Update app.py

app.py

@@ -1,6 +1,252 @@
 import gradio as gr
-from src.interface import create_interface
+import pixeltable as pxt
+from pixeltable.iterators import DocumentSplitter
+from pixeltable.functions import openai
+import os
+import requests
+import tempfile
+
+def process_document(pdf_file, api_key, voice_choice, style_choice, chunk_size, temperature, max_tokens, progress=gr.Progress()):
+    try:
+        os.environ['OPENAI_API_KEY'] = api_key
+        
+        progress(0.1, desc="Initializing...")
+        pxt.drop_dir('document_audio', force=True)
+        pxt.create_dir('document_audio')
+        
+        docs = pxt.create_table(
+            'document_audio.documents',
+            {
+                'document': pxt.DocumentType(),
+                'voice': pxt.StringType(),
+                'style': pxt.StringType()
+            }
+        )
+        
+        progress(0.2, desc="Processing document...")
+        docs.insert([{
+            'document': pdf_file.name, 
+            'voice': voice_choice, 
+            'style': style_choice
+        }])
+        
+        chunks = pxt.create_view(
+            'document_audio.chunks',
+            docs,
+            iterator=DocumentSplitter.create(
+                document=docs.document,
+                separators='token_limit',
+                limit=chunk_size
+            )
+        )
+        
+        progress(0.4, desc="Text processing...")
+        chunks['content_response'] = openai.chat_completions(
+            messages=[
+                {
+                    'role': 'system',
+                    'content': """Transform this text segment into clear, concise content.
+                    Structure:
+                    1. Core concepts and points
+                    2. Supporting details
+                    3. Key takeaways"""
+                },
+                {'role': 'user', 'content': chunks.text}
+            ],
+            model='gpt-4o-mini-2024-07-18',
+            max_tokens=max_tokens,
+            temperature=temperature
+        )
+        chunks['content'] = chunks.content_response['choices'][0]['message']['content']
+
+        progress(0.6, desc="Script generation...")
+        chunks['script_response'] = openai.chat_completions(
+            messages=[
+                {
+                    'role': 'system',
+                    'content': f"""Convert content to audio script.
+                    Style: {docs.style}
+                    Format:
+                    - Clear sentence structures
+                    - Natural pauses (...)
+                    - Term definitions when needed
+                    - Proper transitions
+                    - Appropriate pronunciation guidance"""
+                },
+                {'role': 'user', 'content': chunks.content}
+            ],
+            model='gpt-4o-mini-2024-07-18',
+            max_tokens=max_tokens,
+            temperature=temperature
+        )
+        chunks['script'] = chunks.script_response['choices'][0]['message']['content']
+
+        progress(0.8, desc="Audio synthesis...")
+        @pxt.udf(return_type=pxt.AudioType())
+        def generate_audio(script: str, voice: str):
+            if not script or not voice:
+                return None
+            try:
+                response = requests.post(
+                    "https://api.openai.com/v1/audio/speech",
+                    headers={"Authorization": f"Bearer {api_key}"},
+                    json={"model": "tts-1", "input": script, "voice": voice}
+                )
+                if response.status_code == 200:
+                    temp_file = tempfile.NamedTemporaryFile(delete=False, suffix='.mp3')
+                    temp_file.write(response.content)
+                    temp_file.close()
+                    return temp_file.name
+            except Exception as e:
+                print(f"Error in audio synthesis: {e}")
+            return None
+
+        chunks['audio'] = generate_audio(chunks.script, docs.voice)
+        
+        audio_path = chunks.select(chunks.audio).tail(1)['audio'][0]
+        
+        results = chunks.select(chunks.content, chunks.script).collect()
+        
+        display_data = [
+            [f"Segment {idx + 1}", row['content'], row['script']]
+            for idx, row in enumerate(results)
+        ]
+        
+        progress(1.0, desc="Complete")
+        return display_data, audio_path, "Processing complete"
+        
+    except Exception as e:
+        return None, None, f"Error: {str(e)}"
+
+with gr.Blocks(theme=gr.themes.Base()) as demo:
+    gr.HTML(
+        """
+        <div style="margin-bottom: 1rem;">
+            <img src="https://raw.githubusercontent.com/pixeltable/pixeltable/main/docs/source/data/pixeltable-logo-large.png" 
+                 alt="Pixeltable" style="max-width: 150px;" />
+            <h1>📄 Document to Audio Synthesis 🎧</h1>
+        </div>
+        """
+    )
+
+    with gr.Row():
+        with gr.Column():
+            with gr.Accordion("🎯 What does it do?", open=False):
+                gr.Markdown("""
+                    1. ��� **Document Processing:** PDF extraction and token-based chunking
