Pydantic Programs
A pydantic program is a generic abstraction that takes in an input string and converts it to a structured Pydantic object type.
Because this abstraction is so generic, it encompasses a broad range of LLM workflows. The programs are composable and be for more generic or specific use cases.
There’s a few general types of Pydantic Programs:
- Text Completion Pydantic Programs: These convert input text into a user-specified structured object through a text completion API + output parsing.
- Function Calling Pydantic Programs: These convert input text into a user-specified structured object through an LLM function calling API.
- Prepackaged Pydantic Programs: These convert input text into prespecified structured objects.
Text Completion Pydantic Programs
Section titled “Text Completion Pydantic Programs”See the example notebook on LLM Text Completion programs
Function Calling Pydantic Programs
Section titled “Function Calling Pydantic Programs”- Function Calling Pydantic Program
- OpenAI Pydantic Program
- Guidance Pydantic Program
- Guidance Sub-Question Generator
Prepackaged Pydantic Programs
Section titled “Prepackaged Pydantic Programs”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/