ai_fallback.py

"""
ai_fallback.py
--------------
This file talks to Google's Gemini AI when the FAQ database doesn't
have a good match for the student's question.

How it works:
- We load the API key safely from the .env file (never hardcoded)
- We give Gemini a short "system instruction" so it knows it's a
  university helpdesk assistant and should stay on-topic
- We send the student's question and return Gemini's answer
- If anything goes wrong (no internet, bad key, timeout), we catch
  the error and return a safe fallback message instead of crashing
"""

import os
from dotenv import load_dotenv
from google import genai
from google.genai import types

# Load the .env file so we can read GEMINI_API_KEY from it
load_dotenv()

API_KEY = os.getenv("GEMINI_API_KEY")

# This instruction shapes how Gemini behaves for every question
SYSTEM_INSTRUCTION = (
    "You are a helpful university helpdesk assistant for IUB "
    "(The Islamia University of Bahawalpur). Answer student questions "
    "clearly and briefly, in 2-4 sentences. If a question is not "
    "related to university life, politely say you can only help with "
    "university-related questions."
)

# ``google.generativeai`` and gemini-2.5-flash-lite are retired for new users.
# The current Google Gen AI SDK uses a client object and this supported model.
client = genai.Client(api_key=API_KEY) if API_KEY else None


def ask_ai(user_question):
    """
    Sends the student's question to Gemini and returns the answer.
    Returns a tuple: (answer_text, success_flag)
    success_flag is True if it worked, False if there was an error.
    """
    if not API_KEY:
        print("Gemini API error: GEMINI_API_KEY is not configured.")
        return (
            "Sorry, the AI help service is not configured right now. "
            "Please contact the help desk directly for assistance.",
            False,
        )

    try:
        response = client.models.generate_content(
            model="gemini-2.5-flash",
            contents=user_question,
            config=types.GenerateContentConfig(
                system_instruction=SYSTEM_INSTRUCTION,
            ),
        )
        answer = (response.text or "").strip()
        if not answer:
            raise RuntimeError("Gemini returned an empty response.")
        return answer, True
    except Exception as error:
        # Something went wrong (bad key, no internet, quota, etc.)
        print(f"Gemini API error: {error}")
        safe_message = (
            "Sorry, I couldn't process that right now. "
            "Please contact the help desk directly for assistance."
        )
        return safe_message, False


if __name__ == "__main__":
    # Quick manual test
    test_question = "Can I bring my own laptop to campus?"
    answer, success = ask_ai(test_question)
    print(f"Question: {test_question}")
    print(f"Success: {success}")
    print(f"Answer: {answer}")