File size: 1,423 Bytes
1277216
 
5d324b0
1277216
 
 
 
afae04c
1277216
 
 
 
 
 
 
 
 
 
 
 
 
 
d280e75
1277216
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
d280e75
1277216
 
6bb5a75
caf090a
 
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
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
import os
import requests
#from google.colab import userdata  # Secure storage for API keys in Colab
import gradio as gr


# Get the Groq API key securely (use userdata in Colab)
groq_api_key = os.getenv("GROQ_API_KEY")  # Store using userdata.set("GROQ_API_KEY", "your_api_key")

if not groq_api_key:
    raise ValueError("GROQ_API_KEY not found! Set it using userdata.set('GROQ_API_KEY', 'your_api_key')")

# Define the URL for the Groq API endpoint
url = "https://api.groq.com/openai/v1/chat/completions"

# Set the headers for the API request
headers = {
    "Authorization": f"Bearer {groq_api_key}"
}

def chat_with_groq(user_input):
  body = {
      "model": "deepseek-r1-distill-qwen-32b",
      "messages": [
          {"role": "user", "content": user_input}
      ]
  }

  # Send a POST request to the Groq API
  response = requests.post(url, headers=headers, json=body)



# Check if the request was successful
  if response.status_code == 200:
     return response.json()['choices'][0]['message']['content']
  else:
     return "Error:", response.json()


interface=gr.Interface(
    fn=chat_with_groq,
    inputs=gr.Textbox("Ask me anything..."),
    outputs=gr.Textbox(),
    title="Chat bot using groq (deepseek-r1-distill-qwen-32b)",
    description="Type your question below and get a response powered by Groq's Llama 3.1-8B model"
    )
if __name__ =="__main__":
    interface.launch()
#interface.launch()