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import os
import gradio as gr
from huggingface_hub import InferenceClient
# Clients for both providers
llama_client = InferenceClient(provider="sambanova", api_key=os.environ["HF_TOKEN"])
minimax_client = InferenceClient(provider="novita", api_key=os.environ["HF_TOKEN"])
def chat_with_model(model_choice, prompt, image_url):
if not prompt:
return "Please enter a text prompt."
try:
if model_choice == "LLaMA 4 (SambaNova)":
# Prepare message with optional image
content = [{"type": "text", "text": prompt}]
if image_url:
content.append({
"type": "image_url",
"image_url": {"url": image_url}
})
messages = [{"role": "user", "content": content}]
completion = llama_client.chat.completions.create(
model="meta-llama/Llama-4-Maverick-17B-128E-Instruct",
messages=messages
)
return completion.choices[0].message.content
elif model_choice == "MiniMax M1 (Novita)":
messages = [{"role": "user", "content": prompt}]
completion = minimax_client.chat.completions.create(
model="MiniMaxAI/MiniMax-M1-80k",
messages=messages
)
return completion.choices[0].message.content
else:
return "Unsupported model selected."
except Exception as e:
return f"Error: {e}"
# Gradio UI
with gr.Blocks() as demo:
gr.Markdown("## 🤖 Multimodel Chatbot: LLaMA 4 & MiniMax M1")
gr.Markdown("Choose a model, enter your prompt, and optionally add an image URL for LLaMA.")
model_dropdown = gr.Dropdown(
choices=["LLaMA 4 (SambaNova)", "MiniMax M1 (Novita)"],
value="LLaMA 4 (SambaNova)",
label="Select Model"
)
prompt_input = gr.Textbox(label="Text Prompt", placeholder="Ask something...", lines=2)
image_url_input = gr.Textbox(label="Optional Image URL (for LLaMA only)", placeholder="https://example.com/image.jpg")
submit_btn = gr.Button("Generate Response")
output_box = gr.Textbox(label="Response", lines=8)
submit_btn.click(
fn=chat_with_model,
inputs=[model_dropdown, prompt_input, image_url_input],
outputs=output_box
)
demo.launch()
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