Update app.py

app.py

@@ -1,156 +1,180 @@
-import os
-import tempfile
-import shutil
-from flask import Flask, request, jsonify, render_template, redirect, url_for, flash
-import asyncio
-from retriever.document_store import DocumentStore
-from retriever.rag_pipeline import RAGPipeline
-from models.model_loader import load_llm
-from config import Config
-
-app = Flask(__name__)
-app.config.from_object(Config)
-app.secret_key = os.getenv('SECRET_KEY', 'your-secret-key-here')
-
-# Initialize components
-print("Initializing document store...")
-document_store = DocumentStore()
-print("Document store initialized")
-
-print("Loading LLM...")
-llm = load_llm(api_key=app.config["LLAMA_API_KEY"])
-print("LLM loaded")
-
-print("Initializing RAG pipeline...")
-rag_pipeline = RAGPipeline(document_store, llm)
-print("RAG pipeline initialized")
-
-@app.route('/')
-def index():
-    """Home page"""
-    return render_template('index.html')
-
-@app.route('/add_data', methods=['GET', 'POST'])
-def add_data():
-    """Add data to the document store"""
-    if request.method == 'POST':
-        content = request.form.get('content')
-        title = request.form.get('title', 'Untitled')
-        
-        if content:
-            try:
-                document_store.add_text(content=content, title=title)
-                flash('Data added successfully!', 'success')
-                return redirect(url_for('index'))
-            except Exception as e:
-                flash(f'Error adding data: {str(e)}', 'error')
-        else:
-            flash('Content is required', 'error')
-    
-    return render_template('add_data.html')
-
-@app.route('/upload_file', methods=['POST'])
-def upload_file():
-    """Upload and process a file (PDF, TXT, etc.)"""
-    if 'file' not in request.files:
-        flash('No file selected', 'error')
-        return redirect(url_for('add_data'))
-    
-    file = request.files['file']
-    if file.filename == '':
-        flash('No file selected', 'error')
-        return redirect(url_for('add_data'))
-    
-    if file:
-        try:
-            # Create a temporary file
-            with tempfile.NamedTemporaryFile(delete=False, suffix=os.path.splitext(file.filename)[1]) as tmp_file:
-                file.save(tmp_file.name)
-                
-                # Process the file and add to document store
-                document_store.add_document(tmp_file.name)
-                
-                # Clean up temporary file
-                os.unlink(tmp_file.name)
-                
-            flash('File uploaded and processed successfully!', 'success')
-        except Exception as e:
-            flash(f'Error processing file: {str(e)}', 'error')
-        
-        return redirect(url_for('add_data'))
-
-@app.route('/api/generate', methods=['POST'])
-async def api_generate():
-    """API endpoint to generate text based on stored data"""
-    data = request.json
-    query = data.get('query', '')
-    gen_type = data.get('type', 'bio')  # bio, cover_letter, general
-    
-    if not query:
-        return jsonify({"error": "Query is required"}), 400
-    
-    try:
-        # Generate response using RAG pipeline
-        response = await rag_pipeline.generate(query, gen_type)
-        return jsonify({"response": response})
-    except Exception as e:
-        return jsonify({"error": f"Error generating response: {str(e)}"}), 500
-
-@app.route('/generate', methods=['GET', 'POST'])
-def generate():
-    """Generate text based on a query and display results"""
-    if request.method == 'POST':
-        query = request.form.get('query', '')
-        gen_type = request.form.get('type', 'bio')
-        
-        if query:
-            try:
-                # Run the async function using asyncio
-                response = asyncio.run(rag_pipeline.generate(query, gen_type))
-                return render_template('generate.html', query=query, response=response, gen_type=gen_type)
-            except Exception as e:
-                flash(f'Error generating response: {str(e)}', 'error')
-                return render_template('generate.html', query=query, error=str(e))
