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import gradio as gr | |
def generate_ielts_essay(prompt): | |
# You may want to customize the max_length and other parameters according to your needs | |
return "Hello " + prompt + "!!" | |
def format_chat_prompt(message, band, chat_history, instruction): | |
prompt = f"System:{instruction}" | |
for turn in chat_history: | |
user_message, bot_message = turn | |
prompt = f"{prompt}\nUser: {user_message}\nAssistant: {bot_message}" | |
prompt = f"{prompt}\nUser: IELTS Writing Band {band} - {message}\nAssistant:" | |
return prompt | |
def respond(message, band, chat_history, instruction, temperature=0.7): | |
prompt = format_chat_prompt(message, band, chat_history, instruction) | |
chat_history = chat_history + [[message, ""]] | |
max_tokens = {6: 100, 7: 200, 8: 300, 9: 400}[int(band)] # Change these values as needed | |
stream = client.generate_stream(prompt, | |
max_new_tokens=max_tokens, | |
stop_sequences=["\nUser:", ""], | |
temperature=temperature) | |
acc_text = "" | |
for idx, response in enumerate(stream): | |
text_token = response.token.text | |
if response.details: | |
return | |
if idx == 0 and text_token.startswith(" "): | |
text_token = text_token[1:] | |
acc_text += text_token | |
last_turn = list(chat_history.pop(-1)) | |
last_turn[-1] += acc_text | |
chat_history = chat_history + [last_turn] | |
yield "", chat_history | |
acc_text = "" | |
with gr.Blocks() as demo: | |
chatbot = gr.Chatbot(height=240) | |
msg = gr.Textbox(label="IELTS Writing Prompt") | |
band = gr.Radio([6, 7, 8, 9], label="Band") | |
with gr.Accordion(label="Advanced options",open=False): | |
system = gr.Textbox(label="System message", lines=2, value="A conversation between a user and an LLM-based AI assistant. The assistant writes IELTS articles of various bands.") | |
temperature = gr.Slider(label="Temperature", minimum=0.1, maximum=1, value=0.7, step=0.1) | |
btn = gr.Button("Submit") | |
clear = gr.ClearButton(components=[msg, chatbot], value="Clear console") | |
btn.click(respond, inputs=[msg, band, chatbot, system], outputs=[msg, chatbot]) | |
msg.submit(respond, inputs=[msg, band, chatbot, system], outputs=[msg, chatbot]) | |
gr.close_all() | |
demo.queue().launch(share=True) | |