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from huggingface_hub import InferenceClient | |
import gradio as gr | |
client = InferenceClient("mistralai/Mistral-7B-Instruct-v0.2") | |
def format_prompt(message, history, system_prompt=None): | |
prompt = "<s>" | |
for user_prompt, bot_response in history: | |
prompt += f"[INST] {user_prompt} [/INST]" | |
prompt += f" {bot_response}</s> " | |
if system_prompt: | |
prompt += f"[SYS] {system_prompt} [/SYS]" | |
prompt += f"[INST] {message} [/INST]" | |
return prompt | |
def generate( | |
prompt, history, system_prompt=None, temperature=0.2, max_new_tokens=1024, top_p=0.95, repetition_penalty=1.0, | |
): | |
temperature = float(temperature) | |
if temperature < 1e-2: | |
temperature = 1e-2 | |
top_p = float(top_p) | |
generate_kwargs = dict( | |
temperature=temperature, | |
max_new_tokens=max_new_tokens, | |
top_p=top_p, | |
repetition_penalty=repetition_penalty, | |
do_sample=True, | |
seed=42, | |
) | |
formatted_prompt = format_prompt(prompt, history, system_prompt) | |
stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False) | |
output = "" | |
for response in stream: | |
output += response.token.text | |
yield output | |
return output | |
mychatbot = gr.Chatbot( | |
avatar_images=["./user.png", "./botm.png"], bubble_full_width=False, show_label=False, show_copy_button=True, likeable=True,) | |
demo = gr.ChatInterface( | |
fn=generate, | |
chatbot=mychatbot, | |
title="Hello! I'm a AI Chatbot by Exnrt.π How can I help you today?", | |
css="body { background-color: inherit; overflow-x:hidden;}" | |
":root {--color-accent: transparent !important; --color-accent-soft:transparent !important; --code-background-fill:black !important; --body-text-color:white !important;}" | |
"#component-2 {background:#ffffff1a; display:contents;}" | |
"div#component-0 { height: auto !important;}" | |
".gradio-container.gradio-container-4-8-0.svelte-1kyws56.app {max-width: 100% !important;}" | |
"gradio-app {background: linear-gradient(134deg,#00425e 0%,#001a3f 43%,#421438 77%) !important; background-attachment: fixed !important; background-position: top;}" | |
".panel.svelte-vt1mxs {background: transparent; padding:0;}" | |
".block.svelte-90oupt { background: transparent; border-color: transparent;}" | |
".bot.svelte-12dsd9j.svelte-12dsd9j.svelte-12dsd9j { background: #ffffff1a; border-color: transparent; color: white;}" | |
".user.svelte-12dsd9j.svelte-12dsd9j.svelte-12dsd9j { background: #ffffff1a; border-color: transparent; color: white; padding: 10px 18px;}" | |
"div.svelte-iyf88w{ background: #cc98d445; border-color: transparent; border-radius: 25px;}" | |
"textarea.scroll-hide.svelte-1f354aw { background: transparent; color: #fff !important;}" | |
".primary.svelte-cmf5ev { background: transparent; color: white;}" | |
".primary.svelte-cmf5ev:hover { background: transparent; color: white;}" | |
"button#component-8 { display: none; position: absolute; margin-top: 60px; border-radius: 25px;}" | |
"div#component-9 { max-width: fit-content; margin-left: auto; margin-right: auto;}" | |
"button#component-10, button#component-11, button#component-12 { flex: none; background: #ffffff1a; border: none; color: white; margin-right: auto; margin-left: auto; border-radius: 9px; min-width: fit-content;}" | |
".share-button.svelte-12dsd9j { display: none;}" | |
"footer.svelte-mpyp5e { display: none !important;}" | |
".message-buttons-bubble.svelte-12dsd9j.svelte-12dsd9j.svelte-12dsd9j { border-color: #31546E; background: #31546E;}" | |
".bubble-wrap.svelte-12dsd9j.svelte-12dsd9j.svelte-12dsd9j {padding: 0;}" | |
".prose h1 { color: white !important; font-size: 16px !important; font-weight: normal !important; background: #ffffff1a; padding: 20px; border-radius: 20px; width: 90%; margin-left: auto !important; margin-right: auto !important;}" | |
".toast-wrap.svelte-pu0yf1 { display:none !important;}" | |
".scroll-hide { scrollbar-width: auto !important;}" | |
".main svelte-1kyws56 {max-width: 800px; align-self: center;}" | |
"div#component-4 {max-width: 650px; margin-left: auto; margin-right: auto;}" | |
"body::-webkit-scrollbar { display: none;}" | |
) | |
demo.queue().launch(show_api=False) |