Update app.py

app.py

@@ -2,12 +2,47 @@ import gradio as gr
 import os
 from huggingface_hub import login
 
-# api_key = os.getenv('llama3token')
-# login(api_key)
+# # api_key = os.getenv('llama3token')
+# # login(api_key)
+
+# HF_TOKEN = os.getenv('llama3token')
+# login(HF_TOKEN)
+
+# demo = gr.load("deepseek-ai/DeepSeek-R1-Distill-Llama-8B", src="models")
+# demo.launch()
+
+
+import streamlit as st
+import requests
+
+# Hugging Face API URL
+API_URL = "https://api-inference.huggingface.co/models/deepseek-ai/DeepSeek-R1-Distill-Llama-8B"
 
 HF_TOKEN = os.getenv('llama3token')
-login(HF_TOKEN)
 
-demo = gr.load("deepseek-ai/DeepSeek-R1-Distill-Llama-8B", src="models")
-demo.launch()
+
+# Function to query the Hugging Face API
+def query(payload):
+    headers = {"Authorization": f"Bearer {HF_TOKEN}"}
+    response = requests.post(API_URL, headers=headers, json=payload)
+    return response.json()
+
+# Streamlit app
+st.title("DeepSeek-R1-Distill-Qwen-32B Chatbot")
+
+# Input text box
+user_input = st.text_input("Enter your message:")
+
+if user_input:
+    # Query the Hugging Face API with the user input
+    payload = {"inputs": user_input}
+    output = query(payload)
+    
+    # Display the output
+    if isinstance(output, list) and len(output) > 0 and 'generated_text' in output[0]:
+        st.write("Response:")
+        st.write(output[0]['generated_text'])
+    else:
+        st.write("Error: Unable to generate a response. Please try again.")
+