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import pixeltable as pxt |
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from pixeltable.iterators import DocumentSplitter |
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from pixeltable.functions import openai |
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import os |
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import requests |
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import tempfile |
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import gradio as gr |
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def process_document(pdf_file, api_key, voice_choice, style_choice, chunk_size, temperature, max_tokens, progress=gr.Progress()): |
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try: |
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os.environ['OPENAI_API_KEY'] = api_key |
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progress(0.1, desc="Initializing...") |
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pxt.drop_dir('document_audio', force=True) |
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pxt.create_dir('document_audio') |
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docs = pxt.create_table( |
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'document_audio.documents', |
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{ |
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'document': pxt.Document, |
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'voice': pxt.String, |
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'style': pxt.String |
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} |
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) |
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progress(0.2, desc="Processing document...") |
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docs.insert([{'document': pdf_file.name, 'voice': voice_choice, 'style': style_choice}]) |
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chunks = pxt.create_view( |
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'document_audio.chunks', |
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docs, |
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iterator=DocumentSplitter.create( |
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document=docs.document, |
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separators='token_limit', |
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limit=chunk_size |
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) |
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) |
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progress(0.4, desc="Text processing...") |
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chunks['content_response'] = openai.chat_completions( |
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messages=[ |
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{ |
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'role': 'system', |
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'content': """Transform this text segment into clear, concise content. |
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Structure: |
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1. Core concepts and points |
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2. Supporting details |
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3. Key takeaways""" |
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}, |
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{'role': 'user', 'content': chunks.text} |
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], |
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model='gpt-4o-mini-2024-07-18', |
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max_tokens=max_tokens, |
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temperature=temperature |
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) |
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chunks['content'] = chunks.content_response['choices'][0]['message']['content'] |
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progress(0.6, desc="Script generation...") |
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chunks['script_response'] = openai.chat_completions( |
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messages=[ |
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{ |
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'role': 'system', |
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'content': f"""Convert content to audio script. |
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Style: {docs.style} |
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Format: |
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- Clear sentence structures |
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- Natural pauses (...) |
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- Term definitions when needed |
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- Proper transitions""" |
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}, |
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{'role': 'user', 'content': chunks.content} |
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], |
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model='gpt-4o-mini-2024-07-18', |
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max_tokens=max_tokens, |
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temperature=temperature |
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) |
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chunks['script'] = chunks.script_response['choices'][0]['message']['content'] |
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progress(0.8, desc="Audio synthesis...") |
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@pxt.udf(return_type=pxt.Audio) |
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def generate_audio(script: str, voice: str): |
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if not script or not voice: |
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return None |
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try: |
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response = requests.post( |
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"https://api.openai.com/v1/audio/speech", |
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headers={"Authorization": f"Bearer {api_key}"}, |
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json={"model": "tts-1", "input": script, "voice": voice} |
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) |
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if response.status_code == 200: |
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temp_file = tempfile.NamedTemporaryFile(delete=False, suffix='.mp3') |
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temp_file.write(response.content) |
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temp_file.close() |
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return temp_file.name |
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except Exception as e: |
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print(f"Error in audio synthesis: {e}") |
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return None |
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chunks['audio'] = generate_audio(chunks.script, docs.voice) |
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audio_path = chunks.select(chunks.audio).tail(1)['audio'][0] |
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results = chunks.select( |
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chunks.content, |
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chunks.script |
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).collect() |
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display_data = [ |
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[f"Segment {idx + 1}", row['content'], row['script']] |
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for idx, row in enumerate(results) |
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] |
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progress(1.0, desc="Complete") |
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return display_data, audio_path, "Processing complete" |
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except Exception as e: |
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return None, None, f"Error: {str(e)}" |
