Update app.py

app.py

@@ -1,64 +1,62 @@
-import gradio as gr
-import os
-import requests
-
-# Read API key from environment (Hugging Face will provide it)
-GROQ_API_KEY = os.environ.get("GROQ_API_KEY")
-
-GROQ_API_URL = "https://api.groq.com/openai/v1/chat/completions"
-MODEL_NAME = "llama3-8b-8192"
-
-# 🧠 This defines what your chatbot is
-SYSTEM_PROMPT = """
-You are a friendly Data Science Tutor.
-You help students understand data science, machine learning,
-statistics, Python, and big data concepts in simple words.
-"""
-
-def query_groq(user_message, chat_history):
-    headers = {
-        "Authorization": f"Bearer {GROQ_API_KEY}",
-        "Content-Type": "application/json"
-    }
-
-    messages = [{"role": "system", "content": SYSTEM_PROMPT}]
-
-    for user, bot in chat_history:
-        messages.append({"role": "user", "content": user})
-        messages.append({"role": "assistant", "content": bot})
-
-    messages.append({"role": "user", "content": user_message})
-
-    response = requests.post(
-        GROQ_API_URL,
-        headers=headers,
-        json={
-            "model": MODEL_NAME,
-            "messages": messages,
-            "temperature": 0.7
-        }
-    )
-
-    if response.status_code == 200:
-        return response.json()["choices"][0]["message"]["content"]
-    else:
-        return "Error connecting to GROQ API"
-
-def respond(message, chat_history):
-    reply = query_groq(message, chat_history)
-    chat_history.append((message, reply))
-    return "", chat_history
-
-with gr.Blocks() as demo:
-    gr.Markdown("## 📊 Data Science Tutor Chatbot")
-
-    chatbot = gr.Chatbot()
-    msg = gr.Textbox(label="Ask your question")
-    clear = gr.Button("Clear Chat")
-
-    state = gr.State([])
-
-    msg.submit(respond, [msg, state], [msg, chatbot])
-    clear.click(lambda: ([], []), None, [chatbot, state])
-
-demo.launch()
+import gradio as gr
+import os
+import requests
+
+GROQ_API_KEY = os.environ.get("GROQ_API_KEY")
+
+GROQ_API_URL = "https://api.groq.com/openai/v1/chat/completions"
+MODEL_NAME = "llama3-8b-8192"
+
+SYSTEM_PROMPT = """
+You are a friendly Data Science Tutor.
+You explain data science, machine learning,
+statistics, Python, and big data concepts clearly.
+"""
+
+def query_groq(user_message, chat_history):
+    headers = {
+        "Authorization": f"Bearer {GROQ_API_KEY}",
+        "Content-Type": "application/json"
+    }
+
+    messages = [{"role": "system", "content": SYSTEM_PROMPT}]
+
+    for user, bot in chat_history:
+        messages.append({"role": "user", "content": user})
+        messages.append({"role": "assistant", "content": bot})
+
+    messages.append({"role": "user", "content": user_message})
+
+    response = requests.post(
+        GROQ_API_URL,
+        headers=headers,
+        json={
+            "model": MODEL_NAME,
+            "messages": messages,
+            "temperature": 0.7
+        }
+    )
+
+    if response.status_code == 200:
+        return response.json()["choices"][0]["message"]["content"]
+    else:
+        return "❌ Error connecting to GROQ API"
+
+def respond(message, chat_history):
+    reply = query_groq(message, chat_history)
+    chat_history.append((message, reply))
+    return chat_history, chat_history
+
+with gr.Blocks() as demo:
+    gr.Markdown("## 📊 Data Science Tutor Chatbot")
+
+    chatbot = gr.Chatbot()
+    msg = gr.Textbox(label="Ask your question")
+    clear = gr.Button("Clear Chat")
+
+    state = gr.State([])
+
+    msg.submit(respond, [msg, state], [chatbot, state])
+    clear.click(lambda: ([], []), None, [chatbot, state])
+
+demo.launch()