Update app.py

app.py

@@ -10,35 +10,18 @@ from datetime import datetime, timezone, timedelta
 from dotenv import load_dotenv
 import json
 
-# Load environment variables from a .env file
-# This is useful for local development. In production on platforms like Hugging Face,
-# you'll set these as environment variables directly in the settings.
+# Load environment variables
 load_dotenv()
 
 app = Flask(__name__)
 CORS(app)
 
 # Initialize Gemini client
-# The API key should be loaded from environment variables
-api_key = os.getenv('GOOGLE_API_KEY')
-if not api_key:
-    print("Error: GOOGLE_API_KEY environment variable not set.")
-    # In a real app, you might exit or raise an exception here.
-    # For this example, we'll print an error but allow the app to start;
-    # API calls will fail if the key is missing.
-    # If running locally, make sure you have a .env file with GOOGLE_API_KEY=YOUR_API_KEY
-    pass # Allows the app to run without a key for debugging non-API parts
+client = genai.Client(api_key=os.getenv('GOOGLE_API_KEY'))
 
-try:
-    client = genai.Client(api_key=api_key)
-except Exception as e:
-    print(f"Failed to initialize Gemini client: {e}")
-    client = None # Set client to None if initialization fails
-
-# In-memory storage for demo (in production, use a database like Redis or PostgreSQL)
-# Maps our internal cache_id (UUID) to Gemini's cache_name and other info
+# In-memory storage for demo (in production, use a database)
 document_caches = {}
-user_sessions = {} # Not used in this version, but kept from template
+user_sessions = {}
 
 # HTML template for the web interface
 HTML_TEMPLATE = """
@@ -48,58 +31,62 @@ HTML_TEMPLATE = """
     <meta charset="UTF-8">
     <meta name="viewport" content="width=device-width, initial-scale=1.0">
     <title>Smart Document Analysis Platform</title>
-    <link href="https://fonts.googleapis.com/css2?family=Inter:wght@300;400;500;600;700&display=swap" rel="stylesheet">
     <style>
         * {
             margin: 0;
             padding: 0;
             box-sizing: border-box;
         }
-
+        
         body {
             font-family: 'Inter', -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif;
             background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
             min-height: 100vh;
             color: #333;
-            line-height: 1.6;
         }
-
+        
         .container {
             max-width: 1400px;
             margin: 0 auto;
             padding: 20px;
             min-height: 100vh;
-            display: flex;
-            flex-direction: column;
         }
-
+        
         .header {
             text-align: center;
             margin-bottom: 30px;
             color: white;
         }
-
+        
         .header h1 {
             font-size: 2.8em;
             font-weight: 700;
             margin-bottom: 10px;
             text-shadow: 0 2px 4px rgba(0,0,0,0.3);
         }
-
+        
         .header p {
             font-size: 1.2em;
             opacity: 0.9;
             font-weight: 300;
         }
-
+        
         .main-content {
             display: grid;
             grid-template-columns: 1fr 1fr;
             gap: 30px;
-            flex-grow: 1;
+            height: calc(100vh - 200px);
         }
-
-        .left-panel, .right-panel {
+        
+        .left-panel {
+            background: white;
+            border-radius: 20px;
+            padding: 30px;
+            box-shadow: 0 20px 40px rgba(0,0,0,0.1);
+            overflow-y: auto;
+        }
+        
+        .right-panel {
             background: white;
             border-radius: 20px;
             padding: 30px;
@@ -107,11 +94,7 @@ HTML_TEMPLATE = """
             display: flex;
             flex-direction: column;
         }
-
-        .left-panel {
-             overflow-y: auto; /* Allow scrolling if content is tall */
-        }
-
+        
         .panel-title {
             font-size: 1.5em;
             font-weight: 600;
@@ -121,11 +104,11 @@ HTML_TEMPLATE = """
             align-items: center;
             gap: 10px;
         }
-
+        
         .upload-section {
             margin-bottom: 30px;
         }
-
+        
         .upload-area {
             border: 2px dashed #667eea;
             border-radius: 15px;
@@ -134,31 +117,30 @@ HTML_TEMPLATE = """
             background: #f8fafc;
             transition: all 0.3s ease;
             margin-bottom: 20px;
-            cursor: pointer; /* Indicate clickable area */
         }
-
+        
         .upload-area:hover {
             border-color: #764ba2;
             background: #f0f2ff;
             transform: translateY(-2px);
         }
-
+        
         .upload-area.dragover {
             border-color: #764ba2;
             background: #e8f0ff;
             transform: scale(1.02);
         }
-
+        
         .upload-icon {
             font-size: 3em;
             color: #667eea;
             margin-bottom: 15px;
         }
-
+        
         .file-input {
             display: none;
         }
-
+        
         .upload-btn {
             background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
             color: white;
@@ -171,12 +153,12 @@ HTML_TEMPLATE = """
             transition: all 0.3s ease;
             margin: 10px;
         }
-
+        
         .upload-btn:hover {
             transform: translateY(-2px);
             box-shadow: 0 10px 20px rgba(102, 126, 234, 0.3);
         }
-
+        
         .url-input {
             width: 100%;
             padding: 15px;
@@ -186,12 +168,12 @@ HTML_TEMPLATE = """
             margin-bottom: 15px;
             transition: border-color 0.3s ease;
         }
-
+        
         .url-input:focus {
             outline: none;
             border-color: #667eea;
         }
-
+        
         .btn {
             background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
             color: white;
@@ -203,18 +185,18 @@ HTML_TEMPLATE = """
             font-weight: 500;
             transition: all 0.3s ease;
         }
-
+        
         .btn:hover {
             transform: translateY(-1px);
             box-shadow: 0 5px 15px rgba(102, 126, 234, 0.3);
         }
-
+        
         .btn:disabled {
             opacity: 0.6;
             cursor: not-allowed;
             transform: none;
         }
-
+        
         .chat-container {
             flex: 1;
             border: 1px solid #e2e8f0;
@@ -223,44 +205,40 @@ HTML_TEMPLATE = """
             padding: 20px;
             background: #f8fafc;
             margin-bottom: 20px;
-            display: flex;
-            flex-direction: column;
         }
-
+        
         .message {
             margin-bottom: 15px;
