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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() | |