Update app.py

app.py

@@ -5,11 +5,12 @@ import gradio as gr
 import datetime
 from collections import defaultdict
 import os
+import re
 
-# Load environment variables from .env (includes OPENAI_API_KEY)
+# Load environment variables (OPENAI_API_KEY)
 load_dotenv(override=True)
 
-# In-memory daily question tracker
+# Track how many questions each user asks per day (per session)
 user_question_counter = defaultdict(lambda: {"date": None, "count": 0})
 
 
@@ -18,7 +19,7 @@ class Me:
         self.openai = OpenAI()
         self.name = "Narendra"
 
-        # Load LinkedIn profile text from PDF
+        # Load LinkedIn profile text
         reader = PdfReader("me/linkedin.pdf")
         self.linkedin = ""
         for page in reader.pages:
@@ -33,30 +34,35 @@ class Me:
     def system_prompt(self):
         return (
             f"You are acting as {self.name}, an experienced Python technical interviewer. "
-            f"You are helping users by asking or answering Python-related technical questions. "
-            f"Always stay professional, helpful, and concise. Do not generate responses over 100 tokens. "
-            f"The user can only ask 3 questions per day—enforce this limit politely. "
-            f"\n\n## About {self.name} (your interviewer):\n"
-            f"{self.summary}\n\n"
-            f"## LinkedIn Profile:\n{self.linkedin}\n\n"
-            f"Use this background to answer in character as {self.name}."
+            f"Only answer Python-related technical questions — nothing else. "
+            f"If the question is not Python-related, respond politely that you only discuss Python. "
+            f"Be concise, helpful, and professional. Limit all answers to 100 tokens. "
+            f"The user can ask up to 3 questions per day. Enforce this limit politely. "
+            f"\n\n## About {self.name}:\n{self.summary}\n\n"
+            f"## LinkedIn Profile:\n{self.linkedin}"
         )
 
+    def is_python_related(self, text):
+        """Basic keyword-based check to filter Python-related content"""
+        python_keywords = ["python", "flask", "django", "numpy", "pandas", "py", "jupyter", "interpreter", "decorator", "list comprehension", "PEP"]
+        return any(re.search(rf"\b{kw}\b", text.lower()) for kw in python_keywords)
+
     def chat(self, message, history):
-        user_id = "user"  # Replace with session-based ID for real tracking
+        user_id = "user"  # Replace with unique ID in production
         today = datetime.date.today()
         record = user_question_counter[user_id]
 
-        # Reset question count if date changed
         if record["date"] != today:
             record["date"] = today
             record["count"] = 0
 
-        # Check daily question limit
         if record["count"] >= 3:
-            return "🚫 You've reached your daily limit of 3 questions. Please try again tomorrow."
+            return "🚫 You've reached your daily limit of 3 Python questions. Please try again tomorrow."
+
+        if not self.is_python_related(message):
+            return "⚠️ I can only answer questions related to **Python programming**. Please ask something Python-specific."
 
-        # Prepare conversation
+        # Construct full conversation
         messages = [{"role": "system", "content": self.system_prompt()}] + history + [{"role": "user", "content": message}]
         
         response = self.openai.chat.completions.create(