr.update(visible=True, value=result["feedback_text"]) metrics_update = ui_updates.get("metrics_display", gr.update()) if "gr_show_and_update" in result["ui_updates"].values(): metrics_update = gr.update(visible=True, value=result["metrics"]) return ( result["status"], result["answer_text"], result["interview_state"], feedback_update, metrics_update, ui_updates.get("audio_input", gr.update()), ui_updates.get("submit_answer_btn", gr.update()), ui_updates.get("next_question_btn", gr.update()), ui_updates.get("submit_interview_btn", gr.update()), ui_updates.get("question_display", gr.update()), ui_updates.get("answer_instructions", gr.update()) ) def next_question_handler(interview_state): """Handles next question event.""" result = interview_logic.next_question_logic(interview_state) ui_updates = apply_ui_updates(result["ui_updates"]) return ( result["status"], result["next_q"], result["interview_state"], ui_updates.get("audio_input", gr.update()), ui_updates.get("submit_answer_btn", gr.update()), ui_updates.get("next_question_btn", gr.update()), ui_updates.get("feedback_display", gr.update()), ui_updates.get("metrics_display", gr.update()), ui_updates.get("submit_interview_btn", gr.update()), ui_updates.get("question_display", gr.update()), ui_updates.get("answer_instructions", gr.update()), ui_updates.get("answer_display", ""), # Clear ui_updates.get("metrics_display_clear", {}) # Clear ) def submit_interview_handler(interview_state, user_id_state=""): """Handles interview submission event.""" result = interview_logic.submit_interview_logic(interview_state, TEXT_MODEL) ui_updates = apply_ui_updates(result["ui_updates"]) # --- NEW: Save Interview History --- if FIREBASE_AVAILABLE and user_id_state and "report_text" in result and "chart_buffer" in result: print(f"Attempting to save history for user: {user_id_state} in submit_interview_handler") # Package data for saving (using data from interview_state and result) interview_summary_data = { "timestamp": datetime.datetime.now().isoformat(), "resume_overview": interview_state.get("resume_data", ""), "selected_roles": interview_state.get("selected_roles", []), "questions": list(interview_state.get("interactions", {}).keys()), "answers": list(interview_state.get("interactions", {}).values()), "feedback": interview_state.get("feedback", []), "interactions": interview_state.get("interactions", {}), "metrics_list": interview_state.get("metrics_list", []), "final_metrics": interview_logic.parse_metrics(interview_logic.getmetrics(interview_state.get("interactions", {}), interview_state.get("resume_data", ""), TEXT_MODEL)), # Recalculate or pass from logic? # Use average from report text parsing or recalculate if needed, or pass from logic if stored "average_rating": sum(interview_logic.parse_metrics(interview_logic.getmetrics(interview_state.get("interactions", {}), interview_state.get("resume_data", ""), TEXT_MODEL)).values()) / len(interview_logic.parse_metrics(interview_logic.getmetrics(interview_state.get("interactions", {}), interview_state.get("resume_data", ""), TEXT_MODEL))) if interview_logic.parse_metrics(interview_logic.getmetrics(interview_state.get("interactions", {}), interview_state.get("resume_data", ""), TEXT_MODEL)) else 0.0, "evaluation_report": result["report_text"] } save_success = interview_history.save_interview_history(user_id_state, interview_summary_data) if save_success: print("Interview history saved successfully in submit_interview_handler.") # Optionally append to report text # result["report_text"] += "\n\n---\n*Interview history saved successfully.*" else: print("Failed to save interview history in submit_interview_handler.") # result["report_text"] += "\n\n---\n*Failed to save interview history.