Build an enterprise-grade Agentic Document Extraction System that leverages an LLM Council Architecture where multiple AI models collaborate, deliberate, and reach consensus on document extraction tasks—similar to how a panel of experts would analyze complex documents together.
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feat: add FUNDING.yml to support various funding platforms
ccb79ffView on GitHubfix: configure bandit to exclude tests and fix pre-commit hooks
700affcView on GitHubfeat: update dependencies and improve RAG LLM answer generation
18ac23eView on GitHubfeat: Enhance document processing with table extraction and rendering
e5a82caView on GitHubAdd unit tests for cross-field validation, OCR post-processing, and security features
eaa745cView on GitHubfeat: Enhance HITLQueue with document type metadata and learning event recording
e849295View on GitHubfeat: Add page count to document status response and update related tests
cc7a7f8View on GitHubRefactor tests and configurations to replace "deepseek" with "olmocr"
0139d3eView on GitHubfeat: Enhance setup process with mock mode, update model paths, and improve error handling for model downloads
1cd68adView on GitHub