Create app.py

app.py

@@ -0,0 +1,65 @@
+
+from flask import Flask, request, jsonify
+from flask_cors import CORS
+from scraper import WebScraper
+from vector_db import VectorDatabase
+from chatbot import ChatBot
+import os
+from dotenv import load_dotenv
+
+load_dotenv()
+
+app = Flask(__name__)
+CORS(app)  # Enable CORS for all routes
+
+# Initialize our components
+scraper = WebScraper()
+vector_db = VectorDatabase()
+chatbot = ChatBot()
+
+@app.route('/api/scrape', methods=['POST'])
+def scrape_url():
+    try:
+        data = request.json
+        url = data.get('url')
+        if not url:
+            return jsonify({'error': 'URL is required'}), 400
+
+        # Scrape the URL
+        result = scraper.scrape_url(url)
+        if not result or not result['content']:
+            return jsonify({'error': 'Failed to scrape website'}), 400
+
+        # Process and store in vector database
+        chunks_count, vector_store_id = vector_db.process_and_store(result)
+        
+        return jsonify({
+            'message': f'Successfully scraped and processed into {chunks_count} chunks', 
+            'chunks': chunks_count,
+            'url': result['url']
+        })
+    except Exception as e:
+        return jsonify({'error': str(e)}), 500
+
+@app.route('/api/chat', methods=['POST'])
+def chat():
+    try:
+        data = request.json
+        message = data.get('message')
+        url = data.get('url')  # Optional URL to specify context
+
+        if not message:
+            return jsonify({'error': 'Message is required'}), 400
+
+        # Get context from vector database
+        context = vector_db.search(message, url)
+
+        # Generate response
+        response = chatbot.generate_response(message, context, url)
+        
+        return jsonify({'response': response})
+    except Exception as e:
+        return jsonify({'error': str(e)}), 500
+
+if __name__ == '__main__':
+    app.run(host='0.0.0.0', port=7860)