Llama Index
a framework that helps LLM apps to ingest and access data sources.
Created:
LlamaIndex is a flexible framework that enables LLM applications to ingest, structure, access, and retrieve private data sources. The end result is that your model’s responses will be more relevant and context-specific.
Tools: Data Ingestion, Data Indexing and Query Interface
Data Ingestion from existing data soruces and data formats - PDF, Docs, SQL to use with a LLM.
Data Indexing Store and index your data for different use cases. Integrate with downstream vector store and database providers.
Query Interface accepts any input prompt over your data and returns a knowledge-augmented response.
Kinds of Applications that can be built with LlamaIndex:
- Documents Q&A
- Data Augmented chatbots
- Knowledge Agents
- Structured analytics – Query structured data with natural language
Related:
- Llama Hub - Connect custom data sources to your LLM with one or more of these plugins (via LlamaIndex or LangChain)
- run-llama/llama-lab (github.com) – playground to build projects using LlamaIndex.