A simple Langfuse integration script to work with OpenAI-compatible LLM APIs (I'm using a local LM Studio dev server in this case)

langfuse_prompt.py

from langfuse.openai import openai
import os

def init_connection():
    public_key = ".."
    private_key = ".."
    os.environ["LANGFUSE_PUBLIC_KEY"] = public_key
    os.environ["LANGFUSE_SECRET_KEY"] = private_key
    os.environ["LANGFUSE_HOST"] = "http://localhost:3000"  # For self-hosted

def init_llm():
    local_model = "claudegpt-code-logic-debugger-v0.1" # or whatever model you have

    llm_client = openai.OpenAI(base_url="http://127.0.0.1:1234/v1", api_key="lm-studio")

    completion = llm_client.chat.completions.create(
        model=local_model,  # Replace with your loaded model's identifier
        messages=[
            {"role": "system", "content": "You are a helpful assistant."},
            {"role": "user", "content": "What is the origin of hello world?"}
        ],
        temperature=0.7
    )
    print(completion.choices[0].message.content)


if __name__ == '__main__':
    init_connection()
    init_llm()