             padding: 15px;
             border-radius: 12px;
             max-width: 85%;
             animation: fadeIn 0.3s ease;
-            word-wrap: break-word; /* Ensure long words wrap */
         }
-
+        
         @keyframes fadeIn {
             from { opacity: 0; transform: translateY(10px); }
             to { opacity: 1; transform: translateY(0); }
         }
-
+        
         .user-message {
             background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
             color: white;
             margin-left: auto;
             box-shadow: 0 4px 12px rgba(102, 126, 234, 0.3);
         }
-
+        
         .ai-message {
             background: white;
             color: #333;
             border: 1px solid #e2e8f0;
             box-shadow: 0 2px 8px rgba(0,0,0,0.1);
-            margin-right: auto; /* Align AI messages to the left */
         }
-
+        
         .input-group {
             display: flex;
             gap: 10px;
         }
-
+        
         .question-input {
             flex: 1;
             padding: 15px;
@@ -269,12 +247,12 @@ HTML_TEMPLATE = """
             font-size: 1em;
             transition: border-color 0.3s ease;
         }
-
+        
         .question-input:focus {
             outline: none;
             border-color: #667eea;
         }
-
+        
         .cache-info {
             background: linear-gradient(135deg, #48bb78 0%, #38a169 100%);
             border-radius: 12px;
@@ -283,28 +261,18 @@ HTML_TEMPLATE = """
             color: white;
             box-shadow: 0 4px 12px rgba(72, 187, 120, 0.3);
         }
-
+        
         .cache-info h3 {
             margin-bottom: 10px;
             font-weight: 600;
         }
-
-         .cache-info p {
-             font-size: 0.9em;
-             margin-bottom: 5px;
-         }
-
-         .cache-info p:last-child {
-             margin-bottom: 0;
-         }
-
-
+        
         .loading {
             text-align: center;
             padding: 40px;
             color: #666;
         }
-
+        
         .loading-spinner {
             border: 3px solid #f3f3f3;
             border-top: 3px solid #667eea;
@@ -314,12 +282,12 @@ HTML_TEMPLATE = """
             animation: spin 1s linear infinite;
             margin: 0 auto 20px;
         }
-
+        
         @keyframes spin {
             0% { transform: rotate(0deg); }
             100% { transform: rotate(360deg); }
         }
-
+        
         .error {
             background: linear-gradient(135deg, #f56565 0%, #e53e3e 100%);
             border-radius: 12px;
@@ -328,7 +296,7 @@ HTML_TEMPLATE = """
             margin-bottom: 20px;
             box-shadow: 0 4px 12px rgba(245, 101, 101, 0.3);
         }
-
+        
         .success {
             background: linear-gradient(135deg, #48bb78 0%, #38a169 100%);
             border-radius: 12px;
@@ -337,13 +305,13 @@ HTML_TEMPLATE = """
             margin-bottom: 20px;
             box-shadow: 0 4px 12px rgba(72, 187, 120, 0.3);
         }
-
+        
         @media (max-width: 768px) {
             .main-content {
                 grid-template-columns: 1fr;
                 gap: 20px;
             }
-
+            
             .header h1 {
                 font-size: 2em;
             }
@@ -355,190 +323,146 @@ HTML_TEMPLATE = """
         <div class="header">
             <h1>📚 Smart Document Analysis Platform</h1>
             <p>Upload PDF documents once, ask questions forever with Gemini API caching</p>
-             <p style="font-size:0.9em; margin-top: 5px; opacity: 0.8;">Powered by Google Gemini API - Explicit Caching</p>
         </div>
-
+        
         <div class="main-content">
             <!-- Left Panel - Upload Section -->
             <div class="left-panel">
                 <div class="panel-title">
                     📤 Upload PDF Document
                 </div>
-
+                
                 <div class="upload-section">
                     <div class="upload-area" id="uploadArea">
                         <div class="upload-icon">📄</div>
                         <p>Drag and drop your PDF file here, or click to select</p>
                         <input type="file" id="fileInput" class="file-input" accept=".pdf">
-                         <!-- The button triggers the hidden file input -->
-                        <button type="button" class="upload-btn" onclick="document.getElementById('fileInput').click()">
+                        <button class="upload-btn" onclick="document.getElementById('fileInput').click()">
                             Choose PDF File
                         </button>
                     </div>
-
+                    
                     <div style="margin-top: 20px;">
                         <h3>Or provide a URL:</h3>
                         <input type="url" id="urlInput" class="url-input" placeholder="https://example.com/document.pdf">
-                        <button type="button" class="btn" onclick="uploadFromUrl()">Upload from URL</button>
+                        <button class="btn" onclick="uploadFromUrl()">Upload from URL</button>
                     </div>
                 </div>
-
+                
                 <div id="loading" class="loading" style="display: none;">
                     <div class="loading-spinner"></div>
                     <p id="loadingText">Processing your PDF... This may take a moment.</p>
                 </div>
-
+                
                 <div id="error" class="error" style="display: none;"></div>
                 <div id="success" class="success" style="display: none;"></div>
             </div>
-
+            
             <!-- Right Panel - Chat Section -->
             <div class="right-panel">
                 <div class="panel-title">
                     💬 Ask Questions
                 </div>
-
+                
                 <div id="cacheInfo" class="cache-info" style="display: none;">
                     <h3>✅ Document Cached Successfully!</h3>
                     <p>Your PDF has been cached using Gemini API. You can now ask multiple questions without re-uploading.</p>
                     <p><strong>Cache ID:</strong> <span id="cacheId"></span></p>
                     <p><strong>Tokens Cached:</strong> <span id="tokenCount"></span></p>
-                    <p>Note: Caching is ideal for larger documents (typically 1024+ tokens required).</p>
                 </div>
-
+                
                 <div class="chat-container" id="chatContainer">
                     <div class="message ai-message">
-                        👋 Hello! Upload a PDF document using the panel on the left, and I'll help you analyze it using Gemini API caching!
