Add Docling Support, Pydantic JSON Validation, and Configurable LLM API URL#101
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mohamed-em2m wants to merge 4 commits intoVectifyAI:mainfrom
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Add Docling Support, Pydantic JSON Validation, and Configurable LLM API URL#101mohamed-em2m wants to merge 4 commits intoVectifyAI:mainfrom
mohamed-em2m wants to merge 4 commits intoVectifyAI:mainfrom
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mohamed-em2m
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This was referenced Feb 11, 2026
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Hey, I saw your implementation and it looks fantastic !! |
Thomasyyj
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Feb 18, 2026
…tructured output Integrate new features from PR VectifyAI#101 into LiteLLM architecture: - Add PDFReader class supporting docling, PyMuPDF, and PyPDF2 parsers - Add response_format (Pydantic BaseModel) support to all LLM API functions - Add read_pdf() utility function with page/full output formats - Update extract_text_from_pdf, get_text_of_pages, get_page_tokens to use PDFReader - Add docling and pydantic to requirements.txt - Add PDF parser config options to config.yaml Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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This pull request introduces several enhancements to improve flexibility, structure, and extensibility:
✅ Added Docling support for improved document processing and parsing.
✅ Integrated Pydantic models to ensure structured and validated JSON outputs.
✅ Added support for custom LLM API base URLs, allowing easier integration with self-hosted or alternative LLM providers.
♻️ Refactored parts of the codebase to improve clarity and maintainability.