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Zapier LLM Example with LangChain Go

examples/zapier-llm-example/README.md

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Zapier LLM Example with LangChain Go

Hello there! 👋 This example demonstrates how to use LangChain Go to create an AI agent that can interact with Zapier's Natural Language Actions (NLA) API. It's a fantastic way to combine the power of language models with the automation capabilities of Zapier!

What This Example Does

This example showcases the following:

  1. Setting up an OpenAI Language Model: It initializes an OpenAI LLM, which will be used as the brain of our agent.

  2. Integrating Zapier NLA Tools: The code fetches all available Zapier NLA tools using your Zapier API key.

  3. Creating an AI Agent: It sets up an agent using the "Zero Shot React Description" approach, which allows the agent to decide how to use tools based on their descriptions.

  4. Executing a Task: The agent is given a specific task: "Get the last email from [email protected]". It will use the Zapier tools to accomplish this task.

  5. Displaying Results: Finally, it prints out the agent's response to the given task.

How to Use

  1. Make sure you have your OpenAI API key set in your environment variables.
  2. Set your Zapier NLA API key in the ZAPIER_NLA_API_KEY environment variable.
  3. Run the example, and watch as the AI agent uses Zapier tools to fetch the last email from [email protected]!

This example is a great starting point for building more complex AI-powered automation workflows that leverage both language models and Zapier's vast ecosystem of app integrations.

Happy coding! 🚀