Fix: chat_history addition

agents/academic_agent.py

@@ -413,7 +413,9 @@ Your reasoning process must be:
 1. First, analyze the CONVERSATION HISTORY to understand the immediate context of the CURRENT QUESTION. This is especially important to understand what "this," "that," or "it" refers to.
 2. Once you understand the user's real question, check if the UPLOADED FILE context is relevant to the topic.
 3. Formulate your answer based on this reasoning, keeping an encouraging and professional tone.
+
 CONVERSATION HISTORY:
+{history_for_prompt}
 {context_section}
 CURRENT QUESTION:
 User: {query}

app.py

@@ -1,303 +1,62 @@
-# # Shiva
-# from flask import Flask, render_template, request, jsonify, session
-# import os
-# from dotenv import load_dotenv
-# import json
-# import random
-# from werkzeug.utils import secure_filename
-# import google.generativeai as genai
-# from pathlib import Path
-
-# # Load environment variables
-# load_dotenv()
-
-# app = Flask(__name__)
-# app.config['SECRET_KEY'] = os.getenv('FLASK_SECRET_KEY', 'dev-secret-key')
-# app.config['MAX_CONTENT_LENGTH'] = 16 * 1024 * 1024  # 16MB max file size
-
-# # Configure upload settings
-# UPLOAD_FOLDER = 'uploads'
-# ALLOWED_EXTENSIONS = {'txt', 'pdf', 'docx', 'doc', 'json', 'csv'}
-# app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER
-
-# # Create upload directory
-# os.makedirs(UPLOAD_FOLDER, exist_ok=True)
-
-# # Configure Gemini API
-# GEMINI_API_KEY = os.getenv('GEMINI_API_KEY')
-# if GEMINI_API_KEY:
-#     genai.configure(api_key=GEMINI_API_KEY)
-#     model = genai.GenerativeModel('gemini-1.5-pro')
-#     print("✅ Gemini API configured successfully!")
-# else:
-#     model = None
-#     print("⚠️ No Gemini API key found. Using fallback responses.")
-
-# # Import agents and utilities
-# from agents.router_agent import RouterAgent
-# from utils.helpers import load_quotes, get_greeting
-# from utils.file_processor import FileProcessor
-
-# def allowed_file(filename):
-#     return '.' in filename and filename.rsplit('.', 1)[1].lower() in ALLOWED_EXTENSIONS
-
-# class MyPharmaAI:
-#     def __init__(self):
-#         self.router = RouterAgent(model)  # Pass model to router
-#         self.quotes = load_quotes()
-#         self.file_processor = FileProcessor()
-        
-#     def process_query(self, query, user_name="Student", uploaded_files=None):
-#         """Process user query through the router agent with optional file context"""
-#         try:
-#             # Check if we have uploaded files to reference
-#             file_context = ""
-#             if uploaded_files and 'uploaded_files' in session:
-#                 file_context = self.get_file_context(session['uploaded_files'])
-            
-#             # Route the query to appropriate agent
-#             response = self.router.route_query(query, file_context)
-#             return {
-#                 'success': True,
-#                 'response': response,
-#                 'agent_used': response.get('agent_type', 'unknown')
-#             }
-#         except Exception as e:
-#             return {
-#                 'success': False,
-#                 'response': f"माफ करें (Sorry), I encountered an error: {str(e)}",
-#                 'agent_used': 'error'
-#             }
-    
-#     def get_file_context(self, uploaded_files):
-#         """Get context from uploaded files"""
-#         context = ""
-#         for file_info in uploaded_files[-3:]:  # Last 3 files only
-#             file_path = file_info['path']
-#             if os.path.exists(file_path):
-#                 try:
-#                     content = self.file_processor.extract_text(file_path)
-#                     if content:
-#                         context += f"\n\n📄 Content from {file_info['original_name']}:\n{content[:2000]}..."  # Limit context
-#                 except Exception as e:
-#                     context += f"\n\n❌ Error reading {file_info['original_name']}: {str(e)}"
-#         return context
-    
-#     def get_daily_quote(self):
-#         """Get inspirational quote from Gita/Vedas"""
-#         return random.choice(self.quotes) if self.quotes else "विद्या धनं सर्व धन प्रधानम्"
-    
-#     def process_file_upload(self, file):
-#         """Process uploaded file and extract information"""
-#         try:
-#             if file and allowed_file(file.filename):
-#                 filename = secure_filename(file.filename)
-#                 timestamp = str(int(time.time()))
-#                 filename = f"{timestamp}_{filename}"
-#                 file_path = os.path.join(app.config['UPLOAD_FOLDER'], filename)
-#                 file.save(file_path)
-                
-#                 # Extract text content
-#                 content = self.file_processor.extract_text(file_path)
-                
-#                 # Store in session
-#                 if 'uploaded_files' not in session:
-#                     session['uploaded_files'] = []
-                
-#                 file_info = {
-#                     'original_name': file.filename,
-#                     'saved_name': filename,
-#                     'path': file_path,
-#                     'size': os.path.getsize(file_path),
-#                     'preview': content[:500] if content else "No text content extracted"
-#                 }
-                
-#                 session['uploaded_files'].append(file_info)
-#                 session.modified = True
-                
-#                 return {
-#                     'success': True,
-#                     'message': f'File "{file.filename}" uploaded successfully! You can now ask questions about its content.',
-#                     'file_info': file_info
-#                 }
-#             else:
-#                 return {
-#                     'success': False,
-#                     'message': 'Invalid file type. Supported: TXT, PDF, DOCX, DOC, JSON, CSV'
-#                 }
-#         except Exception as e:
-#             return {
-#                 'success': False,
-#                 'message': f'Error uploading file: {str(e)}'
-#             }
-
-# # Initialize the AI system
-# import time
-# pharma_ai = MyPharmaAI()
-
-# @app.route('/')
-# def index():
-#     """Main chat interface"""
-#     greeting = get_greeting()
-#     daily_quote = pharma_ai.get_daily_quote()
-    
-#     # Get uploaded files info
-#     uploaded_files = session.get('uploaded_files', [])
-    
-#     return render_template('index.html', 
-#                          greeting=greeting, 
-#                          daily_quote=daily_quote,
-#                          uploaded_files=uploaded_files,
-#                          api_available=bool(GEMINI_API_KEY))
-
-# @app.route('/chat', methods=['POST'])
-# def chat():
-#     """Main chat endpoint"""
-#     try:
-#         data = request.get_json()
-        
-#         if not data or 'query' not in data:
-#             return jsonify({
-#                 'success': False,
-#                 'error': 'No query provided'
-#             }), 400
-        
-#         user_query = data.get('query', '').strip()
-#         user_name = data.get('user_name', 'Student')
-        
-#         if not user_query:
-#             return jsonify({
-#                 'success': False,
-#                 'error': 'Empty query'
-#             }), 400
-        
-#         # Process the query (with file context if available)
-#         result = pharma_ai.process_query(user_query, user_name, session.get('uploaded_files'))
-        
-#         return jsonify(result)
-        
-#     except Exception as e:
-#         return jsonify({
-#             'success': False,
-#             'error': f'Server error: {str(e)}'
-#         }), 500
-
-# @app.route('/upload', methods=['POST'])
-# def upload_file():
-#     """Handle file upload"""
-#     try:
-#         if 'file' not in request.files:
-#             return jsonify({
-#                 'success': False,
-#                 'error': 'No file provided'
-#             }), 400
-        
-#         file = request.files['file']
-        
-#         if file.filename == '':
-#             return jsonify({
-#                 'success': False,
-#                 'error': 'No file selected'
-#             }), 400
-        
-#         result = pharma_ai.process_file_upload(file)
-#         return jsonify(result)
-        
-#     except Exception as e:
-#         return jsonify({
-#             'success': False,
-#             'error': f'Upload error: {str(e)}'
-#         }), 500
-
-# @app.route('/files')
-# def get_uploaded_files():
-#     """Get list of uploaded files"""
-#     uploaded_files = session.get('uploaded_files', [])
-#     return jsonify({
-#         'files': uploaded_files,
-#         'count': len(uploaded_files)
-#     })
-
-# @app.route('/clear_files', methods=['POST'])
-# def clear_files():
-#     """Clear uploaded files"""
-#     try:
-#         # Remove files from disk
-#         if 'uploaded_files' in session:
-#             for file_info in session['uploaded_files']:
-#                 file_path = file_info['path']
-#                 if os.path.exists(file_path):
-#                     os.remove(file_path)
-        
-#         # Clear session
-#         session.pop('uploaded_files', None)
-        
-#         return jsonify({
-#             'success': True,
-#             'message': 'All files cleared successfully'
-#         })
-#     except Exception as e:
-#         return jsonify({
-#             'success': False,
-#             'error': f'Error clearing files: {str(e)}'
-#         }), 500
-
-# @app.route('/quote')
-# def get_quote():
-#     """Get a random inspirational quote"""
-#     quote = pharma_ai.get_daily_quote()
-#     return jsonify({'quote': quote})
-
-# @app.route('/health')
-# def health_check():
-#     """Health check endpoint"""
-#     return jsonify({
-#         'status': 'healthy',
-#         'app': 'MyPharma AI',
-#         'version': '2.0.0',
-#         'gemini_api': 'connected' if GEMINI_API_KEY else 'not configured',
-#         'features': ['chat', 'file_upload', 'multi_agent', 'indian_theme']
-#     })
-
-# if __name__ == '__main__':
-#     # Create necessary directories
-#     for directory in ['data', 'static/css', 'static/js', 'templates', 'agents', 'utils', 'uploads']:
-#         os.makedirs(directory, exist_ok=True)
-    
-#     print("🇮🇳 MyPharma AI Starting...")
-#     print(f"📁 Upload folder: {UPLOAD_FOLDER}")
-#     print(f"🤖 Gemini API: {'✅ Ready' if GEMINI_API_KEY else '❌ Not configured'}")
-#     print("🚀 Server starting on http://localhost:5000")
-    
-#     # Run the app
-#     app.run(debug=True, port=5000)
-# # #### app.py (Main Application)
-# # from flask import Flask, render_template, request, jsonify
+# # # Shiva
+# # from flask import Flask, render_template, request, jsonify, session
 # # import os
 # # from dotenv import load_dotenv
 # # import json
 # # import random
+# # from werkzeug.utils import secure_filename
+# # import google.generativeai as genai
+# # from pathlib import Path
 
