File size: 958 Bytes
eb3516b
 
a887949
257fbd4
0bb6457
a819876
eb3516b
0bb6457
 
eb3516b
0bb6457
 
 
 
a819876
257fbd4
 
a819876
 
eb3516b
257fbd4
 
 
 
 
 
 
 
eb3516b
0bb6457
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
import gradio as gr
import requests

# Function to send your prompt to NVIDIA LLaMA 4 Scout
def talk_to_llama(prompt):
    url = "https://api.nvcf.nvidia.com/v1/messages"  # ✅ Correct endpoint
    headers = {
        "Authorization": "Bearer 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",
        "Content-Type": "application/json"
    }
    data = {
        "messages": [{"role": "user", "content": prompt}]
    }
    response = requests.post(url, headers=headers, json=data)
    
    try:
        return response.json()["choices"][0]["message"]["content"]
    except Exception as e:
        return f"Something went wrong. Here's what the server said:\n{response.text}"

# Build the chatbot interface
chat = gr.Interface(
    fn=talk_to_llama,
    inputs="text",
    outputs="text",
    title="Chat with LLaMA 4 Scout",
    description="Ask anything! This chatbot uses NVIDIA’s 3.5M token LLaMA 4 Scout model."
)

chat.launch()