*" else: if not user_id_state: print("User not logged in. Skipping history save in submit_interview_handler.") else: print("Firestore not available. Skipping history save in submit_interview_handler.") # Handle special updates for report and chart that need value setting report_update = ui_updates.get("evaluation_report_display", gr.update()) if "gr_show_and_update" in result["ui_updates"].values(): report_update = gr.update(visible=True, value=result["report_text"]) elif "gr_show_and_update_error" in result["ui_updates"].values(): report_update = gr.update(visible=True, value=result["report_text"]) # Show error chart_update = ui_updates.get("evaluation_chart_display", gr.update()) if "gr_show_and_update" in result["ui_updates"].values(): chart_update = gr.update(visible=True, value=result["chart_buffer"]) elif "gr_show_and_update_error" in result["ui_updates"].values(): chart_update = gr.update(visible=False) # Hide chart on error return ( result["status"], result["interview_state"], # Pass through report_update, chart_update ) # --- Login/Logout Logic (Simplified here, could be in auth_logic) --- def login(email, password): if not FIREBASE_AVAILABLE: return ( "Firebase not initialized. Login unavailable.", gr.update(visible=True), gr.update(visible=False), gr.update(visible=False), "", "", "", "" ) if not email or not password: return ( "Please enter email and password.", gr.update(visible=True), gr.update(visible=False), gr.update(visible=False), email, password, "", "" ) try: user = auth.get_user_by_email(email) welcome_msg = f"Welcome, {user.display_name or user.uid}!" return ( welcome_msg, gr.update(visible=False), gr.update(visible=False), gr.update(visible=True), "", "", user.uid, user.email ) except auth.UserNotFoundError: return ( "User not found. Please check your email or sign up.", gr.update(visible=True), gr.update(visible=False), gr.update(visible=False), email, password, "", "" ) except Exception as e: error_msg = f"Login failed: {str(e)}" print(error_msg) return ( error_msg, gr.update(visible=True), gr.update(visible=False), gr.update(visible=False), email, password, "", "" ) def signup(email, password, username): if not FIREBASE_AVAILABLE: return ( "Firebase not initialized. Signup unavailable.", gr.update(visible=True), gr.update(visible=False), gr.update(visible=False), "", "", "", "", "" ) if not email or not password or not username: return ( "Please fill all fields.", gr.update(visible=False), gr.update(visible=True), gr.update(visible=False), email, password, username, "", "" ) try: user = auth.create_user(email=email, password=password, uid=username, display_name=username) success_msg = f"Account created successfully for {username}!" return ( success_msg, gr.update(visible=True), gr.update(visible=False), gr.update(visible=False), "", "", "", user.uid, user.email ) except auth.UidAlreadyExistsError: return ( "Username already exists. Please choose another.", gr.update(visible=False), gr.update(visible=True), gr.update(visible=False), email, password, username, "", "" ) except auth.EmailAlreadyExistsError: return ( "Email already exists. Please use another email.", gr.update(visible=False), gr.update(visible=True), gr.update(visible=False), email, password, username, "", "" ) except Exception as e: error_msg = f"Signup failed: {str(e)}" print(error_msg) return ( error_msg, gr.update(visible=False), gr.update(visible=True), gr.update(visible=False), email, password, username, "", "" ) def logout(): return ( "", gr.update(visible=True), gr.update(visible=False), gr.update(visible=False), "", "", "", "", "" ) # --- Gradio Interface --- with gr.Blocks(title="PrepGenie - Mock Interviewer") as demo: interview_state = gr.State({}) user_state = gr.State("") # Holds user.uid user_email_state = gr.State("") # Holds user.email processed_resume_data_state = gr.State("") # --- Header Section --- with gr.Row(): gr.Markdown( """

PrepGenie- Interview Preparation App

