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  1. Home
  2. /Repositories
  3. /thiswillbeyourgithub/wdoc
Read original ↗
repoGitHubTrust 82 · PrimaryPublished 1mo agoLive · 1mo ago

thiswillbeyourgithub/wdoc

Summarize and query from a lot of heterogeneous documents. Any LLM provider, any filetype, advanced RAG, advanced summaries, scriptable, etc

Lineage graph

Paper → model → repo connections mined from source citations (Tier-1 exact match).

Why these links exist

Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.

  • PossiblePossibly related (embedding) · 53%Set up a retrieval pipeline →
  • PossiblePossibly related (embedding) · 47%A Tree-of-Thoughts Inspired Hybrid Approach for Legal Case Judgement Summarization using LLMs →
  • PossiblePossibly related (embedding) · 49%A Production RAG Pipeline for PDFs: Relational Parsing, TOC Retrieval, Typed Answers - Towards Data Science →

Related to

tutorialSet up a retrieval pipeline

Implements

paperA Tree-of-Thoughts Inspired Hybrid Approach for Legal Case Judgement Summarization using LLMs

Covers (incoming)

newsA Production RAG Pipeline for PDFs: Relational Parsing, TOC Retrieval, Typed Answers - Towards Data Science

Related across the graph

paperA Tree-of-Thoughts Inspired Hybrid Approach for Legal Case Judgement Summarization using LLMsnewsA Production RAG Pipeline for PDFs: Relational Parsing, TOC Retrieval, Typed Answers - Towards Data SciencetutorialSet up a retrieval pipeline
Knowledge path·PA Tree-of-Thoughts Inspired Hybrid Approach for Legal Case Judgement Summarization using LLMs→NA Production RAG Pipeline for PDFs: Relational Parsing, TOC Retrieval, Typed Answers - Towards Data Science→LSet up a retrieval pipeline→Rthiswillbeyourgithub/wdoc

Topics

langchainllmnewsparserpdfpythonquestion-answeringragsummarizer

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Search similar →Knowledge graph →All repos →Full intelligence feed →
Graph trust82Primary
Graph score517