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import gradio as gr
from gpt4all import GPT4All
from urllib.request import urlopen
import json
import time
from load_llms import model_choices, llm_intro, load_model
from config import space_hardware
# Construct chatbot
def generate_response(model_name, message, chat_history):
model = load_model(model_name)
response = model.generate(message, max_tokens=100)
chat_history.append((message, response))
return "", chat_history
# Create Gradio UI
with gr.Blocks(
css=".contain { display: flex !important; flex-direction: column !important; }"
"#chatbot { flex-grow: 1 !important; overflow: auto !important; }"
"#col { height: 100% !important; }"
"#submit:hover { background-color: green !important; }"
"#clear { background-color: darkred !important; }",
theme=gr.themes.Soft(font=[gr.themes.GoogleFont("Martel Sans")])
) as demo:
gr.Markdown("# GPT4All Chatbot")
with gr.Row():
with gr.Column(scale=1):
model_dropdown = gr.Dropdown(
choices=model_choices(),
multiselect=False,
type="value",
value="orca-mini-3b-gguf2-q4_0.gguf",
label="LLMs to choose from"
)
explanation = gr.Textbox(label="Model Description", interactive=False, value=llm_intro("orca-mini-3b-gguf2-q4_0.gguf"))
# Link the dropdown with the textbox to update the description based on the selected model
model_dropdown.change(fn=llm_intro, inputs=model_dropdown, outputs=explanation)
gr.Textbox(value=f"{space_hardware()}\n2 vCPU • 16 GB RAM \nFree tier", label="Space Hardware use")
with gr.Column(scale=4, elem_id='col'):
chatbot = gr.Chatbot(label="Chatroom", value=[(None, "How may I help you today?")], elem_id="chatbot")
with gr.Row():
message = gr.Textbox(label="Message", scale=10)
message.submit(generate_response, inputs=[model_dropdown, message, chatbot], outputs=[message, chatbot])
submit_button = gr.Button("Submit", scale=1, elem_id="submit")
submit_button.click(generate_response, inputs=[model_dropdown, message, chatbot], outputs=[message, chatbot])
clear = gr.ClearButton([message, chatbot], elem_id="clear")
# Launch the Gradio app
demo.launch()
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