Update app.py

app.py

@@ -6,9 +6,14 @@ import re
 import struct
 import tempfile
 import asyncio
+import logging
 from google import genai
 from google.genai import types
 
+# Configure logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
 # Direct API key - WARNING: This is not recommended for production use
 GEMINI_API_KEY = "AIzaSyDy5hjn9NFamWhBjqsVsD2WSoFNr2MrHSw"
 
@@ -76,267 +81,324 @@ def parse_audio_mime_type(mime_type: str) -> dict[str, int | None]:
 
 def fetch_web_content(url, progress=gr.Progress()):
     """Fetch and analyze web content using Gemini with tools."""
-    progress(0.1, desc="Initializing Gemini client...")
-    
-    if not GEMINI_API_KEY:
-        raise ValueError("GEMINI_API_KEY is not set")
-    
-    client = genai.Client(api_key=GEMINI_API_KEY)
-    
-    progress(0.2, desc="Fetching web content...")
+    try:
+        progress(0.1, desc="Initializing Gemini client...")
+        logger.info("Initializing Gemini client...")
+        
+        if not GEMINI_API_KEY:
+            raise ValueError("GEMINI_API_KEY is not set")
+        
+        client = genai.Client(api_key=GEMINI_API_KEY)
+        
+        progress(0.2, desc="Fetching web content...")
+        logger.info(f"Fetching content from URL: {url}")
 
-    model = "gemini-2.5-flash-preview-04-17"
-    contents = [
-        types.Content(
-            role="user",
-            parts=[
-                types.Part.from_text(text=f"""Please analyze the content from this URL: {url}
-                
-                Create a comprehensive summary that would be suitable for a podcast discussion between two hosts. 
-                Focus on the key points, interesting aspects, and discussion-worthy topics.
-                
-                Format your response as a natural conversation between two podcast hosts discussing the content."""),
-            ],
-        ),
-    ]
-    
-    tools = [
-        types.Tool(url_context=types.UrlContext()),
-        types.Tool(google_search=types.GoogleSearch()),
-    ]
-    
-    generate_content_config = types.GenerateContentConfig(
-        tools=tools,
-        response_mime_type="text/plain",
-    )
+        model = "gemini-2.5-flash-preview-04-17"
+        contents = [
+            types.Content(
+                role="user",
+                parts=[
+                    types.Part.from_text(text=f"""Please analyze the content from this URL: {url}
+                    
+                    Create a comprehensive summary that would be suitable for a podcast discussion between two hosts. 
+                    Focus on the key points, interesting aspects, and discussion-worthy topics.
+                    
+                    Format your response as a natural conversation between two podcast hosts discussing the content."""),
+                ],
+            ),
+        ]
+        
+        tools = [
+            types.Tool(url_context=types.UrlContext()),
+            types.Tool(google_search=types.GoogleSearch()),
+        ]
+        
+        generate_content_config = types.GenerateContentConfig(
+            tools=tools,
+            response_mime_type="text/plain",
+        )
 
-    progress(0.4, desc="Analyzing content with AI...")
-    
-    content_text = ""
-    for chunk in client.models.generate_content_stream(
-        model=model,
-        contents=contents,
-        config=generate_content_config,
-    ):
-        content_text += chunk.text
-    
-    progress(0.6, desc="Content analysis complete!")
-    return content_text
+        progress(0.4, desc="Analyzing content with AI...")
+        logger.info("Generating content with Gemini...")
+        
+        content_text = ""
+        for chunk in client.models.generate_content_stream(
+            model=model,
+            contents=contents,
+            config=generate_content_config,
+        ):
+            if chunk.text:
+                content_text += chunk.text
+        
+        progress(0.6, desc="Content analysis complete!")
+        logger.info(f"Content generation complete. Length: {len(content_text)} characters")
+        return content_text
+        
+    except Exception as e:
+        logger.error(f"Error in fetch_web_content: {e}")
+        raise e
 
 
 def generate_podcast_from_content(content_text, speaker1_name="Anna Chope", speaker2_name="Adam Chan", progress=gr.Progress()):
     """Generate audio podcast from text content."""
-    progress(0.7, desc="Generating podcast audio...")
-    
-    if not GEMINI_API_KEY:
-        raise ValueError("GEMINI_API_KEY is not set")
-    
-    client = genai.Client(api_key=GEMINI_API_KEY)
+    try:
+        progress(0.7, desc="Generating podcast audio...")
+        logger.info("Starting audio generation...")
+        
+        if not GEMINI_API_KEY:
+            raise ValueError("GEMINI_API_KEY is not set")
+        
+        client = genai.Client(api_key=GEMINI_API_KEY)
 
