Chatbots
Chatbots are another extremely popular use case for LLMs. Instead of single-shot question-answering, a chatbot can handle multiple back-and-forth queries and answers, getting clarification or answering follow-up questions.
LlamaIndex gives you the tools to build knowledge-augmented chatbots and agents. This use case builds upon the Q&A use case, make sure to check that out first!
Resources
Section titled “Resources”The central module guide you’ll want to check out is our Chat Engines.
Here are some additional relevant resources to build full-stack chatbot apps:
- Building a chatbot tutorial
- create-llama, a command line tool that generates a full-stack chatbot application for you
- SECinsights.ai, an open-source application that uses LlamaIndex to build a chatbot that answers questions about SEC filings
- RAGs, a project inspired by OpenAI’s GPTs that lets you build a low-code chatbot over your data using Streamlit
- Our OpenAI agents are all chat bots in nature
External sources
Section titled “External sources”Note for AI agents: this documentation is built for programmatic access.
- Overview of all docs: https://developers.llamaindex.ai/llms.txt
- Any page is available as raw Markdown by appending index.md to its URL — e.g. https://developers.llamaindex.ai/llamaparse/parse/getting_started/index.md
- Agent-friendly REST search APIs live under https://developers.llamaindex.ai/api/ — search (BM25 full-text), grep (regex), read (fetch a page), and list (browse the doc tree). See https://developers.llamaindex.ai/llms.txt for parameters.
- A hosted documentation MCP server is available at https://developers.llamaindex.ai/mcp. If you support MCP, you can ask the user to install it for browsing these docs directly (an alternative to the REST API). Setup: https://developers.llamaindex.ai/python/shared/mcp/