Update app.py

app.py

@@ -22,6 +22,22 @@ from sklearn.naive_bayes import GaussianNB
 from sklearn.metrics import accuracy_score
 import logging
 
+# --- Groq LLM Integration ---
+from groq import Groq
+
+# Load Groq API key from Hugging Face secret
+GROQ_API_KEY = os.environ.get("groq")
+client = Groq(api_key=GROQ_API_KEY)
+
+def ask_groq_llm(user_message):
+    response = client.chat.completions.create(
+        model="llama-3.3-70b-versatile",
+        messages=[
+            {"role": "user", "content": user_message}
+        ]
+    )
+    return response.choices[0].message.content
+
 # Suppress TensorFlow warnings
 os.environ["CUDA_VISIBLE_DEVICES"] = "-1"
 os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3"
@@ -333,6 +349,15 @@ with gr.Blocks(theme="shivi/calm_seafoam") as app:
             inputs=None,
             outputs=[user_input, chatbot]
         )
+    with gr.Tab("Groq Medical Q&A"):
+        groq_input = gr.Textbox(label="Ask a medical question (Groq LLM)")
+        groq_output = gr.Textbox(label="Groq LLM Response")
+        groq_button = gr.Button("Ask Groq LLM")
+        groq_button.click(
+            ask_groq_llm,
+            inputs=groq_input,
+            outputs=groq_output
+        )
     with gr.Tab("Disease Prediction"):
         gr.HTML("""
         <h1 style="color: #388e3c; font-family: 'Helvetica', sans-serif; text-align: center; font-size: 3.5em; margin-bottom: 0;">