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* Integrate litellm for multi-provider LLM support * recover the default config yaml * Use litellm.acompletion for native async support * fix tob * Rename llm_complete/allm_complete to llm_completion/llm_acompletion, remove unused llm_complete_stream * Pin litellm to version 1.82.0 * resolve comments * args from cli is used to overrides config.yaml * Fix get_page_tokens hardcoded model default Pass opt.model to get_page_tokens so tokenization respects the configured model instead of always using gpt-4o-2024-11-20. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * Remove explicit openai dependency from requirements.txt openai is no longer directly imported; it comes in as a transitive dependency of litellm. Pinning it explicitly risks version conflicts. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * Restore openai==1.101.0 pin in requirements.txt litellm==1.82.0 and openai-agents have conflicting openai version requirements, but openai==1.101.0 works at runtime for both. The pin is necessary to prevent litellm from pulling in openai>=2.x which would break openai-agents. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * Remove explicit openai dependency from requirements.txt openai is not directly used; it comes in as a transitive dependency of litellm. No openai-agents in this branch so no pin needed. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * fix an litellm error log * resolve comments --------- Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
134 lines
No EOL
6 KiB
Python
134 lines
No EOL
6 KiB
Python
import argparse
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import os
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import json
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from pageindex import *
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from pageindex.page_index_md import md_to_tree
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from pageindex.utils import ConfigLoader
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if __name__ == "__main__":
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# Set up argument parser
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parser = argparse.ArgumentParser(description='Process PDF or Markdown document and generate structure')
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parser.add_argument('--pdf_path', type=str, help='Path to the PDF file')
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parser.add_argument('--md_path', type=str, help='Path to the Markdown file')
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parser.add_argument('--model', type=str, default=None, help='Model to use (overrides config.yaml)')
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parser.add_argument('--toc-check-pages', type=int, default=None,
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help='Number of pages to check for table of contents (PDF only)')
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parser.add_argument('--max-pages-per-node', type=int, default=None,
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help='Maximum number of pages per node (PDF only)')
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parser.add_argument('--max-tokens-per-node', type=int, default=None,
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help='Maximum number of tokens per node (PDF only)')
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parser.add_argument('--if-add-node-id', type=str, default=None,
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help='Whether to add node id to the node')
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parser.add_argument('--if-add-node-summary', type=str, default=None,
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help='Whether to add summary to the node')
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parser.add_argument('--if-add-doc-description', type=str, default=None,
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help='Whether to add doc description to the doc')
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parser.add_argument('--if-add-node-text', type=str, default=None,
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help='Whether to add text to the node')
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# Markdown specific arguments
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parser.add_argument('--if-thinning', type=str, default='no',
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help='Whether to apply tree thinning for markdown (markdown only)')
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parser.add_argument('--thinning-threshold', type=int, default=5000,
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help='Minimum token threshold for thinning (markdown only)')
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parser.add_argument('--summary-token-threshold', type=int, default=200,
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help='Token threshold for generating summaries (markdown only)')
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args = parser.parse_args()
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# Validate that exactly one file type is specified
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if not args.pdf_path and not args.md_path:
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raise ValueError("Either --pdf_path or --md_path must be specified")
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if args.pdf_path and args.md_path:
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raise ValueError("Only one of --pdf_path or --md_path can be specified")
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if args.pdf_path:
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# Validate PDF file
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if not args.pdf_path.lower().endswith('.pdf'):
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raise ValueError("PDF file must have .pdf extension")
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if not os.path.isfile(args.pdf_path):
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raise ValueError(f"PDF file not found: {args.pdf_path}")
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# Process PDF file
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user_opt = {
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'model': args.model,
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'toc_check_page_num': args.toc_check_pages,
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'max_page_num_each_node': args.max_pages_per_node,
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'max_token_num_each_node': args.max_tokens_per_node,
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'if_add_node_id': args.if_add_node_id,
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'if_add_node_summary': args.if_add_node_summary,
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'if_add_doc_description': args.if_add_doc_description,
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'if_add_node_text': args.if_add_node_text,
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}
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opt = ConfigLoader().load({k: v for k, v in user_opt.items() if v is not None})
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# Process the PDF
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toc_with_page_number = page_index_main(args.pdf_path, opt)
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print('Parsing done, saving to file...')
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# Save results
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pdf_name = os.path.splitext(os.path.basename(args.pdf_path))[0]
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output_dir = './results'
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output_file = f'{output_dir}/{pdf_name}_structure.json'
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os.makedirs(output_dir, exist_ok=True)
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with open(output_file, 'w', encoding='utf-8') as f:
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json.dump(toc_with_page_number, f, indent=2)
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print(f'Tree structure saved to: {output_file}')
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elif args.md_path:
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# Validate Markdown file
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if not args.md_path.lower().endswith(('.md', '.markdown')):
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raise ValueError("Markdown file must have .md or .markdown extension")
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if not os.path.isfile(args.md_path):
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raise ValueError(f"Markdown file not found: {args.md_path}")
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# Process markdown file
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print('Processing markdown file...')
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# Process the markdown
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import asyncio
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# Use ConfigLoader to get consistent defaults (matching PDF behavior)
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from pageindex.utils import ConfigLoader
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config_loader = ConfigLoader()
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# Create options dict with user args
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user_opt = {
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'model': args.model,
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'if_add_node_summary': args.if_add_node_summary,
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'if_add_doc_description': args.if_add_doc_description,
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'if_add_node_text': args.if_add_node_text,
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'if_add_node_id': args.if_add_node_id
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}
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# Load config with defaults from config.yaml
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opt = config_loader.load(user_opt)
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toc_with_page_number = asyncio.run(md_to_tree(
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md_path=args.md_path,
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if_thinning=args.if_thinning.lower() == 'yes',
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min_token_threshold=args.thinning_threshold,
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if_add_node_summary=opt.if_add_node_summary,
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summary_token_threshold=args.summary_token_threshold,
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model=opt.model,
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if_add_doc_description=opt.if_add_doc_description,
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if_add_node_text=opt.if_add_node_text,
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if_add_node_id=opt.if_add_node_id
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))
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print('Parsing done, saving to file...')
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# Save results
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md_name = os.path.splitext(os.path.basename(args.md_path))[0]
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output_dir = './results'
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output_file = f'{output_dir}/{md_name}_structure.json'
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os.makedirs(output_dir, exist_ok=True)
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with open(output_file, 'w', encoding='utf-8') as f:
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json.dump(toc_with_page_number, f, indent=2, ensure_ascii=False)
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print(f'Tree structure saved to: {output_file}') |