 # # # Load environment variables
 # # load_dotenv()
 
 # # app = Flask(__name__)
 # # app.config['SECRET_KEY'] = os.getenv('FLASK_SECRET_KEY', 'dev-secret-key')
-
-# # # Import agents
+# # app.config['MAX_CONTENT_LENGTH'] = 16 * 1024 * 1024  # 16MB max file size
+
+# # # Configure upload settings
+# # UPLOAD_FOLDER = 'uploads'
+# # ALLOWED_EXTENSIONS = {'txt', 'pdf', 'docx', 'doc', 'json', 'csv'}
+# # app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER
+
+# # # Create upload directory
+# # os.makedirs(UPLOAD_FOLDER, exist_ok=True)
+
+# # # Configure Gemini API
+# # GEMINI_API_KEY = os.getenv('GEMINI_API_KEY')
+# # if GEMINI_API_KEY:
+# #     genai.configure(api_key=GEMINI_API_KEY)
+# #     model = genai.GenerativeModel('gemini-1.5-pro')
+# #     print("✅ Gemini API configured successfully!")
+# # else:
+# #     model = None
+# #     print("⚠️ No Gemini API key found. Using fallback responses.")
+
+# # # Import agents and utilities
 # # from agents.router_agent import RouterAgent
 # # from utils.helpers import load_quotes, get_greeting
+# # from utils.file_processor import FileProcessor
+
+# # def allowed_file(filename):
+# #     return '.' in filename and filename.rsplit('.', 1)[1].lower() in ALLOWED_EXTENSIONS
 
 # # class MyPharmaAI:
 # #     def __init__(self):
-# #         self.router = RouterAgent()
+# #         self.router = RouterAgent(model)  # Pass model to router
 # #         self.quotes = load_quotes()
+# #         self.file_processor = FileProcessor()
         
-# #     def process_query(self, query, user_name="Student"):
-# #         """Process user query through the router agent"""
+# #     def process_query(self, query, user_name="Student", uploaded_files=None):
+# #         """Process user query through the router agent with optional file context"""
 # #         try:
+# #             # Check if we have uploaded files to reference
+# #             file_context = ""
+# #             if uploaded_files and 'uploaded_files' in session:
+# #                 file_context = self.get_file_context(session['uploaded_files'])
+            
 # #             # Route the query to appropriate agent
-# #             response = self.router.route_query(query)
+# #             response = self.router.route_query(query, file_context)
 # #             return {
 # #                 'success': True,
 # #                 'response': response,
@@ -310,11 +69,70 @@
 # #                 'agent_used': 'error'
 # #             }
     
