gpt4-sandbox / app.py
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Add app.py and requirements
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import gradio as gr
import openai
openai.api_key = "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"
default_system_message = {"role": "system", "content": "You are a brilliant, helpful assistant, always providing answers to the best of your knowledge. If you are unsure of the answer, you indicate it to the user."}
def get_completion(model, user_message, message_history, chatlog_history, temperature, maximum_length, top_p, frequency_penalty, presence_penalty):
new_history_row = {"role": "user", "content": user_message}
updated_message_history = message_history + [new_history_row]
completion = openai.ChatCompletion.create(
model=model,
messages=updated_message_history,
temperature=temperature,
max_tokens=maximum_length,
top_p=top_p,
frequency_penalty=frequency_penalty,
presence_penalty=presence_penalty,
)
assistant_message = completion["choices"][0]["message"]["content"]
new_history_row = {"role": "assistant", "content": assistant_message}
updated_message_history = updated_message_history + [new_history_row]
updated_chatlog_history = chatlog_history + [(user_message, assistant_message)]
token_count = completion["usage"]["total_tokens"]
return "", updated_message_history, updated_chatlog_history, updated_chatlog_history, token_count
def retry_completion(model, message_history, chatlog_history, temperature, maximum_length, top_p, frequency_penalty, presence_penalty):
# get latest user message
user_message = chatlog_history[-1][0]
# delete latest entries from chatlog history
updated_chatlog_history = chatlog_history[:-1]
# delete latest assistant message from message_history
updated_message_history = message_history[:-1]
completion = openai.ChatCompletion.create(
model=model,
messages=updated_message_history,
temperature=temperature,
max_tokens=maximum_length,
top_p=top_p,
frequency_penalty=frequency_penalty,
presence_penalty=presence_penalty,
)
assistant_message = completion["choices"][0]["message"]["content"]
new_history_row = {"role": "assistant", "content": assistant_message}
updated_message_history = updated_message_history + [new_history_row]
updated_chatlog_history = updated_chatlog_history + [(user_message, assistant_message)]
token_count = completion["usage"]["total_tokens"]
return "", updated_message_history, updated_chatlog_history, updated_chatlog_history, token_count
def reset_chat():
return "", [default_system_message], [], [], 0
theme = gr.themes.Monochrome()
with gr.Blocks(theme=theme) as app:
message_history = gr.State([default_system_message])
chatlog_history = gr.State([])
with gr.Row():
with gr.Column(scale=4):
chatbot = gr.Chatbot(label="Chat").style(height=600)
with gr.Column(scale=1):
# model = gr.Textbox(lines=3, value="You are a brilliant, helpful assistant, always providing answers to the best of your knowledge. If you are unsure of the answer, you indicate it to the user.", interactive=True, label="System")
model = gr.Dropdown(choices=["gpt-3.5-turbo", "gpt-4", "gpt-4-32k"], value="gpt-3.5-turbo", interactive=True, label="Model")
temperature = gr.Slider(minimum=0, maximum=1, step=0.05, value=0.5, interactive=True, label="Temperature")
maximum_length = gr.Slider(minimum=0, maximum=2048, step=64, value=256, interactive=True, label="Maximum length")
top_p = gr.Slider(minimum=0, maximum=1, step=0.01, value=1, interactive=True, label="Top P")
frequency_penalty = gr.Slider(minimum=0, maximum=2, step=0.01, value=0, interactive=True, label="Frequency penalty")
presence_penalty = gr.Slider(minimum=0, maximum=2, step=0.01, value=0, interactive=True, label="Presence penalty")
token_count = gr.Number(interactive=False, label="Token Count")
with gr.Row():
user_message = gr.Textbox(label="Message")
with gr.Row():
reset_button = gr.Button("Reset Chat")
retry_button = gr.Button("Retry")
user_message.submit(get_completion, inputs=[model, user_message, message_history, chatlog_history, temperature, maximum_length, top_p, frequency_penalty, presence_penalty], outputs=[user_message, message_history, chatlog_history, chatbot, token_count])
retry_button.click(retry_completion, inputs=[model, message_history, chatlog_history, temperature, maximum_length, top_p, frequency_penalty, presence_penalty], outputs=[user_message, message_history, chatlog_history, chatbot, token_count])
reset_button.click(reset_chat, inputs=[], outputs=[user_message, message_history, chatlog_history, chatbot, token_count])
app.launch()
# app.launch(auth=("admin", "C%nc6mrn8*BCwQF9HhH4CX35d7Q**eQY"))