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StMarkSchool/StMarkFinancialAI

sourceHugging Faceapache-2.0updated 2y agoView on Hugging Face
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util.py49 linesDownload Raw Back to root
1from openai import OpenAI2def print_ascii_splash() : # Print ASCII Art for the initial splash screen3    print(r'''4 _       __     __                             __           _______                        _       __   __    __    __  ___5| |     / /__  / /________  ____ ___  ___     / /_____     / ____(_)___  ____ _____  _____(_)___ _/ /  / /   / /   /  |/  /6| | /| / / _ \/ / ___/ __ \/ __ `__ \/ _ \   / __/ __ \   / /_  / / __ \/ __ `/ __ \/ ___/ / __ `/ /  / /   / /   / /|_/ / 7| |/ |/ /  __/ / /__/ /_/ / / / / / /  __/  / /_/ /_/ /  / __/ / / / / / /_/ / / / / /__/ / /_/ / /  / /___/ /___/ /  / /  8|__/|__/\___/_/\___/\____/_/ /_/ /_/\___/   \__/\____/  /_/   /_/_/ /_/\__,_/_/ /_/\___/_/\__,_/_/  /_____/_____/_/  /_/   9                                                                                                                           10 ''')11 12def load_model() : 13    client = OpenAI()14    return client15 16def get_response(question, client, history = None, model = "gpt-4o-mini") : 17    if history is None : 18        history = [19                {"role": "system", 20                "content": "You are a personal finance assistant working with K-12 students, you should ONLY answer questions related to personal finance, finance, economics, and strictly refrain from answering any other questions. Structure your input to multiple steps, but be as concise as possible. Use simple English fit for K-12 students. Cite, and link to all resources used."21                },22 23                {24                    "role": "user",25                    "content": question26                }27                ,28            ]29    else : 30        added_dict = {31            "role": "user",32            "content": question33        }34        history.append(added_dict)35    response = client.chat.completions.create(36        model = model,37        messages= history38    )39    response = response.choices[0].message.content40    added_dict = {41        "role": "assistant",42        "content": response43    }44    history.append(added_dict)45    return response, history46 47def clear_memory(history) : 48    history =  None49    return history