+# #     def get_file_context(self, uploaded_files):
+# #         """Get context from uploaded files"""
+# #         context = ""
+# #         for file_info in uploaded_files[-3:]:  # Last 3 files only
+# #             file_path = file_info['path']
+# #             if os.path.exists(file_path):
+# #                 try:
+# #                     content = self.file_processor.extract_text(file_path)
+# #                     if content:
+# #                         context += f"\n\n📄 Content from {file_info['original_name']}:\n{content[:2000]}..."  # Limit context
+# #                 except Exception as e:
+# #                     context += f"\n\n❌ Error reading {file_info['original_name']}: {str(e)}"
+# #         return context
+    
 # #     def get_daily_quote(self):
 # #         """Get inspirational quote from Gita/Vedas"""
 # #         return random.choice(self.quotes) if self.quotes else "विद्या धनं सर्व धन प्रधानम्"
+    
+# #     def process_file_upload(self, file):
+# #         """Process uploaded file and extract information"""
+# #         try:
+# #             if file and allowed_file(file.filename):
+# #                 filename = secure_filename(file.filename)
+# #                 timestamp = str(int(time.time()))
+# #                 filename = f"{timestamp}_{filename}"
+# #                 file_path = os.path.join(app.config['UPLOAD_FOLDER'], filename)
+# #                 file.save(file_path)
+                
+# #                 # Extract text content
+# #                 content = self.file_processor.extract_text(file_path)
+                
+# #                 # Store in session
+# #                 if 'uploaded_files' not in session:
+# #                     session['uploaded_files'] = []
+                
+# #                 file_info = {
+# #                     'original_name': file.filename,
+# #                     'saved_name': filename,
+# #                     'path': file_path,
+# #                     'size': os.path.getsize(file_path),
+# #                     'preview': content[:500] if content else "No text content extracted"
+# #                 }
+                
+# #                 session['uploaded_files'].append(file_info)
+# #                 session.modified = True
+                
+# #                 return {
+# #                     'success': True,
+# #                     'message': f'File "{file.filename}" uploaded successfully! You can now ask questions about its content.',
+# #                     'file_info': file_info
+# #                 }
+# #             else:
+# #                 return {
+# #                     'success': False,
+# #                     'message': 'Invalid file type. Supported: TXT, PDF, DOCX, DOC, JSON, CSV'
+# #                 }
+# #         except Exception as e:
+# #             return {
+# #                 'success': False,
+# #                 'message': f'Error uploading file: {str(e)}'
+# #             }
 
 # # # Initialize the AI system
+# # import time
 # # pharma_ai = MyPharmaAI()
 
 # # @app.route('/')
@@ -322,9 +140,15 @@
 # #     """Main chat interface"""
 # #     greeting = get_greeting()
 # #     daily_quote = pharma_ai.get_daily_quote()
+    
+# #     # Get uploaded files info
+# #     uploaded_files = session.get('uploaded_files', [])
+    
 # #     return render_template('index.html', 
 # #                          greeting=greeting, 
-# #                          daily_quote=daily_quote)
+# #                          daily_quote=daily_quote,
+# #                          uploaded_files=uploaded_files,
+# #                          api_available=bool(GEMINI_API_KEY))
 
 # # @app.route('/chat', methods=['POST'])
 # # def chat():
@@ -347,8 +171,8 @@
 # #                 'error': 'Empty query'
 # #             }), 400
         
-# #         # Process the query
-# #         result = pharma_ai.process_query(user_query, user_name)
+# #         # Process the query (with file context if available)
+# #         result = pharma_ai.process_query(user_query, user_name, session.get('uploaded_files'))
         
 # #         return jsonify(result)
         
@@ -358,6 +182,66 @@
 # #             'error': f'Server error: {str(e)}'
 # #         }), 500
 
+# # @app.route('/upload', methods=['POST'])
+# # def upload_file():
+# #     """Handle file upload"""
+# #     try:
+# #         if 'file' not in request.files:
+# #             return jsonify({
+# #                 'success': False,
+# #                 'error': 'No file provided'
+# #             }), 400
+        
+# #         file = request.files['file']
+        
+# #         if file.filename == '':
+# #             return jsonify({
+# #                 'success': False,
+# #                 'error': 'No file selected'
+# #             }), 400
+        
+# #         result = pharma_ai.process_file_upload(file)
+# #         return jsonify(result)
+        
+# #     except Exception as e:
+# #         return jsonify({
+# #             'success': False,
+# #             'error': f'Upload error: {str(e)}'
+# #         }), 500
+
+# # @app.route('/files')
+# # def get_uploaded_files():
+# #     """Get list of uploaded files"""
+# #     uploaded_files = session.get('uploaded_files', [])
+# #     return jsonify({
+# #         'files': uploaded_files,
+# #         'count': len(uploaded_files)
+# #     })
+
+# # @app.route('/clear_files', methods=['POST'])
+# # def clear_files():
+# #     """Clear uploaded files"""
+# #     try:
+# #         # Remove files from disk
+# #         if 'uploaded_files' in session:
+# #             for file_info in session['uploaded_files']:
+# #                 file_path = file_info['path']
+# #                 if os.path.exists(file_path):
+# #                     os.remove(file_path)
+        
+# #         # Clear session
+# #         session.pop('uploaded_files', None)
+        
+# #         return jsonify({
+# #             'success': True,
+# #             'message': 'All files cleared successfully'
+# #         })
+# #     except Exception as e:
+# #         return jsonify({
+# #             'success': False,
+# #             'error': f'Error clearing files: {str(e)}'
+# #         }), 500
+
 # # @app.route('/quote')
 # # def get_quote():
 # #     """Get a random inspirational quote"""
@@ -370,248 +254,464 @@
 # #     return jsonify({
 # #         'status': 'healthy',
 # #         'app': 'MyPharma AI',
-# #         'version': '1.0.0'
+# #         'version': '2.0.0',
+# #         'gemini_api': 'connected' if GEMINI_API_KEY else 'not configured',
+# #         'features': ['chat', 'file_upload', 'multi_agent', 'indian_theme']
 # #     })
 
 # # if __name__ == '__main__':
-# #     # Create data directories if they don't exist
-# #     os.makedirs('data', exist_ok=True)
-# #     os.makedirs('static/css', exist_ok=True)
-# #     os.makedirs('static/js', exist_ok=True)
-# #     os.makedirs('templates', exist_ok=True)
-# #     os.makedirs('agents', exist_ok=True)
-# #     os.makedirs('utils', exist_ok=True)
+# #     # Create necessary directories
+# #     for directory in ['data', 'static/css', 'static/js', 'templates', 'agents', 'utils', 'uploads']:
+# #         os.makedirs(directory, exist_ok=True)
+    
+# #     print("🇮🇳 MyPharma AI Starting...")
+# #     print(f"📁 Upload folder: {UPLOAD_FOLDER}")
+# #     print(f"🤖 Gemini API: {'✅ Ready' if GEMINI_API_KEY else '❌ Not configured'}")
+# #     print("🚀 Server starting on http://localhost:5000")
     