+                    2. 🤖 **Content Pipeline:** LLM-powered text optimization and script generation
+                    3. 🔊 **Audio Generation:** Neural TTS synthesis with voice modulation
+                """)
+        with gr.Column():
+            with gr.Accordion("⚡ How does it work?", open=False):
+                gr.Markdown("""
+                    1. 📑 **Segmentation:** Token-based document chunking with configurable limits
+                    2. 🔍 **Transformation:** Dual-pass LLM processing with temperature control
+                    3. 🎵 **Synthesis:** OpenAI TTS with multi-voice capability
+                """)
+
+    gr.HTML(
+        """
+        <div style="background-color: #FFF3CD; border: 1px solid #FFEEBA; padding: 1rem; margin: 1rem 0; border-radius: 4px;">
+            <p style="margin: 0; color: #856404;">
+                ⚠️ <strong>API Cost Notice:</strong> This application uses OpenAI's Text-to-Speech API which incurs costs per use. 
+                See <a href="https://platform.openai.com/docs/guides/text-to-speech" target="_blank" style="color: #856404; text-decoration: underline;">OpenAI's TTS Documentation</a> 
+                for current pricing information.
+            </p>
+        </div>
+        """
+    )
+
+    with gr.Row():
+        with gr.Column():
+            with gr.Accordion("🔑 Input & Voice", open=True):
+                api_key = gr.Textbox(
+                    label="OpenAI API Key",
+                    placeholder="sk-...",
+                    type="password"
+                )
+                file_input = gr.File(
+                    label="PDF Document",
+                    file_types=[".pdf"]
+                )
+        
+        with gr.Column():
+            with gr.Accordion("⚙️ Processing Configuration", open=True):
+                style_select = gr.Radio(
+                    choices=["Technical", "Narrative", "Instructional", "Descriptive"],
+                    value="Technical",
+                    label="💫 Style"
+                )
+                with gr.Row():
+                    voice_select = gr.Radio(
+                        choices=["alloy", "echo", "fable", "onyx", "nova", "shimmer"],
+                        value="onyx",
+                        label="🎙️ Voice Model"
+                    )
+                with gr.Row():
+                    chunk_size = gr.Slider(
+                        minimum=100, maximum=1000, value=300, step=50,
+                        label="📏 Chunk Size"
+                    )
+                    temperature = gr.Slider(
+                        minimum=0, maximum=1, value=0.7, step=0.1,
+                        label="🌡️ Temperature"
+                    )
+                    max_tokens = gr.Slider(
+                        minimum=100, maximum=1000, value=300, step=50,
+                        label="📊 Tokens"
+                    )
+                with gr.Row():
+                    process_btn = gr.Button("🚀 Generate Audio", variant="primary", scale=2)
+
+    with gr.Tabs():
+        with gr.TabItem("📝 Content"):
+            output_table = gr.Dataframe(
+                headers=["🔍 Segment", "📄 Content", "🎭 Script"],
+                wrap=True
+            )
+        with gr.TabItem("🎧 Audio"):
+            with gr.Row():
+                with gr.Column(scale=2):
+                    audio_output = gr.Audio(
+                        label="🔊 Generated Audio", 
+                        type="filepath",
+                        show_download_button=True
+                    )
+                with gr.Column(scale=1):
+                    with gr.Accordion("📚 Technical Notes", open=True):
+                        gr.Markdown("""
+                            - 🎯 Temperature < 0.5: Deterministic output
+                            - 📏 Chunk size affects token context
+                            - 🎙️ Voice models vary in prosody
+                            - 💰 API usage is billed per character
+                        """)
+
+    gr.HTML(
+        """
+        <div style="text-align: center; margin-top: 1rem; padding-top: 1rem; border-top: 1px solid #ccc;">
+            <p style="margin: 0; color: #666; font-size: 0.8em;">
+                🚀 Powered by <a href="https://github.com/pixeltable/pixeltable" target="_blank" style="color: #F25022; text-decoration: none;">Pixeltable</a>
+                | 📚 <a href="https://docs.pixeltable.io" target="_blank" style="color: #666;">Docs</a>
+                | 🤗 <a href="https://huggingface.co/spaces/Pixeltable/document-to-audio-synthesis" target="_blank" style="color: #666;">HF Space</a>
+            </p>
+        </div>
+        """
+    )
+    
+    def update_interface(pdf_file, api_key, voice, style, chunk_size, temperature, max_tokens):
+        return process_document(
+            pdf_file, api_key, voice, style, chunk_size, temperature, max_tokens
+        )
+    
+    process_btn.click(
+        update_interface,
+        inputs=[
+            file_input, api_key, voice_select, style_select,
+            chunk_size, temperature, max_tokens
+        ],
+        outputs=[output_table, audio_output]
+    )
 
 if __name__ == "__main__":
-    demo = create_interface()
     demo.launch(debug=True)