Blog
- Recent posts
- Adding Browsing Capabilities to AG2
- Riding the Web with WebSurferAgent
- RealtimeAgent with Gemini API
- Tools with ChatContext Dependency Injection
- Streaming input and output using WebSockets
- Real-Time Voice Interactions over WebRTC
- Real-Time Voice Interactions with the WebSocket Audio Adapter
- Tools Dependency Injection
- Cross-Framework LLM Tool Integration with AG2
- ReasoningAgent Update - Beam Search, MCTS, and LATS for LLM Reasoning
- Introducing RealtimeAgent Capabilities in AG2
- Knowledgeable Agents with FalkorDB Graph RAG
- ReasoningAgent - Tree of Thoughts with Beam Search in AG2
- Agentic testing for prompt leakage security
- Building Swarm-based agents with AG2
- Introducing CaptainAgent for Adaptive Team Building
- Unlocking the Power of Agentic Workflows at Nexla with Autogen
- AgentOps, the Best Tool for AutoGen Agent Observability
- Enhanced Support for Non-OpenAI Models
- AgentEval: A Developer Tool to Assess Utility of LLM-powered Applications
- Agents in AutoGen
- AutoDefense - Defend against jailbreak attacks with AutoGen
- What's New in AutoGen?
- StateFlow - Build State-Driven Workflows with Customized Speaker Selection in GroupChat
- FSM Group Chat -- User-specified agent transitions
- Anny: Assisting AutoGen Devs Via AutoGen
- AutoGen with Custom Models: Empowering Users to Use Their Own Inference Mechanism
- AutoGenBench -- A Tool for Measuring and Evaluating AutoGen Agents
- Code execution is now by default inside docker container
- All About Agent Descriptions
- AgentOptimizer - An Agentic Way to Train Your LLM Agent
- AutoGen Studio: Interactively Explore Multi-Agent Workflows
- Agent AutoBuild - Automatically Building Multi-agent Systems
- How to Assess Utility of LLM-powered Applications?
- AutoGen Meets GPTs
- EcoAssistant - Using LLM Assistants More Accurately and Affordably
- Multimodal with GPT-4V and LLaVA
- AutoGen's Teachable Agents
- Retrieval-Augmented Generation (RAG) Applications with AutoGen
- Use AutoGen for Local LLMs
- MathChat - An Conversational Framework to Solve Math Problems
- Achieve More, Pay Less - Use GPT-4 Smartly
- Does Model and Inference Parameter Matter in LLM Applications? - A Case Study for MATH
Riding the Web with WebSurferAgent
Introduction
In our Adding Browsing Capabilities to AG2 guide, we explored how to build agents with basic web surfing capabilities. Now, let’s take it to the next level with WebSurferAgent
—a powerful agent that comes with built-in web browsing tools right out of the box!
With WebSurferAgent
, your agents can seamlessly browse the web, retrieve real-time information, and interact with web pages—all with minimal setup.
WebSurferAgent with BrowserUseTool
Installation
To get started with the Browser Use
integration in AG2, follow these steps:
-
Install AG2 with the
browser-use
extra:pip install ag2[browser-use]
-
Set up Playwright:
playwright install
-
For running the code in Jupyter, use
nest_asyncio
to allow nested event loops.pip install nest_asyncio
You’re all set! Now you can start using browsing features in AG2.
Imports
import os
import nest_asyncio
from autogen.agentchat import UserProxyAgent
from autogen.agents import WebSurferAgent
nest_asyncio.apply()
Configure WebSurferAgent with Browser Use
WebSurferAgent
is the one responsible for browsing the web and retrieving information. The web_tool="browser_use"
tells the agent to use the BrowserUseTool
to surf the web.
After creating the WebSurferAgent
, its tools (such as the BrowserUseTool
) are registered with the UserProxyAgent
so they can be used during the interaction.
