Create app.py
Browse files
app.py
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import gradio as gr
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import pixeltable as pxt
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import numpy as np
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from datetime import datetime
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from pixeltable.functions.huggingface import sentence_transformer
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from pixeltable.functions import openai
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import os
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# Ensure OpenAI API key is set
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if 'OPENAI_API_KEY' not in os.environ:
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os.environ['OPENAI_API_KEY'] = input('Enter your OpenAI API key: ')
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# Initialize Pixeltable
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pxt.drop_dir('story_builder', force=True)
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pxt.create_dir('story_builder')
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# Create embedding function
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@pxt.expr_udf
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def embed_text(text: str) -> np.ndarray:
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return sentence_transformer(text, model_id='all-MiniLM-L6-v2')
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# Create a table to store story contributions
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story_table = pxt.create_table(
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'story_builder.contributions',
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{
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'contributor': pxt.StringType(),
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'content': pxt.StringType(),
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'timestamp': pxt.TimestampType(),
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'cumulative_story': pxt.StringType()
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}
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)
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# Add an embedding index to the content column
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story_table.add_embedding_index('content', string_embed=embed_text)
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@pxt.udf
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def generate_summary(story: str) -> list[dict]:
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system_msg = "You are an expert summarizer. Provide a concise summary of the given story, highlighting key plot points and themes."
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user_msg = f"Story: {story}\n\nSummarize this story:"
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return [
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{'role': 'system', 'content': system_msg},
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{'role': 'user', 'content': user_msg}
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]
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story_table['summary_prompt'] = generate_summary(story_table.cumulative_story)
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story_table['summary_response'] = openai.chat_completions(
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messages=story_table.summary_prompt,
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model='gpt-3.5-turbo',
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max_tokens=200
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)
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@pxt.udf
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def generate_continuation(context: str) -> list[dict]:
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system_msg = "You are a creative writer. Continue the story based on the given context. Write a paragraph that logically follow the provided content."
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user_msg = f"Context: {context}\n\nContinue the story:"
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return [
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{'role': 'system', 'content': system_msg},
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{'role': 'user', 'content': user_msg}
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]
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story_table['continuation_prompt'] = generate_continuation(story_table.cumulative_story)
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story_table['continuation_response'] = openai.chat_completions(
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messages=story_table.continuation_prompt,
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model='gpt-3.5-turbo',
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max_tokens=50
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)
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# Function to get the current cumulative story
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def get_current_story():
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latest_entry = story_table.tail(1)
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if len(latest_entry) > 0:
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return latest_entry['cumulative_story'][0]
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return ""
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# Functions for Gradio interface
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def add_contribution(contributor, content):
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current_story = get_current_story()
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new_cumulative_story = current_story + " " + content if current_story else content
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story_table.insert([{
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'contributor': contributor,
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'content': content,
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'timestamp': datetime.now(),
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'cumulative_story': new_cumulative_story
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}])
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return "Contribution added successfully!", new_cumulative_story
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def get_similar_parts(query, num_results=5):
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sim = story_table.content.similarity(query)
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results = story_table.order_by(sim, asc=False).limit(num_results).select(story_table.content, story_table.contributor, sim=sim).collect()
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return results.to_pandas()
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def generate_next_part():
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continuation = story_table.select(continuation=story_table.continuation_response.choices[0].message.content).tail(1)['continuation'][0]
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return continuation
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def summarize_story():
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summary = story_table.select(summary=story_table.summary_response.choices[0].message.content).tail(1)['summary'][0]
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return summary
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# Gradio interface
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with gr.Blocks(theme=gr.themes.Base()) as demo:
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gr.HTML(
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"""
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<div style="text-align: left; margin-bottom: 1rem;">
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<img src="https://raw.githubusercontent.com/pixeltable/pixeltable/main/docs/source/data/pixeltable-logo-large.png" alt="Pixeltable" style="max-width: 150px;" />
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</div>
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"""
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)
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gr.Markdown(
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"""
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# 📚 Collaborative Story Builder
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Welcome to the Collaborative Story Builder! This app allows multiple users to contribute to a story,
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building it incrementally. Pixeltable manages the data, enables similarity search, and helps generate
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continuations and summaries.
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"""
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)
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with gr.Tabs():
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with gr.TabItem("Contribute"):
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with gr.Row():
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with gr.Column(scale=2):
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contributor = gr.Textbox(label="Your Name")
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content = gr.Textbox(label="Your Contribution", lines=5)
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submit_btn = gr.Button("Submit Contribution", variant="primary")
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with gr.Column(scale=3):
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status = gr.Textbox(label="Status")
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current_story = gr.Textbox(label="Current Story", lines=10, interactive=False)
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with gr.TabItem("Search & Generate"):
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with gr.Row():
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with gr.Column():
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search_query = gr.Textbox(label="Search Current Contributions")
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num_results = gr.Slider(minimum=1, maximum=10, value=5, step=1, label="Number of Results")
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search_btn = gr.Button("Search", variant="secondary")
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search_results = gr.Dataframe(
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headers=["Content", "Contributor", "Similarity"],
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label="Similar Parts"
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)
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with gr.Column():
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generate_btn = gr.Button("Generate Next Part", variant="primary")
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generated_part = gr.Textbox(label="Generated Continuation", lines=5)
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with gr.TabItem("Summary"):
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summarize_btn = gr.Button("Summarize Story", variant="primary")
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summary = gr.Textbox(label="Story Summary", lines=8)
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submit_btn.click(add_contribution, inputs=[contributor, content], outputs=[status, current_story])
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search_btn.click(get_similar_parts, inputs=[search_query, num_results], outputs=[search_results])
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generate_btn.click(generate_next_part, outputs=[generated_part])
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summarize_btn.click(summarize_story, outputs=[summary])
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gr.HTML(
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"""
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<div style="text-align: center; margin-top: 1rem; padding-top: 1rem; border-top: 1px solid #ccc;">
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<p style="margin: 0; color: #666; font-size: 0.8em;">
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Powered by <a href="https://github.com/pixeltable/pixeltable" target="_blank" style="color: #F25022; text-decoration: none;">Pixeltable</a>
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| <a href="https://github.com/pixeltable/pixeltable" target="_blank" style="color: #666; text-decoration: none;">GitHub</a>
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</p>
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</div>
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"""
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)
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if __name__ == "__main__":
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demo.launch()
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