Create processor.py

processor.py

@@ -0,0 +1,117 @@
+import pixeltable as pxt
+from pixeltable.iterators import DocumentSplitter
+from pixeltable.functions import openai
+import os
+import requests
+import tempfile
+import gradio as gr
+
+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.Document,
+                'voice': pxt.String,
+                'style': pxt.String
+            }
+        )
+        
+        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"""
+                },
+                {'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.Audio)
+        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)}"