ai_utils.py

# ai_utils.py
import os
from dotenv import load_dotenv
from openai import OpenAI

# Load environment variables from .env
load_dotenv()

GEMINI_API_KEY = os.getenv("GEMINI_API_KEY")

if not GEMINI_API_KEY:
    raise ValueError("GEMINI_API_KEY is missing in .env file")

# Gemini OpenAI-compatible endpoint
client = OpenAI(
    api_key=GEMINI_API_KEY,
    base_url="https://generativelanguage.googleapis.com/v1beta/openai/",
)

MODEL_NAME = "gemini-2.0-flash-001"  # You can upgrade to Gemini 3 later safely


def summarize_pdf_text(pdf_text: str) -> str:
    """
    Send the extracted PDF text to Gemini and get a clean study summary.
    """
    # Safety guard: avoid sending empty text
    if not pdf_text or pdf_text.isspace():
        return "No readable text found in the PDF."

    system_prompt = (
        "You are a helpful study assistant. "
        "Summarize the given PDF content into clear, exam-focused notes. "
        "Use short paragraphs and bullet points where helpful. "
        "Ignore blank pages, headers, and footers."
    )

    # Truncate huge PDFs so the model doesn't overflow
    max_chars = 12000
    trimmed_text = pdf_text[:max_chars]

    response = client.chat.completions.create(
        model=MODEL_NAME,
        messages=[
            {"role": "system", "content": system_prompt},
            {
                "role": "user",
                "content": (
                    "Here is the PDF content. Summarize it into clean, helpful study notes:\n\n"
                    + trimmed_text
                ),
            },
        ],
        temperature=0.3,
    )

    return response.choices[0].message.content.strip()