-    model = "gemini-2.5-flash-preview-tts"
-    
-    podcast_prompt = f"""Please read aloud the following content in a natural podcast interview style with two distinct speakers. 
-    Make it sound conversational and engaging:
+        model = "gemini-2.5-flash-preview-tts"
+        
+        podcast_prompt = f"""Please read aloud the following content in a natural podcast interview style with two distinct speakers. 
+        Make it sound conversational and engaging:
 
-    {content_text}
-    
-    If the content is not already in dialogue format, please convert it into a natural conversation between two podcast hosts Speaker 1 {speaker1_name} and Speaker 2 {speaker2_name} discussing the topic. They should introduce themselves at the beginning."""
+        {content_text}
+        
+        If the content is not already in dialogue format, please convert it into a natural conversation between two podcast hosts Speaker 1 {speaker1_name} and Speaker 2 {speaker2_name} discussing the topic. They should introduce themselves at the beginning."""
 
-    contents = [
-        types.Content(
-            role="user",
-            parts=[
-                types.Part.from_text(text=podcast_prompt),
+        contents = [
+            types.Content(
+                role="user",
+                parts=[
+                    types.Part.from_text(text=podcast_prompt),
+                ],
+            ),
+        ]
+        
+        generate_content_config = types.GenerateContentConfig(
+            temperature=1,
+            response_modalities=[
+                "audio",
             ],
-        ),
-    ]
-    
-    generate_content_config = types.GenerateContentConfig(
-        temperature=1,
-        response_modalities=[
-            "audio",
-        ],
-        speech_config=types.SpeechConfig(
-            multi_speaker_voice_config=types.MultiSpeakerVoiceConfig(
-                speaker_voice_configs=[
-                    types.SpeakerVoiceConfig(
-                        speaker="Speaker 1",
-                        voice_config=types.VoiceConfig(
-                            prebuilt_voice_config=types.PrebuiltVoiceConfig(
-                                voice_name="Zephyr"
-                            )
+            speech_config=types.SpeechConfig(
+                multi_speaker_voice_config=types.MultiSpeakerVoiceConfig(
+                    speaker_voice_configs=[
+                        types.SpeakerVoiceConfig(
+                            speaker="Speaker 1",
+                            voice_config=types.VoiceConfig(
+                                prebuilt_voice_config=types.PrebuiltVoiceConfig(
+                                    voice_name="Zephyr"
+                                )
+                            ),
                         ),
-                    ),
-                    types.SpeakerVoiceConfig(
-                        speaker="Speaker 2",
-                        voice_config=types.VoiceConfig(
-                            prebuilt_voice_config=types.PrebuiltVoiceConfig(
-                                voice_name="Puck"
-                            )
+                        types.SpeakerVoiceConfig(
+                            speaker="Speaker 2",
+                            voice_config=types.VoiceConfig(
+                                prebuilt_voice_config=types.PrebuiltVoiceConfig(
+                                    voice_name="Puck"
+                                )
+                            ),
                         ),
-                    ),
-                ]
+                    ]
+                ),
             ),
-        ),
-    )
+        )
 
-    progress(0.8, desc="Converting to audio...")
-    
-    # Create temporary file
-    temp_file = tempfile.NamedTemporaryFile(delete=False, suffix=".wav")
-    temp_file.close()
-    
-    audio_chunks = []
-    
-    for chunk in client.models.generate_content_stream(
-        model=model,
-        contents=contents,
-        config=generate_content_config,
-    ):
-        if (
-            chunk.candidates is None
-            or chunk.candidates[0].content is None
-            or chunk.candidates[0].content.parts is None
+        progress(0.8, desc="Converting to audio...")
+        logger.info("Generating audio stream...")
+        
+        # Create temporary file
+        temp_file = tempfile.NamedTemporaryFile(delete=False, suffix=".wav")
+        temp_file.close()
+        
+        audio_chunks = []
+        
+        for chunk in client.models.generate_content_stream(
+            model=model,
+            contents=contents,
+            config=generate_content_config,
         ):
-            continue
-            
-        if (chunk.candidates[0].content.parts[0].inline_data and 
-            chunk.candidates[0].content.parts[0].inline_data.data):
-            
-            inline_data = chunk.candidates[0].content.parts[0].inline_data
-            data_buffer = inline_data.data
-            
-            # Convert to WAV if needed
-            if inline_data.mime_type != "audio/wav":
-                data_buffer = convert_to_wav(inline_data.data, inline_data.mime_type)
+            if (
+                chunk.candidates is None
+                or chunk.candidates[0].content is None
+                or chunk.candidates[0].content.parts is None
+            ):
+                continue
+                
+            if (chunk.candidates[0].content.parts[0].inline_data and 
+                chunk.candidates[0].content.parts[0].inline_data.data):
+                
+                inline_data = chunk.candidates[0].content.parts[0].inline_data
+                data_buffer = inline_data.data
+                
+                # Convert to WAV if needed
+                if inline_data.mime_type != "audio/wav":
+                    data_buffer = convert_to_wav(inline_data.data, inline_data.mime_type)
+                
+                audio_chunks.append(data_buffer)
+        
+        # Combine all audio chunks
+        if audio_chunks:
+            # For simplicity, just use the first chunk (you might want to concatenate them)
+            final_audio = audio_chunks[0]
+            save_binary_file(temp_file.name, final_audio)
+            progress(1.0, desc="Podcast generated successfully!")
+            logger.info(f"Audio file saved: {temp_file.name}")
+            return temp_file.name
+        else:
+            raise ValueError("No audio data generated")
             
