rag

Advanced Retrieval-Augmented Generation (RAG) system combining semantic search with powerful language models to provide contextually rich responses across multiple knowledge domains.

https://github.com/ingenuity-app/rag

Science Score: 13.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
  • DOI references
  • Academic links in README
  • Academic email domains
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (1.6%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

Repository

Advanced Retrieval-Augmented Generation (RAG) system combining semantic search with powerful language models to provide contextually rich responses across multiple knowledge domains.

Basic Info
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  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created about 1 year ago · Last pushed about 1 year ago
Metadata Files
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Dependencies

deployment/Dockerfile docker
  • python 3.10-slim build
deployment/docker-compose.yml docker
deployment/requirements.txt pypi
  • anthropic >=0.5.0
  • beautifulsoup4 >=4.12.0
  • faiss-cpu >=1.7.4
  • fastapi >=0.95.0
  • graphviz >=0.20.0
  • gunicorn >=20.1.0
  • line-profiler >=4.0.0
  • matplotlib >=3.7.0
  • memory-profiler >=0.60.0
  • networkx >=3.0.0
  • numpy >=1.24.0
  • openai >=1.0.0
  • pandas >=2.0.0
  • plotly >=5.14.0
  • psutil >=5.9.0
  • python-dotenv >=1.0.0
  • python-louvain >=0.16
  • requests >=2.30.0
  • scikit-learn >=1.2.0
  • sentence-transformers >=2.2.0
  • spacy >=3.5.0
  • streamlit >=1.22.0
  • tmdbsimple >=2.9.0
  • torch >=2.0.0
  • transformers >=4.30.0
  • uvicorn >=0.22.0
requirements.txt pypi
  • beautifulsoup4 ==4.12.3
  • faiss-cpu ==1.7.4
  • line-profiler ==4.1.2
  • matplotlib *
  • memory-profiler ==0.61.0
  • networkx *
  • numpy ==1.24.3
  • openai ==1.12.0
  • pandas ==2.0.1
  • psutil ==5.9.8
  • python-dotenv ==1.0.0
  • requests ==2.32.3
  • scikit-learn ==1.2.2
  • sentence-transformers ==2.3.1
  • time-machine ==2.14.1
  • tmdbsimple ==2.9.1
  • torch *
  • transformers ==4.48.0