# Hugging Face LLM Example with LangChain Go

This example demonstrates how to use the LangChain Go library to interact with Hugging Face's language models. It's a simple and fun way to generate text using various models hosted on the Hugging Face platform.

## What This Example Does

1. **Sets up a Hugging Face LLM Client**: 
   - The example shows how to create a client for Hugging Face's language models.
   - It provides options to use a custom token and model or use default settings.

2. **Generates Text**:
   - The script sends a prompt to the language model asking for a company name that makes colorful socks.
   - It demonstrates how to use different generation options like specifying a model (in this case, "gpt2").

3. **Handles Responses**:
   - The generated text is printed to the console.
   - Any errors during the process are properly handled and logged.

## Key Features

- **Flexibility in Model Selection**: You can easily switch between different Hugging Face models.
- **Customizable Generation Options**: The example shows how to use options like `WithModel`, and comments out additional options like `WithTopK`, `WithTopP`, and `WithSeed` for further customization.
- **Error Handling**: Demonstrates proper error checking and logging.

## How to Use

1. Ensure you have the necessary dependencies installed.
2. Optionally, set up your Hugging Face API token as an environment variable.
3. Run the script to see a generated company name for a colorful sock company!

This example is perfect for anyone looking to get started with LangChain Go and Hugging Face's language models. It's a springboard for more complex applications and experiments with different models and prompts. Have fun generating creative company names!
