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{ EMBEDDING_MODELS } from '@mastra/core/llm';\nimport type { MastraVector, QueryResult, IndexStats } from '@mastra/core/vector';\nimport { HTTPException } from '../http-exception';\nimport {\n  vectorNamePathParams,\n  vectorIndexPathParams,\n  upsertVectorsBodySchema,\n  upsertVectorsResponseSchema,\n  createIndexBodySchema,\n  createIndexResponseSchema,\n  queryVectorsBodySchema,\n  queryVectorsResponseSchema,\n  listIndexesResponseSchema,\n  describeIndexResponseSchema,\n  deleteIndexResponseSchema,\n  listVectorsResponseSchema,\n  listEmbeddersResponseSchema,\n} from '../schemas/vectors';\nimport { createRoute } from '../server-adapter/routes/route-builder';\nimport type { Context } from '../types';\n\nimport { handleError } from './error';\n\ninterface VectorContext extends Context {\n  vectorName?: string;\n}\n\ninterface UpsertRequest {\n  indexName: string;\n  vectors: number[][];\n  metadata?: Record<string, any>[];\n  ids?: string[];\n}\n\ninterface CreateIndexRequest {\n  indexName: string;\n  dimension: number;\n  metric?: 'cosine' | 'euclidean' | 'dotproduct';\n}\n\ninterface QueryRequest {\n  indexName: string;\n  queryVector: number[];\n  topK?: number;\n  filter?: Record<string, any>;\n  includeVector?: boolean;\n}\n\nfunction getVector(mastra: Context['mastra'], vectorName?: string): MastraVector {\n  if (!vectorName) {\n    throw new HTTPException(400, { message: 'Vector name is required' });\n  }\n\n  const vector = mastra.getVector(vectorName);\n  if (!vector) {\n    throw new HTTPException(404, { message: `Vector store ${vectorName} not found` });\n  }\n\n  return vector;\n}\n\n// Upsert vectors\nexport async function upsertVectors({\n  mastra,\n  vectorName,\n  indexName,\n  vectors,\n  metadata,\n  ids,\n}: VectorContext & UpsertRequest) {\n  try {\n    if (!indexName || !vectors || !Array.isArray(vectors)) {\n      throw new HTTPException(400, { message: 'Invalid request index. indexName and vectors array are required.' });\n    }\n\n    const vector = getVector(mastra, vectorName);\n    const result = await vector.upsert({ indexName, vectors, metadata, ids });\n    return { ids: result };\n  } catch (error) {\n    return handleError(error, 'Error upserting vectors');\n  }\n}\n\n// Create index\nexport async function createIndex({\n  mastra,\n  vectorName,\n  indexName,\n  dimension,\n  metric,\n}: Pick<VectorContext, 'mastra' | 'vectorName'> & CreateIndexRequest) {\n  try {\n    if (!indexName || typeof dimension !== 'number' || dimension <= 0) {\n      throw new HTTPException(400, {\n        message: 'Invalid request index, indexName and positive dimension number are required.',\n      });\n    }\n\n    if (metric && !['cosine', 'euclidean', 'dotproduct'].includes(metric)) {\n      throw new HTTPException(400, { message: 'Invalid metric. Must be one of: cosine, euclidean, dotproduct' });\n    }\n\n    const vector = getVector(mastra, vectorName);\n    await vector.createIndex({ indexName, dimension, metric });\n    return { success: true };\n  } catch (error) {\n    return handleError(error, 'Error creating index');\n  }\n}\n\n// Query vectors\nexport async function queryVectors({\n  mastra,\n  vectorName,\n  indexName,\n  queryVector,\n  topK,\n  filter,\n  includeVector,\n}: Pick<VectorContext, 'mastra' | 'vectorName'> & QueryRequest) {\n  try {\n    if (!indexName || !queryVector || !Array.isArray(queryVector)) {\n      throw new HTTPException(400, { message: 'Invalid request query. indexName and queryVector array are required.' });\n    }\n\n    const vector = getVector(mastra, vectorName);\n    const results: QueryResult[] = await vector.query({ indexName, queryVector, topK, filter, includeVector });\n    return results;\n  } catch (error) {\n    return handleError(error, 'Error querying vectors');\n  }\n}\n\n// List indexes\nexport async function listIndexes({ mastra, vectorName }: Pick<VectorContext, 'mastra' | 'vectorName'>) {\n  try {\n    const vector = getVector(mastra, vectorName);\n\n    const indexes = await vector.listIndexes();\n    return indexes.filter(Boolean);\n  } catch (error) {\n    return handleError(error, 'Error listing indexes');\n  }\n}\n\n// Describe index\nexport async function describeIndex({\n  mastra,\n  vectorName,\n  indexName,\n}: Pick<VectorContext, 'mastra' | 'vectorName'> & { indexName?: string }) {\n  