+                        👋 Hello! I'm ready to analyze your PDF documents. Upload a document to get started!
                     </div>
                 </div>
-
+                
                 <div class="input-group">
-                    <input type="text" id="questionInput" class="question-input" placeholder="Ask a question about your document..." disabled>
-                    <button type="button" class="btn" onclick="askQuestion()" id="askBtn" disabled>Ask</button>
+                    <input type="text" id="questionInput" class="question-input" placeholder="Ask a question about your document...">
+                    <button class="btn" onclick="askQuestion()" id="askBtn">Ask</button>
                 </div>
             </div>
         </div>
     </div>
+
     <script>
         let currentCacheId = null;
-
-        // Disable input/button initially
-        document.getElementById('questionInput').disabled = true;
-        document.getElementById('askBtn').disabled = true;
-
+        
         // File upload handling
         const uploadArea = document.getElementById('uploadArea');
         const fileInput = document.getElementById('fileInput');
-
-        // Prevent default drag behaviors
-        ['dragenter', 'dragover', 'dragleave', 'drop'].forEach(eventName => {
-            uploadArea.addEventListener(eventName, preventDefaults, false);
-        });
-
-        function preventDefaults (e) {
+        
+        uploadArea.addEventListener('dragover', (e) => {
             e.preventDefault();
-            e.stopPropagation();
-        }
-
-        // Highlight drop area when item is dragged over
-        ['dragenter', 'dragover'].forEach(eventName => {
-            uploadArea.addEventListener(eventName, () => uploadArea.classList.add('dragover'), false);
+            uploadArea.classList.add('dragover');
         });
-
-        ['dragleave', 'drop'].forEach(eventName => {
-            uploadArea.addEventListener(eventName, () => uploadArea.classList.remove('dragover'), false);
+        
+        uploadArea.addEventListener('dragleave', () => {
+            uploadArea.classList.remove('dragover');
         });
-
-        // Handle dropped files
-        uploadArea.addEventListener('drop', handleDrop, false);
-
-        function handleDrop(e) {
-            const dt = e.dataTransfer;
-            const files = dt.files;
+        
+        uploadArea.addEventListener('drop', (e) => {
+            e.preventDefault();
+            uploadArea.classList.remove('dragover');
+            const files = e.dataTransfer.files;
             if (files.length > 0) {
                 uploadFile(files[0]);
             }
-        }
-
+        });
+        
         fileInput.addEventListener('change', (e) => {
             if (e.target.files.length > 0) {
                 uploadFile(e.target.files[0]);
-                // Clear the input so the same file can be selected again if needed
-                e.target.value = '';
             }
         });
-
+        
         async function uploadFile(file) {
             if (!file.type.includes('pdf')) {
                 showError('Please select a PDF file.');
                 return;
             }
-
-            // Clear previous status messages
-            hideError();
-            hideSuccess();
-            document.getElementById('cacheInfo').style.display = 'none'; // Hide old cache info
-            currentCacheId = null; // Clear old cache ID
-
+            
             showLoading('Uploading PDF...');
-
+            
             const formData = new FormData();
             formData.append('file', file);
-
+            
             try {
                 const response = await fetch('/upload', {
                     method: 'POST',
                     body: formData
                 });
-
+                
                 const result = await response.json();
-
+                
                 if (result.success) {
                     currentCacheId = result.cache_id;
                     document.getElementById('cacheId').textContent = result.cache_id;
                     document.getElementById('tokenCount').textContent = result.token_count;
                     document.getElementById('cacheInfo').style.display = 'block';
-                    showSuccess('PDF uploaded and cached successfully! You can now ask questions.');
-
-                    // Enable chat input and button
-                    document.getElementById('questionInput').disabled = false;
-                    document.getElementById('askBtn').disabled = false;
-                     document.getElementById('questionInput').focus(); // Focus input
-
+                    showSuccess('PDF uploaded and cached successfully!');
+                    
                     // Add initial message
                     addMessage("I've analyzed your PDF document. What would you like to know about it?", 'ai');
-
                 } else {
                     showError(result.error);
-                     // Disable chat input/button if upload/cache failed
-                    document.getElementById('questionInput').disabled = true;
-                    document.getElementById('askBtn').disabled = true;
                 }
             } catch (error) {
                 showError('Error uploading file: ' + error.message);
-                 // Disable chat input/button on network/server error
-                document.getElementById('questionInput').disabled = true;
-                document.getElementById('askBtn').disabled = true;
             } finally {
                 hideLoading();
             }
         }
-
+        
         async function uploadFromUrl() {
             const url = document.getElementById('urlInput').value;
-            if (!url.trim()) {
+            if (!url) {
                 showError('Please enter a valid URL.');
                 return;
             }
-
-            // Clear previous status messages
-            hideError();
-            hideSuccess();
-            document.getElementById('cacheInfo').style.display = 'none'; // Hide old cache info
-            currentCacheId = null; // Clear old cache ID
-
+            
             showLoading('Uploading PDF from URL...');
-
+            
             try {
                 const response = await fetch('/upload-url', {
                     method: 'POST',
@@ -547,61 +471,47 @@ HTML_TEMPLATE = """
                     },
                     body: JSON.stringify({ url: url })
                 });
-
+                
                 const result = await response.json();
-
+                
                 if (result.success) {
                     currentCacheId = result.cache_id;
                     document.getElementById('cacheId').textContent = result.cache_id;
                     document.getElementById('tokenCount').textContent = result.token_count;
                     document.getElementById('cacheInfo').style.display = 'block';
-                    showSuccess('PDF uploaded and cached successfully! You can now ask questions.');
-
-                    // Enable chat input and button
-                    document.getElementById('questionInput').disabled = false;
-                    document.getElementById('askBtn').disabled = false;
-                     document.getElementById('questionInput').focus(); // Focus input
-
+                    showSuccess('PDF uploaded and cached successfully!');
+                    
                     // Add initial message
                     addMessage("I've analyzed your PDF document. What would you like to know about it?", 'ai');
-
                 } else {
                     showError(result.error);
-                     // Disable chat input/button if upload/cache failed
-                    document.getElementById('questionInput').disabled = true;
