> For clean Markdown of any page, append .md to the page URL. > For a complete documentation index, see https://docs.athenaintel.com/python-guides/build-with-agents/llms.txt. > For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.athenaintel.com/_mcp/server. # Build with Agents > Use the General Agent to perform long-running tasks with tool use. This example shows a multi-step workflow with the General Agent, the default agent in [Spaces](https://resources.athenaintel.com/docs/applications/spaces). Key features: * Use prebuilt tools like web browsing and search * Compatible with LangChain message objects * Support for multi-step conversations ### Install Package #### Jupyter Notebook ```python !pip install -U athenaintel ``` #### Terminal/Shell ```bash pip install -U athenaintel ``` ### Set Up Client ```python from athena import GeneralAgentConfig, GeneralAgentRequest from athena.client import Athena from langchain_core.messages import HumanMessage from langchain_core.load import load athena = Athena(api_key="") ``` ### Run the Agent ```python # Enable tools config = GeneralAgentConfig( enabled_tools=["search", "browse"] ) # Create message messages = [{ "type": "human", "content": "Use the search tool to search for information about Athena Intelligence and summarize the results." }] # Get response response = athena.agents.general.invoke( request=GeneralAgentRequest( config=config, messages=messages ) ).messages # Access the response text directly latest_response = response[-1].content ``` ### Continue Conversation Pass the full message list to maintain context between steps. ```python # Add follow-up as LangChain message object new_messages = load(response) + [HumanMessage(content="Tell me more about what you found")] # Get response continued_response = athena.agents.general.invoke( request=GeneralAgentRequest( config=config, messages=new_messages ) ).messages ``` > Use the General Agent to perform long-running tasks with tool use.