Tool Calling Agent
==================

This guide will walk you through creating an agent that can call external tools using the Agentstr SDK, expanding on the concepts from the :doc:`payment_enabled_agent` example.

Step 1: Initialize Your Project
-------------------------------

Start by initializing a new project if you haven't already:

.. code-block:: bash

   agentstr init tool_calling_agent

This sets up a `tool_calling_agent` directory with the necessary structure.

Step 2: Update .env file
------------------------

Update the `tool_calling_agent/.env` file with your LLM information and NWC connection string.

.. code-block:: bash

   LLM_BASE_URL=https://api.openai.com/v1
   LLM_API_KEY=your-api-key
   LLM_MODEL_NAME=gpt-3.5-turbo
   NWC_CONN_STR=nostr+walletconnect://<your-nwc-connection-string>
   MCP_SERVER_PUBKEY=<your-mcp-server-public-key>

.. note::
   - `NWC_CONN_STR` is the default environment variable for `NWCRelay` to enable Nostr Wallet Connect. You can override this by passing a connection string directly to the `NostrClient` constructor.
   - `LLM_BASE_URL`, `LLM_API_KEY`, and `LLM_MODEL_NAME` are the default environment variables for `AgentstrAgent` to enable LLM integration. You can override these by passing them directly to the agent constructor.
   - Replace `<your-mcp-server-key>` with the actual public key of a Nostr MCP server. If you're testing locally, ensure an MCP server is also running locally.
   - You can follow the :doc:`creating_an_mcp_server` guide to set up Nostr MCP server.
   
Step 3: Define Tools for Your Agent
-----------------------------------

Open `tool_calling_agent/main.py` and modify it to include tool calling functionality. You'll need to integrate with the Model Context Protocol (MCP) for tool access.

.. literalinclude:: ../../../getting_started/tool_calling_agent/main.py
   :language: python
   :linenos:

Step 4: Update Test Client
--------------------------

Update `tool_calling_agent/test_client.py` to interact with your tool-enabled agent.

.. literalinclude:: ../../../getting_started/tool_calling_agent/test_client.py
   :language: python
   :linenos:

Step 5: Start a Local Relay
---------------------------

Start a local Nostr relay for testing:

.. code-block:: bash

   agentstr relay start

Keep this running in a separate terminal.

Step 6: Run Your Tool-Enabled Agent
-----------------------------------

Run your agent with tool calling capabilities:

.. code-block:: bash

   python tool_calling_agent/main.py

Step 7: Test Your Agent
-----------------------

Use the test client to interact with your agent and see the tool listing response:

.. code-block:: bash

   python tool_calling_agent/test_client.py

You should see a response indicating the answer to a math question. If you check the MCP Server logs, you'll see that the addition tool was called by the agent.

Feel free to play around with the test client to ask the agent additional questions. Just note that any premium tools will require a Lightning payment.

.. note::
   If you encounter connection issues with the MCP server, ensure the server is running and accessible. Refer to troubleshooting tips in the :doc:`hello_world` guide for general connectivity issues.


Step 8 (Optional): Deploy to the Cloud
--------------------------------------

Deploy your Tool Calling Agent to the cloud for continuous operation and public accessibility. Assuming you are already logged into the Agentstr CLI, follow these steps:

1. **Set your cloud provider**:

   .. code-block:: bash

      export AGENTSTR_PROVIDER=aws  # or gcp, azure

2. **Deploy the agent**:

   .. code-block:: bash

      agentstr deploy -f tool_calling_agent/deploy.yml

   This command packages your agent and deploys it to the specified cloud provider. Ensure your project directory structure is compatible with the deployment requirements.

For more information on cloud deployment and CI/CD, see the :doc:`../cloud_cicd` guide.

Next Steps
----------

- **Expand Tool Integration**: Explore more MCP tools and services to enhance your agent's capabilities. Check out :doc:`../key_concepts/mcp` for advanced integration techniques.
- **Dive into the API**: Learn more about the capabilities of the SDK by exploring the :doc:`../../agentstr` documentation.
- **Explore the Cookbook**: Check out the :doc:`../cookbook` for more advanced use cases and examples.