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#

cache-augmented-generation

Here are 8 public repositories matching this topic...

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The most accurate document search and store for building AI apps

  • UpdatedNov 27, 2025
  • Python

A Demo of Cache-Augmented Generation (CAG) in an LLM

  • UpdatedJun 10, 2025
  • Jupyter Notebook

Integrate Anyparser's powerful content extraction capabilities with LangChain for enhanced AI workflows. This integration package enables seamless use of Anyparser's document processing and data extraction features within your LangChain applications.

  • UpdatedFeb 17, 2025
  • Python

Anyparser Typescript SDK for RAG/ETL Pipelines - File Content Extraction. Supports extraction from various file formats including PDF, Microsoft Office documents, OCR/Image to Text, Audio to Text, and Website to Text.

  • UpdatedFeb 26, 2025
  • TypeScript

This repository demonstrates Cache-Augmented Generation (CAG) using the Mistral-7B model.

  • UpdatedJan 15, 2025
  • Jupyter Notebook

Anyparser Python SDK for RAG/ETL Pipelines - File Content Extraction. Supports extraction from various file formats including PDF, Microsoft Office documents, OCR/Image to Text, Audio to Text, and Website to Text.

  • UpdatedFeb 26, 2025
  • Python

Supercharge your AI workflows by combining Anyparser’s advanced content extraction with Crew AI. With this integration, you can effortlessly leverage Anyparser’s document processing and data extraction tools within your Crew AI applications.

  • UpdatedFeb 17, 2025
  • Python

Instantly access Anyparser's robust document processing and data extraction capabilities directly within your LlamaIndex workflows. Enhance your AI applications with superior content understanding and data quality.

  • UpdatedFeb 17, 2025
  • Python

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