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| import subprocess | |
| import gradio as gr | |
| from transformers import TFAutoModelForCausalLM, AutoTokenizer | |
| import openai | |
| from dotenv import load_dotenv | |
| import os | |
| load_dotenv() # load environment variables from .env file | |
| api_key = os.getenv("OPENAI_API_KEY") # access the value of the OPENAI_API_KEY environment variable | |
| def openai_chat(prompt): | |
| completions = openai.Completion.create(engine="text-davinci-003", prompt=prompt, max_tokens=1024, n=1, temperature=0.5,) | |
| message = completions.choices[0].text | |
| return message.strip() | |
| def chatbot(talk_to_chatsherman, history=[]): | |
| output = openai_chat(talk_to_chatsherman) | |
| history.append((talk_to_chatsherman, output)) | |
| return history, history | |
| title = "My Chatbot Title" | |
| description = "This is a chatbot powered by OpenAI's GPT-3 model." | |
| examples = [ | |
| ["Hello, how are you?", []], | |
| ["What's the meaning of life?", []], | |
| ["Tell me a joke.", []] | |
| ] | |
| inputs = [gr.inputs.Textbox(label="Talk to ChatSherman: "), "state"] | |
| outputs = ["chatbot", "state"] | |
| interface = gr.Interface(fn=chatbot, inputs=inputs, outputs=outputs, title=title, description=description, examples=examples) | |
| interface.launch(debug=True) |