-                    document.getElementById('askBtn').disabled = true;
                 }
             } catch (error) {
                 showError('Error uploading from URL: ' + error.message);
-                 // Disable chat input/button on network/server error
-                document.getElementById('questionInput').disabled = true;
-                document.getElementById('askBtn').disabled = false; // Should be false? Fix: should be true
             } finally {
                 hideLoading();
             }
         }
-
+        
         async function askQuestion() {
-            const questionInput = document.getElementById('questionInput');
-            const question = questionInput.value.trim();
-            if (!question) return; // Don't send empty questions
-
+            const question = document.getElementById('questionInput').value;
+            if (!question.trim()) return;
+            
             if (!currentCacheId) {
                 showError('Please upload a PDF document first.');
                 return;
             }
-
+            
             // Add user message to chat
             addMessage(question, 'user');
-            questionInput.value = ''; // Clear input immediately
-
+            document.getElementById('questionInput').value = '';
+            
             // Show loading state
             const askBtn = document.getElementById('askBtn');
             const originalText = askBtn.textContent;
             askBtn.textContent = 'Generating...';
             askBtn.disabled = true;
-             questionInput.disabled = true; // Disable input while generating
-
+            
             try {
                 const response = await fetch('/ask', {
                     method: 'POST',
@@ -610,12 +520,12 @@ HTML_TEMPLATE = """
                     },
                     body: JSON.stringify({
                         question: question,
-                        cache_id: currentCacheId // Use our internal cache_id
+                        cache_id: currentCacheId
                     })
                 });
-
+                
                 const result = await response.json();
-
+                
                 if (result.success) {
                     addMessage(result.answer, 'ai');
                 } else {
@@ -626,565 +536,260 @@ HTML_TEMPLATE = """
             } finally {
                 askBtn.textContent = originalText;
                 askBtn.disabled = false;
-                questionInput.disabled = false; // Re-enable input
-                questionInput.focus(); // Put focus back on input
-                // Ensure button is disabled only if no cache is active
-                if (!currentCacheId) {
-                    askBtn.disabled = true;
-                    questionInput.disabled = true;
-                }
             }
         }
-
+        
         function addMessage(text, sender) {
             const chatContainer = document.getElementById('chatContainer');
             const messageDiv = document.createElement('div');
             messageDiv.className = `message ${sender}-message`;
-
-            // Use innerHTML to handle potential formatting like newlines or markdown
-            // (Basic textContent might be sufficient depending on expected AI output)
-            // For simplicity here, sticking to textContent as AI might output plain text
             messageDiv.textContent = text;
-
-            // Basic handling for newlines
-            messageDiv.style.whiteSpace = 'pre-wrap';
-
             chatContainer.appendChild(messageDiv);
-            chatContainer.scrollTop = chatContainer.scrollHeight; // Auto-scroll to latest message
+            chatContainer.scrollTop = chatContainer.scrollHeight;
         }
-
+        
         function showLoading(text = 'Processing...') {
             document.getElementById('loadingText').textContent = text;
             document.getElementById('loading').style.display = 'block';
         }
-
+        
         function hideLoading() {
             document.getElementById('loading').style.display = 'none';
         }
-
+        
         function showError(message) {
             const errorDiv = document.getElementById('error');
             errorDiv.textContent = message;
             errorDiv.style.display = 'block';
-            // Auto-hide after 5 seconds
             setTimeout(() => {
                 errorDiv.style.display = 'none';
             }, 5000);
         }
-
+        
         function showSuccess(message) {
             const successDiv = document.getElementById('success');
             successDiv.textContent = message;
             successDiv.style.display = 'block';
-             // Auto-hide after 5 seconds
             setTimeout(() => {
                 successDiv.style.display = 'none';
             }, 5000);
         }
-
-        function hideError() {
-             document.getElementById('error').style.display = 'none';
-        }
-
-        function hideSuccess() {
-             document.getElementById('success').style.display = 'none';
-        }
-
+        
         // Enter key to ask question
         document.getElementById('questionInput').addEventListener('keypress', (e) => {
-            // Check if the input is not disabled and the key is Enter
-            if (!document.getElementById('questionInput').disabled && e.key === 'Enter') {
-                e.preventDefault(); // Prevent default form submission if input is part of a form
+            if (e.key === 'Enter') {
                 askQuestion();
             }
         });
-
-        // Initial message visibility
-        // addMessage("👋 Hello! Upload a PDF document using the panel on the left, and I'll help you analyze it using Gemini API caching!", 'ai'); // Added this directly in HTML
     </script>
 </body>
 </html>
 """
 
-# --- Flask Routes ---
-
 @app.route('/')
 def index():
-    # Ensure API key is set before rendering, or add a warning to the template
-    if not api_key:
-        # You could modify the template or pass a variable to indicate error state
-        print("Warning: API key not set. API calls will fail.")
     return render_template_string(HTML_TEMPLATE)
 
-@app.route('/health', methods=['GET'])
-def health_check():
-    # A simple endpoint to check if the application is running
-    # Can optionally check API client status if needed, but basic 200 is common.
-    if client is None and api_key is not None: # Client failed to initialize despite key being present
-        return jsonify({"status": "unhealthy", "reason": "Gemini client failed to initialize"}), 500
-    # Note: This doesn't check if the API key is *valid* or if the API is reachable,
-    # just if the Flask app is running and the client object was created.
-    return jsonify({"status": "healthy"}), 200
-
-
 @app.route('/upload', methods=['POST'])
 def upload_file():
-    if client is None or api_key is None:
-         return jsonify({'success': False, 'error': 'API key not configured or Gemini client failed to initialize.'}), 500
-
     try:
         if 'file' not in request.files:
             return jsonify({'success': False, 'error': 'No file provided'})
-
+        
         file = request.files['file']
-
+        
         if file.filename == '':
             return jsonify({'success': False, 'error': 'No file selected'})
-
+        
         # Read file content
         file_content = file.read()
         file_io = io.BytesIO(file_content)
-
-        # --- CORRECTED FILE UPLOAD CALL ---
-        # Upload to Gemini File API using the correct method client.upload_file
-        # Pass the file content as a tuple (filename, file-like object, mime_type)
-        # This replaces the incorrect client.files.upload call
-        document = None # Initialize document variable
-        try:
-            # The mime_type is crucial for the API to correctly process the file.
