import { Pinecone } from '@pinecone-database/pinecone';

// Initialize a client.
// API key is required, but the value does not matter.
// Host and port of the Pinecone Local instance
// is required when starting without indexes.
const pc = new Pinecone({ 
    apiKey: 'pclocal', 
    controllerHostUrl: 'http://localhost:5080' 
});

// Create two indexes, one dense and one sparse
const denseIndexName = 'dense-index';
const sparseIndexName = 'sparse-index';

const denseIndexModel = await pc.createIndex({
  name: denseIndexName,
  vectorType: 'dense',
  dimension: 2,
  metric: 'cosine',
  spec: {
    serverless: {
      cloud: 'aws',
      region: 'us-east-1'
    }
  },
  deletionProtection: 'disabled',
  tags: { environment: 'development' }, 
});

console.log('Dense index model:', denseIndexModel);

const sparseIndexModel = await pc.createIndex({
    name: sparseIndexName,
    vectorType: 'sparse',
    metric: 'dotproduct',
    spec: {
      serverless: {
        cloud: 'aws',
        region: 'us-east-1'
      }
    },
    deletionProtection: 'disabled',
    tags: { environment: 'development' }, 
  });
  
console.log('\nSparse index model:', sparseIndexModel);
  
// Target each index
const denseIndexHost = (await pc.describeIndex(denseIndexName)).host;
const denseIndex = await pc.index(denseIndexName, 'http://' + denseIndexHost);
const sparseIndexHost = (await pc.describeIndex(sparseIndexName)).host;
const sparseIndex = await pc.index(sparseIndexName, 'http://' + sparseIndexHost);

// Upsert records into the dense index
await denseIndex.namespace('example-namespace').upsert([
    {
        id: 'vec1', 
        values: [1.0, -2.5],
        metadata: { genre: 'drama' },
    },
    {
        id: 'vec2', 
        values: [3.0, -2.0],
        metadata: { genre: 'documentary' },
    },
    {
        id: 'vec3', 
        values: [0.5, -1.5],
        metadata: { genre: 'documentary' },
    }
]);

// Upsert records into the sparse index
await sparseIndex.namespace('example-namespace').upsert([
    {
        id: 'vec1',
        sparseValues: {
            indices: [822745112, 1009084850, 1221765879, 1408993854, 1504846510, 1596856843, 1640781426, 1656251611, 1807131503, 2543655733, 2902766088, 2909307736, 3246437992, 3517203014, 3590924191],
            values: [1.7958984, 0.41577148, 2.828125, 2.8027344, 2.8691406, 1.6533203, 5.3671875, 1.3046875, 0.49780273, 0.5722656, 2.71875, 3.0820312, 2.5019531, 4.4414062, 3.3554688]
        },
        metadata: { 
            chunk_text: 'AAPL reported a year-over-year revenue increase, expecting stronger Q3 demand for its flagship phones.', 
            category: 'technology',
            quarter: 'Q3' 
        }
    },
    {
        id: 'vec2',
        sparseValues: {
            indices: [131900689, 592326839, 710158994, 838729363, 1304885087, 1640781426, 1690623792, 1807131503, 2066971792, 2428553208, 2548600401, 2577534050, 3162218338, 3319279674, 3343062801, 3476647774, 3485013322, 3517203014, 4283091697],
            values: [0.4362793, 3.3457031, 2.7714844, 3.0273438, 3.3164062, 5.6015625, 2.4863281, 0.38134766, 1.25, 2.9609375, 0.34179688, 1.4306641, 0.34375, 3.3613281, 1.4404297, 2.2558594, 2.2597656, 4.8710938, 0.5605469]
        },
        metadata: { 
            chunk_text: "Analysts suggest that AAPL's upcoming Q4 product launch event might solidify its position in the premium smartphone market.", 
            category: 'technology',
            quarter: 'Q4' 
        }
    },
    {
        id: 'vec3',
        sparseValues: {
            indices: [8661920, 350356213, 391213188, 554637446, 1024951234, 1640781426, 1780689102, 1799010313, 2194093370, 2632344667, 2641553256, 2779594451, 3517203014, 3543799498, 3837503950, 4283091697],
            values: [2.6875, 4.2929688, 3.609375, 3.0722656, 2.1152344, 5.78125, 3.7460938, 3.7363281, 1.2695312, 3.4824219, 0.7207031, 0.0826416, 4.671875, 3.7011719, 2.796875, 0.61621094]
        },
        metadata: { 
            chunk_text: "AAPL's strategic Q3 partnerships with semiconductor suppliers could mitigate component risks and stabilize iPhone production", 
            category: 'technology',
            quarter: 'Q3' 
        }
    }
]);
  
// Check the number of records in each index
console.log('\nDense index stats:', await denseIndex.describeIndexStats());
console.log('\nSparse index stats:', await sparseIndex.describeIndexStats());

// Query the dense index with a metadata filter
const denseQueryResponse = await denseIndex.namespace('example-namespace').query({
    vector: [3.0, -2.0],
    filter: {
        'genre': {'$eq': 'documentary'}
    },
    topK: 1,
    includeValues: false,
    includeMetadata: true,
});

console.log('\nDense query response:', denseQueryResponse);

const sparseQueryResponse = await sparseIndex.namespace('example-namespace').query({
    sparseVector: {
        indices: [767227209, 1640781426, 1690623792, 2021799277, 2152645940, 2295025838, 2443437770, 2779594451, 2956155693, 3476647774, 3818127854, 4283091697],
        values: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
    },
    topK: 1,
    includeValues: false,
    includeMetadata: true
});

console.log('\nSparse query response:', sparseQueryResponse);

// Delete the index
await pc.deleteIndex(denseIndexName);
await pc.deleteIndex(sparseIndexName);