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import gradio as gr
from huggingface_hub import InferenceClient
# Inference
#model_text = "meta-llama/Llama-4-Scout-17B-16E-Instruct"
model_text = "meta-llama/Llama-3.2-3B-Instruct"
model_vision = "meta-llama/Llama-3.2-11B-Vision-Instruct"
client = InferenceClient()
def fn_text(
prompt,
history,
system_prompt,
max_tokens,
temperature,
top_p,
):
messages = [{"role": "system", "content": [{"type": "text", "text": system_prompt}]}]
history.append(messages[0])
messages.append({"role": "user", "content": [{"type": "text", "text": prompt}]})
history.append(messages[1])
stream = client.chat.completions.create(
model = model_text,
messages = history,
max_tokens = max_tokens,
temperature = temperature,
top_p = top_p,
stream = True,
)
chunks = []
for chunk in stream:
chunks.append(chunk.choices[0].delta.content or "")
yield "".join(chunks)
app_text = gr.ChatInterface(
fn = fn_text,
type = "messages",
additional_inputs = [
gr.Textbox(value="You are a helpful assistant.", label="System Prompt"),
gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max Tokens"),
gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-P"),
],
title = "Meta Llama",
description = model_text,
)
def fn_vision(
prompt,
image_url,
#system_prompt,
max_tokens,
temperature,
top_p,
):
messages = [{"role": "user", "content": [{"type": "text", "text": prompt}]}]
if image_url:
messages[0]["content"].append({"type": "image_url", "image_url": {"url": image_url}})
stream = client.chat.completions.create(
model = model_vision,
messages = messages,
max_tokens = max_tokens,
temperature = temperature,
top_p = top_p,
stream = True,
)
chunks = []
for chunk in stream:
chunks.append(chunk.choices[0].delta.content or "")
yield "".join(chunks)
app_vision = gr.Interface(
fn = fn_vision,
inputs = [
gr.Textbox(label="Prompt"),
gr.Textbox(label="Image URL")
],
outputs = [
gr.Textbox(label="Output")
],
additional_inputs = [
#gr.Textbox(value="You are a helpful assistant.", label="System Prompt"),
gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max Tokens"),
gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-P"),
],
title = "Meta Llama",
description = model_vision,
)
app = gr.TabbedInterface(
[app_text, app_vision],
["Text", "Vision"]
).launch()
#if __name__ == "__main__":
# app.launch() |