The user can ask the WebSurferAgent
to fetch information from a specific webpage, in this case, the AG2 documentation home page.
config_list = [{"model": "gpt-4o-mini", "api_key": os.environ["OPENAI_API_KEY"]}]
llm_config = {
"config_list": config_list,
}
user_proxy = UserProxyAgent(name="user_proxy", human_input_mode="NEVER")
websurfer = WebSurferAgent(name="WebSurfer", llm_config=llm_config, web_tool="browser_use")
websurfer_tools = websurfer.tools
# WebSurferAgent has a list of tools which are registered for LLM
# We need to register the tools for execution with the UserProxyAgent
for tool in websurfer_tools:
tool.register_for_execution(user_proxy)
user_proxy.initiate_chat(
recipient=websurfer,
message="Get info from https://docs.ag2.ai/docs/Home",
max_turns=2,
)
user_proxy (to WebSurfer):
Get info from https://docs.ag2.ai/docs/Home
--------------------------------------------------------------------------------
>>>>>>>> USING AUTO REPLY...
WebSurfer (to user_proxy):
***** Suggested tool call (call_rl777jGrOGhc68goW5142urK): browser_use *****
Arguments:
{"task":"Get info from https://docs.ag2.ai/docs/Home"}
****************************************************************************
--------------------------------------------------------------------------------
>>>>>>>> EXECUTING FUNCTION browser_use...
Call ID: call_rl777jGrOGhc68goW5142urK
Input arguments: {'task': 'Get info from https://docs.ag2.ai/docs/Home'}
INFO [agent] 🚀 Starting task: Get info from https://docs.ag2.ai/docs/Home
INFO [agent]
📍 Step 1
INFO [agent] 🤷 Eval: Unknown - No previous actions to evaluate.
INFO [agent] 🧠 Memory:
INFO [agent] 🎯 Next goal: Navigate to the specified URL to gather information
INFO [agent] 🛠️ Action 1/1: {"go_to_url":{"url":"https://docs.ag2.ai/docs/Home"}}
INFO [controller] 🔗 Navigated to https://docs.ag2.ai/docs/Home
INFO [agent]
📍 Step 2
INFO [agent] 🤷 Eval: Unknown - No previous actions to evaluate.
INFO [agent] 🧠 Memory:
INFO [agent] 🎯 Next goal: Extract useful information regarding AG2 from the home page.
INFO [agent] 🛠️ Action 1/1: {"extract_content":{"include_links":true}}
INFO [controller] 📄 Extracted page as markdown
: [AG2 home page![light logo](https://mintlify.s3.us-
west-1.amazonaws.com/ag2ai/logo/ag2.svg)![dark logo](https://mintlify.s3.us-
west-1.amazonaws.com/ag2ai/logo/ag2-white.svg)](/)
Search or ask...
⌘K
Search...A
Navigation
Home
AG2
[Home](/docs/home/Home)[User Guide](/docs/user-guide/quick-start)[API
References](/docs/api-reference/autogen/overview)[Use Cases](/docs/use-
cases/use-cases/customer-service)[Contribute](/contributor-
guide/contributing)[FAQs](/faq/FAQ)[Ecosystem](/ecosystem/agentops)[Blog](/docs/blog/2025-01-29-RealtimeAgent-
with-gemini/index)
##### Home
* [AG2](/docs/home/Home)
![AG2 Logo](https://mintlify.s3.us-
west-1.amazonaws.com/ag2ai/static/img/ag2.svg)
## AG2
The Open Source Agent OS
[Getting Started - 3 Minute](/docs/user-guide/quick-start)
###
Key Features
##
![Multi-Agent Conversation Framework](https://mintlify.s3.us-
west-1.amazonaws.com/ag2ai/static/img/conv_2.svg)**Multi-Agent Conversation
Framework**
AG2 provides multi-agent conversation framework as a high-level abstraction.
With this framework, one can conveniently build LLM workflows.
##
![Easily Build Diverse Applications](https://mintlify.s3.us-
west-1.amazonaws.com/ag2ai/static/img/autogen_app.svg)**Easily Build Diverse
Applications**
AG2 offers a collection of working systems spanning a wide range of
applications from various domains and complexities.
##
![Enhanced LLM Inference & Optimization](https://mintlify.s3.us-
west-1.amazonaws.com/ag2ai/static/img/extend.svg)**Enhanced LLM Inference &
Optimization**
AG2 supports enhanced LLM inference APIs, which can be used to improve
inference performance and reduce cost.
