src/geminiService.ts

import { GoogleGenerativeAI } from "@google/generative-ai";
import { GeneratedTheme } from '../types';

const getClient = () => {
  return new GoogleGenerativeAI({ apiKey: process.env.API_KEY });
};

export const generateNFTTheme = async (trend: string): Promise<GeneratedTheme | null> => {
  try {
    const ai = getClient();
    const prompt = `
      Create a unique and engaging NFT collection theme for a newsletter loyalty program.
      The context is: "${trend}".
      Provide a name, a short storyline (2 sentences), a visual style description, and 3 hypothetical utility perks for holders.
    `;

    const response = await ai.models.generateContent({
      model: 'gemini-3-flash-preview',
      contents: prompt,
      config: {
        responseMimeType: "application/json",
        responseSchema: {
          type: Type.OBJECT,
          properties: {
            name: { type: Type.STRING },
            storyline: { type: Type.STRING },
            visualStyle: { type: Type.STRING },
            perks: {
              type: Type.ARRAY,
              items: { type: Type.STRING }
            }
          },
          required: ["name", "storyline", "visualStyle", "perks"]
        }
      }
    });

    if (response.text) {
      return JSON.parse(response.text) as GeneratedTheme;
    }
    return null;
  } catch (error) {
    console.error("Error generating theme:", error);
    return null;
  }
};

export const analyzeStrategy = async (ideaDescription: string): Promise<string> => {
  try {
    const ai = getClient();
    const prompt = `
      I am a newsletter creator. I have an engagement strategy:
      "${ideaDescription}"
      
      Act as a senior growth marketing consultant. 
      1. Analyze the strengths and weaknesses of this model.
      2. Suggest 2 ways to prevent abuse (e.g. people just clicking links without reading).
      3. Suggest a "Golden Ticket" mechanic to make it more exciting.
      
      Format the response with Markdown. Keep it concise.
    `;

    const response = await ai.models.generateContent({
      model: 'gemini-3-flash-preview',
      contents: prompt
    });

    return response.text || "No analysis available.";
  } catch (error) {
    console.error("Error analyzing strategy:", error);
    return "Could not generate analysis at this time.";
  }
};

export const generateProposalScript = async (type: 'executive' | 'walkthrough' = 'executive'): Promise<string> => {
  try {
    const ai = getClient();
    const prompts = {
      executive: `
        Write a 60-second professional script for a video proposal to 'the bosses' about the Shib Insider Weekly Trail.
        Focus on:
        1. Boosting subscribers through gamification (Shards/NFTs).
        2. Increasing income via high-value sponsor spots.
        3. Technical feasibility (Shibarium L2).
        Tone: Visionary, confident, professional.
        Return ONLY text.
      `,
      walkthrough: `
        Write a 45-second energetic voice-over script for a screen recording of the Shib Insider Dashboard.
        Narrate the following actions:
        - Landing on the dashboard.
        - Clicking 'Sync Shard' to verify daily engagement.
        - Seeing the 5-shard progress bar fill up.
        - The 'Forge Reward' button becoming active on Monday.
        - The Minting process (Metamask interaction).
        - Finalizing and viewing the NFT in the Vault.
        Tone: Excited, fast-paced, "builder" vibe.
        Return ONLY text.
      `
    };

    const response = await ai.models.generateContent({
      model: 'gemini-3-flash-preview',
      contents: prompts[type]
    });

    return response.text || "";
  } catch (error) {
    console.error("Error generating script:", error);
    return "Welcome to the Shib Insider Weekly Trail. A new era of subscriber engagement.";
  }
};

export const generateSpeech = async (text: string): Promise<string | undefined> => {
  try {
    const ai = getClient();
    const response = await ai.models.generateContent({
      model: "gemini-2.5-flash-preview-tts",
      contents: [{ parts: [{ text: `Say professionally and confidently: ${text}` }] }],
      config: {
        responseModalities: [Modality.AUDIO],
        speechConfig: {
          voiceConfig: {
            prebuiltVoiceConfig: { voiceName: 'Charon' },
          },
        },
      },
    });
    return response.candidates?.[0]?.content?.parts?.[0]?.inlineData?.data;
  } catch (error) {
    console.error("Error generating speech:", error);
    return undefined;
  }
};