 # #     # Run the app
 # #     app.run(debug=True, port=5000)
+# # # #### app.py (Main Application)
+# # # from flask import Flask, render_template, request, jsonify
+# # # import os
+# # # from dotenv import load_dotenv
+# # # import json
+# # # import random
+
+# # # # Load environment variables
+# # # load_dotenv()
+
+# # # app = Flask(__name__)
+# # # app.config['SECRET_KEY'] = os.getenv('FLASK_SECRET_KEY', 'dev-secret-key')
+
+# # # # Import agents
+# # # from agents.router_agent import RouterAgent
+# # # from utils.helpers import load_quotes, get_greeting
+
+# # # class MyPharmaAI:
+# # #     def __init__(self):
+# # #         self.router = RouterAgent()
+# # #         self.quotes = load_quotes()
+        
+# # #     def process_query(self, query, user_name="Student"):
+# # #         """Process user query through the router agent"""
+# # #         try:
+# # #             # Route the query to appropriate agent
+# # #             response = self.router.route_query(query)
+# # #             return {
+# # #                 'success': True,
+# # #                 'response': response,
+# # #                 'agent_used': response.get('agent_type', 'unknown')
+# # #             }
+# # #         except Exception as e:
+# # #             return {
+# # #                 'success': False,
+# # #                 'response': f"माफ करें (Sorry), I encountered an error: {str(e)}",
+# # #                 'agent_used': 'error'
+# # #             }
+    
+# # #     def get_daily_quote(self):
+# # #         """Get inspirational quote from Gita/Vedas"""
+# # #         return random.choice(self.quotes) if self.quotes else "विद्या धनं सर्व धन प्रधानम्"
+
+# # # # Initialize the AI system
+# # # pharma_ai = MyPharmaAI()
+
+# # # @app.route('/')
+# # # def index():
+# # #     """Main chat interface"""
+# # #     greeting = get_greeting()
+# # #     daily_quote = pharma_ai.get_daily_quote()
+# # #     return render_template('index.html', 
+# # #                          greeting=greeting, 
+# # #                          daily_quote=daily_quote)
+
+# # # @app.route('/chat', methods=['POST'])
+# # # def chat():
+# # #     """Main chat endpoint"""
+# # #     try:
+# # #         data = request.get_json()
+        
+# # #         if not data or 'query' not in data:
+# # #             return jsonify({
+# # #                 'success': False,
+# # #                 'error': 'No query provided'
+# # #             }), 400
+        
+# # #         user_query = data.get('query', '').strip()
+# # #         user_name = data.get('user_name', 'Student')
+        
+# # #         if not user_query:
+# # #             return jsonify({
+# # #                 'success': False,
+# # #                 'error': 'Empty query'
+# # #             }), 400
+        
+# # #         # Process the query
+# # #         result = pharma_ai.process_query(user_query, user_name)
+        
+# # #         return jsonify(result)
+        
+# # #     except Exception as e:
+# # #         return jsonify({
+# # #             'success': False,
+# # #             'error': f'Server error: {str(e)}'
+# # #         }), 500
+
+# # # @app.route('/quote')
+# # # def get_quote():
+# # #     """Get a random inspirational quote"""
+# # #     quote = pharma_ai.get_daily_quote()
+# # #     return jsonify({'quote': quote})
+
+# # # @app.route('/health')
+# # # def health_check():
+# # #     """Health check endpoint"""
+# # #     return jsonify({
+# # #         'status': 'healthy',
+# # #         'app': 'MyPharma AI',
+# # #         'version': '1.0.0'
+# # #     })
+
+# # # if __name__ == '__main__':
+# # #     # Create data directories if they don't exist
+# # #     os.makedirs('data', exist_ok=True)
+# # #     os.makedirs('static/css', exist_ok=True)
+# # #     os.makedirs('static/js', exist_ok=True)
+# # #     os.makedirs('templates', exist_ok=True)
+# # #     os.makedirs('agents', exist_ok=True)
+# # #     os.makedirs('utils', exist_ok=True)
+    
+# # #     # Run the app
+# # #     app.run(debug=True, port=5000)
+
+# # app.py
+# # Main Flask application for MyPharma AI
+
+# from flask import Flask, render_template, request, jsonify, session
+# import os
+# import json
+# import random
+# import time
+# from dotenv import load_dotenv
+# from werkzeug.utils import secure_filename
+# import google.generativeai as genai
+
+# # Load environment variables from a .env file
+# load_dotenv()
+
+# # --- App Configuration ---
+# app = Flask(__name__)
+# app.config['SECRET_KEY'] = os.getenv('FLASK_SECRET_KEY', 'a-very-secret-key-for-dev')
+# app.config['MAX_CONTENT_LENGTH'] = 16 * 1024 * 1024  # 16MB max file size
+
+# # --- Upload Configuration ---
+# UPLOAD_FOLDER = '/tmp/uploads'
+# ALLOWED_EXTENSIONS = {'txt', 'pdf', 'docx', 'json', 'csv'}
+# app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER
+# os.makedirs(UPLOAD_FOLDER, exist_ok=True)
+
+# # --- Gemini API Configuration ---
+# GEMINI_API_KEY = os.getenv('GEMINI_API_KEY')
+# model = None
+# if GEMINI_API_KEY:
+#     try:
+#         genai.configure(api_key=GEMINI_API_KEY)
+#         # Using gemini-1.5-flash for speed and cost-effectiveness
+#         model = genai.GenerativeModel('gemini-1.5-flash')
+#         print("✅ Gemini 1.5 Flash Model configured successfully!")
+#     except Exception as e:
+#         print(f"❌ Error configuring Gemini API: {e}")
+# else:
+#     print("⚠️ No Gemini API key found. AI features will be disabled.")
+
+# # --- Import Agents and Utilities ---
+# # (Ensure these files exist in their respective directories)
+# from agents.router_agent import RouterAgent
+# from utils.helpers import load_quotes, get_greeting
+# from utils.file_processor import FileProcessor
+
+# def allowed_file(filename):
+#     """Check if the uploaded file has an allowed extension."""
+#     return '.' in filename and filename.rsplit('.', 1)[1].lower() in ALLOWED_EXTENSIONS
+
+# # --- Main AI Application Class ---
+# class MyPharmaAI:
+#     """Orchestrator for the entire AI system."""
+#     def __init__(self):
+#         self.router = RouterAgent(model)  # The router now gets the configured model
+#         self.quotes = load_quotes()
+#         self.file_processor = FileProcessor()
+
+#     def process_query(self, query, user_name="Student", viva_state=None, uploaded_files=None, chat_history=None):
+#             """Routes a user's query to the appropriate agent, handling context."""
+#             try:
+#                 # This block correctly gets the file content from the session data
+#                 file_context = ""
+#                 if uploaded_files:
+#                     file_context = self.get_file_context(uploaded_files)
+                
+#                 # This passes the file content and chat history to the router
+#                 response_data = self.router.route_query(query, file_context, viva_state, chat_history)
+                
+#                 return {
+#                     'success': True,