###
Explore content
## [Quick StartStart building your AG2 application.](/docs/user-guide/quick-
start)## [ConceptsWork through the key concepts of AG2 including
ConversableAgent, GroupChat, Swarm, and tools.](/docs/user-guide/basic-
concepts/installing-ag2)## [Advanced ConceptsAdvance to RAG, Code Execution,
and more complex GroupChats and Swarms.](/docs/user-guide/advanced-concepts)##
[Use CasesTry out use case workflows including Customer Service, Travel
Planning, and Game Design.](/docs/use-cases/use-cases)## [Notebook ExamplesA
collection of interactive notebooks across all AG2 topics.](/docs/use-
cases/notebooks/Notebooks)## [API ReferenceDelve into the AG2 API
reference.](/docs/api-reference)## [How to ContributeGet involved with AG2 by
adding what you need and making the framework even better!](/contributor-
guide/contributing)
###
Popular resources
##
[Foundation Capital Interview with Dr. Chi
Wang](https://www.youtube.com/watch?v=RLwyXRVvlNk)
##
[Learn AG2 on DeepLearningAI](https://www.youtube.com/watch?v=TBNTH-fwGPE)
On this page
* Key Features
* Explore content
* Popular resources
INFO [agent]
📍 Step 3
INFO [agent] 👍 Eval: Success - Successfully extracted information from the AG2 home page.
INFO [agent] 🧠 Memory: Extracted information includes the key features and content related to AG2.
INFO [agent] 🎯 Next goal: Complete the task and summarize the extracted information.
INFO [agent] 🛠️ Action 1/1: {"done":{"text":"Extracted information from AG2 home page:\n\n### AG2\n\n**The Open Source Agent OS** \n[Getting Started - 3 Minute](https://docs/user-guide/quick-start)\n\n#### Key Features\n\n- **Multi-Agent Conversation Framework**: AG2 provides a high-level abstraction for building LLM workflows.\n- **Easily Build Diverse Applications**: Offers a collection of systems across various domains and complexities.\n- **Enhanced LLM Inference & Optimization**: Supports APIs to improve inference performance and reduce costs.\n\n#### Explore Content\n- [Quick Start](https://docs/user-guide/quick-start)\n- [Concepts](https://docs/user-guide/basic-concepts/installing-ag2)\n- [Advanced Concepts](https://docs/user-guide/advanced-concepts)\n- [Use Cases](https://docs/use-cases/use-cases)\n- [API Reference](https://docs/api-reference)\n- [How to Contribute](https://contributor-guide/contributing) \n\n#### Popular Resources\n- [Foundation Capital Interview with Dr. Chi Wang](https://www.youtube.com/watch?v=RLwyXRVvlNk) \n- [Learn AG2 on DeepLearningAI](https://www.youtube.com/watch?v=TBNTH-fwGPE) \n"}}
INFO [agent] 📄 Result: Extracted information from AG2 home page:
### AG2
**The Open Source Agent OS**
[Getting Started - 3 Minute](https://docs/user-guide/quick-start)
#### Key Features
- **Multi-Agent Conversation Framework**: AG2 provides a high-level abstraction for building LLM workflows.
- **Easily Build Diverse Applications**: Offers a collection of systems across various domains and complexities.
- **Enhanced LLM Inference & Optimization**: Supports APIs to improve inference performance and reduce costs.
