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Update app.py
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app.py
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@@ -2,17 +2,7 @@ import os
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import openai
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import gradio as gr
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#openai.api_key = "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"
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#openai.api_key = "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"
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openai.api_key ="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"
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#openai.api_key = "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"
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#openai.api_key = "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"
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#openai.api_key = "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"
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#openai.api_key = "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"
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#openai.api_key = "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"
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#openai.api_key = "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"
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#openai.api_key = "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"
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#openai.api_key = "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"
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start_sequence = "\nAI:"
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restart_sequence = "\nHuman: "
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@@ -21,14 +11,11 @@ def predict(input, history=[]):
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s = list(sum(history, ()))
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s.append(input)
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# 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"
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# \n\nHuman: Hello, who are you?\nAI: I am an AI created by OpenAI. How can I help you today?\nHuman: "
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response = openai.Completion.create(
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model="text-davinci-003",
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#model="text-curie-001",
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prompt= str(s),
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temperature=0.9,
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max_tokens=
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top_p=1,
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frequency_penalty=0,
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presence_penalty=0.6,
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@@ -39,8 +26,4 @@ def predict(input, history=[]):
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return history, history
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gr.
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gr.Interface(fn=predict,
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inputs=["text",'state'],
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outputs=["chatbot",'state']).launch()
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import openai
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import gradio as gr
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openai.api_key ="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"
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start_sequence = "\nAI:"
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restart_sequence = "\nHuman: "
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s = list(sum(history, ()))
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s.append(input)
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response = openai.Completion.create(
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model="text-davinci-003",
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prompt= str(s),
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temperature=0.9,
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max_tokens=250,
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top_p=1,
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frequency_penalty=0,
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presence_penalty=0.6,
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return history, history
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gr.Interface(fn=predict, inputs=["text",'state'], outputs=["chatbot",'state']).launch()
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