Data Framework

To help your company amaze customers with technically advanced products.

  • Supports faster time-to-market for products using advanced data processing algorithms and artificial intelligence.
  • Built by developers for developers.
  • Integrated with knowledge base.

What data framework is?

It is a data utility tool for building applications powered by Large Language Models (LLMs). It simplifies connecting LLMs with your own data, a process known as data augmentation, by providing tools for data ingestion, indexing, and querying. Its primary use case is creating Retrieval-Augmented Generation (RAG) applications, like chatbots that can answer questions based on your specific documents and knowledge bases. 

Key functions

  • Data Connection: Allows you to connect to various data sources, including structured, unstructured, and semi-structured data from PDFs, databases, and more. 
  • Data Indexing: It organizes and stores your data in an efficient format, like a vector store, or graph store, to make it easy for the LLM to retrieve relevant information quickly.
  • Data Querying: It enables you to query your data through the LLM, which combines the user’s query with the relevant data to generate an augmented and context-aware answer.
  • RAG Pipeline: It provides a framework to build production-ready RAG pipelines, which retrieve relevant data and feed it to the LLM to improve the accuracy and relevance of its responses.

Use cases

  • Conversational Chatbots: Creating chatbots that can answer questions using a company’s internal documents and knowledge bases.
  • Semantic Search: Building search engines that can understand and respond to natural language queries against large datasets.
  • Knowledge Agents: Developing intelligent agents that can process and reason over complex information to perform tasks.
  • Data Augmentation: Enriching public LLMs with private data to create applications tailored for specific domains.

API Reference

Data framework API is compliant with LlamaIndex API:

See the original LlamaIndex API reference

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