#### Explore Content
- [Quick Start](https://docs/user-guide/quick-start)
- [Concepts](https://docs/user-guide/basic-concepts/installing-ag2)
- [Advanced Concepts](https://docs/user-guide/advanced-concepts)
- [Use Cases](https://docs/use-cases/use-cases)
- [API Reference](https://docs/api-reference)
- [How to Contribute](https://contributor-guide/contributing)
#### Popular Resources
- [Foundation Capital Interview with Dr. Chi Wang](https://www.youtube.com/watch?v=RLwyXRVvlNk)
- [Learn AG2 on DeepLearningAI](https://www.youtube.com/watch?v=TBNTH-fwGPE)
INFO [agent] ✅ Task completed successfully
user_proxy (to WebSurfer):
***** Response from calling tool (call_rl777jGrOGhc68goW5142urK) *****
{"extracted_content":["🔗 Navigated to https://docs.ag2.ai/docs/Home","📄 Extracted page as markdown\n: [AG2 home page![light logo](https://mintlify.s3.us-\nwest-1.amazonaws.com/ag2ai/logo/ag2.svg)![dark logo](https://mintlify.s3.us-\nwest-1.amazonaws.com/ag2ai/logo/ag2-white.svg)](/)\n\nSearch or ask...\n\n⌘K\n\nSearch...\n\nNavigation\n\nHome\n\nAG2\n\n[Home](/docs/home/Home)[User Guide](/docs/user-guide/quick-start)[API\nReferences](/docs/api-reference/autogen/overview)[Use Cases](/docs/use-\ncases/use-cases/customer-service)[Contribute](/contributor-\nguide/contributing)[FAQs](/faq/FAQ)[Ecosystem](/ecosystem/agentops)[Blog](/docs/blog/2025-01-29-RealtimeAgent-\nwith-gemini/index)\n\n##### Home\n\n * [AG2](/docs/home/Home)\n\n![AG2 Logo](https://mintlify.s3.us-\nwest-1.amazonaws.com/ag2ai/static/img/ag2.svg)\n\n## AG2\n\nThe Open Source Agent OS\n\n[Getting Started - 3 Minute](/docs/user-guide/quick-start)\n\n###\n\n\n\nKey Features\n\n##\n\n![Multi-Agent Conversation Framework](https://mintlify.s3.us-\nwest-1.amazonaws.com/ag2ai/static/img/conv_2.svg)**Multi-Agent Conversation\nFramework**\n\nAG2 provides multi-agent conversation framework as a high-level abstraction.\nWith this framework, one can conveniently build LLM workflows.\n\n##\n\n![Easily Build Diverse Applications](https://mintlify.s3.us-\nwest-1.amazonaws.com/ag2ai/static/img/autogen_app.svg)**Easily Build Diverse\nApplications**\n\nAG2 offers a collection of working systems spanning a wide range of\napplications from various domains and complexities.\n\n##\n\n![Enhanced LLM Inference & Optimization](https://mintlify.s3.us-\nwest-1.amazonaws.com/ag2ai/static/img/extend.svg)**Enhanced LLM Inference &\nOptimization**\n\nAG2 supports enhanced LLM inference APIs, which can be used to improve\ninference performance and reduce cost.\n\n###\n\n\n\nExplore content\n\n## [Quick StartStart building your AG2 application.](/docs/user-guide/quick-\nstart)## [ConceptsWork through the key concepts of AG2 including\nConversableAgent, GroupChat, Swarm, and tools.](/docs/user-guide/basic-\nconcepts/installing-ag2)## [Advanced ConceptsAdvance to RAG, Code Execution,\nand more complex GroupChats and Swarms.](/docs/user-guide/advanced-concepts)##\n[Use CasesTry out use case workflows including Customer Service, Travel\nPlanning, and Game Design.](/docs/use-cases/use-cases)## [Notebook ExamplesA\ncollection of interactive notebooks across all AG2 topics.](/docs/use-\ncases/notebooks/Notebooks)## [API ReferenceDelve into the AG2 API\nreference.](/docs/api-reference)## [How to ContributeGet involved with AG2 by\nadding what you need and making the framework even better!](/contributor-\nguide/contributing)\n\n###\n\n\n\nPopular resources\n\n##\n\n[Foundation Capital Interview with Dr. Chi\nWang](https://www.youtube.com/watch?v=RLwyXRVvlNk)\n\n##\n\n[Learn AG2 on DeepLearningAI](https://www.youtube.com/watch?v=TBNTH-fwGPE)\n\nOn this page\n\n * Key Features\n * Explore content\n * Popular resources\n\n\n","Extracted information from AG2 home page:\n\n### AG2\n\n**The Open Source Agent OS** \n[Getting Started - 3 Minute](https://docs/user-guide/quick-start)\n\n#### Key Features\n\n- **Multi-Agent Conversation Framework**: AG2 provides a high-level abstraction for building LLM workflows.