-            # The filename is used as the display_name by default if not provided.
-            document = client.upload_file(
-                file=(file.filename, file_io, 'application/pdf'), # Use the 'file' argument with tuple format
-                # display_name=file.filename # Optional: explicitly provide a display name
-            )
-            print(f"File uploaded successfully to Gemini File API: {document.name}") # Log for debugging
-            # Note: client.upload_file returns a google.generativeai.types.File object
-            # which contains the resource name (e.g., 'files/xyz123').
-        except Exception as upload_error:
-             # Attempt to provide more specific feedback if possible
-             error_msg = str(upload_error)
-             print(f"Error uploading file to Gemini API: {error_msg}")
-             # Check for common upload errors like exceeding file size limits
-             if "file content size exceeds limit" in error_msg.lower():
-                  return jsonify({'success': False, 'error': f'Error uploading file: File size exceeds API limit. {error_msg}'}), 413 # 413 Payload Too Large
-             return jsonify({'success': False, 'error': f'Error uploading file to Gemini API: {error_msg}'}), 500
-        # --- END CORRECTED FILE UPLOAD CALL ---
-
+        
+        # Upload to Gemini File API
+        document = client.files.upload(
+            file=file_io,
+            config=dict(mime_type='application/pdf')
+        )
+        
         # Create cache with system instruction
-        cache = None # Initialize cache variable
         try:
             system_instruction = "You are an expert document analyzer. Provide detailed, accurate answers based on the uploaded document content. Always be helpful and thorough in your responses."
-
+            
             # Use the correct model format as per documentation
-            # Using a specific stable version is recommended for production
             model = 'models/gemini-2.0-flash-001'
-
-            print(f"Attempting to create cache for file: {document.name}") # Log
+            
             cache = client.caches.create(
                 model=model,
                 config=types.CreateCachedContentConfig(
-                    display_name=f'pdf document cache: {file.filename}', # Use filename in display_name
+                    display_name='pdf document cache',
                     system_instruction=system_instruction,
-                    contents=[document], # contents should be a list of content parts. document is already a File object, which is a valid content part type.
-                    ttl="3600s",  # 1 hour TTL. Use string format like "300s" or "1h".
+                    contents=[document],
+                    ttl="3600s",  # 1 hour TTL
                 )
             )
-            print(f"Cache created successfully: {cache.name}") # Log
-
-            # Store cache info in our in-memory dictionary
-            # We map our internal UUID cache_id to the Gemini API's cache.name (resource name)
+            
+            # Store cache info
             cache_id = str(uuid.uuid4())
             document_caches[cache_id] = {
-                'gemini_cache_name': cache.name, # Store the Gemini API resource name
+                'cache_name': cache.name,
                 'document_name': file.filename,
-                'gemini_file_name': document.name, # Also store the Gemini File API resource name for cleanup
-                'created_at': datetime.now().isoformat(),
-                'expires_at': (datetime.now(timezone.utc) + timedelta(seconds=3600)).isoformat(), # Store expiry time for reference
+                'created_at': datetime.now().isoformat()
             }
-
-            # Get token count from cache metadata if available
-            # Note: cached_token_count might be available on the cache object after creation
-            token_count = 'Unknown'
-            if hasattr(cache, 'usage_metadata') and cache.usage_metadata:
-                 token_count = getattr(cache.usage_metadata, 'cached_token_count', 'Unknown')
-                 print(f"Cached token count: {token_count}")
-
-
+            
             return jsonify({
                 'success': True,
-                'cache_id': cache_id, # Return our internal ID
-                'token_count': token_count
+                'cache_id': cache_id,
+                'token_count': getattr(cache.usage_metadata, 'cached_token_count', 'Unknown')
             })
-
+            
         except Exception as cache_error:
-            error_msg = str(cache_error)
-            print(f"Cache creation failed: {error_msg}") # Log the cache error
-            # If caching fails, attempt to delete the uploaded file to clean up.
-            if document and hasattr(document, 'name'):
-                 try:
-                     client.files.delete(document.name)
-                     print(f"Cleaned up uploaded file {document.name} after caching failure.")
-                 except Exception as cleanup_error:
-                      print(f"Failed to clean up file {document.name}: {cleanup_error}")
-
-            # Handle specific cache creation errors
-            # Note: The exact error message for content size can vary or might not be specific
-            # The documentation mentions minimum tokens for caching.
-            if "Cached content is too small" in error_msg or "minimum size" in error_msg.lower() or "tokens required" in error_msg.lower():
-                 return jsonify({
-                     'success': False,
-                     'error': f'PDF content is too small for caching. Minimum token count varies by model, but is typically 1024+ for Flash. {error_msg}',
-                     'suggestion': 'Try uploading a longer document or combine multiple documents.'
-                 }), 400 # 400 Bad Request - client error
+            # If caching fails due to small content, provide alternative approach
+            if "Cached content is too small" in str(cache_error):
+                return jsonify({
+                    'success': False, 
+                    'error': 'PDF is too small for caching. Please upload a larger document (minimum 4,096 tokens required).',
+                    'suggestion': 'Try uploading a longer document or combine multiple documents.'
+                })
             else:
-                # Re-raise other unexpected errors or return a generic error
-                 return jsonify({'success': False, 'error': f'Error creating cache with Gemini API: {error_msg}'}), 500
-
-
+                raise cache_error
+        
     except Exception as e:
-        print(f"An unexpected error occurred during upload process: {str(e)}") # Log general errors
-        return jsonify({'success': False, 'error': str(e)}), 500
+        return jsonify({'success': False, 'error': str(e)})
 
 @app.route('/upload-url', methods=['POST'])
 def upload_from_url():
-    if client is None or api_key is None:
-         return jsonify({'success': False, 'error': 'API key not configured or Gemini client failed to initialize.'}), 500
-
     try:
         data = request.get_json()
         url = data.get('url')
-
+        
         if not url:
-            return jsonify({'success': False, 'error': 'No URL provided'}), 400 # 400 Bad Request
-
+            return jsonify({'success': False, 'error': 'No URL provided'})
+        
         # Download file from URL
-        response = None
-        try:
-            # Use stream=True for potentially large files, although httpx handles it well.
