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RAGstack

github.com/psychic-api/rag-stack is an open-source framework for building question-answering applications using the Retrieval Augmented Generation (RAG) model. RAG combines a retriever and a generator to answer questions by retrieving relevant information from a corpus and generating a final answer.



Pricing

As an open-source project hosted on GitHub, the RAG-stack framework is free to use, modify, and distribute under the Apache 2.0 license.




Pros

  • Open-source and customizable
  • Leverages the power of retrieval and language generation
  • Can be fine-tuned on domain-specific data
  • Supports various question-answering tasks

Cons

  • Requires significant computational resources
  • Performance depends on the quality of the corpus
  • Potential for hallucinations or inconsistent answers


Use Cases

  • Building conversational AI assistants
  • Creating knowledge-based question-answering systems
  • Developing research prototypes for language understanding

Target Market

  • AI researchers and developers
  • Companies building question-answering systems
  • Educational institutions and research labs


Competitors

  • Hugging Face RAG
  • Google REALM
  • Facebook FiD

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