\n- **Easily Build Diverse Applications**: Offers a collection of systems across various domains and complexities.\n- **Enhanced LLM Inference & Optimization**: Supports APIs to improve inference performance and reduce costs.\n\n#### Explore Content\n- [Quick Start](https://docs/user-guide/quick-start)\n- [Concepts](https://docs/user-guide/basic-concepts/installing-ag2)\n- [Advanced Concepts](https://docs/user-guide/advanced-concepts)\n- [Use Cases](https://docs/use-cases/use-cases)\n- [API Reference](https://docs/api-reference)\n- [How to Contribute](https://contributor-guide/contributing) \n\n#### Popular Resources\n- [Foundation Capital Interview with Dr. Chi Wang](https://www.youtube.com/watch?v=RLwyXRVvlNk) \n- [Learn AG2 on DeepLearningAI](https://www.youtube.com/watch?v=TBNTH-fwGPE) \n"],"final_result":"Extracted information from AG2 home page:\n\n### AG2\n\n**The Open Source Agent OS** \n[Getting Started - 3 Minute](https://docs/user-guide/quick-start)\n\n#### Key Features\n\n- **Multi-Agent Conversation Framework**: AG2 provides a high-level abstraction for building LLM workflows.\n- **Easily Build Diverse Applications**: Offers a collection of systems across various domains and complexities.\n- **Enhanced LLM Inference & Optimization**: Supports APIs to improve inference performance and reduce costs.\n\n#### Explore Content\n- [Quick Start](https://docs/user-guide/quick-start)\n- [Concepts](https://docs/user-guide/basic-concepts/installing-ag2)\n- [Advanced Concepts](https://docs/user-guide/advanced-concepts)\n- [Use Cases](https://docs/use-cases/use-cases)\n- [API Reference](https://docs/api-reference)\n- [How to Contribute](https://contributor-guide/contributing) \n\n#### Popular Resources\n- [Foundation Capital Interview with Dr. Chi Wang](https://www.youtube.com/watch?v=RLwyXRVvlNk) \n- [Learn AG2 on DeepLearningAI](https://www.youtube.com/watch?v=TBNTH-fwGPE) \n"}
**********************************************************************
--------------------------------------------------------------------------------
>>>>>>>> USING AUTO REPLY...
WebSurfer (to user_proxy):
Here's the information extracted from the AG2 home page:
### AG2
**The Open Source Agent OS**
[Getting Started - 3 Minute](https://docs/user-guide/quick-start)
#### Key Features
- **Multi-Agent Conversation Framework**: AG2 provides a high-level abstraction for building LLM (Large Language Model) workflows.
- **Easily Build Diverse Applications**: Offers a collection of systems across various domains and complexities.
- **Enhanced LLM Inference & Optimization**: Supports enhanced inference APIs to improve performance and reduce costs.
#### Explore Content
- [Quick Start](https://docs/user-guide/quick-start)
- [Concepts](https://docs/user-guide/basic-concepts/installing-ag2)
- [Advanced Concepts](https://docs/user-guide/advanced-concepts)
- [Use Cases](https://docs/use-cases/use-cases)
- [API Reference](https://docs/api-reference)
- [How to Contribute](https://contributor-guide/contributing)
#### Popular Resources
- [Foundation Capital Interview with Dr. Chi Wang](https://www.youtube.com/watch?v=RLwyXRVvlNk)
- [Learn AG2 on DeepLearningAI](https://www.youtube.com/watch?v=TBNTH-fwGPE)
--------------------------------------------------------------------------------
WebSurferAgent with Crawl4AITool
Installation
To integrate Crawl4AI
with AG2, follow these steps:
-
Install AG2 with the
crawl4ai
extra:pip install ag2[crawl4ai]
-
Set up Playwright:
playwright install
-
For running the code in Jupyter, use
nest_asyncio
to allow nested event loops.pip install nest_asyncio
Once installed, you’re ready to start using the browsing features in AG2.
