Update app.py

app.py

@@ -4,8 +4,26 @@ import PyPDF2
 import re
 import os
 import io
-from google import genai
-from google.genai import types
+
+# Try different import methods for google genai
+try:
+    from google import genai
+    from google.genai import types
+    print("✅ Imported google.genai successfully")
+except ImportError:
+    try:
+        import google.genai as genai
+        from google.genai import types
+        print("✅ Imported google.genai as module")
+    except ImportError:
+        try:
+            from google_genai import genai
+            from google_genai import types
+            print("✅ Imported google_genai")
+        except ImportError as e:
+            print(f"❌ Failed to import google genai: {e}")
+            genai = None
+            types = None
 
 # Setup tokens
 hf_token = os.getenv("HF_TOKEN")
@@ -16,12 +34,26 @@ print(f"GEMINI_API_KEY: {gemini_key is not None}")
 
 # Configure Gemini client
 client = None
-if gemini_key:
+if gemini_key and genai:
     try:
-        client = genai.Client(api_key=gemini_key)
-        print("✅ Gemini client configured")
+        # Try different initialization methods
+        try:
+            client = genai.Client(api_key=gemini_key)
+        except:
+            try:
+                client = genai.client.Client(api_key=gemini_key)
+            except:
+                # Fallback to old SDK if available
+                import google.generativeai as old_genai
+                old_genai.configure(api_key=gemini_key)
+                client = old_genai
+                print("✅ Using legacy google.generativeai")
+        
+        if client:
+            print("✅ Gemini client configured")
     except Exception as e:
         print(f"❌ Gemini config error: {e}")
+        client = None
 
 # Lazy load summarizer
 summarizer = None
@@ -39,8 +71,10 @@ def load_summarizer():
 
 def check_status():
     if client:
-        return "✅ Gemini 2.5 Flash Ready"
-    return "❌ Add GEMINI_API_KEY to Space Settings"
+        return "✅ Gemini Ready"
+    elif gemini_key:
+        return "⚠️ Gemini key present but SDK not loaded"
+    return "❌ Add GEMINI_API_KEY"
 
 def extract_text_from_pdf(pdf_file):
     """Extract text from PDF - handle both file path and bytes"""
@@ -63,12 +97,17 @@ def extract_text_from_pdf(pdf_file):
             if hasattr(pdf_file, 'read'):
                 # File object - read bytes
                 pdf_bytes = pdf_file.read()
-                pdf_file.seek(0)  # Reset if possible
+                if hasattr(pdf_file, 'seek'):
+                    pdf_file.seek(0)  # Reset if possible
             else:
                 pdf_bytes = pdf_file
             
             # Create reader from bytes
-            pdf_stream = io.BytesIO(pdf_bytes) if isinstance(pdf_bytes, bytes) else io.BytesIO(pdf_bytes.encode())
+            if isinstance(pdf_bytes, bytes):
+                pdf_stream = io.BytesIO(pdf_bytes)
+            else:
+                pdf_stream = io.BytesIO(pdf_bytes.encode() if isinstance(pdf_bytes, str) else pdf_bytes)
+            
             pdf_reader = PyPDF2.PdfReader(pdf_stream)
             
             text = ""
@@ -87,24 +126,57 @@ def extract_text_from_pdf(pdf_file):
     except Exception as e:
         return None, f"Error reading PDF: {str(e)}"
 
+def summarize_with_gemini(text, max_length, min_length):
+    """Try to use Gemini for summarization"""
+    if not client or not gemini_key:
+        return None
+    
+    try:
+        # Try new SDK first
+        if hasattr(client, 'models'):
+            prompt = f"Summarize the following text in {min_length}-{max_length} words. Be concise and clear:\n\n{text[:15000]}"
+            
+            try:
+                response = client.models.generate_content(
+                    model="gemini-2.5-flash",
+                    contents=prompt
+                )
+                return response.text
+            except:
+                # Try with config
+                try:
+                    response = client.models.generate_content(
+                        model="gemini-2.5-flash",
+                        contents=prompt,
+                        config=types.GenerateContentConfig(
+                            max_output_tokens=500
+                        ) if types else None
+                    )
+                    return response.text
+                except:
+                    pass
+        
+        # Try legacy SDK
+        if hasattr(client, 'GenerativeModel'):
+            model = client.GenerativeModel('gemini-2.5-flash')
+            prompt = f"Summarize the following text in {min_length}-{max_length} words:\n\n{text[:15000]}"
+            response = model.generate_content(prompt)
+            return response.text
+            
+    except Exception as e:
+        print(f"Gemini summary error: {e}")
+    
+    return None
+
 def summarize_pdf(pdf_file, max_length, min_length):
     text, error = extract_text_from_pdf(pdf_file)
     if error:
         return error
     
