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import gradio as gr |
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import os |
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from src.processing.gemini_processor import GeminiProcessor |
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from src.analysis.coverage_generator import CoverageGenerator |
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from pathlib import Path |
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def process_pdf(pdf_file, progress=gr.Progress()): |
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if pdf_file is None: |
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raise gr.Error("Please upload a PDF file") |
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progress(0.1, desc="Initializing...") |
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processor = GeminiProcessor() |
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coverage_gen = CoverageGenerator() |
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try: |
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progress(0.4, desc="Processing screenplay...") |
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cleaned_path = Path("cleaned_screenplay_long.txt") |
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success = processor.process_screenplay(pdf_file.name, str(cleaned_path)) |
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if not success: |
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raise gr.Error("Failed to process screenplay") |
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progress(0.8, desc="Generating coverage...") |
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success = coverage_gen.generate_coverage(cleaned_path) |
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if not success: |
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raise gr.Error("Failed to generate coverage") |
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with open(cleaned_path, 'r') as f: |
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cleaned_text = f.read() |
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with open(Path("coverage.txt"), 'r') as f: |
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coverage = f.read() |
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progress(1.0, desc="Complete!") |
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return cleaned_text, coverage |
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except Exception as e: |
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raise gr.Error(f"Error: {str(e)}") |
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demo = gr.Interface( |
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fn=process_pdf, |
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inputs=gr.File(label="Upload Screenplay PDF", file_types=[".pdf"]), |
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outputs=[ |
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gr.Textbox(label="Cleaned Screenplay", lines=10), |
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gr.Textbox(label="Coverage Document", lines=10) |
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], |
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title="Screenplay Coverage Generator", |
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description="Upload a screenplay PDF to generate coverage analysis" |
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) |
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if __name__ == "__main__": |
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demo.launch() |