+#                     **response_data
+#                 }
+#             except Exception as e:
+#                 print(f"Error in MyPharmaAI.process_query: {e}")
+#                 return {
+#                     'success': False,
+#                     'message': f"Sorry, a critical error occurred: {str(e)}",
+#                     'agent_used': 'error'
+#                 }
+
+
+#     def get_file_context(self, uploaded_files_session):
+#         """Extracts text from the most recent files to use as context."""
+#         context = ""
+#         for file_info in uploaded_files_session[-3:]: # Limit to last 3 files
+#             file_path = file_info.get('path')
+#             if file_path and os.path.exists(file_path):
+#                 try:
+#                     content = self.file_processor.extract_text(file_path)
+#                     if content:
+#                         # Limit context from each file to 2000 characters
+#                         context += f"\n\n--- Content from {file_info['original_name']} ---\n{content[:2000]}..."
+#                 except Exception as e:
+#                     context += f"\n\n--- Error reading {file_info['original_name']}: {str(e)} ---"
+#         return context
+
+#     def get_daily_quote(self):
+#         """Returns a random quote."""
+#         return random.choice(self.quotes) if self.quotes else "विद्या धनं सर्व धन प्रधानम्"
+
+# # Initialize the AI system
+# pharma_ai = MyPharmaAI()
+
+# # --- Flask Routes ---
+
+# @app.route('/')
+# def index():
+#     """Renders the main chat interface."""
+#     greeting = get_greeting()
+#     daily_quote = pharma_ai.get_daily_quote()
+#     uploaded_files = session.get('uploaded_files', [])
+#     return render_template('index.html', 
+#                            greeting=greeting, 
+#                            daily_quote=daily_quote,
+#                            uploaded_files=uploaded_files)
+
+# @app.route('/chat', methods=['POST'])
+# def chat():
+#     """Handles the main chat logic, including session management for the Viva Agent."""
+#     try:
+#         data = request.get_json()
+#         query = data.get('query', '').strip()
+#         if not query:
+#             return jsonify({'success': False, 'error': 'Empty query'}), 400
+        
+#          # --- HISTORY MANAGEMENT START ---
+
+#         # Get the conversation history from the session (or start a new one)
+#         chat_history = session.get('chat_history', [])
+
+#         # Get current viva state from session for the Viva Agent
+#         viva_state = session.get('viva_state', None)
+#         uploaded_files = session.get('uploaded_files', None)
+
+#         # Process the query through the main orchestrator
+#         result = pharma_ai.process_query(query, viva_state=viva_state, uploaded_files=uploaded_files,chat_history=chat_history)
+#         # If the query was successful, update the history
+#         if result.get('success'):
+#             # Add the user's query and the AI's message to the history
+#             chat_history.append({'role': 'user', 'parts': [query]})
+#             chat_history.append({'role': 'model', 'parts': [result.get('message', '')]})
+
+#             # Keep the history from getting too long (e.g., last 10 exchanges)
+#             session['chat_history'] = chat_history[-20:]
+
+#         # --- HISTORY MANAGEMENT END ---
+
+#         # If the Viva agent returns an updated state, save it to the session
+#         if 'viva_state' in result:
+#             session['viva_state'] = result.get('viva_state')
+        
+#         return jsonify(result)
+        
+#     except Exception as e:
+#         print(f"Error in /chat endpoint: {e}")
+#         return jsonify({'success': False, 'error': f'Server error: {str(e)}'}), 500
+
+# @app.route('/upload', methods=['POST'])
+# def upload_file():
+#     """Handles file uploads."""
+#     if 'file' not in request.files:
+#         return jsonify({'success': False, 'error': 'No file part'}), 400
+#     file = request.files['file']
+#     if file.filename == '':
+#         return jsonify({'success': False, 'error': 'No selected file'}), 400
+#     if file and allowed_file(file.filename):
+#         filename = secure_filename(file.filename)
+#         file_path = os.path.join(app.config['UPLOAD_FOLDER'], filename)
+#         file.save(file_path)
+
+#         if 'uploaded_files' not in session:
+#             session['uploaded_files'] = []
+        
+#         file_info = {'original_name': filename, 'path': file_path}
+#         session['uploaded_files'].append(file_info)
+#         session.modified = True
+
+#         return jsonify({
+#             'success': True, 
+#             'message': f'File "{filename}" uploaded. You can now ask questions about it.',
+#             'files': session['uploaded_files']
+#         })
+#     return jsonify({'success': False, 'error': 'File type not allowed'}), 400
+
+# @app.route('/files', methods=['GET'])
+# def get_uploaded_files():
+#     """Returns the list of uploaded files from the session."""
+#     return jsonify({'files': session.get('uploaded_files', [])})
+
+# @app.route('/clear_files', methods=['POST'])
+# def clear_files():
+#     """Deletes uploaded files from disk and clears them from the session."""
+#     if 'uploaded_files' in session:
+#         for file_info in session['uploaded_files']:
+#             if os.path.exists(file_info['path']):
+#                 os.remove(file_info['path'])
+#     session.pop('uploaded_files', None)
+#     session.pop('viva_state', None) # Also clear viva state
+#     return jsonify({'success': True, 'message': 'All files and sessions cleared.'})
+
+# @app.route('/quote')
+# def get_quote():
+#     """Returns a new random quote."""
+#     return jsonify({'quote': pharma_ai.get_daily_quote()})
+
+# # --- Main Execution ---
+# # if __name__ == '__main__':
+# #     # Ensure all necessary directories exist
+# #     for directory in ['data', 'static/css', 'static/js', 'templates', 'agents', 'utils', 'uploads']:
+# #         os.makedirs(directory, exist_ok=True)
+    
+# #     print("🇮🇳 MyPharma AI Starting...")
+# #     print(f"🤖 Gemini API Status: {'✅ Ready' if model else '❌ Not configured'}")
+# #     print("🚀 Server starting on http://127.0.0.1:5000")
+# #     app.run(debug=True, port=5000)
+# if __name__ == '__main__':
+#     # Create necessary directories (this is good practice)
+#     for directory in ['data', 'uploads', 'templates']:
+#         os.makedirs(directory, exist_ok=True)
+    
+#     # Get port from environment variable, defaulting to 5000 for local testing
+#     port = int(os.environ.get('PORT', 7860))
+    
+#     print("🇮🇳 MyPharma AI Starting...")
+#     print(f"🤖 Gemini API Status: {'✅ Ready' if model else '❌ Not configured'}")
+#     print(f"🚀 Server starting on http://0.0.0.0:{port}")
+    
+#     # Run the app to be accessible on the server
+#     app.run(host='0.0.0.0', port=port)
+
+
+
 
