const fs = require("fs");
const path = require("path");
const { GoogleGenAI } = require("@google/genai");

const outputDir = path.join(__dirname, "../../../storage/documents");

if (!fs.existsSync(outputDir)) {
    fs.mkdirSync(outputDir, { recursive: true });
}

const ai = new GoogleGenAI({
    apiKey: process.env.GOOGLE_API_KEY
});

module.exports = {
    name: "llm-gemini",
    type: "llm",
    displayname: "Gemini LLM",
    description: "Generates documents using Google Gemini LLM",

    async function(parameter) {
        try {
            console.log("Gemini LLM module invoked with parameters:", parameter);

            await this.createDocumentFromTranscript(
                parameter.inputTranscriptPath,
                parameter.documentTypePath,
                parameter.language
            );

        } catch (error) {
            console.error("Error in Gemini LLM module:", error);
        }
    },

    createDocumentFromTranscript: async function(transcriptPath, documentTypePath, language = "en") {
        try {
            const transcript = await fs.promises.readFile(transcriptPath, "utf-8");
            const documentType = await fs.promises.readFile(documentTypePath, "utf-8");

            const promptText = `${documentType}, in language ${language}, transcript:\n\n${transcript}`;

            const response = await ai.models.generateContent({
                model: "gemini-2.5-flash",
                contents: promptText
            });

            const output = response.text || "";

            const outPath = path.join(outputDir, "test.md");
            fs.writeFileSync(outPath, output, "utf8");

            console.log("Generated document written to:", outPath);

        } catch (error) {
            console.error("Error generating Gemini content:", error);
        }
    }
};