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Read File

beta.retrieval.read(RetrievalReadParams**kwargs) -> RetrievalReadResponse
POST/api/v1/retrieval/files/read

Read the parsed text content of a specific file.

ParametersExpand Collapse
file_id: str

ID of the file to read.

index_id: str

ID of the index the file belongs to.

organization_id: Optional[str]
project_id: Optional[str]
max_length: Optional[int]

Maximum number of characters to read from the offset.

offset: Optional[int]

Starting character offset.

ReturnsExpand Collapse
class RetrievalReadResponse:

File read result.

content: str

Parsed text content of the file.

Read File

import os
from llama_cloud import LlamaCloud

client = LlamaCloud(
    api_key=os.environ.get("LLAMA_CLOUD_API_KEY"),  # This is the default and can be omitted
)
response = client.beta.retrieval.read(
    file_id="file_id",
    index_id="idx-abc123",
)
print(response.content)
{
  "content": "content"
}
Returns Examples
{
  "content": "content"
}
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/