-            audio_chunks.append(data_buffer)
-    
-    # Combine all audio chunks
-    if audio_chunks:
-        # For simplicity, just use the first chunk (you might want to concatenate them)
-        final_audio = audio_chunks[0]
-        save_binary_file(temp_file.name, final_audio)
-        progress(1.0, desc="Podcast generated successfully!")
-        return temp_file.name
-    else:
-        raise ValueError("No audio data generated")
+    except Exception as e:
+        logger.error(f"Error in generate_podcast_from_content: {e}")
+        raise e
 
 
 def generate_web_podcast(url, speaker1_name, speaker2_name, progress=gr.Progress()):
     """Main function to fetch web content and generate podcast."""
     try:
         progress(0.0, desc="Starting podcast generation...")
+        logger.info(f"Starting podcast generation for URL: {url}")
+        
+        # Validate inputs
+        if not url or not url.strip():
+            raise ValueError("Please enter a valid URL")
         
-        # Validate URL
-        if not url or not url.startswith(('http://', 'https://')):
+        if not url.startswith(('http://', 'https://')):
             raise ValueError("Please enter a valid URL starting with http:// or https://")
         
+        if not speaker1_name or not speaker1_name.strip():
+            speaker1_name = "Anna Chope"
+        
+        if not speaker2_name or not speaker2_name.strip():
+            speaker2_name = "Adam Chan"
+        
         # Step 1: Fetch and analyze web content
-        content_text = fetch_web_content(url, progress)
+        content_text = fetch_web_content(url.strip(), progress)
+        
+        if not content_text or len(content_text.strip()) < 50:
+            raise ValueError("Unable to extract sufficient content from the URL")
         
         # Step 2: Generate podcast from the content
-        audio_file = generate_podcast_from_content(content_text, speaker1_name, speaker2_name, progress)
+        audio_file = generate_podcast_from_content(content_text, speaker1_name.strip(), speaker2_name.strip(), progress)
         
+        logger.info("Podcast generation completed successfully")
         return audio_file, "✅ Podcast generated successfully!", content_text
         
     except Exception as e:
         error_msg = f"❌ Error generating podcast: {str(e)}"
+        logger.error(f"Error in generate_web_podcast: {e}")
         return None, error_msg, ""
 
