Retrieval
Retrieve
client.beta.retrieval.retrieve(RetrievalRetrieveParams { index_id, query, organization_id, 9 more } params, RequestOptionsoptions?): RetrievalRetrieveResponse { results }
POST/api/v1/retrieval/retrieve
Find Files
client.beta.retrieval.find(RetrievalFindParams { index_id, organization_id, project_id, 4 more } params, RequestOptionsoptions?): PaginatedCursorPost<RetrievalFindResponse { file_id, file_name } >
POST/api/v1/retrieval/files/find
Grep File
client.beta.retrieval.grep(RetrievalGrepParams { file_id, index_id, pattern, 5 more } params, RequestOptionsoptions?): PaginatedCursorPost<RetrievalGrepResponse { content, end_char, start_char } >
POST/api/v1/retrieval/files/grep
Read File
client.beta.retrieval.read(RetrievalReadParams { file_id, index_id, organization_id, 3 more } params, RequestOptionsoptions?): RetrievalReadResponse { content }
POST/api/v1/retrieval/files/read
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/