 # app.py
-# Main Flask application for MyPharma AI
 
-from flask import Flask, render_template, request, jsonify, session
 import os
-import json
 import random
-import time
 from dotenv import load_dotenv
-from werkzeug.utils import secure_filename
+from flask import Flask, render_template, request, jsonify, session
 import google.generativeai as genai
 
-# Load environment variables from a .env file
+# Import new langchain components and our helper
+from langchain_google_genai import GoogleGenerativeAIEmbeddings
+from langchain_community.vectorstores import FAISS
+from utils.helpers import create_vector_store, get_greeting, load_quotes
+from agents.router_agent import RouterAgent
+
+# --- Initial Setup ---
 load_dotenv()
+# Create the knowledge library on first startup if it doesn't exist
+create_vector_store()
 
 # --- App Configuration ---
 app = Flask(__name__)
 app.config['SECRET_KEY'] = os.getenv('FLASK_SECRET_KEY', 'a-very-secret-key-for-dev')
-app.config['MAX_CONTENT_LENGTH'] = 16 * 1024 * 1024  # 16MB max file size
 
-# --- Upload Configuration ---
-UPLOAD_FOLDER = '/tmp/uploads'
-ALLOWED_EXTENSIONS = {'txt', 'pdf', 'docx', 'json', 'csv'}
-app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER
-os.makedirs(UPLOAD_FOLDER, exist_ok=True)
-
-# --- Gemini API Configuration ---
-GEMINI_API_KEY = os.getenv('GEMINI_API_KEY')
+# --- Gemini API & Knowledge Base Configuration ---
 model = None
-if GEMINI_API_KEY:
-    try:
+vector_store = None
+try:
+    GEMINI_API_KEY = os.getenv('GEMINI_API_KEY')
+    if GEMINI_API_KEY:
         genai.configure(api_key=GEMINI_API_KEY)
-        # Using gemini-1.5-flash for speed and cost-effectiveness
         model = genai.GenerativeModel('gemini-1.5-flash')
-        print("✅ Gemini 1.5 Flash Model configured successfully!")
-    except Exception as e:
-        print(f"❌ Error configuring Gemini API: {e}")
-else:
-    print("⚠️ No Gemini API key found. AI features will be disabled.")
-
-# --- Import Agents and Utilities ---
-# (Ensure these files exist in their respective directories)
-from agents.router_agent import RouterAgent
-from utils.helpers import load_quotes, get_greeting
-from utils.file_processor import FileProcessor
-
-def allowed_file(filename):
-    """Check if the uploaded file has an allowed extension."""
-    return '.' in filename and filename.rsplit('.', 1)[1].lower() in ALLOWED_EXTENSIONS
+        
+        # Load the persistent knowledge base from disk
+        if os.path.exists('faiss_index'):
+            embeddings = GoogleGenerativeAIEmbeddings(model="models/embedding-001")
+            vector_store = FAISS.load_local("faiss_index", embeddings, allow_dangerous_deserialization=True)
+            print("✅ Gemini Model and Knowledge Base loaded successfully!")
+        else:
+            print("✅ Gemini Model loaded. No knowledge base found.")
+    else:
+        print("⚠️ No Gemini API key found.")
+except Exception as e:
+    print(f"❌ Error during initialization: {e}")
 
 # --- Main AI Application Class ---
 class MyPharmaAI:
-    """Orchestrator for the entire AI system."""
-    def __init__(self):
-        self.router = RouterAgent(model)  # The router now gets the configured model
+    def __init__(self, gemini_model, vector_store_db):
+        self.router = RouterAgent(gemini_model)
         self.quotes = load_quotes()
-        self.file_processor = FileProcessor()
-
-    def process_query(self, query, user_name="Student", viva_state=None, uploaded_files=None, chat_history=None):
-            """Routes a user's query to the appropriate agent, handling context."""
-            try:
-                # This block correctly gets the file content from the session data
-                file_context = ""
-                if uploaded_files:
-                    file_context = self.get_file_context(uploaded_files)
-                
-                # This passes the file content and chat history to the router
-                response_data = self.router.route_query(query, file_context, viva_state, chat_history)
-                
-                return {
-                    'success': True,
-                    **response_data
-                }
-            except Exception as e:
-                print(f"Error in MyPharmaAI.process_query: {e}")
-                return {
-                    'success': False,
-                    'message': f"Sorry, a critical error occurred: {str(e)}",
-                    'agent_used': 'error'
-                }
-
-
-    def get_file_context(self, uploaded_files_session):
-        """Extracts text from the most recent files to use as context."""
-        context = ""
-        for file_info in uploaded_files_session[-3:]: # Limit to last 3 files
-            file_path = file_info.get('path')
-            if file_path and os.path.exists(file_path):
-                try:
-                    content = self.file_processor.extract_text(file_path)
-                    if content:
-                        # Limit context from each file to 2000 characters
-                        context += f"\n\n--- Content from {file_info['original_name']} ---\n{content[:2000]}..."
-                except Exception as e:
-                    context += f"\n\n--- Error reading {file_info['original_name']}: {str(e)} ---"
-        return context
-
-    def get_daily_quote(self):
-        """Returns a random quote."""
-        return random.choice(self.quotes) if self.quotes else "विद्या धनं सर्व धन प्रधानम्"
-
-# Initialize the AI system
-pharma_ai = MyPharmaAI()
+        self.vector_store = vector_store_db
+
+    def process_query(self, query, viva_state, chat_history):
+        file_context = ""
+        if self.vector_store:
+            # Search the knowledge base for relevant documents
+            relevant_docs = self.vector_store.similarity_search(query)
+            # Join the content of the relevant docs to create the context
+            file_context = "\n".join(doc.page_content for doc in relevant_docs)
+        
+        # Pass the retrieved context to the router, maintaining the existing structure
+        return self.router.route_query(query, file_context, viva_state, chat_history)
 
-# --- Flask Routes ---
+pharma_ai = MyPharmaAI(model, vector_store)
 
+# --- Flask Routes ---
 @app.route('/')
 def index():
-    """Renders the main chat interface."""
-    greeting = get_greeting()
-    daily_quote = pharma_ai.get_daily_quote()
-    uploaded_files = session.get('uploaded_files', [])
-    return render_template('index.html', 
-                           greeting=greeting, 
-                           daily_quote=daily_quote,
-                           uploaded_files=uploaded_files)
+    return render_template('index.html', greeting=get_greeting(), daily_quote=random.choice(pharma_ai.quotes))
 
 @app.route('/chat', methods=['POST'])
 def chat():
-    """Handles the main chat logic, including session management for the Viva Agent."""
-    try:
-        data = request.get_json()
-        query = data.get('query', '').strip()
-        if not query:
-            return jsonify({'success': False, 'error': 'Empty query'}), 400
-        
-         # --- HISTORY MANAGEMENT START ---
-
-        # Get the conversation history from the session (or start a new one)
-        chat_history = session.get('chat_history', [])
+    data = request.get_json()
+    query = data.get('query', '').strip()
+    if not query:
+        return jsonify({'success': False, 'error': 'Empty query'}), 400
 
