LLMChain to trigger a state variable change in the application

[levi-katarok]

Hello all! I've been working with langchain and llms pretty heavily recently. I'm wondering if anyone knows how/if its possible in a reliable sense to enable a model to make a change to a state variable. For example I have a conversational bot that has a lists of steps it tries to guide the conversation in. I want it to also at some point either return a very direct "Conversation_over" which I can listen for and then trigger the window to close on my front end is there a better way to do this with agents any functions.

Any help is greatly appreciated!

[dosubot[bot]]

🤖

Hello!

From your description, it seems like you want to use the output of the language model to trigger a state change in your application. While LangChain does support state management within its language models, it doesn't provide a direct mechanism to trigger state variable changes from the language model's output.

However, you can implement this functionality in your application. You can listen for a specific output from the language model (like "Conversation_over") and then trigger the desired state change in your application. Here's a simple example of how you might do this:

def handle_model_output(output):
    if output == "Conversation_over":
        # Trigger state change
        close_window()

# Run the language model
output = run_model(input)
handle_model_output(output)

In this example, run_model(input) is a function that runs the language model with the given input and returns the output. handle_model_output(output) is a function that checks if the output is "Conversation_over" and, if so, triggers the state change.

This is a simple example and your actual implementation might be more complex, depending on your application's requirements. But the basic idea is the same: listen for a specific output from the language model and trigger a state change in response.

I hope this helps! If you have any other questions, feel free to ask.

Sources

• libs/langchain/langchain/cache.py
• libs/langchain/tests/unit_tests/chains/test_conversation.py

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