LlamaIndex Module

A LlamaIndex Module is a Python library module within a LlamaIndex library.

• Context:
  • It can contain related LlamaIndex Classes, LlamaIndex Functions, and LlamaIndex Data Structures.
  • It can range from being a LlamaIndex Index/Data Module, LlamaIndex Query Module, LlamaIndex Agent Module, to being a LlamaIndex Supporting Module.
  • It can (typically) be a key part of the overall LlamaIndex Package Architecture.
  • ...
• Example(s):
  • llama_index.indices, contains index implementations like VectorStoreIndex.
  • llama_index.retrievers, contains retriever implementations like DenseRetriever.
  • llama_index.pipelines, contains pipeline classes like BasicPipeline.
  • llama_index.connectors, contains connector classes like DatabaseConnector.
  • llama_index.query_engines, contains query engines like SimpleQueryEngine.
  • llama_index.nodes, contains node classes like TextNode.
  • llama_index.reranking, contains rerankers like QueryContextReranker.
  • ...
• Counter-Example(s):
  • a LangChain Module.
• See: LlamaIndex Class.

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References

2023

• (GBard, 2023) ⇒ Google Bard. (2023). Retrieved from chat transcript.
  • QUOTE: The main modules within LlamaIndex are:
    • Data connectors: These modules allow you to ingest data from a variety of sources, such as APIs, databases, PDFs, and plain text files.
    • Indices: These modules store the ingested data in a way that can be efficiently searched by LLMs.
    • Retrievers: These modules retrieve the most relevant documents from an index based on a user query.
    • Query engines: These modules process user queries and interact with retrievers to return the most relevant documents.
    • Reranking modules: These modules can be used to rerank the documents returned by retrievers, taking into account factors such as the user's context and the content of the documents.
    • Pipelines: These modules combine the different modules to provide a complete end-to-end solution for building LLM applications.
  • NOTE: It provides examples of key LlamaIndex modules across categories like connectors, indices, retrievers, pipelines etc. that enable building LLM apps.

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