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import os
import openai
import gradio as gr
openai.api_key = "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"
start_sequence = "\nAI:"
restart_sequence = "\nHuman:"
def predict(input, history=[]):
s = list(sum(history, ()))
s.append(input)
response = openai.Completion.create(
model_name="gpt-3.5-turbo",
prompt= str(s),
temperature=0.9,
max_tokens=1050,
top_p=1,
frequency_penalty=0,
presence_penalty=0.6,
stop=[" Human:", " AI:"])
response2 = response["choices"][0]["text"]
history.append((input, response2))
return history, history
gr.Markdown("heyoo")
gr.Interface(fn=predict,
inputs=["text",'state'],
outputs=["chatbot",'state']).launch()
#def get_model_reply(user_input, context=[]):
# context+=[user_input]
# completion = openai.Completion.create(
# engine="gpt-3.5-turbo", # one of the most capable models available
# prompt='\\n'.join([f"I am {role}.", *context])[:4096],
# max_tokens = 1048,
# temperature = 0.9,
# top_p = 1,
# frequency_penalty=0,
# presence_penalty=0.6,
# )
# append response to context
# response = completion.choices[0].text.strip('\\n')
# context += [response]
# list of (user, bot) responses. We will use this format later
# responses = [(u,b) for u,b in zip(context[::2], context[1::2])]
# return responses, context
# ```
# defines a basic dialog interface using Gradio
#with gr.Blocks() as dialog_app:
# chatbot = gr.Chatbot() # dedicated "chatbot" component
# state = gr.State([]) # session state that persists across multiple submits
# with gr.Row():
# txt = gr.Textbox(
# show_label=False,
# placeholder="Enter text and press enter"
# ).style(container=False)
# txt.submit(get_model_reply, [txt, state], [chatbot, state])
#dialog_app.launch()
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