""", elem_id="title" ) # --- Login Section --- with gr.Column(visible=True) as login_section: gr.Markdown("## Login") login_email_input = gr.Textbox(label="Email Address") login_password_input = gr.Textbox(label="Password", type="password") login_btn = gr.Button("Login") login_status = gr.Textbox(label="Login Status", interactive=False) switch_to_signup_btn = gr.Button("Don't have an account? Sign Up") # --- Signup Section --- with gr.Column(visible=False) as signup_section: gr.Markdown("## Sign Up") signup_email_input = gr.Textbox(label="Email Address") signup_password_input = gr.Textbox(label="Password", type="password") signup_username_input = gr.Textbox(label="Unique Username") signup_btn = gr.Button("Create my account") signup_status = gr.Textbox(label="Signup Status", interactive=False) switch_to_login_btn = gr.Button("Already have an account? Login") # --- Main App Sections --- with gr.Column(visible=False) as main_app: with gr.Row(): with gr.Column(scale=1): logout_btn = gr.Button("Logout") with gr.Column(scale=4): welcome_display = gr.Markdown("### Welcome, User!") with gr.Row(): with gr.Column(scale=1): interview_btn = gr.Button("Mock Interview") if CHAT_MODULE_AVAILABLE: chat_btn = gr.Button("Chat with Resume") else: chat_btn = gr.Button("Chat with Resume (Unavailable)", interactive=False) history_btn = gr.Button("My Interview History") with gr.Column(scale=4): # --- Interview Section --- with gr.Column(visible=False) as interview_selection: gr.Markdown("## Mock Interview") with gr.Row(): with gr.Column(): file_upload_interview = gr.File(label="Upload Resume (PDF)", file_types=[".pdf"]) process_btn_interview = gr.Button("Process Resume") with gr.Column(): file_status_interview = gr.Textbox(label="Status", interactive=False) role_selection = gr.Dropdown( choices=["Data Scientist", "Software Engineer", "Product Manager", "Data Analyst", "Business Analyst"], multiselect=True, label="Select Job Role(s)", visible=False ) start_interview_btn = gr.Button("Start Interview", visible=False) question_display = gr.Textbox(label="Question", interactive=False, visible=False) answer_instructions = gr.Markdown("Click 'Record Answer' and speak your response.", visible=False) audio_input = gr.Audio(label="Record Answer", type="numpy", visible=False) submit_answer_btn = gr.Button("Submit Answer", visible=False) next_question_btn = gr.Button("Next Question", visible=False) submit_interview_btn = gr.Button("Submit Interview", visible=False, variant="primary") answer_display = gr.Textbox(label="Your Answer", interactive=False, visible=False) feedback_display = gr.Textbox(label="Feedback", interactive=False, visible=False) metrics_display = gr.JSON(label="Metrics", visible=False) processed_resume_data_hidden_interview = gr.Textbox(visible=False) # --- Evaluation Results Section --- with gr.Column(visible=False) as evaluation_selection: gr.Markdown("## Interview Evaluation Results") evaluation_report_display = gr.Markdown(label="Your Evaluation Report", visible=False) evaluation_chart_display = gr.Image(label="Skills Breakdown", type="pil", visible=False) # --- Chat Section --- if CHAT_MODULE_AVAILABLE: with gr.Column(visible=False) as chat_selection: gr.Markdown("## Chat with Resume") with gr.Row(): with gr.Column(): file_upload_chat = gr.File(label="Upload Resume (PDF)", file_types=[".pdf"]) process_chat_btn = gr.Button("Process Resume") with gr.Column(): file_status_chat = gr.Textbox(label="Status", interactive=False) chatbot = gr.Chatbot(label="Chat History", visible=False, type="messages") query_input = gr.Textbox(label="Ask about your resume", placeholder="Type your question here...", visible=False) send_btn = gr.Button("Send", visible=False) else: with gr.Column(visible=False) as chat_selection: gr.Markdown("## Chat with Resume (Unavailable)") gr.Textbox(value="Chat module is not available.", interactive=False) # --- History Section --- with gr.Column(visible=False) as history_selection: gr.Markdown("## Your Interview History") load_history_btn = gr.Button("Load My Past Interviews") history_output = gr.Textbox(label="Past