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import os | |
import gradio as gr | |
import openai | |
openai.api_key = os.environ['OPENAI_API_KEY'] | |
user_db = {os.environ['username1']: os.environ['password1'], os.environ['username2']: os.environ['password2'], os.environ['username3']: os.environ['password3']} | |
def textGPT(text): | |
#messages = [{"role": "system", "content": 'You are a coding assistant.'}] | |
cuda_codes = "Translate this CUDA code into HIP code:\n" + text + "\n\n###" | |
#messages.append({"role": "user", "content": cuda_codes}) | |
response = openai.Completion.create(model="davinci:ft-zhaoyi-2023-06-21-07-18-01", prompt=cuda_codes, stop="###") | |
hip_codes = response['choices'][0]['text'] | |
#hip_codes = system_message["content"] | |
return hip_codes | |
text = gr.Interface(fn=textGPT, inputs="text", outputs="text") | |
demo = gr.TabbedInterface([text], [ "HipifyPlus"]) | |
if __name__ == "__main__": | |
demo.launch(enable_queue=False, auth=lambda u, p: user_db.get(u) == p, | |
auth_message="This is not designed to be used publicly as it links to a personal openAI API. However, you can copy my code and create your own multi-functional ChatGPT with your unique ID and password by utilizing the 'Repository secrets' feature in huggingface.") | |
#demo.launch() | |