Llama-index
- 1. A toolkit designed to easily connect LLM’s with your external data LlamaIndex
- 2. Context LLMs are powerful for knowledge generation and reasoning, pre-trained on publicly available data. To augment LLMs with private data, in- context learning has emerged as a paradigm, where context is inserted into the input prompt. In-context learning takes advantage of LLMs' reasoning capabilities to generate a response, offering a simple and effective way to use them for data augmentation.
- 3. To perform LLM’s data augmentation in a performant, efficient, and cheap manner, we need to solve two components: Data Ingestion Data Indexing
- 4. 1 2 3 Provides indices over your unstructured and structured data for use with LLM’s. These indices help to abstract away common boilerplate and pain points for in-context learning: Storing context in an easy-to-access format for prompt insertion. Dealing with prompt limitations (e.g. 4096 tokens for Davinci) when context is too big. Dealing with text splitting.
- 5. Just Starting Out (Vector Store Indices) Connecting LlamaIndex to an External Data Source of Documents Summarization over Documents Combining information across multiple indices Routing a Query to the Right Index Using Keyword Filters Including Hierarchical Context in your Answer Use cases
- 6. How Each Index Works Vector Store Index The vector store index stores each Node and a corresponding embedding in a Vector Store.
- 7. Querying
- 9. Data Connectors This module contains the data connectors for LlamaIndex. Each connector inherits from a BaseReader class, connects to a data source, and loads Document objects from that data source.
- 10. Github repository reader BeautifulSoup web page reader Discord reader Google Docs reader Generic interface for a data document Notion Page reader. LLama Hub Simple directory reader. Youtube Transcript reader. File/audio reader Image loader (text extract) https://llamahub.ai/ and so on....
- 11. Example of usage with Gmail connector This loader seaches your Gmail account and parses the resulting emails into Documents.
- 12. Example of usage with Audio connector This loader uses OpenAI's Whisper model to transcribe the text of an audio file or the audio track of a video file.
- 13. And many other uses LlamaIndex - Unlock the Full Potential of Your Data with LLMs