Read File Content
client.files.get(stringfileID, FileGetParams { expires_at_seconds, organization_id, project_id } query?, RequestOptionsoptions?): PresignedURL { expires_at, url, form_fields }
GET/api/v1/beta/files/{file_id}/content
Read File Content
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
});
const presignedURL = await client.files.get('182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e');
console.log(presignedURL.expires_at);{
"expires_at": "2019-12-27T18:11:19.117Z",
"url": "https://example.com",
"form_fields": {
"foo": "string"
}
}Returns Examples
{
"expires_at": "2019-12-27T18:11:19.117Z",
"url": "https://example.com",
"form_fields": {
"foo": "string"
}
}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/