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#!/usr/bin/env python
# coding: utf-8
# In[ ]:
import os
import openai
import gradio as gr
#openai.api_key = "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"
openai.api_key = "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"
start_sequence = "\nAI:"
restart_sequence = "\nHuman: "
def predict(input,initial_prompt, history=[]):
s = list(sum(history, ()))
s.append(input)
# initial_prompt="The following is a conversation with an AI movie recommendation assistant. The assistant is helpful, creative, clever, and very friendly.Along with movie recommendation it also talks about general topics"
# \n\nHuman: Hello, who are you?\nAI: I am an AI created by OpenAI. How can I help you today?\nHuman: "
response = openai.Completion.create(
model="text-davinci-003",
prompt= initial_prompt + "\n" + str(s),
temperature=0.9,
max_tokens=150,
top_p=1,
frequency_penalty=0,
presence_penalty=0.6,
stop=[" Human:", " AI:"])
# tokenize the new input sentence
response2 = response["choices"][0]["text"]
history.append((input, response2))
return history, history
gr.Interface(fn=predict,
inputs=["text","text",'state'],
outputs=["chatbot",'state']).launch()
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