Grep File
beta.retrieval.grep(RetrievalGrepParams**kwargs) -> SyncPaginatedCursorPost[RetrievalGrepResponse]
POST/api/v1/retrieval/files/grep
Grep within a file’s parsed content using a regex pattern.
Grep 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
)
page = client.beta.retrieval.grep(
file_id="file_id",
index_id="idx-abc123",
pattern="revenue|profit",
)
page = page.items[0]
print(page.content){
"items": [
{
"content": "content",
"end_char": 0,
"start_char": 0
}
],
"next_page_token": "next_page_token",
"total_size": 0
}Returns Examples
{
"items": [
{
"content": "content",
"end_char": 0,
"start_char": 0
}
],
"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/