-    # Use Gemini if available
-    if client:
-        try:
-            prompt = f"Summarize the following text in {min_length}-{max_length} words. Be concise and clear:\n\n{text[:15000]}"
-            
-            response = client.models.generate_content(
-                model="gemini-2.5-flash",
-                contents=prompt
-            )
-            
-            return response.text
-        except Exception as e:
-            print(f"Gemini summary error: {e}")
+    # Try Gemini first
+    gemini_result = summarize_with_gemini(text, max_length, min_length)
+    if gemini_result:
+        return gemini_result
     
     # Fallback to local
     summ = load_summarizer()
@@ -117,17 +189,10 @@ def summarize_pdf(pdf_file, max_length, min_length):
     
     return "Error: No summarization available"
 
-def generate_essay(prompt, essay_type, word_count, tone):
-    if not prompt or len(prompt.strip()) < 10:
-        return "Please provide a detailed prompt (at least 10 characters)."
-    
-    if not client:
-        return """❌ Gemini API key not configured.
-
-Get your free API key:
-1. Visit: https://aistudio.google.com/app/apikey
-2. Click "Create API Key"
-3. Add to Space Settings → Repository secrets as GEMINI_API_KEY"""
+def generate_essay_with_gemini(prompt, essay_type, word_count, tone):
+    """Generate essay using Gemini"""
+    if not client or not gemini_key:
+        return None
     
     try:
         full_prompt = f"""You are an expert academic writer. Write a {essay_type} essay in {tone} tone.
@@ -141,25 +206,33 @@ Requirements:
 - Well-structured body paragraphs with supporting arguments and evidence
 - Strong conclusion that summarizes main points
 - Use academic vocabulary and formal writing style
-- Ensure logical flow between paragraphs
 
 Write the essay now:"""
-
-        response = client.models.generate_content(
-            model="gemini-2.5-flash",
-            contents=full_prompt,
-            config=types.GenerateContentConfig(
-                temperature=0.7,
-                top_p=0.9,
-                max_output_tokens=min(word_count * 2, 2000)
-            )
-        )
         
-        essay = response.text.strip()
+        # Try new SDK
+        if hasattr(client, 'models'):
+            try:
+                response = client.models.generate_content(
+                    model="gemini-2.5-flash",
+                    contents=full_prompt
+                )
+                essay = response.text.strip()
+            except:
+                # Try with legacy
+                if hasattr(client, 'GenerativeModel'):
+                    model = client.GenerativeModel('gemini-2.5-flash')
+                    response = model.generate_content(full_prompt)
+                    essay = response.text.strip()
+                else:
+                    return None
+        else:
+            # Legacy SDK
+            model = client.GenerativeModel('gemini-2.5-flash')
+            response = model.generate_content(full_prompt)
+            essay = response.text.strip()
         
-        # Clean up any markdown headers if present
+        # Clean up
         essay = re.sub(r'^#+\s*', '', essay)
-        
         word_count_actual = len(essay.split())
         
         return f"""# {essay_type} Essay: {prompt[:50]}{'...' if len(prompt) > 50 else ''}
@@ -167,31 +240,49 @@ Write the essay now:"""
 {essay}
 
 ---
-*~{word_count_actual} words | {tone} tone | Generated with Gemini 2.5 Flash*
-
-Note: Please review and edit this AI-generated content before submission."""
+*~{word_count_actual} words | {tone} | Gemini*"""
         
     except Exception as e:
-        error_msg = str(e)
-        print(f"Essay generation error: {error_msg}")
-        return f"Error: {error_msg}"
+        print(f"Essay generation error: {e}")
+        return None
+
+def generate_essay(prompt, essay_type, word_count, tone):
+    if not prompt or len(prompt.strip()) < 10:
+        return "Please provide a detailed prompt (at least 10 characters)."
+    
+    # Try Gemini first
+    if client and gemini_key:
+        gemini_result = generate_essay_with_gemini(prompt, essay_type, word_count, tone)
+        if gemini_result:
+            return gemini_result
+    
+    # Template fallback
+    return f"""❌ AI generation not available.
+
+Template Essay: {prompt}
+
+Introduction:
+{prompt} is an important topic that requires careful consideration. This essay explores its key aspects.
+
+Body:
+The significance of {prompt} cannot be overstated. Various perspectives exist on this matter, with experts debating the best approaches. Research continues to reveal new insights.
+
+Conclusion:
+In conclusion, {prompt} represents a complex issue that demands attention.
+
+---
+*Template fallback - Gemini SDK issue*
+
+Check: 1) GEMINI_API_KEY is set 2) google-genai package is installed"""
 
 def summarize_text(text, max_length, min_length):
     if len(text.strip()) < 100:
         return "Please provide at least 100 characters to summarize."
     
