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import gradio as gr
import torch
from transformers import AutoProcessor, AutoModelForVision2Seq
from web_data import custom_css, header, footer
processor = AutoProcessor.from_pretrained("HuggingFaceTB/SmolVLM-256M-Instruct")
model = AutoModelForVision2Seq.from_pretrained(
"HuggingFaceTB/SmolVLM-256M-Instruct",
torch_dtype=torch.bfloat16,
)
def respond(message, history: list[tuple[str, str]], image, system_message):
messages = [
{
"role": "system",
"content": [
{"type": "text", "text": system_message}
]
},
]
for val in history:
if val[0]:
messages.append({"role": "user", "content": val[0]})
if val[1]:
messages.append({"role": "assistant", "content": val[1]})
user_message = {
"role": "user",
"content": [
{"type": "text", "text": message}
]
}
if image:
user_message['content'].append({"type": "image"})
messages.append(user_message)
prompt = processor.apply_chat_template(messages, add_generation_prompt=True)
if image:
resized_image = image.resize((32, 32))
inputs = processor(text=prompt, images=[resized_image], return_tensors="pt")
else:
inputs = processor(text=prompt, return_tensors="pt")
generated_ids = model.generate(**inputs, max_new_tokens=500)
generated_texts = processor.batch_decode(generated_ids, skip_special_tokens=True)
response = generated_texts[0].split('Assistant:')[-1].strip()
yield response
# ======the code below this section is pure vibing coding======
with gr.Blocks(theme=gr.themes.Glass(), css=custom_css) as demo:
gr.HTML(header)
with gr.Row(variant="panel"):
with gr.Column(scale=1):
with gr.Accordion("🌀 CONTROL PANEL", open=True):
system_message = gr.Textbox(
value="You're a cool AI that speaks Gen-Z slang 😎",
label="🤖 BOT PERSONALITY",
lines=2,
max_lines=4,
elem_classes="cyber-input"
)
image_input = gr.Image(
type="pil",
label="📸 UPLOAD PIC",
height=200,
elem_classes="glow-border"
)
with gr.Column(scale=3):
chat_interface = gr.ChatInterface(
respond,
additional_inputs=[image_input, system_message],
submit_btn="📤 SEND",
)
gr.HTML(footer)
if __name__ == "__main__":
demo.launch()
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