Imports
import os
import nest_asyncio
from autogen.agentchat import UserProxyAgent
from autogen.agents import WebSurferAgent
nest_asyncio.apply()
Configure WebSurferAgent with Crawl4AI
The only difference from the previous example is that the web_tool
parameter must be set to crawl4ai
in order for the Crawl4AITool
to be used.
config_list = [{"model": "gpt-4o-mini", "api_key": os.environ["OPENAI_API_KEY"]}]
llm_config = {
"config_list": config_list,
}
user_proxy = UserProxyAgent(name="user_proxy", human_input_mode="NEVER")
websurfer = WebSurferAgent(name="WebSurfer", llm_config=llm_config, web_tool="crawl4ai")
websurfer_tools = websurfer.tools
# WebSurferAgent has a list of tools which are registered for LLM
# We need to register the tools for execution with the UserProxyAgent
for tool in websurfer_tools:
tool.register_for_execution(user_proxy)
user_proxy.initiate_chat(
recipient=websurfer,
message="Get info from https://docs.ag2.ai/docs/Home",
max_turns=2,
)
user_proxy (to WebSurfer):
Get info from https://docs.ag2.ai/docs/Home
--------------------------------------------------------------------------------
>>>>>>>> USING AUTO REPLY...
WebSurfer (to user_proxy):
***** Suggested tool call (call_UvcLMFR8osM9AsyxVdmzgmBs): crawl4ai *****
Arguments:
{"url":"https://docs.ag2.ai/docs/Home","instruction":"Extract the main sections and any key information such as features, usage guidelines, and any other relevant details."}
*************************************************************************
--------------------------------------------------------------------------------
>>>>>>>> EXECUTING FUNCTION crawl4ai...
Call ID: call_UvcLMFR8osM9AsyxVdmzgmBs
Input arguments: {'url': 'https://docs.ag2.ai/docs/Home', 'instruction': 'Extract the main sections and any key information such as features, usage guidelines, and any other relevant details.'}
[INIT].... → Crawl4AI 0.4.247
[FETCH]... ↓ https://docs.ag2.ai/docs/Home... | Status: True | Time: 1.36s
[SCRAPE].. ◆ Processed https://docs.ag2.ai/docs/Home... | Time: 47ms
INFO:httpx:HTTP Request: GET https://raw.githubusercontent.com/BerriAI/litellm/main/model_prices_and_context_window.json "HTTP/1.1 200 OK"
/Users/robert/projects/ag2/.venv-crawl4ai/lib/python3.11/site-packages/pydantic/_internal/_config.py:345: UserWarning: Valid config keys have changed in V2:
* 'fields' has been removed
warnings.warn(message, UserWarning)
14:23:43 - LiteLLM:INFO: utils.py:2825 -
LiteLLM completion() model= gpt-4o-mini; provider = openai
INFO:LiteLLM:
LiteLLM completion() model= gpt-4o-mini; provider = openai
INFO:httpx:HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK"
14:23:57 - LiteLLM:INFO: utils.py:1030 - Wrapper: Completed Call, calling success_handler
INFO:LiteLLM:Wrapper: Completed Call, calling success_handler
[EXTRACT]. ■ Completed for https://docs.ag2.ai/docs/Home... | Time: 15.169699541991577s
[COMPLETE] ● https://docs.ag2.ai/docs/Home... | Status: True | Total: 16.59s
user_proxy (to WebSurfer):
***** Response from calling tool (call_UvcLMFR8osM9AsyxVdmzgmBs) *****
[
{
"index": 0,
"tags": [
"introduction"
],
"content": [
"# AG2",
"The Open Source Agent OS"
],
"error": false
},
{
"index": 1,
"tags": [
"getting_started"
],
"content": [
"[Getting Started - 3 Minute](https://docs.ag2.ai/docs/</docs/user-guide/quick-start>)"
],
"error": false
},
{
"index": 2,
"tags": [
"key_features"
],
"content": [
"Key Features",
"**Multi-Agent Conversation Framework**",
"AG2 provides multi-agent conversation framework as a high-level abstraction. With this framework, one can conveniently build LLM workflows.",
"**Easily Build Diverse Applications**",
"AG2 offers a collection of working systems spanning a wide range of applications from various domains and complexities.",
"**Enhanced LLM Inference & Optimization**",
"AG2 supports enhanced LLM inference APIs, which can be used to improve inference performance and reduce cost."