-    if client:
-        try:
-            prompt = f"Summarize the following text in {min_length}-{max_length} words:\n\n{text[:15000]}"
-            
-            response = client.models.generate_content(
-                model="gemini-2.5-flash",
-                contents=prompt
-            )
-            
-            return response.text
-        except Exception as e:
-            print(f"Gemini text error: {e}")
+    # Try Gemini
+    gemini_result = summarize_with_gemini(text, max_length, min_length)
+    if gemini_result:
+        return gemini_result
     
     # Fallback
     summ = load_summarizer()
@@ -206,180 +297,51 @@ def summarize_text(text, max_length, min_length):
 
 # CSS
 custom_css = """
-.header { 
-    text-align: center; 
-    margin-bottom: 2rem; 
-    padding: 2rem;
-    background: linear-gradient(135deg, #059669 0%, #6b7280 100%);
-    border-radius: 12px;
-    color: white;
-}
-.header h1 { 
-    font-size: 2.5rem; 
-    margin-bottom: 0.5rem;
-}
-.header p {
-    font-size: 1.2rem;
-    opacity: 0.9;
-}
-.status-ok { 
-    background: #d1fae5; 
-    border: 2px solid #059669; 
-    padding: 1rem; 
-    border-radius: 8px; 
-    text-align: center; 
-    color: #065f46; 
-    font-weight: bold; 
-    margin-bottom: 1rem;
-}
-.status-warn { 
-    background: #fef3c7; 
-    border: 2px solid #f59e0b; 
-    padding: 1rem; 
-    border-radius: 8px; 
-    text-align: center; 
-    color: #92400e; 
-    margin-bottom: 1rem;
-}
-.info-box { 
-    background: #dbeafe; 
-    border-left: 4px solid #3b82f6; 
-    padding: 1rem; 
-    margin: 1rem 0; 
-    color: #1e40af;
-}
-.gemini-box { 
-    background: #e0e7ff; 
-    border-left: 4px solid #4f46e5; 
-    padding: 1rem; 
-    margin: 1rem 0; 
-    color: #3730a3;
-}
+.header { text-align: center; margin-bottom: 2rem; padding: 2rem; background: linear-gradient(135deg, #059669, #6b7280); border-radius: 12px; color: white; }
+.header h1 { font-size: 2.5rem; margin-bottom: 0.5rem; }
+.status-ok { background: #d1fae5; border: 2px solid #059669; padding: 1rem; border-radius: 8px; text-align: center; color: #065f46; font-weight: bold; margin-bottom: 1rem; }
+.status-warn { background: #fef3c7; border: 2px solid #f59e0b; padding: 1rem; border-radius: 8px; text-align: center; color: #92400e; margin-bottom: 1rem; }
+.status-error { background: #fee2e2; border: 2px solid #ef4444; padding: 1rem; border-radius: 8px; text-align: center; color: #991b1b; margin-bottom: 1rem; }
 """
 
-with gr.Blocks(title="Student AI Assistant - Gemini 2.5 Flash") as demo:
+with gr.Blocks(title="Student AI Assistant") as demo:
     
-    # Status check
     status = check_status()
     if "✅" in status:
         gr.HTML(f'<div class="status-ok">{status}</div>')
-    else:
+    elif "⚠️" in status:
         gr.HTML(f'<div class="status-warn">{status}</div>')
+    else:
+        gr.HTML(f'<div class="status-error">{status}</div>')
     
-    gr.HTML("""
-    <div class="header">
-        <h1>🎓 Student AI Assistant</h1>
-        <p>Powered by Google Gemini 2.5 Flash</p>
-    </div>
-    """)
-    
-    gr.HTML("""
-    <div class="gemini-box">
-        <strong>🚀 Gemini 2.5 Flash Features:</strong><br>
-        • High-quality essay generation with proper structure<br>
-        • Fast inference (typically 5-10 seconds)<br>
-        • 1 million token context window for long PDFs
-    </div>
-    """)
+    gr.HTML('<div class="header"><h1>🎓 Student AI Assistant</h1><p>Essay & PDF Tools</p></div>')
     
     with gr.Tabs():
         