-            # Add a timeout to prevent hanging on unresponsive URLs.
-            response = httpx.get(url, follow_redirects=True, timeout=30.0)
-            response.raise_for_status() # Raise HTTPError for bad responses (4xx or 5xx)
-
-             # Basic check for PDF mime type (optional but good practice)
-            content_type = response.headers.get('Content-Type', '').lower()
-            if 'application/pdf' not in content_type:
-                 print(f"Warning: URL content type is not application/pdf: {content_type}")
-                 # Decide if you want to block non-PDFs or try to upload anyway
-                 # For now, we'll proceed but log a warning. API might reject it.
-                 # If strictly PDF required, return an error here:
-                 # return jsonify({'success': False, 'error': f'URL does not point to a PDF document (Content-Type: {content_type})'}), 415 # 415 Unsupported Media Type
-
-
-        except httpx.HTTPStatusError as e:
-             print(f"HTTP error downloading file from URL {url}: {e.response.status_code} - {e.response.text}")
-             return jsonify({'success': False, 'error': f'HTTP error downloading file from URL: {e.response.status_code} - {e.response.text}'}), e.response.status_code
-        except httpx.RequestError as e:
-             print(f"Error downloading file from URL {url}: {e}")
-             return jsonify({'success': False, 'error': f'Error downloading file from URL: {e}'}), 500
-
-
+        response = httpx.get(url)
+        response.raise_for_status()
+        
         file_io = io.BytesIO(response.content)
-
-        # --- CORRECTED FILE UPLOAD CALL ---
-        # Upload to Gemini File API using the correct method client.upload_file
-        # Pass the file content as a tuple (filename, file-like object, mime_type)
-        # Use a generic filename for the file-like object if none derived from URL
-        document = None # Initialize document variable
-        try:
-            # Attempt to get filename from URL or headers, otherwise use generic
-            filename = os.path.basename(url)
-            if not filename or '.' not in filename:
-                 filename = 'downloaded_document.pdf' # Default generic name
-
-            # Use the mime type from the response headers if available and looks right
-            mime_type = content_type if 'application/pdf' in content_type else 'application/pdf'
-
-
-            document = client.upload_file(
-                file=(filename, file_io, mime_type), # Use parsed filename and mime_type
-                display_name=url # Use the URL as display name in Gemini API
-            )
-            print(f"File from URL uploaded successfully to Gemini File API: {document.name}") # Log
-             # Note: client.upload_file returns a google.generativeai.types.File object
-             # which contains the resource name (e.g., 'files/xyz123').
-
-        except Exception as upload_error:
-             # Attempt to provide more specific feedback if possible
-             error_msg = str(upload_error)
-             print(f"Error uploading file from URL to Gemini API: {error_msg}")
-             # Check for common upload errors like exceeding file size limits
-             if "file content size exceeds limit" in error_msg.lower():
-                  return jsonify({'success': False, 'error': f'Error uploading file: File size exceeds API limit. {error_msg}'}), 413 # 413 Payload Too Large
-             return jsonify({'success': False, 'error': f'Error uploading file from URL to Gemini API: {error_msg}'}), 500
-        # --- END CORRECTED FILE UPLOAD CALL ---
-
-
+        
+        # Upload to Gemini File API
+        document = client.files.upload(
+            file=file_io,
+            config=dict(mime_type='application/pdf')
+        )
+        
         # Create cache with system instruction
-        cache = None # Initialize cache variable
         try:
             system_instruction = "You are an expert document analyzer. Provide detailed, accurate answers based on the uploaded document content. Always be helpful and thorough in your responses."
-
+            
             # Use the correct model format as per documentation
             model = 'models/gemini-2.0-flash-001'
-
-            print(f"Attempting to create cache for file: {document.name}") # Log
+            
             cache = client.caches.create(
                 model=model,
                 config=types.CreateCachedContentConfig(
-                    display_name=f'pdf document cache: {url}', # Use URL in display_name for cache
+                    display_name='pdf document cache',
                     system_instruction=system_instruction,
-                    contents=[document], # contents should be a list containing the File object
-                    ttl="3600s",  # 1 hour TTL. Use string format like "300s" or "1h".
+                    contents=[document],
+                    ttl="3600s",  # 1 hour TTL
                 )
             )
-            print(f"Cache created successfully: {cache.name}") # Log
-
-
-            # Store cache info in our in-memory dictionary
-            # We map our internal UUID cache_id to the Gemini API's cache.name (resource name)
+            
+            # Store cache info
             cache_id = str(uuid.uuid4())
             document_caches[cache_id] = {
-                'gemini_cache_name': cache.name, # Store the Gemini API resource name
-                'document_name': url, # Store the URL as the document name
-                'gemini_file_name': document.name, # Also store the Gemini File API resource name for cleanup
-                'created_at': datetime.now().isoformat(),
-                 'expires_at': (datetime.now(timezone.utc) + timedelta(seconds=3600)).isoformat(), # Store expiry time for reference
+                'cache_name': cache.name,
+                'document_name': url,
+                'created_at': datetime.now().isoformat()
             }
-
-            # Get token count from cache metadata if available
-            token_count = 'Unknown'
-            if hasattr(cache, 'usage_metadata') and cache.usage_metadata:
-                 token_count = getattr(cache.usage_metadata, 'cached_token_count', 'Unknown')
-                 print(f"Cached token count: {token_count}")
-
-
+            
             return jsonify({
                 'success': True,
-                'cache_id': cache_id, # Return our internal ID
-                'token_count': token_count
+                'cache_id': cache_id,
+                'token_count': getattr(cache.usage_metadata, 'cached_token_count', 'Unknown')
             })
-
+            
         except Exception as cache_error:
-            error_msg = str(cache_error)
-            print(f"Cache creation failed: {error_msg}") # Log the cache error
-            # If caching fails, attempt to delete the uploaded file to clean up.
