LlamaIndex Tools Integration: Keenable
Keenable is a web search and page-fetch API built for AI
agents. This package provides KeenableToolSpec, a LlamaIndex tool spec with
two tools, search and fetch, usable from any LlamaIndex agent.
Keyless by default: with no API key the keyless public endpoints are used. Provide a key to use the authenticated endpoints (for higher rate limits).
Install
pip install llama-index-tools-keenable
Usage
from llama_index.tools.keenable import KeenableToolSpec
from llama_index.agent.openai import OpenAIAgent
# No api_key -> keyless public endpoints. Pass api_key=... or set
# KEENABLE_API_KEY to use the authenticated endpoints.
keenable_tool = KeenableToolSpec()
agent = OpenAIAgent.from_tools(keenable_tool.to_tool_list())
agent.chat("Find recent TypeScript best practices and summarize the top result")
Call the tools directly:
docs = keenable_tool.search("typescript best practices", site="github.com")
page = keenable_tool.fetch(docs[0].metadata["url"])
print(page[0].text)
search accepts optional per-query filters (site, published_after/before,
acquired_after/before, mode) and returns one Document per result. fetch
returns the page's main content as markdown. There is no max_results argument:
the API returns a fixed-size result set as-is.
Configuration
- API key (optional). Constructor
api_key=...or theKEENABLE_API_KEYenvironment variable. Blank → keyless public endpoints. - Endpoint (optional).
KEENABLE_API_URLoverrides the base URL (HTTPS enforced; plainhttponly for loopback). The endpoint is never a tool argument the model can set, so it cannot be used to redirect requests.
The fetch tool rejects non-http(s) schemes and private/internal hosts
client-side before sending.
License
MIT © Keenable
1 maintainer
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