         with gr.TabItem("📄 PDF Summarizer"):
+            pdf_input = gr.File(label="Upload PDF", file_types=[".pdf"], type="binary")
             with gr.Row():
-                with gr.Column():
-                    gr.Markdown("### Upload Document")
-                    pdf_input = gr.File(
-                        label="Upload PDF", 
-                        file_types=[".pdf"],
-                        type="binary"  # Changed from "filepath" to "binary"
-                    )
-                    with gr.Row():
-                        max_len = gr.Slider(50, 500, 200, step=10, label="Max Summary Length")
-                        min_len = gr.Slider(20, 200, 50, step=10, label="Min Summary Length")
-                    summarize_btn = gr.Button("📝 Summarize PDF", variant="primary")
-                
-                with gr.Column():
-                    gr.Markdown("### Summary Result")
-                    pdf_output = gr.Textbox(
-                        label="", 
-                        lines=12,
-                        placeholder="Your summary will appear here..."
-                    )
+                max_len = gr.Slider(50, 500, 200, step=10, label="Max Length")
+                min_len = gr.Slider(20, 200, 50, step=10, label="Min Length")
+            summarize_btn = gr.Button("📝 Summarize PDF", variant="primary")
+            pdf_output = gr.Textbox(label="Summary", lines=12)
             
             gr.Markdown("---")
-            gr.Markdown("### Or Paste Text Directly")
-            
-            text_input = gr.Textbox(
-                label="Paste your text here", 
-                lines=5,
-                placeholder="Paste lecture notes or any text to summarize..."
-            )
-            text_btn = gr.Button("Summarize Text", variant="secondary")
-            text_output = gr.Textbox(
-                label="Summary", 
-                lines=8,
-                placeholder="Summary will appear here..."
-            )
+            text_input = gr.Textbox(label="Or paste text", lines=5)
+            text_btn = gr.Button("Summarize Text")
+            text_output = gr.Textbox(label="Summary", lines=8)
         
         with gr.TabItem("✍️ Essay Generator"):
-            with gr.Row():
-                with gr.Column():
-                    gr.Markdown("### Essay Parameters")
-                    prompt_input = gr.Textbox(
-                        label="Essay Topic / Prompt", 
-                        placeholder="Example: 'The impact of artificial intelligence on modern healthcare'",
-                        lines=3
-                    )
-                    essay_type = gr.Dropdown(
-                        choices=["Argumentative", "Expository", "Descriptive", "Persuasive", "Analytical"],
-                        value="Argumentative",
-                        label="Essay Type"
-                    )
-                    tone = gr.Dropdown(
-                        choices=["Academic", "Formal", "Professional", "Neutral"],
-                        value="Academic",
-                        label="Writing Tone"
-                    )
-                    words = gr.Slider(200, 1000, 500, step=50, label="Target Word Count")
-                    gen_btn = gr.Button("✨ Generate Essay with Gemini", variant="primary")
-                
-                with gr.Column():
-                    gr.Markdown("### Generated Essay")
-                    essay_output = gr.Textbox(
-                        label="", 
-                        lines=25,
-                        placeholder="Your high-quality essay will appear here..."
-                    )
-    
-    gr.Markdown("""
-    ---
-    ### 💡 Tips for Best Results:
-    - **Be specific**: "The impact of social media on teenage mental health" → better than "Social media"
-    - **Use 300-600 words** for optimal quality
-    - **Review and edit** AI-generated content before submission
-    - **PDFs**: Ensure text is selectable (not scanned images)
-    
-    **Powered by Google Gemini 2.5 Flash**
-    """)
-    
-    # Event handlers
-    summarize_btn.click(
-        fn=summarize_pdf, 
-        inputs=[pdf_input, max_len, min_len], 
-        outputs=pdf_output
-    )
-    
-    text_btn.click(
-        fn=summarize_text, 
-        inputs=[text_input, max_len, min_len], 
-        outputs=text_output
-    )
+            prompt_input = gr.Textbox(label="Essay Topic", placeholder="Example: 'The impact of AI on education'", lines=3)
+            essay_type = gr.Dropdown(["Argumentative", "Expository", "Descriptive", "Persuasive"], value="Argumentative")
+            tone = gr.Dropdown(["Academic", "Formal", "Neutral"], value="Academic")
+            words = gr.Slider(200, 1000, 500, step=50, label="Word Count")
+            gen_btn = gr.Button("✨ Generate Essay", variant="primary")
+            essay_output = gr.Textbox(label="Generated Essay", lines=25)
     
-    gen_btn.click(
-        fn=generate_essay, 
-        inputs=[prompt_input, essay_type, words, tone], 
-        outputs=essay_output
-    )
+    summarize_btn.click(summarize_pdf, [pdf_input, max_len, min_len], pdf_output)
+    text_btn.click(summarize_text, [text_input, max_len, min_len], text_output)
+    gen_btn.click(generate_essay, [prompt_input, essay_type, words, tone], essay_output)
 
 if __name__ == "__main__":
     demo.launch(css=custom_css)