Interviews", max_lines=30, interactive=False, visible=True) # Assign view variables for navigation interview_view = interview_selection chat_view = chat_selection history_view = history_selection # Navigation button listeners interview_btn.click(fn=navigate_to_interview, inputs=None, outputs=[interview_view, chat_view, history_view]) if CHAT_MODULE_AVAILABLE: chat_btn.click(fn=navigate_to_chat, inputs=None, outputs=[interview_view, chat_view, history_view]) history_btn.click(fn=navigate_to_history, inputs=None, outputs=[interview_view, chat_view, history_view]) # --- Event Listeners for Interview --- process_btn_interview.click( fn=process_resume_handler, inputs=[file_upload_interview], outputs=[ file_status_interview, role_selection, start_interview_btn, question_display, answer_instructions, audio_input, submit_answer_btn, next_question_btn, submit_interview_btn, answer_display, feedback_display, metrics_display, processed_resume_data_hidden_interview ] ) start_interview_btn.click( fn=start_interview_handler, inputs=[role_selection, processed_resume_data_hidden_interview], outputs=[ file_status_interview, question_display, audio_input, submit_answer_btn, next_question_btn, submit_interview_btn, feedback_display, metrics_display, question_display, answer_instructions, interview_state ] ) submit_answer_btn.click( fn=submit_answer_handler, inputs=[audio_input, interview_state], outputs=[ file_status_interview, answer_display, interview_state, feedback_display, metrics_display, audio_input, submit_answer_btn, next_question_btn, submit_interview_btn, question_display, answer_instructions ] ) next_question_btn.click( fn=next_question_handler, inputs=[interview_state], outputs=[ file_status_interview, question_display, interview_state, audio_input, submit_answer_btn, next_question_btn, feedback_display, metrics_display, submit_interview_btn, question_display, answer_instructions, answer_display, metrics_display # Clear previous ] ) submit_interview_btn.click( fn=submit_interview_handler, inputs=[interview_state, user_state], # Pass user_state for history saving outputs=[ file_status_interview, interview_state, evaluation_report_display, evaluation_chart_display ] ) # --- Event Listeners for Chat --- if CHAT_MODULE_AVAILABLE: process_chat_btn.click( fn=chat_module.process_resume_chat, inputs=[file_upload_chat], outputs=[file_status_chat, processed_resume_data_state, query_input, send_btn, chatbot] ) send_btn.click( fn=chat_module.chat_with_resume, inputs=[query_input, processed_resume_data_state, chatbot], outputs=[query_input, chatbot] ) query_input.submit( fn=chat_module.chat_with_resume, inputs=[query_input, processed_resume_data_state, chatbot], outputs=[query_input, chatbot] ) # --- NEW: Event Listener for History --- load_history_btn.click(fn=interview_history.load_user_history, inputs=[user_state], outputs=[history_output]) # --- Login/Logout Event Listeners --- login_btn.click( fn=login, inputs=[login_email_input, login_password_input], outputs=[login_status, login_section, signup_section, main_app, login_email_input, login_password_input, user_state, user_email_state] ) signup_btn.click( fn=signup, inputs=[signup_email_input, signup_password_input, signup_username_input], outputs=[signup_status, login_section, signup_section, main_app, signup_email_input, signup_password_input, signup_username_input, user_state, user_email_state] ) logout_btn.click( fn=logout, inputs=None, outputs=[login_status, login_section, signup_section, main_app, login_email_input, login_password_input, signup_username_input, user_state, user_email_state] ) switch_to_signup_btn.click( fn=lambda: (gr.update(visible=False), gr.update(visible=True)), inputs=None, outputs=[login_section, signup_section] ) switch_to_login_btn.click( fn=lambda: (gr.update(visible=True), gr.update(visible=False)), inputs=None, outputs=[login_section, signup_section] ) if __name__ == "__main__": demo.launch(server_name="0.0.0.0")