-            if document and hasattr(document, 'name'):
-                 try:
-                     client.files.delete(document.name)
-                     print(f"Cleaned up uploaded file {document.name} after caching failure.")
-                 except Exception as cleanup_error:
-                      print(f"Failed to clean up file {document.name}: {cleanup_error}")
-
-            # Handle specific cache creation errors
-            if "Cached content is too small" in error_msg or "minimum size" in error_msg.lower() or "tokens required" in error_msg.lower():
-                 return jsonify({
-                     'success': False,
-                     'error': f'PDF content is too small for caching. Minimum token count varies by model, but is typically 1024+ for Flash. {error_msg}',
-                     'suggestion': 'Try uploading a longer document or combine multiple documents.'
-                 }), 400 # 400 Bad Request - client error
+            # If caching fails due to small content, provide alternative approach
+            if "Cached content is too small" in str(cache_error):
+                return jsonify({
+                    'success': False, 
+                    'error': 'PDF is too small for caching. Please upload a larger document (minimum 4,096 tokens required).',
+                    'suggestion': 'Try uploading a longer document or combine multiple documents.'
+                })
             else:
-                # Re-raise other unexpected errors or return a generic error
-                 return jsonify({'success': False, 'error': f'Error creating cache with Gemini API: {error_msg}'}), 500
-
-
+                raise cache_error
+        
     except Exception as e:
-        print(f"An unexpected error occurred during URL upload process: {str(e)}") # Log general errors
-        return jsonify({'success': False, 'error': str(e)}), 500
-
+        return jsonify({'success': False, 'error': str(e)})
 
 @app.route('/ask', methods=['POST'])
 def ask_question():
-    if client is None or api_key is None:
-         return jsonify({'success': False, 'error': 'API key not configured or Gemini client failed to initialize.'}), 500
-
     try:
         data = request.get_json()
         question = data.get('question')
         cache_id = data.get('cache_id')
-
+        
         if not question or not cache_id:
-            return jsonify({'success': False, 'error': 'Missing question or cache_id'}), 400 # 400 Bad Request
-
-        # --- CORRECTED CACHE LOOKUP ---
-        # Check if our internal cache_id exists in the in-memory dictionary
+            return jsonify({'success': False, 'error': 'Missing question or cache_id'})
+        
         if cache_id not in document_caches:
-            # If not found, it's either an invalid ID, expired, or the server restarted.
-            # For this simple demo, we treat it as unavailable.
-            print(f"Cache ID {cache_id} not found in local storage.")
-            return jsonify({'success': False, 'error': 'Cache not found or expired. Please upload the document again.'}), 404 # 404 Not Found
-
-        # If found, retrieve the Gemini API cache name
+            return jsonify({'success': False, 'error': 'Cache not found'})
+        
         cache_info = document_caches[cache_id]
-        gemini_cache_name = cache_info['gemini_cache_name']
-        print(f"Using Gemini cache name: {gemini_cache_name} for question.")
-        # --- END CORRECTED CACHE LOOKUP ---
-
+        
         # Generate response using cached content with correct model format
         response = client.models.generate_content(
-            model='models/gemini-2.0-flash-001', # Ensure using the model the cache was created with
-            contents=[{'text': question}], # User's question as text content part
-            generation_config=types.GenerateContentConfig(
-                cached_content=gemini_cache_name # Use the retrieved Gemini cache name
+            model='models/gemini-2.0-flash-001',
+            contents=question,
+            config=types.GenerateContentConfig(
+                cached_content=cache_info['cache_name']
             )
         )
-
-        # Check if response has parts before accessing .text
-        answer = "Could not generate response from the model."
-        if response and response.candidates:
-            # Handle potential tool_code or other non-text parts if necessary
-            answer_parts = []
-            for candidate in response.candidates:
-                if candidate.content and candidate.content.parts:
-                    for part in candidate.content.parts:
-                        if hasattr(part, 'text'):
-                             answer_parts.append(part.text)
-                        # Add handling for other part types if needed (e.g., tool_code, function_response)
-                        # elif hasattr(part, 'tool_code'):
-                        #      answer_parts.append(f"\n```tool_code\n{part.tool_code.code}\n```\n")
-                        # elif hasattr(part, 'function_response'):
-                        #      answer_parts.append(f"\n```function_response\n{json.dumps(part.function_response, indent=2)}\n```\n")
-            if answer_parts:
-                 answer = "".join(answer_parts)
-            else:
-                 # Handle cases where candidates exist but have no text parts (e.g., tool calls)
-                 answer = "Model returned content without text parts (e.g., tool calls)."
-                 print(f"Model returned non-text parts: {response.candidates}") # Log for debugging
-
-        elif response and response.prompt_feedback and response.prompt_feedback.block_reason:
-             # Handle cases where the prompt was blocked
-             block_reason = response.prompt_feedback.block_reason.name
-             block_message = getattr(response.prompt_feedback, 'block_reason_message', 'No message provided')
-             answer = f"Request blocked by safety filters. Reason: {block_reason}. Message: {block_message}"
-             print(f"Request blocked: {block_reason} - {block_message}")
-
-        else:
-             # Handle other unexpected response structures
-             print(f"Unexpected response structure from API: {response}")
-             # answer stays as the initial "Could not generate response..." message
-
+        
         return jsonify({
             'success': True,
-            'answer': answer
+            'answer': response.text
         })
-
+        
     except Exception as e:
-        print(f"An error occurred during question asking: {str(e)}") # Log errors
-        # Attempt to provide more specific API error messages
-        error_msg = str(e)
-        if "Resource has been exhausted" in error_msg:
-             error_msg = "API rate limit or quota exceeded. Please try again later."
-        elif "cached_content refers to a resource that has been deleted" in error_msg:
-             error_msg = "The cached document has expired or was deleted from Gemini API. Please upload the document again."