 
 # Create Gradio interface
 def create_interface():
-    with gr.Blocks(title="🎙️ Web-to-Podcast Generator", theme=gr.themes.Soft()) as demo:
-        gr.Markdown("""
-        # 🎙️ Web-to-Podcast Generator
-        
-        Transform any website into an engaging podcast conversation between two AI hosts!
-        
-        Simply paste a URL and let AI create a natural dialogue discussing the content.
-        """)
-        
-        with gr.Row():
-            with gr.Column(scale=2):
-                url_input = gr.Textbox(
-                    label="Website URL",
-                    placeholder="https://example.com",
-                    info="Enter the URL of the website you want to convert to a podcast"
-                )
-                
-                with gr.Row():
-                    speaker1_input = gr.Textbox(
-                        label="Host 1 Name",
-                        value="Anna Chope",
-                        info="Name of the first podcast host"
-                    )
-                    speaker2_input = gr.Textbox(
-                        label="Host 2 Name", 
-                        value="Adam Chan",
-                        info="Name of the second podcast host"
+    try:
+        with gr.Blocks(
+            title="🎙️ Web-to-Podcast Generator", 
+            theme=gr.themes.Soft(),
+            analytics_enabled=False
+        ) as demo:
+            gr.Markdown("""
+            # 🎙️ Web-to-Podcast Generator
+            
+            Transform any website into an engaging podcast conversation between two AI hosts!
+            
+            Simply paste a URL and let AI create a natural dialogue discussing the content.
+            """)
+            
+            with gr.Row():
+                with gr.Column(scale=2):
+                    url_input = gr.Textbox(
+                        label="Website URL",
+                        placeholder="https://example.com",
+                        info="Enter the URL of the website you want to convert to a podcast",
+                        lines=1
                     )
-                
-                generate_btn = gr.Button("🎙️ Generate Podcast", variant="primary", size="lg")
-                
-            with gr.Column(scale=1):
-                gr.Markdown("""
-                ### Instructions:
-                1. Enter a website URL
-                2. Customize host names (optional)
-                3. Click "Generate Podcast"
-                4. Wait for the AI to analyze content and create audio
-                5. Download your podcast!
-                
-                ### Examples:
-                - News articles
-                - Blog posts
-                - Product pages
-                - Documentation
-                - Research papers
-                """)
-        
-        with gr.Row():
-            status_output = gr.Textbox(label="Status", interactive=False)
-        
-        with gr.Row():
-            audio_output = gr.Audio(label="Generated Podcast", type="filepath")
-        
-        with gr.Accordion("📝 Generated Script Preview", open=False):
-            script_output = gr.Textbox(
-                label="Podcast Script",
-                lines=10,
-                interactive=False,
-                info="Preview of the conversation script generated from the website content"
+                    
+                    with gr.Row():
+                        speaker1_input = gr.Textbox(
+                            label="Host 1 Name",
+                            value="Anna Chope",
+                            info="Name of the first podcast host",
+                            lines=1
+                        )
+                        speaker2_input = gr.Textbox(
+                            label="Host 2 Name", 
+                            value="Adam Chan",
+                            info="Name of the second podcast host",
+                            lines=1
+                        )
+                    
+                    generate_btn = gr.Button("🎙️ Generate Podcast", variant="primary", size="lg")
+                    
+                with gr.Column(scale=1):
+                    gr.Markdown("""
+                    ### Instructions:
+                    1. Enter a website URL
+                    2. Customize host names (optional)
+                    3. Click "Generate Podcast"
+                    4. Wait for the AI to analyze content and create audio
+                    5. Download your podcast!
+                    
+                    ### Examples:
+                    - News articles
+                    - Blog posts
+                    - Product pages
+                    - Documentation
+                    - Research papers
+                    """)
+            
+            with gr.Row():
+                status_output = gr.Textbox(label="Status", interactive=False, lines=2)
+            
+            with gr.Row():
+                audio_output = gr.Audio(label="Generated Podcast", type="filepath")
+            
+            with gr.Accordion("📝 Generated Script Preview", open=False):
+                script_output = gr.Textbox(
+                    label="Podcast Script",
+                    lines=10,
+                    interactive=False,
+                    info="Preview of the conversation script generated from the website content"
+                )
+            
+            # Event handlers
+            generate_btn.click(
+                fn=generate_web_podcast,
+                inputs=[url_input, speaker1_input, speaker2_input],
+                outputs=[audio_output, status_output, script_output],
+                show_progress=True
             )
+            
+            # Examples
+            gr.Examples(
+                examples=[
+                    ["https://github.com/weaviate/weaviate", "Anna", "Adam"],
+                    ["https://huggingface.co/blog", "Sarah", "Mike"],
+                    ["https://openai.com/blog", "Emma", "John"],
+                ],
+                inputs=[url_input, speaker1_input, speaker2_input],
+            )
+            
+            gr.Markdown("""
+            ---
+            **Note:** API key is now directly embedded in the code for convenience.
+            
+            The generated podcast will feature two AI voices having a natural conversation about the website content.
+            """)
         
-        # Event handlers
-        generate_btn.click(
-            fn=generate_web_podcast,
-            inputs=[url_input, speaker1_input, speaker2_input],
-            outputs=[audio_output, status_output, script_output],
-            show_progress=True
-        )
-        
-        # Examples
-        gr.Examples(
-            examples=[
-                ["https://github.com/weaviate/weaviate", "Anna", "Adam"],
-                ["https://huggingface.co/blog", "Sarah", "Mike"],
-                ["https://openai.com/blog", "Emma", "John"],
-            ],
-            inputs=[url_input, speaker1_input, speaker2_input],
-        )
-        
-        gr.Markdown("""
-        ---
-        **Note:** API key is now directly embedded in the code for convenience.
-        
-        The generated podcast will feature two AI voices having a natural conversation about the website content.
-        """)
+        return demo
     
-    return demo
+    except Exception as e:
+        logger.error(f"Error creating interface: {e}")
+        raise e
 
 
 if __name__ == "__main__":
-    demo = create_interface()
-    demo.launch(debug=True)
+    try:
+        logger.info("Starting Web-to-Podcast Generator...")
+        demo = create_interface()
+        demo.launch(
+            server_name="0.0.0.0",
+            server_port=7860,
+            share=False,
+            debug=False,
+            show_error=True
+        )
+    except Exception as e:
+        logger.error(f"Failed to launch application: {e}")
+        print(f"Error: {e}")
+        raise e