/**
 * Gemini Embeddings with Fetch (Cloudflare Workers)
 *
 * Demonstrates embedding generation using fetch API instead of SDK.
 * Perfect for Cloudflare Workers and edge environments.
 *
 * Setup:
 * 1. Add GEMINI_API_KEY to wrangler.jsonc secrets
 * 2. npx wrangler secret put GEMINI_API_KEY
 * 3. Deploy: npx wrangler deploy
 *
 * Usage:
 * GET /?text=your+text+here
 */

interface Env {
  GEMINI_API_KEY: string;
}

interface EmbeddingRequest {
  content: {
    parts: Array<{ text: string }>;
  };
  taskType?: string;
  outputDimensionality?: number;
}

interface EmbeddingResponse {
  embedding: {
    values: number[];
  };
}

export default {
  async fetch(request: Request, env: Env): Promise<Response> {
    // CORS headers for browser access
    const corsHeaders = {
      'Access-Control-Allow-Origin': '*',
      'Access-Control-Allow-Methods': 'GET, POST, OPTIONS',
      'Access-Control-Allow-Headers': 'Content-Type'
    };

    // Handle CORS preflight
    if (request.method === 'OPTIONS') {
      return new Response(null, { headers: corsHeaders });
    }

    try {
      // Get text from query param or request body
      const url = new URL(request.url);
      let text: string;

      if (request.method === 'POST') {
        const body = await request.json<{ text: string }>();
        text = body.text;
      } else {
        text = url.searchParams.get('text') || 'What is the meaning of life?';
      }

      console.log(`Generating embedding for: "${text}"`);

      // Prepare request
      const embeddingRequest: EmbeddingRequest = {
        content: {
          parts: [{ text }]
        },
        taskType: 'SEMANTIC_SIMILARITY',
        outputDimensionality: 768
      };

      // Call Gemini API
      const response = await fetch(
        'https://generativelanguage.googleapis.com/v1beta/models/gemini-embedding-001:embedContent',
        {
          method: 'POST',
          headers: {
            'x-goog-api-key': env.GEMINI_API_KEY,
            'Content-Type': 'application/json'
          },
          body: JSON.stringify(embeddingRequest)
        }
      );

      if (!response.ok) {
        const error = await response.text();
        throw new Error(`Gemini API error: ${response.status} - ${error}`);
      }

      const data = await response.json<EmbeddingResponse>();
      const embedding = data.embedding.values;

      // Calculate vector magnitude
      const magnitude = Math.sqrt(
        embedding.reduce((sum, v) => sum + v * v, 0)
      );

      // Return formatted response
      return new Response(JSON.stringify({
        success: true,
        text,
        embedding: {
          dimensions: embedding.length,
          magnitude: magnitude.toFixed(4),
          firstValues: embedding.slice(0, 10).map(v => parseFloat(v.toFixed(4))),
          fullVector: embedding
        }
      }, null, 2), {
        headers: {
          'Content-Type': 'application/json',
          ...corsHeaders
        }
      });

    } catch (error: any) {
      console.error('Error:', error.message);

      return new Response(JSON.stringify({
        success: false,
        error: error.message,
        hint: error.message.includes('401')
          ? 'Check GEMINI_API_KEY secret is set'
          : error.message.includes('429')
          ? 'Rate limit exceeded (Free tier: 100 RPM)'
          : 'Check error message for details'
      }, null, 2), {
        status: 500,
        headers: {
          'Content-Type': 'application/json',
          ...corsHeaders
        }
      });
    }
  }
};

/**
 * Example wrangler.jsonc configuration:
 *
 * {
 *   "name": "gemini-embeddings-worker",
 *   "main": "src/index.ts",
 *   "compatibility_date": "2025-10-25",
 *   "vars": {
 *     "ENVIRONMENT": "production"
 *   }
 * }
 *
 * Set secret:
 * npx wrangler secret put GEMINI_API_KEY
 *
 * Test locally:
 * npx wrangler dev
 * curl "http://localhost:8787/?text=Hello+world"
 *
 * Deploy:
 * npx wrangler deploy
 */