Create app.py

app.py

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+import os
+from groq import Groq
+import gradio as gr
+from google.colab import userdata
+
+
+# Access the API key from Colab Secrets
+groq_api_key = userdata.get("GROQ_API_KEY")
+if not groq_api_key:
+    raise ValueError("GROQ_API_KEY not found in Colab Secrets. Please add it.")
+
+client = Groq(api_key=groq_api_key)
+
+# IMPORTANT: Check Groq's model deprecation page (https://console.groq.com/docs/deprecations)
+# for the latest available and recommended models.
+# As of July 2025, I'll use a likely available one.
+# You might need to update this model_name if it changes on Groq's side.
+# Recommended current models: "llama-3.1-8b-instant" or "llama-3.3-70b-versatile"
+DEFAULT_GROQ_MODEL = "llama-3.1-8b-instant" 
+
+def get_groq_response(messages: list, model_name: str = DEFAULT_GROQ_MODEL, temperature: float = 0.7):
+    """
+    Generates a response from Groq given a list of messages.
+    Args:
+        messages (list): A list of message dictionaries (e.g., [{"role": "user", "content": "Hello"}]).
+        model_name (str): The Groq model to use.
+        temperature (float): Controls the randomness of the output.
+    Returns:
+        str: The generated response content.
+    """
+    try:
+        chat_completion = client.chat.completions.create(
+            messages=messages,
+            model=model_name,
+            temperature=temperature,
+            max_tokens=1024, # Adjust as needed
+            stream=False,
+        )
+        return chat_completion.choices[0].message.content
+    except Exception as e:
+        print(f"Error calling Groq API: {e}")
+        return "An error occurred while generating a response. Please check your API key and Groq console."
+
+
+# --- Simple Conversational Agent Class ---
+class SimpleGroqAgent:
+    def __init__(self, model_name: str = DEFAULT_GROQ_MODEL, temperature: float = 0.7):
+        self.model_name = model_name
+        self.temperature = temperature
+        # Initialize with a system message to define the agent's persona
+        self.conversation_history = [{"role": "system", "content": "You are a helpful and concise AI assistant powered by Groq. You respond quickly."}]
+
+    def chat(self, user_input: str) -> str:
+        """
+        Processes user input and returns an AI response, updating conversation history.
+        """
+        # Add user's message to history
+        self.conversation_history.append({"role": "user", "content": user_input})
+        
+        # Get response from Groq using the current history
+        response_content = get_groq_response(self.conversation_history, self.model_name, self.temperature)
+        
+        # Add assistant's response to history
+        self.conversation_history.append({"role": "assistant", "content": response_content})
+        
+        return response_content
+
+    def reset_conversation(self):
+        """Resets the conversation history."""
+        self.conversation_history = [{"role": "system", "content": "You are a helpful and concise AI assistant powered by Groq. You respond quickly."}]
+
+        # --- Gradio Interface Setup ---
+
+        # Instantiate your agent
+groq_agent = SimpleGroqAgent()
+
+def chat_interface_function(message, history):
+    """
+    Function to be used by Gradio's ChatInterface.
+    'history' is a list of [user_message, bot_message] pairs.
+    Gradio's Chatbot component manages the visual history,
+    but our SimpleGroqAgent manages the history sent to the LLM.
+    """
+    # The SimpleGroqAgent already manages its own internal history.
+    # We just need to pass the current message to it.
+    response = groq_agent.chat(message)
+    return response
+
+# Create the Gradio ChatInterface
+# In Colab, share=True will generate a public URL.
+demo = gr.ChatInterface(
+    fn=chat_interface_function,
+    chatbot=gr.Chatbot(height=300),
+    textbox=gr.Textbox(placeholder="Ask me anything, powered by Groq!", container=False, scale=7),
+    title="⚡️ Groq-Powered AI Assistant in Colab ⚡️",
+    description=f"Ask a question and get a lightning-fast response from Groq's {DEFAULT_GROQ_MODEL} LLM!",
+    theme="soft",
+    examples=[
+        "Tell me a short, funny story.",
+        "Explain the concept of neural networks in simple terms.",
+        "What are the main components of a computer?",
+        "Write a creative short paragraph about a futuristic city."
+    ],
+)
+
+# Launch the Gradio app
+# This will provide a public URL you can click to access the UI.
+# It will also run the UI directly in the Colab output.
+print(f"Launching Gradio demo with model: {DEFAULT_GROQ_MODEL}")
+demo.launch()