Update app.py

app.py

@@ -1,11 +1,14 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
 import os
-HF_Token = os.getenv("HF_Token")
-# Initialize the inference client with a publicly available chat model
+
+# Get your Hugging Face token from environment variables
+HF_Token = os.getenv("HF_TOKEN")
+
+# Initialize the inference client with a coding specialized model
 client = InferenceClient(
-    model="facebook/blenderbot-400M-distill",  # Using LLaMA 2 chat model
-    token=HF_Token  # Add your HF token if you have access to LLaMA 2
+    model="bigcode/starcoder2-15b",  # Using StarCoder2 which excels at code generation
+    token=HF_Token
 )
 
 def respond(
@@ -17,7 +20,7 @@ def respond(
     top_p,
 ):
     """
-    Generate responses for the chatbot using the LLaMA 2 chat model.
+    Generate coding-focused responses using the selected model.
     
     Args:
         message (str): The current user input message
@@ -29,17 +32,14 @@ def respond(
     """
     # Format the conversation history into messages
     messages = [{"role": "system", "content": system_message}]
-
     for val in history:
         if val[0]:
             messages.append({"role": "user", "content": val[0]})
         if val[1]:
             messages.append({"role": "assistant", "content": val[1]})
-
     messages.append({"role": "user", "content": message})
-
+    
     response = ""
-
     # Stream the response tokens
     for message in client.chat_completion(
         messages,
@@ -57,34 +57,41 @@ demo = gr.ChatInterface(
     respond,
     additional_inputs=[
         gr.Textbox(
-            value="You are a helpful and friendly AI assistant. Provide informative and accurate responses.",
+            value="You are an expert coding assistant. Provide detailed, correct, and efficient code solutions with explanations.",
             label="System message"
         ),
         gr.Slider(
             minimum=1,
             maximum=2048,
-            value=512,
+            value=1024,
             step=1,
             label="Max new tokens"
         ),
         gr.Slider(
             minimum=0.1,
-            maximum=2.0,
-            value=0.7,
+            maximum=1.0,
+            value=0.5,
             step=0.1,
             label="Temperature"
         ),
         gr.Slider(
             minimum=0.1,
             maximum=1.0,
-            value=0.95,
+            value=0.9,
             step=0.05,
             label="Top-p (nucleus sampling)"
         ),
     ],
-    title="LLaMA 2 Chatbot",
-    description="A conversational AI powered by Meta's LLaMA 2 model"
+    title="Coding Expert Assistant",
+    description="A specialized coding assistant powered by StarCoder2, a model trained on code repositories",
+    examples=[
+        "Write a Python function to find the longest palindromic substring",
+        "Create a React component that displays a color picker",
+        "How do I implement quicksort in JavaScript?",
+        "Explain the difference between Promise.all and Promise.allSettled in JavaScript",
+        "Generate a Python script to download and process CSV data from an API"
+    ]
 )
 
 if __name__ == "__main__":
-    demo.launch(share=True)  # Added share=True to create a public link
+    demo.launch(share=True)