import { NextResponse } from "next/server";
import { GoogleGenerativeAI } from "@google/generative-ai";

const genAI = new GoogleGenerativeAI(process.env.GEMINI_API_KEY!);
const MODEL_ID = "gemini-2.0-flash";

export async function POST(request: Request) {
  try {
    const formData = await request.formData();
    const file = formData.get("file") as File;
    const schema = JSON.parse(formData.get("schema") as string);

    // Convert PDF to base64
    const buffer = await file.arrayBuffer();
    const base64 = Buffer.from(buffer).toString("base64");

    const model = genAI.getGenerativeModel({
      model: MODEL_ID,
      generationConfig: {
        responseMimeType: "application/json",
        responseSchema: schema,
      },
    });

    const prompt = "Extract the structured data from the following PDF file";

    const result = await model.generateContent([
      prompt,
      {
        inlineData: {
          mimeType: "application/pdf",
          data: base64,
        },
      },
    ]);

    const response = await result.response;
    const extractedData = JSON.parse(response.text());

    return NextResponse.json(extractedData);
  } catch (error) {
    console.error("Error extracting data:", error);
    return NextResponse.json(
      {
        error:
          "Failed to extract data, open a thread in discussions, could be be a rate limit issue.s",
      },
      { status: 500 }
    );
  }
}