-        else:
-            flash('Query is required', 'error')
-    
-    return render_template('generate.html')
-
-@app.route('/debug/documents', methods=['GET'])
-def debug_documents():
-    """Debug endpoint to view stored documents"""
-    try:
-        doc_count = len(document_store.documents)
-        chunk_count = sum(len(doc.get('chunks', [])) for doc in document_store.documents.values())
-        
-        docs_summary = []
-        for doc_id, doc in document_store.documents.items():
-            docs_summary.append({
-                "id": doc_id,
-                "title": doc.get("title", "Untitled"),
-                "chunks": len(doc.get("chunks", [])),
-                "first_chunk_preview": doc.get("chunks", [""])[0][:100] + "..." if doc.get("chunks") else ""
-            })
-        
-        return render_template(
-            'debug.html', 
-            doc_count=doc_count,
-            chunk_count=chunk_count,
-            docs=docs_summary
-        )
-    except Exception as e:
-        return f"Error in debug endpoint: {str(e)}", 500
-
-@app.route('/health')
-def health_check():
-    """Health check endpoint"""
-    return jsonify({"status": "healthy", "message": "RAG application is running"})
-
-if __name__ == '__main__':
-    # Ensure data directory exists
-    os.makedirs("data", exist_ok=True)
-    
-    # Get port from environment variable (Hugging Face Spaces uses PORT)
-    port = int(os.environ.get('PORT', 7860))
-    
+import os
+import sys
+import tempfile
+import shutil
+from datetime import datetime
+
+# CRITICAL: Set cache directories BEFORE importing any HuggingFace libraries
+os.environ['TRANSFORMERS_CACHE'] = '/tmp/transformers'
+os.environ['SENTENCE_TRANSFORMERS_HOME'] = '/tmp/sentence_transformers'
+os.environ['HF_HOME'] = '/tmp/huggingface'
+os.environ['HF_DATASETS_CACHE'] = '/tmp/datasets'
+
+# Create cache directories
+cache_dirs = ['/tmp/transformers', '/tmp/sentence_transformers', '/tmp/huggingface', '/tmp/datasets']
+for cache_dir in cache_dirs:
+    try:
+        os.makedirs(cache_dir, exist_ok=True)
+        print(f"✓ Created cache directory: {cache_dir}")
+    except PermissionError as e:
+        print(f"✗ Failed to create {cache_dir}: {e}")
+        sys.exit(1)
+
+# Now import other modules
+from flask import Flask, request, jsonify, render_template, redirect, url_for, flash
+import asyncio
+from retriever.document_store import DocumentStore
+from retriever.rag_pipeline import RAGPipeline
+from models.model_loader import load_llm
+from config import Config
+
+app = Flask(__name__)
+app.config.from_object(Config)
+app.secret_key = os.getenv('SECRET_KEY', 'your-secret-key-here')
+
+# Initialize components
+print("===== Application Startup at", datetime.now().strftime("%Y-%m-%d %H:%M:%S"), "=====")
+print("Initializing document store...")
+print(f"Using vector DB path: {os.getenv('VECTOR_DB_PATH', 'data/vector_store')}")
+
+document_store = DocumentStore()
+print("Document store initialized")
+
+print("Loading LLM...")
+llm = load_llm(api_key=app.config["LLAMA_API_KEY"])
+print("LLM loaded")
+
+print("Initializing RAG pipeline...")
+rag_pipeline = RAGPipeline(document_store, llm)
+print("RAG pipeline initialized")
+
+@app.route('/')
+def index():
+    """Home page"""
+    return render_template('index.html')
+
+@app.route('/add_data', methods=['GET', 'POST'])
+def add_data():
+    """Add data to the document store"""
+    if request.method == 'POST':
+        content = request.form.get('content')
+        title = request.form.get('title', 'Untitled')
+        
+        if content:
+            try:
+                document_store.add_text(content=content, title=title)
+                flash('Data added successfully!', 'success')
+                return redirect(url_for('index'))
+            except Exception as e:
+                flash(f'Error adding data: {str(e)}', 'error')
+        else:
+            flash('Content is required', 'error')
+    
+    return render_template('add_data.html')
+
+@app.route('/upload_file', methods=['POST'])
+def upload_file():
+    """Upload and process a file (PDF, TXT, etc.)"""