],
"error": false
},
{
"index": 3,
"tags": [
"explore_content"
],
"content": [
"## [Quick StartStart building your AG2 application.](https://docs.ag2.ai/docs/</docs/user-guide/quick-start>)",
"## [ConceptsWork through the key concepts of AG2 including ConversableAgent, GroupChat, Swarm, and tools.](https://docs.ag2.ai/docs/</docs/user-guide/basic-concepts/installing-ag2>)",
"## [Advanced ConceptsAdvance to RAG, Code Execution, and more complex GroupChats and Swarms.](https://docs.ag2.ai/docs/</docs/user-guide/advanced-concepts>)",
"## [Use CasesTry out use case workflows including Customer Service, Travel Planning, and Game Design.](https://docs.ag2.ai/docs/</docs/use-cases/use-cases>)",
"## [Notebook ExamplesA collection of interactive notebooks across all AG2 topics.](https://docs.ag2.ai/docs/</docs/use-cases/notebooks/Notebooks>)",
"## [API ReferenceDelve into the AG2 API reference.](https://docs.ag2.ai/docs/</docs/api-reference>)",
"## [How to ContributeGet involved with AG2 by adding what you need and making the framework even better!](https://docs.ag2.ai/docs/</contributor-guide/contributing>)"
],
"error": false
},
{
"index": 4,
"tags": [
"popular_resources"
],
"content": [
"Popular resources",
"[Foundation Capital Interview with Dr. Chi Wang](https://docs.ag2.ai/docs/<https:/www.youtube.com/watch?v=RLwyXRVvlNk>)",
"[Learn AG2 on DeepLearningAI](https://docs.ag2.ai/docs/<https:/www.youtube.com/watch?v=TBNTH-fwGPE>)"
],
"error": false
}
]
**********************************************************************
--------------------------------------------------------------------------------
>>>>>>>> USING AUTO REPLY...
INFO:httpx:HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK"
WebSurfer (to user_proxy):
Here is the extracted information from the AG2 documentation website:
### Introduction
- **AG2**: The Open Source Agent OS
### Getting Started
- [Quick Start - 3 Minute Guide](https://docs.ag2.ai/docs/user-guide/quick-start)
### Key Features
1. **Multi-Agent Conversation Framework**: AG2 provides a framework for multi-agent conversations, allowing users to build LLM workflows conveniently.
2. **Easily Build Diverse Applications**: AG2 comes with a collection of systems that cater to a range of applications across various domains and complexities.
3. **Enhanced LLM Inference & Optimization**: The platform supports enhanced LLM inference APIs, improving performance and reducing costs.
### Explore Content
- [Quick Start: Start building your AG2 application.](https://docs.ag2.ai/docs/user-guide/quick-start)
- [Concepts: Learn about key concepts including ConversableAgent, GroupChat, Swarm, and tools.](https://docs.ag2.ai/docs/user-guide/basic-concepts/installing-ag2)
- [Advanced Concepts: Explore topics such as RAG, Code Execution, and complex GroupChats and Swarms.](https://docs.ag2.ai/docs/user-guide/advanced-concepts)
- [Use Cases: Experiment with workflows in areas like Customer Service, Travel Planning, and Game Design.](https://docs.ag2.ai/docs/use-cases/use-cases)
- [Notebook Examples: Access a collection of interactive notebooks covering all AG2 topics.](https://docs.ag2.ai/docs/use-cases/notebooks/Notebooks)
- [API Reference: Detailed exploration of the AG2 API reference.](https://docs.ag2.ai/docs/api-reference)
- [How to Contribute: Guidelines for getting involved with AG2 and enhancing the framework.](https://docs.ag2.ai/docs/contributor-guide/contributing)
### Popular Resources
...
This summary covers the main sections, key features, links to further exploration, and resources available in the documentation.
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Conclusion
In this post, we’ve shown how to boost your agents with web browsing abilities using the WebSurferAgent
. By using tools like BrowserUseTool
and Crawl4AITool
, your agents can easily fetch real-time information from the web. This makes your agents more useful and flexible, whether you’re getting data from specific pages or gathering info across different topics. With these tools, AG2 helps you create smarter agents that can navigate the web and bring back the details you need with minimal effort.