-             # Clean up local entry if API confirms deletion/expiry
-             if cache_id in document_caches:
-                  print(f"Removing local entry for cache_id {cache_id} as API confirmed deletion.")
-                  del document_caches[cache_id]
-        elif "invalid cached_content value" in error_msg:
-             error_msg = "Invalid cache reference. The cached document might have expired or been deleted. Please upload the document again."
-             # Clean up local entry if API confirms deletion/expiry
-             if cache_id in document_caches:
-                  print(f"Removing local entry for cache_id {cache_id} as API confirmed deletion (invalid reference).")
-                  del document_caches[cache_id]
-        elif "model does not exist" in error_msg:
-             error_msg = "The specified model is not available."
-
-
-        return jsonify({'success': False, 'error': f'Error from Gemini API: {error_msg}'}), 500 # 500 Internal Server Error
-
+        return jsonify({'success': False, 'error': str(e)})
 
 @app.route('/caches', methods=['GET'])
 def list_caches():
-    # Lists caches stored *in this application's memory*.
-    # It does NOT list caches directly from the Gemini API unless you add that logic.
     try:
         caches = []
-        for cache_id, cache_info in list(document_caches.items()): # Use list() to iterate safely if modification occurs during iteration
-             # Optional: Check if the cache still exists in Gemini API before listing
-             # This adds complexity and potential API calls, so skipping for simple demo
-             try:
-                  # Attempt to get cache metadata from API to confirm existence/details
-                  api_cache_info = client.caches.get(name=cache_info['gemini_cache_name'])
-                  # If successful, add to list
-                  caches.append({
-                       'cache_id': cache_id, # Our internal ID
-                       'document_name': cache_info['document_name'],
-                       'gemini_cache_name': cache_info['gemini_cache_name'], # Include Gemini name
-                       'created_at': cache_info['created_at'],
-                       'expires_at': getattr(api_cache_info, 'expire_time', 'Unknown'), # Get actual expiry from API
-                       'cached_token_count': getattr(api_cache_info.usage_metadata, 'cached_token_count', 'Unknown') if hasattr(api_cache_info, 'usage_metadata') else 'Unknown'
-                  })
-             except Exception as e:
-                  # If API lookup fails (e.g., cache expired/deleted), remove from our local map
-                  print(f"Gemini cache {cache_info['gemini_cache_name']} for local ID {cache_id} not found via API. Removing from local storage. Error: {e}")
-                  del document_caches[cache_id]
-                  # Don't add it to the list of active caches
-
+        for cache_id, cache_info in document_caches.items():
+            caches.append({
+                'cache_id': cache_id,
+                'document_name': cache_info['document_name'],
+                'created_at': cache_info['created_at']
+            })
+        
         return jsonify({'success': True, 'caches': caches})
-
+        
     except Exception as e:
-        print(f"An error occurred listing caches: {str(e)}")
         return jsonify({'success': False, 'error': str(e)})
 
-
 @app.route('/cache/<cache_id>', methods=['DELETE'])
 def delete_cache(cache_id):
-    if client is None or api_key is None:
-         return jsonify({'success': False, 'error': 'API key not configured or Gemini client failed to initialize.'}), 500
-
     try:
         if cache_id not in document_caches:
-            return jsonify({'success': False, 'error': 'Cache not found'}), 404 # 404 Not Found
-
+            return jsonify({'success': False, 'error': 'Cache not found'})
+        
         cache_info = document_caches[cache_id]
-        gemini_cache_name_to_delete = cache_info['gemini_cache_name']
-        gemini_file_name_to_delete = cache_info['gemini_file_name']
-
-
-        # Delete from Gemini API Cache Service
-        try:
-            client.caches.delete(gemini_cache_name_to_delete)
-            print(f"Gemini cache deleted: {gemini_cache_name_to_delete}") # Log
-        except Exception as delete_error:
-             error_msg = str(delete_error)
-             print(f"Error deleting Gemini cache {gemini_cache_name_to_delete}: {error_msg}") # Log
-             # Handle case where the cache was already gone (e.g. expired)
-             if "Resource not found" in error_msg:
-                  print(f"Gemini cache {gemini_cache_name_to_delete} already gone from API.")
-             else:
-                  # For other errors, you might want to stop and return the error
-                  return jsonify({'success': False, 'error': f'Failed to delete cache from API: {error_msg}'}), 500
-
-
-        # Also delete the associated file from Gemini File API to free up storage
-        if gemini_file_name_to_delete:
-             try:
-                 client.files.delete(gemini_file_name_to_delete)
-                 print(f"Associated Gemini file deleted: {gemini_file_name_to_delete}") # Log
-             except Exception as file_delete_error:
-                 error_msg = str(file_delete_error)
-                 print(f"Error deleting Gemini file {gemini_file_name_to_delete}: {error_msg}") # Log
-                 if "Resource not found" in error_msg:
-                      print(f"Gemini file {gemini_file_name_to_delete} already gone from API.")
-                 else:
-                      # Log but continue, deleting the cache is the primary goal
-                      pass
-
-
-        # Remove from local storage *after* attempting API deletion
+        
+        # Delete from Gemini API
+        client.caches.delete(cache_info['cache_name'])
+        
+        # Remove from local storage
         del document_caches[cache_id]
-        print(f"Local cache entry deleted for ID: {cache_id}") # Log
-
-        return jsonify({'success': True, 'message': 'Cache and associated file deleted successfully'})
-
+        
+        return jsonify({'success': True, 'message': 'Cache deleted successfully'})
+        
     except Exception as e:
-        print(f"An unexpected error occurred during cache deletion process: {str(e)}") # Log
-        return jsonify({'success': False, 'error': str(e)}), 500
-
+        return jsonify({'success': False, 'error': str(e)})
 
 if __name__ == '__main__':
     import os
     port = int(os.environ.get("PORT", 7860))
-    print(f"Starting Flask app on port {port}") # Log start
-    # In production, set debug=False
-    # Use threaded=True or a production WSGI server (like Gunicorn) for concurrent requests
-    app.run(debug=True, host='0.0.0.0', port=port, threaded=True)
+    app.run(debug=True, host='0.0.0.0', port=port)