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Import Pipeline Metadata

Deprecated
client.pipelines.metadata.create(stringpipelineID, MetadataCreateParams { upload_file } body, RequestOptionsoptions?): MetadataCreateResponse
PUT/api/v1/pipelines/{pipeline_id}/metadata

Import metadata for a pipeline.

ParametersExpand Collapse
pipelineID: string
body: MetadataCreateParams { upload_file }
upload_file: Uploadable
ReturnsExpand Collapse
MetadataCreateResponse = Record<string, string>

Import Pipeline Metadata

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 metadata = await client.pipelines.metadata.create('182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e', {
  upload_file: fs.createReadStream('path/to/file'),
});

console.log(metadata);
{
  "foo": "string"
}
Returns Examples
{
  "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/