Building applications using Large Language Models (LLMs) has never been easier! With langchain_gpt4free, an open-source project, you can leverage free access to GPT-3.5. In this guide, we will walk you through installation, usage, and troubleshooting tips to help you smoothly navigate this powerful tool.

Installation

To begin your journey with langchain_gpt4free, you need to install it using the following command:

pip install git+https://github.com/MIDORIBIN/langchain-gpt4free.git

Usage

Once you have installed langchain_gpt4free, you can start using it to interact with the model. Let’s break down the example code below:

from g4f import Provider, models
from langchain.llms.base import LLM
from langchain_g4f import G4FLLM

def main():
    llm: LLM = G4FLLM(
        model=models.gpt_35_turbo,
        provider=Provider.Aichat,
    )
    res = llm("hello")
    print(res)  # Hello! How can I assist you today?

if __name__ == "__main__":
    main()

Understanding the Code

Imagine you’re a chef in a kitchen, preparing a dish using a specific recipe (or model). Here’s how the analogy fits:

• Ingredients: The inputs like “hello” are your ingredients that you mix into your recipe for flavor.
• Recipe Book: The ‘G4FLLM’ acts like a recipe book that tells you how to combine those ingredients and what to expect in return.
• Chef’s Assistant: The output, in this case, “Hello! How can I assist you today?” is your assistant suggesting how you might want to proceed with your cooking.

To use this code, select the appropriate model and provider, set up the LLM, and send in your query to see the results!

Troubleshooting

If you run into any issues during installation or usage, here’s what you can do:

• Ensure you have the latest version of Python installed, as it may cause compatibility issues.
• Check your internet connection if the installation fails, as it fetches the package remotely.
• If Python throws an error while executing the script, confirm that your indentation is correct, as Python is sensitive to spacing.

For more insights, updates, or to collaborate on AI development projects, stay connected with fxis.ai.

Support and Contributing

If you encounter bugs or need support, don’t hesitate to use the GitHub Issues page to report them. Be sure to provide as much detail as possible. If you want to contribute to the project, follow these steps:

1. Fork the project repository.
2. Clone the forked repository to your local machine.
3. Make necessary changes.
4. Commit the changes and push them back to your forked repository.
5. Create a pull request towards the original project repository.

Final Thoughts

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.