-        # Get current viva state from session for the Viva Agent
-        viva_state = session.get('viva_state', None)
-        uploaded_files = session.get('uploaded_files', None)
-
-        # Process the query through the main orchestrator
-        result = pharma_ai.process_query(query, viva_state=viva_state, uploaded_files=uploaded_files,chat_history=chat_history)
-        # If the query was successful, update the history
+    chat_history = session.get('chat_history', [])
+    viva_state = session.get('viva_state', None)
+    
+    try:
+        result = pharma_ai.process_query(query, viva_state, chat_history)
         if result.get('success'):
-            # Add the user's query and the AI's message to the history
             chat_history.append({'role': 'user', 'parts': [query]})
             chat_history.append({'role': 'model', 'parts': [result.get('message', '')]})
-
-            # Keep the history from getting too long (e.g., last 10 exchanges)
-            session['chat_history'] = chat_history[-20:]
-
-        # --- HISTORY MANAGEMENT END ---
-
-        # If the Viva agent returns an updated state, save it to the session
-        if 'viva_state' in result:
-            session['viva_state'] = result.get('viva_state')
-        
+            session['chat_history'] = chat_history[-10:]
         return jsonify(result)
-        
     except Exception as e:
         print(f"Error in /chat endpoint: {e}")
-        return jsonify({'success': False, 'error': f'Server error: {str(e)}'}), 500
-
-@app.route('/upload', methods=['POST'])
-def upload_file():
-    """Handles file uploads."""
-    if 'file' not in request.files:
-        return jsonify({'success': False, 'error': 'No file part'}), 400
-    file = request.files['file']
-    if file.filename == '':
-        return jsonify({'success': False, 'error': 'No selected file'}), 400
-    if file and allowed_file(file.filename):
-        filename = secure_filename(file.filename)
-        file_path = os.path.join(app.config['UPLOAD_FOLDER'], filename)
-        file.save(file_path)
-
-        if 'uploaded_files' not in session:
-            session['uploaded_files'] = []
-        
-        file_info = {'original_name': filename, 'path': file_path}
-        session['uploaded_files'].append(file_info)
-        session.modified = True
-
-        return jsonify({
-            'success': True, 
-            'message': f'File "{filename}" uploaded. You can now ask questions about it.',
-            'files': session['uploaded_files']
-        })
-    return jsonify({'success': False, 'error': 'File type not allowed'}), 400
-
-@app.route('/files', methods=['GET'])
-def get_uploaded_files():
-    """Returns the list of uploaded files from the session."""
-    return jsonify({'files': session.get('uploaded_files', [])})
-
-@app.route('/clear_files', methods=['POST'])
-def clear_files():
-    """Deletes uploaded files from disk and clears them from the session."""
-    if 'uploaded_files' in session:
-        for file_info in session['uploaded_files']:
-            if os.path.exists(file_info['path']):
-                os.remove(file_info['path'])
-    session.pop('uploaded_files', None)
-    session.pop('viva_state', None) # Also clear viva state
-    return jsonify({'success': True, 'message': 'All files and sessions cleared.'})
-
-@app.route('/quote')
-def get_quote():
-    """Returns a new random quote."""
-    return jsonify({'quote': pharma_ai.get_daily_quote()})
+        return jsonify({'success': False, 'message': f'Server error: {e}', 'agent_used': 'error'}), 500
 
 # --- Main Execution ---
-# if __name__ == '__main__':
-#     # Ensure all necessary directories exist
-#     for directory in ['data', 'static/css', 'static/js', 'templates', 'agents', 'utils', 'uploads']:
-#         os.makedirs(directory, exist_ok=True)
-    
-#     print("🇮🇳 MyPharma AI Starting...")
-#     print(f"🤖 Gemini API Status: {'✅ Ready' if model else '❌ Not configured'}")
-#     print("🚀 Server starting on http://127.0.0.1:5000")
-#     app.run(debug=True, port=5000)
 if __name__ == '__main__':
-    # Create necessary directories (this is good practice)
-    for directory in ['data', 'uploads', 'templates']:
-        os.makedirs(directory, exist_ok=True)
-    
-    # Get port from environment variable, defaulting to 5000 for local testing
+    # Ensure data folder exists for quotes.json
+    os.makedirs('data', exist_ok=True)
     port = int(os.environ.get('PORT', 7860))
-    
-    print("🇮🇳 MyPharma AI Starting...")
-    print(f"🤖 Gemini API Status: {'✅ Ready' if model else '❌ Not configured'}")
-    print(f"🚀 Server starting on http://0.0.0.0:{port}")
-    
-    # Run the app to be accessible on the server
     app.run(host='0.0.0.0', port=port)

templates/index.html

@@ -1,4 +1,4 @@
-<!DOCTYPE html>
+<!--<!DOCTYPE html>
 <html lang="en">
 <head>
     <meta charset="UTF-8">
@@ -330,18 +330,18 @@
 </head>
 <body>
     <div class="container">
-        <!-- Header -->
+      
         <div class="header">
             <h1>🇮🇳 MyPharma AI</h1>
             <div class="subtitle">{{ greeting or "नमस्ते! Your Intelligent Pharmacy Study Companion" }}</div>
         </div>
 
-        <!-- Daily Quote -->
+        
         <div class="quote-container" id="quoteContainer">
             📿 {{ daily_quote or "विद्या धनं सर्व धन प्रधानम् - Knowledge is the supreme wealth" }}
         </div>
 
-        <!-- Chat Container -->
+        
         <div class="chat-container">
             <div class="chat-header">
                 💬 Chat with Your AI Study Buddy
@@ -375,7 +375,7 @@
                     <div id="fileList">
                     </div>
                 </div>
-                <!-- Quick Action Buttons -->
+               
                 <div class="quick-actions">
                     <button class="quick-btn" onclick="populateInput('Explain ')">📊 Explain Topic</button>
                     <button class="quick-btn" onclick="populateInput('What are the side effects of ')">⚗️ Drug Info</button>
@@ -383,7 +383,7 @@
                     <button class="quick-btn" onclick="populateInput('Mnemonic for ')">🧠 Mnemonics</button>
                 </div>
 
