integrate-web-search

name	integrate-web-search
description	Register and use web search tools with AG2 agents to search the web and extract page content
version	1.0.0
authors	["ag2ai"]
tags	["web","search","tools","ag2"]

Integrate Web Search Tools with AG2 Agents

Overview

The web-search tool provides two functions for AG2 agents:

• web_search(query, max_results) — Search the web via DuckDuckGo (no API key needed) and return formatted results with titles, URLs, and snippets.
• fetch_page(url) — Fetch a web page and extract clean, readable text content using BeautifulSoup.

Installation

Install the required dependencies:

pip install httpx>=0.27 beautifulsoup4>=4.12

Usage

Register tools with an AG2 agent

import autogen

from tools.web_search import fetch_page, web_search

# Configure the LLM
config_list = [{"model": "gpt-4o", "api_key": "YOUR_KEY"}]

assistant = autogen.AssistantAgent(
    name="research_assistant",
    llm_config={"config_list": config_list},
)

user_proxy = autogen.UserProxyAgent(
    name="user",
    human_input_mode="NEVER",
    code_execution_config=False,
)

# Register both tools with the agent
assistant.register_for_llm(description="Search the web using DuckDuckGo")(web_search)
assistant.register_for_llm(description="Fetch and extract text from a URL")(fetch_page)
user_proxy.register_for_execution()(web_search)
user_proxy.register_for_execution()(fetch_page)

Complete working example

import autogen

from tools.web_search import fetch_page, web_search

config_list = [{"model": "gpt-4o", "api_key": "YOUR_KEY"}]

assistant = autogen.AssistantAgent(
    name="web_researcher",
    system_message=(
        "You are a helpful research assistant. Use the web_search tool to "
        "find information, then use fetch_page to read the most relevant "
        "results. Summarize your findings clearly."
    ),
    llm_config={"config_list": config_list},
)

user_proxy = autogen.UserProxyAgent(
    name="user",
    human_input_mode="NEVER",
    max_consecutive_auto_reply=10,
    code_execution_config=False,
)

# Register tools
assistant.register_for_llm(description="Search the web using DuckDuckGo")(web_search)
assistant.register_for_llm(description="Fetch and extract text from a URL")(fetch_page)
user_proxy.register_for_execution()(web_search)
user_proxy.register_for_execution()(fetch_page)

# Start the conversation
user_proxy.initiate_chat(
    assistant,
    message="Search the web for 'AG2 multi-agent framework' and summarize what you find.",
)

Using with ConversableAgent and tool decorator

import autogen
from autogen import register_function

from tools.web_search import fetch_page, web_search

config_list = [{"model": "gpt-4o", "api_key": "YOUR_KEY"}]

assistant = autogen.ConversableAgent(
    name="assistant",
    llm_config={"config_list": config_list},
)

user_proxy = autogen.ConversableAgent(
    name="user",
    human_input_mode="NEVER",
    code_execution_config=False,
)

register_function(
    web_search,
    caller=assistant,
    executor=user_proxy,
    name="web_search",
    description="Search the web using DuckDuckGo and return results",
)

register_function(
    fetch_page,
    caller=assistant,
    executor=user_proxy,
    name="fetch_page",
    description="Fetch a web page and extract its text content",
)

Tool Details

web_search

Parameter	Type	Default	Description
query	str	—	The search query string
max_results	int	5	Maximum results to return (1–20)

Returns a formatted string with numbered results including title, URL, and snippet.

fetch_page

Parameter	Type	Default	Description
url	str	—	The URL of the page to fetch

Returns extracted text content (up to ~8000 characters). Strips scripts, styles, navigation, headers, and footers for clean output.

Notes

• No API keys are required for web search (uses DuckDuckGo HTML search).
• fetch_page respects a 15-second timeout and follows redirects.
• Content is truncated at ~8000 characters to stay within LLM context limits.