#from flask import Flask, request, jsonify, session, send_from_directory from flask import Flask, request, jsonify, session, send_from_directory, render_template, url_for from flask_cors import CORS from qa_system import get_next_part, get_recommendation, get_answer from openai import OpenAI import logging logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s') client = OpenAI(api_key='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') # Import OpenAI library #app = Flask(__name__, static_folder='media') app = Flask(__name__, static_folder='static', template_folder='templates') CORS(app) app.secret_key = 'super_secret_key' # OpenAI API Key setup # Maximum phase (end of the process) MAX_PHASE = 12 logging.info(f"MAX PHASE setting: {MAX_PHASE}") # Serve the index.html file through render_template to process Jinja2 expressions @app.route('/') def index(): return render_template('index.html') # Render the HTML template # Serve static files (if you have CSS or JS) @app.route('/static/') def static_files(path): return send_from_directory('static', path) # Serve the index.html file #@app.route('/') #def index(): # return send_from_directory('/var/www/html/test1/', 'index.html') # Serve static files (if you have CSS or JS) #@app.route('/test1/') #def static_files(path): # return send_from_directory('/var/www/html/test1/', path) import re def parse_instructions(phase_text): # Split into segments alternating between text and markers segments = re.split(r'()', phase_text) #print("Segments after split:", segments) # Prepare structured segments and unique sound files list sanitized_segments = [] sound_files = set() for segment in segments: if "', segment) if sound_marker: filename = sound_marker.group(1) sanitized_segments.append({"type": "sound", "value": filename}) sound_files.add(filename) # Collect unique filenames else: # Add non-empty text segments only text_content = segment.strip() if text_content: # Only append if not empty sanitized_segments.append({"type": "text", "value": text_content}) # Convert sound_files set to list before returning sound_files_list = list(sound_files) return sanitized_segments, sound_files_list # Route to reset the phase counter @app.route('/reset-phase', methods=['POST']) def reset_phase(): session.clear() # Clear the entire session session['phase'] = 0 # Set phase to 0 when the process starts (before phase 1) return jsonify({"message": "Phase reset to 0"}), 200 @app.route('/next-phase', methods=['POST']) def next_phase(): data = request.get_json() choice = data.get('choice', "A") # Default to choice A (continue) current_phase = session.get('phase', 0) # Start at phase 0 before moving to phase 1 logging.info(f"current phase when entering function next_phase: {current_phase}") # Logic for starting the process if current_phase == 0: # Initial phase (start of the process) current_phase = 1 # Move to phase 1 for the first set of instructions # Ensure this line is correctly aligned with `if` and not nested incorrectly logging.info(f"MAX PHASE setting: {MAX_PHASE}") elif current_phase == MAX_PHASE: if choice == 'A': # Go to the end current_phase = 13 elif choice == 'B': # Go back to phase 11 pass else: if choice == 'A': # Continue to the next phase current_phase += 1 logging.info(f"current phase after increment: {current_phase}") elif choice == 'B': # Repeat the current phase pass # Keep the current phase unchanged # Save the updated phase in the session session['phase'] = current_phase # Get the content for the current phase phase_text, questions = get_next_part(current_phase) # Parse instructions and sound markers segmented_instructions, sound_files = parse_instructions(phase_text) #print(f"Instructions: {segmented_instructions}") logging.info(f"segmented instructions: {segmented_instructions}") #print(f"Sound files: {sound_files}") logging.info(f"sound files: {sound_files}") # Return the content along with the current phase and sound files as JSON return jsonify({ 'segmentedInstructions': segmented_instructions, 'questions': questions, 'phase': current_phase, # Ensure phase is returned here 'soundFiles': sound_files, # List of sound files for the current phase 'is_last_phase': current_phase == 13 # Added to indicate the end }) # Function to query ChatGPT for feedback-based recommendations def get_chatgpt_recommendation(feedback): try: # Correct usage of the ChatGPT API for conversation style completion response = client.chat.completions.create(model="gpt-4", # Make sure you are using the correct model name messages=[ # {"role": "system", "content": "You are a trauma assistant guiding a patient through mental exercises."}, # {"role": "user", "content": f"The user provided the following feedback: '{feedback}'. Based on this feedback, should the user proceed to the next phase or repeat > {"role": "system", "content": "You are a trauma assistant guiding a patient through mental exercises. Provide recommendations by directly addressing the user in the> {"role": "user", "content": f"I just completed an exercise and my feedback is: '{feedback}'. Based on this feedback, should I proceed to the next phase or repeat th> ]) # Extract and return the model's response return response.choices[0].message.content except Exception as e: #print(f"Error in OpenAI API: {e}") # Log the exact error message logging.info(f"openAI error: {e}") return "Error in generating a recommendation." # Route to handle feedback submission and return a ChatGPT-generated recommendation @app.route('/feedback', methods=['POST']) def feedback(): data = request.get_json() feedback_text = data.get('feedback', '') # Get recommendation from ChatGPT based on feedback recommendation = get_chatgpt_recommendation(feedback_text) # Send the recommendation back to the frontend return jsonify({"recommendation": recommendation}) if __name__ == '__main__': app.run(host='0.0.0.0', port=5000, debug=True)