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
Find Files
import LlamaCloud from '@llamaindex/llama-cloud';
const client = new LlamaCloud({
apiKey: process.env['LLAMA_CLOUD_API_KEY'], // This is the default and can be omitted
});
// Automatically fetches more pages as needed.
for await (const retrievalFindResponse of client.beta.retrieval.find({ index_id: 'idx-abc123' })) {
console.log(retrievalFindResponse.file_id);
}{
"items": [
{
"file_id": "file_id",
"file_name": "file_name"
}
],
"next_page_token": "next_page_token",
"total_size": 0
}Returns Examples
{
"items": [
{
"file_id": "file_id",
"file_name": "file_name"
}
],
"next_page_token": "next_page_token",
"total_size": 0
}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/