LlamaIndex Tools Integration: Octen

This tool connects to Octen, a fast real-time web search API for AI, to enable your agent to search and retrieve content from the Internet.

To begin, you need to obtain an API key at octen.ai.

Installation

pip install llama-index-tools-octen

Usage

import os
from llama_index.tools.octen import OctenToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

octen_tool = OctenToolSpec(
    api_key=os.environ["OCTEN_API_KEY"],
)
agent = FunctionAgent(
    tools=octen_tool.to_tool_list(),
    llm=OpenAI(model="gpt-4.1"),
)

response = await agent.run(
    "What are the latest developments in AI?"
)
print(response)

Basic Search

from llama_index.tools.octen import OctenToolSpec

tool = OctenToolSpec(api_key=os.environ["OCTEN_API_KEY"])

results = tool.search("latest AI research papers", num_results=5)
for r in results:
    print(r["title"], r["url"])

Search with Domain Filtering

results = tool.search(
    "machine learning",
    include_domains=["arxiv.org", "papers.nips.cc"],
)

results = tool.search(
    "Python tutorial",
    exclude_domains=["youtube.com", "reddit.com"],
)

Search with Time Filter

tool = OctenToolSpec(api_key=os.environ["OCTEN_API_KEY"])

results = tool.search(
    "Python release notes",
    start_time="2025-01-01",
    end_time="2026-03-31",
    time_basis="published",
)

Retrieve Full Page Content

tool = OctenToolSpec(api_key=os.environ["OCTEN_API_KEY"], max_characters=3000)

# Returns List[Document], each Document.text contains the full page content
docs = tool.search_and_retrieve_documents(
    query="Python 3.13 new features",
    num_results=3,
    include_domains=["docs.python.org"],
)

for doc in docs:
    print(doc.metadata["title"], doc.metadata["url"])
    print(doc.text[:200])

Retrieve Highlighted Snippets

# Returns List[Document], each Document.text contains a concise snippet
highlights = tool.search_and_retrieve_highlights(
    query="LlamaIndex agent tutorial",
    num_results=5,
    highlight_max_tokens=300,
)

for doc in highlights:
    print(doc.metadata["title"])
    print(doc.text)

Text Filters and Safe Search

results = tool.search(
    "Python web framework",
    include_text=["async"],
    exclude_text=["deprecated"],
    safesearch="strict",
    format="markdown",
)

Available Tools

• search: Search the web using Octen for a list of results matching a natural language query.

• search_and_retrieve_documents: Search and retrieve full page content as LlamaIndex Documents.

• search_and_retrieve_highlights: Search and retrieve highlighted snippets as LlamaIndex Documents.

• current_date: Utility for the agent to get today's date (useful for time-filtered searches).

Configuration

Per-query Parameters

All search functions support:

search_and_retrieve_highlights additionally supports: