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import os
import gradio as gr
import openai
openai.api_base = os.environ.get("OPENAI_API_BASE")
openai.api_key = os.environ.get("OPENAI_API_KEY")
MODEL_TYPE = os.environ.get("MODEL_TYPE")
def make_prediction(history, max_tokens=None, temperature=None, top_p=None):
messages = []
for idx, (user, bot) in enumerate(history):
messages.append({"role": "user", "content": user})
if idx != len(history) - 1:
messages.append({"role": "assistant", "content": bot})
# print(messages)
completion = openai.ChatCompletion.create(model=MODEL_TYPE, messages=messages, max_tokens=max_tokens, temperature=temperature, top_p=top_p, stream=True)
for chunk in completion:
content = chunk["choices"][0]["delta"].get("content", "")
if content:
yield content
def clear_chat(chat_history_state, chat_message):
chat_history_state = []
chat_message = ''
return chat_history_state, chat_message
def user(message, history):
history = history or []
# Append the user's message to the conversation history
history.append([message, ""])
return "", history
def chat(history, max_tokens, temperature, top_p):
history = history or []
prediction = make_prediction(
history,
max_tokens=max_tokens,
temperature=temperature,
top_p=top_p
)
for delta_text in prediction:
history[-1][1] += delta_text
# stream the response
yield history, history, ""
start_message = ""
with gr.Blocks() as demo:
with gr.Tab("Chatbot"):
gr.Markdown("# 🎇 OpenChat 3.5 Playground 💬 ")
chatbot = gr.Chatbot().style(height=500)
with gr.Row():
message = gr.Textbox(
label="What do you want to chat about?",
placeholder="Ask me anything.",
lines=3,
)
with gr.Row():
submit = gr.Button(value="Send message", variant="secondary").style(full_width=True)
clear = gr.Button(value="New topic", variant="secondary").style(full_width=False)
stop = gr.Button(value="Stop", variant="secondary").style(full_width=False)
with gr.Row():
with gr.Column():
max_tokens = gr.Slider(32, 4096, label="Max Tokens", step=32, value=1024)
temperature = gr.Slider(0.0, 1.0, label="Temperature", step=0.1, value=0.5)
top_p = gr.Slider(0.0, 1.0, label="Top P", step=0.05, value=1.0)
chat_history_state = gr.State()
clear.click(clear_chat, inputs=[chat_history_state, message], outputs=[chat_history_state, message], queue=False)
clear.click(lambda: None, None, chatbot, queue=False)
submit_click_event = submit.click(
fn=user, inputs=[message, chat_history_state], outputs=[message, chat_history_state], queue=True
).then(
fn=chat, inputs=[chat_history_state, max_tokens, temperature, top_p], outputs=[chat_history_state, chatbot, message], queue=True
)
stop.click(fn=None, inputs=None, outputs=None, cancels=[submit_click_event], queue=False)
demo.queue(max_size=128, concurrency_count=48).launch(debug=True, server_name="0.0.0.0", server_port=7860)
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