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Runtime error
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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)
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