Update app.py

app.py

@@ -7,10 +7,10 @@ from collections import defaultdict
 import os
 import re
 
-# Load environment variables (OPENAI_API_KEY)
+# Load environment variables (includes OPENAI_API_KEY)
 load_dotenv(override=True)
 
-# Track how many questions each user asks per day (per session)
+# Track daily question count per user IP
 user_question_counter = defaultdict(lambda: {"date": None, "count": 0})
 
 
@@ -19,7 +19,7 @@ class Me:
         self.openai = OpenAI()
         self.name = "Narendra"
 
-        # Load LinkedIn profile text
+        # Load LinkedIn text
         reader = PdfReader("me/linkedin.pdf")
         self.linkedin = ""
         for page in reader.pages:
@@ -27,31 +27,36 @@ class Me:
             if text:
                 self.linkedin += text
 
-        # Load summary text
+        # Load professional summary
         with open("me/summary.txt", "r", encoding="utf-8") as f:
             self.summary = f.read()
 
     def system_prompt(self):
         return (
             f"You are acting as {self.name}, an experienced Python technical interviewer. "
-            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"Only answer questions related to Python programming — skip all non-Python topics. "
+            f"Do not exceed 100 tokens in your response. "
             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 unique ID in production
+        """Smarter keyword-based filter for Python-related questions"""
+        python_keywords = [
+            "python", "list", "dictionary", "dict", "tuple", "set", "loop",
+            "for", "while", "comprehension", "function", "class", "exception",
+            "PEP", "decorator", "lambda", "flask", "django", "pandas", "numpy",
+            "jupyter", "interpreter", "import", "package", "virtualenv", "pytest"
+        ]
+        text_lower = text.lower()
+        return any(kw in text_lower for kw in python_keywords)
+
+    def chat(self, message, history, request: gr.Request):
+        ip = request.client.host or "unknown"
         today = datetime.date.today()
-        record = user_question_counter[user_id]
+        record = user_question_counter[ip]
 
+        # Reset daily count if new day
         if record["date"] != today:
             record["date"] = today
             record["count"] = 0
@@ -60,9 +65,9 @@ class Me:
             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."
+            return "⚠️ I can only answer questions related to Python programming. Please ask something Python-specific."
 
-        # Construct full conversation
+        # Build messages for OpenAI
         messages = [{"role": "system", "content": self.system_prompt()}] + history + [{"role": "user", "content": message}]
         
         response = self.openai.chat.completions.create(
@@ -77,4 +82,5 @@ class Me:
 
 if __name__ == "__main__":
     me = Me()
-    gr.ChatInterface(me.chat, type="messages").launch(share=True)
+    # Pass `request` to get user IP
+    gr.ChatInterface(me.chat, type="messages", additional_inputs=[], concurrency_limit=None).launch(share=True)