-                <!-- Input Container -->
+                
                 <div class="input-container">
                     <input type="text" 
                            id="messageInput" 
@@ -597,4 +597,191 @@
         });
     </script>
 </body>
+</html>-->
+
+
+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>MyPharma AI - Your Study Companion</title>
+    <script src="https://cdn.jsdelivr.net/npm/marked/marked.min.js"></script>
+    <style>
+        :root {
+            --saffron: #FF9933; --maroon: #800000; --gold: #FFD700;
+            --peacock-blue: #005F9E; --cream: #FFF8E7; --light-saffron: #FFE4B5;
+        }
+        * { margin: 0; padding: 0; box-sizing: border-box; }
+        body {
+            font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
+            background: linear-gradient(135deg, var(--cream) 0%, var(--light-saffron) 100%);
+            min-height: 100vh;
+            display: flex; align-items: center; justify-content: center; padding: 20px;
+        }
+        .container {
+            max-width: 800px; margin: 0 auto; width: 100%;
+            height: 90vh; max-height: 850px; display: flex; flex-direction: column;
+            background: white; border-radius: 15px; box-shadow: 0 8px 25px rgba(0,0,0,0.1);
+            border: 3px solid var(--gold); overflow: hidden;
+        }
+        .header {
+            background: linear-gradient(135deg, var(--maroon) 0%, var(--peacock-blue) 100%);
+            color: white; padding: 20px; text-align: center;
+        }
+        .header h1 { font-size: 2em; margin-bottom: 5px; }
+        .header .subtitle { font-size: 1.1em; opacity: 0.9; }
+        .chat-container { flex: 1; display: flex; flex-direction: column; overflow: hidden; }
+        .chat-messages { flex: 1; padding: 20px; overflow-y: auto; }
+        .message { margin-bottom: 20px; display: flex; max-width: 85%; animation: fadeIn 0.3s ease-in; }
+        @keyframes fadeIn { from { opacity: 0; transform: translateY(10px); } to { opacity: 1; transform: translateY(0); } }
+        .message.user { margin-left: auto; flex-direction: row-reverse; }
+        .message-bubble {
+            padding: 12px 18px; border-radius: 20px; word-wrap: break-word; line-height: 1.6;
+        }
+        .message.user .message-bubble {
+            background: linear-gradient(135deg, var(--peacock-blue) 0%, var(--maroon) 100%);
+            color: white; border-bottom-right-radius: 5px;
+        }
+        .message.bot .message-bubble {
+            background: linear-gradient(135deg, var(--light-saffron) 0%, var(--cream) 100%);
+            color: var(--maroon); border: 2px solid var(--saffron); border-bottom-left-radius: 5px;
+        }
+        .agent-badge {
+            display: inline-block; background: var(--gold); color: var(--maroon);
+            padding: 3px 8px; border-radius: 12px; font-size: 0.8em; font-weight: bold; margin-bottom: 8px;
+        }
+        .input-area { padding: 20px; background: var(--cream); border-top: 3px solid var(--gold); }
+        .quick-actions { display: flex; gap: 10px; margin-bottom: 15px; flex-wrap: wrap; }
+        .quick-btn {
+            background: white; color: var(--peacock-blue); border: 2px solid var(--peacock-blue);
+            padding: 8px 15px; border-radius: 20px; cursor: pointer; font-size: 14px; transition: all 0.3s ease;
+        }
+        .quick-btn:hover { background: var(--peacock-blue); color: white; }
+        .input-container { display: flex; gap: 10px; align-items: center; }
+        #messageInput {
+            flex: 1; padding: 15px 20px; border: 2px solid var(--saffron);
+            border-radius: 25px; font-size: 16px; outline: none;
+        }
+        #sendBtn {
+            background: linear-gradient(135deg, var(--saffron) 0%, var(--gold) 100%);
+            color: var(--maroon); border: none; padding: 15px 25px; border-radius: 25px;
+            cursor: pointer; font-weight: bold; font-size: 16px; transition: all 0.3s ease;
+        }
+        #sendBtn:hover { transform: translateY(-2px); box-shadow: 0 5px 15px rgba(255,153,51,0.4); }
+        .typing-indicator span { display: inline-block; width: 8px; height: 8px; border-radius: 50%; background-color: #aaa; margin: 0 2px; animation: bounce 1s infinite; }
+        .typing-indicator span:nth-child(2) { animation-delay: 0.1s; }
+        .typing-indicator span:nth-child(3) { animation-delay: 0.2s; }
+        @keyframes bounce { 0%, 60%, 100% { transform: translateY(0); } 30% { transform: translateY(-6px); } }
+    </style>
+</head>
+<body>
+    <div class="container">
+        <div class="header">
+            <h1>🇮🇳 MyPharma AI</h1>
+            <div class="subtitle">{{ greeting }}</div>
+        </div>
+
+        <div class="chat-container">
+            <div class="chat-messages" id="chatMessages">
+                <div class="message bot">
+                    <div class="message-bubble">
+                        <div class="agent-badge">🤖 AI Study Buddy</div>
+                        🙏 <strong>Namaste!</strong> I have studied the documents in the knowledge library. Ask me anything about your subjects, and I will find the answer for you.
+                    </div>
+                </div>
+            </div>
+
+            <div class="input-area">
+                <div class="quick-actions">
+                    <button class="quick-btn" onclick="populateInput('Explain ')">📊 Explain Topic</button>
+                    <button class="quick-btn" onclick="populateInput('What are the side effects of ')">⚗️ Drug Info</button>
+                    <button class="quick-btn" onclick="populateInput('Make a quiz on ')">❓ Create Quiz</button>
+                </div>
+
+                <div class="input-container">
+                    <input type="text" id="messageInput" placeholder="Ask about your documents..." onkeypress="handleKeyPress(event)">
+                    <button id="sendBtn" onclick="sendMessage()">Send 📨</button>
+                </div>
+            </div>
+        </div>
+    </div>
+
+    <script>
+        let isProcessing = false;
+
+        async function sendMessage() {
+            const input = document.getElementById('messageInput');
+            const message = input.value.trim();
+            if (!message || isProcessing) return;
+
+            addMessage(message, 'user');
+            input.value = '';
+            showLoading(true);
+
+            try {
+                const response = await fetch('/chat', {
+                    method: 'POST',
+                    headers: { 'Content-Type': 'application/json' },
+                    body: JSON.stringify({ query: message })
+                });
+                const data = await response.json();
+                showLoading(false);
+                if (data.success) {
+                    addMessage(data.message, 'bot', data.agent_used);
+                } else {
+                    addMessage(`❌ Error: ${data.error || 'Something went wrong'}`, 'bot', 'error');
+                }
+            } catch (error) {
+                showLoading(false);
+                addMessage(`❌ Connection error: ${error.message}`, 'bot', 'error');
+            }
+        }
+
+        function addMessage(text, sender, agentType = '') {
+            const messagesContainer = document.getElementById('chatMessages');
+            const messageDiv = document.createElement('div');
+            messageDiv.className = `message ${sender}`;
+            const agentIcons = { 'academic': '📚 Academic Agent', 'drug_info': '💊 Drug Info Agent', 'quiz_generation': '❓ Quiz Master' };
+            const agentBadge = sender === 'bot' ? `<div class="agent-badge">${agentIcons[agentType] || '🤖 AI Assistant'}</div>` : '';
+            const formattedText = marked.parse(text || 'Sorry, I received an empty response.');
+            messageDiv.innerHTML = `<div class="message-bubble">${agentBadge}${formattedText}</div>`;
+            messagesContainer.appendChild(messageDiv);
+            messagesContainer.scrollTop = messagesContainer.scrollHeight;
+        }
+
+        function showLoading(show) {
+            document.getElementById('sendBtn').disabled = show;
+            const existingLoading = document.getElementById('loading-indicator');
+            if (existingLoading) existingLoading.remove();
+            
+            if (show) {
+                const messagesContainer = document.getElementById('chatMessages');
+                const loadingDiv = document.createElement('div');
+                loadingDiv.className = 'message bot';
+                loadingDiv.id = 'loading-indicator';
+                loadingDiv.innerHTML = `<div class="message-bubble"><div class="typing-indicator"><span></span><span></span><span></span></div></div>`;
+                messagesContainer.appendChild(loadingDiv);
+                messagesContainer.scrollTop = messagesContainer.scrollHeight;
+            }
+        }
+
+        function handleKeyPress(event) {
+            if (event.key === 'Enter' && !event.shiftKey) {
+                event.preventDefault();
+                sendMessage();
+            }
+        }
+        
+        function populateInput(templateText) {
+            const input = document.getElementById('messageInput');
+            input.value = templateText;
+            input.focus();
+        }
+        
+        document.addEventListener('DOMContentLoaded', () => {
+             document.getElementById('messageInput').focus();
+        });
+    </script>
+</body>
 </html>