app.py

from dotenv import load_dotenv
from openai import OpenAI
from pypdf import PdfReader
import gradio as gr
import datetime
from collections import defaultdict
import os
import re

# Load environment variables (like OPENAI_API_KEY)
load_dotenv(override=True)

# Track questions per IP
user_question_counter = defaultdict(lambda: {"date": None, "count": 0})


class Me:
    def __init__(self):
        self.openai = OpenAI()
        self.name = "Narendra"

        # Load LinkedIn profile
        reader = PdfReader("me/linkedin.pdf")
        self.linkedin = ""
        for page in reader.pages:
            text = page.extract_text()
            if text:
                self.linkedin += text

        # Load 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 questions related to Python programming. If the question is unrelated to Python, say so. "
            f"All answers must be under 100 tokens.\n\n"
            f"## About {self.name}:\n{self.summary}\n\n"
            f"## LinkedIn Profile:\n{self.linkedin}"
        )

    def is_python_related(self, text):
        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",
            "recursion", "palindrome", "factorial", "generator", "iterator"
        ]
        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[ip]

        if record["date"] != today:
            record["date"] = today
            record["count"] = 0

        if record["count"] >= 3:
            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."

        messages = [{"role": "system", "content": self.system_prompt()}] + history + [{"role": "user", "content": message}]
        response = self.openai.chat.completions.create(
            model="gpt-4o-mini",
            messages=messages,
            max_tokens=50
        )

        record["count"] += 1
        return response.choices[0].message.content


if __name__ == "__main__":
    me = Me()
    gr.ChatInterface(
        fn=me.chat,
        type="messages",
        title="👋 Narendra is your Python Interviewer. Ask your Python questions (max 3/day).",
        concurrency_limit=None,
        theme="default"
    ).launch(share=True, show_api=False)