+    if 'file' not in request.files:
+        flash('No file selected', 'error')
+        return redirect(url_for('add_data'))
+    
+    file = request.files['file']
+    if file.filename == '':
+        flash('No file selected', 'error')
+        return redirect(url_for('add_data'))
+    
+    if file:
+        try:
+            # Create a temporary file
+            with tempfile.NamedTemporaryFile(delete=False, suffix=os.path.splitext(file.filename)[1]) as tmp_file:
+                file.save(tmp_file.name)
+                
+                # Process the file and add to document store
+                document_store.add_document(tmp_file.name)
+                
+                # Clean up temporary file
+                os.unlink(tmp_file.name)
+                
+            flash('File uploaded and processed successfully!', 'success')
+        except Exception as e:
+            flash(f'Error processing file: {str(e)}', 'error')
+        
+        return redirect(url_for('add_data'))
+
+@app.route('/api/generate', methods=['POST'])
+async def api_generate():
+    """API endpoint to generate text based on stored data"""
+    data = request.json
+    query = data.get('query', '')
+    gen_type = data.get('type', 'bio')  # bio, cover_letter, general
+    
+    if not query:
+        return jsonify({"error": "Query is required"}), 400
+    
+    try:
+        # Generate response using RAG pipeline
+        response = await rag_pipeline.generate(query, gen_type)
+        return jsonify({"response": response})
+    except Exception as e:
+        return jsonify({"error": f"Error generating response: {str(e)}"}), 500
+
+@app.route('/generate', methods=['GET', 'POST'])
+def generate():
+    """Generate text based on a query and display results"""
+    if request.method == 'POST':
+        query = request.form.get('query', '')
+        gen_type = request.form.get('type', 'bio')
+        
+        if query:
+            try:
+                # Run the async function using asyncio
+                response = asyncio.run(rag_pipeline.generate(query, gen_type))
+                return render_template('generate.html', query=query, response=response, gen_type=gen_type)
+            except Exception as e:
+                flash(f'Error generating response: {str(e)}', 'error')
+                return render_template('generate.html', query=query, error=str(e))
+        else:
+            flash('Query is required', 'error')
+    
+    return render_template('generate.html')
+
+@app.route('/debug/documents', methods=['GET'])
+def debug_documents():
+    """Debug endpoint to view stored documents"""
+    try:
+        doc_count = len(document_store.documents)
+        chunk_count = sum(len(doc.get('chunks', [])) for doc in document_store.documents.values())
+        
+        docs_summary = []
+        for doc_id, doc in document_store.documents.items():
+            docs_summary.append({
+                "id": doc_id,
+                "title": doc.get("title", "Untitled"),
+                "chunks": len(doc.get("chunks", [])),
+                "first_chunk_preview": doc.get("chunks", [""])[0][:100] + "..." if doc.get("chunks") else ""
+            })
+        
+        return render_template(
+            'debug.html', 
+            doc_count=doc_count,
+            chunk_count=chunk_count,
+            docs=docs_summary
+        )
+    except Exception as e:
+        return f"Error in debug endpoint: {str(e)}", 500
+
+@app.route('/health')
+def health_check():
+    """Health check endpoint"""
+    return jsonify({"status": "healthy", "message": "RAG application is running"})
+
+if __name__ == '__main__':
+    # Ensure data directory exists
+    os.makedirs("data", exist_ok=True)
+    
+    # Get port from environment variable (Hugging Face Spaces uses PORT)
+    port = int(os.environ.get('PORT', 7860))
+    
+    print(f"Starting Flask app on port {port}")
     app.run(host='0.0.0.0', port=port, debug=False)