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| from openai import OpenAI | |
| import gradio as gr | |
| api_key = "sk-proj-EDY3jlWEqNq4xkGk0inbT3BlbkFJKbN26l1g02vd16B11Ksb" | |
| client = OpenAI(api_key=api_key) | |
| def predict(message, history): | |
| history_openai_format = [] | |
| for human, assistant in history: | |
| history_openai_format.append({"role": "user", "content": human }) | |
| history_openai_format.append({"role": "assistant", "content":assistant}) | |
| history_openai_format.append({"role": "user", "content": message}) | |
| response = client.chat.completions.create(model='gpt-3.5-turbo', | |
| messages= history_openai_format, | |
| temperature=1.0, | |
| stream=True) | |
| partial_message = "" | |
| for chunk in response: | |
| if chunk.choices[0].delta.content is not None: | |
| partial_message = partial_message + chunk.choices[0].delta.content | |
| yield partial_message | |
| gr.ChatInterface(predict).launch() |