try {\n    if (!indexName) {\n      throw new HTTPException(400, { message: 'Index name is required' });\n    }\n\n    const vector = getVector(mastra, vectorName);\n    const stats: IndexStats = await vector.describeIndex({ indexName });\n\n    return {\n      dimension: stats.dimension,\n      count: stats.count,\n      metric: stats.metric?.toLowerCase(),\n    };\n  } catch (error) {\n    return handleError(error, 'Error describing index');\n  }\n}\n\n// Delete index\nexport async function deleteIndex({\n  mastra,\n  vectorName,\n  indexName,\n}: Pick<VectorContext, 'mastra' | 'vectorName'> & { indexName?: string }) {\n  try {\n    if (!indexName) {\n      throw new HTTPException(400, { message: 'Index name is required' });\n    }\n\n    const vector = getVector(mastra, vectorName);\n    await vector.deleteIndex({ indexName });\n    return { success: true };\n  } catch (error) {\n    return handleError(error, 'Error deleting index');\n  }\n}\n\n// List available vector stores\nexport async function listVectorStores({ mastra }: Pick<VectorContext, 'mastra'>) {\n  try {\n    const vectors = mastra.listVectors();\n    if (!vectors) {\n      return { vectors: [] };\n    }\n\n    // Convert to array and extract metadata\n    const vectorList = Object.entries(vectors).map(([name, vector]) => ({\n      name,\n      id: vector.id || name, // Use the key as fallback when vector has no id property\n      type: vector.constructor.name,\n      // Add any other metadata that might be useful\n    }));\n\n    return { vectors: vectorList };\n  } catch (error) {\n    return handleError(error, 'Error listing vector stores');\n  }\n}\n\n// ============================================================================\n// Route Definitions (new pattern - handlers defined inline with createRoute)\n// ============================================================================\n\nexport const UPSERT_VECTORS_ROUTE = createRoute({\n  method: 'POST',\n  path: '/vector/:vectorName/upsert',\n  responseType: 'json',\n  pathParamSchema: vectorNamePathParams,\n  bodySchema: upsertVectorsBodySchema,\n  responseSchema: upsertVectorsResponseSchema,\n  summary: 'Upsert vectors',\n  description: 'Inserts or updates vectors in the specified index',\n  tags: ['Vectors'],\n  requiresAuth: true,\n  handler: async ({ mastra, vectorName, ...params }) => {\n    try {\n      const { indexName, vectors, metadata, ids } = params;\n\n      if (!indexName || !vectors || !Array.isArray(vectors)) {\n        throw new HTTPException(400, { message: 'Invalid request index. indexName and vectors array are required.' });\n      }\n\n      const vector = getVector(mastra, vectorName);\n      const result = await vector.upsert({ indexName, vectors, metadata, ids });\n      return { ids: result };\n    } catch (error) {\n      return handleError(error, 'Error upserting vectors');\n    }\n  },\n});\n\nexport const CREATE_INDEX_ROUTE = createRoute({\n  method: 'POST',\n  path: '/vector/:vectorName/create-index',\n  responseType: 'json',\n  pathParamSchema: vectorNamePathParams,\n  bodySchema: createIndexBodySchema,\n  responseSchema: createIndexResponseSchema,\n  summary: 'Create index',\n  description: 'Creates a new vector index with the specified dimension and metric',\n  tags: ['Vectors'],\n  requiresAuth: true,\n  handler: async ({ mastra, vectorName, ...params }) => {\n    try {\n      const { indexName, dimension, metric } = params;\n\n      if (!indexName || typeof dimension !== 'number' || dimension <= 0) {\n        throw new HTTPException(400, {\n          message: 'Invalid request index, indexName and positive dimension number are required.',\n        });\n      }\n\n      if (metric && !['cosine', 'euclidean', 'dotproduct'].includes(metric)) {\n        throw new HTTPException(400, { message: 'Invalid metric. Must be one of: cosine, euclidean, dotproduct' });\n      }\n\n      const vector = getVector(mastra, vectorName);\n      await vector.createIndex({ indexName, dimension, metric });\n      return { success: true };\n    } catch (error) {\n      return handleError(error, 'Error creating index');\n    }\n  },\n});\n\nexport const QUERY_VECTORS_ROUTE = createRoute({\n  method: 'POST',\n  path: '/vector/:vectorName/query',\n  responseType: 'json',\n  pathParamSchema: vectorNamePathParams,\n  bodySchema: queryVectorsBodySchema,\n  responseSchema: queryVectorsResponseSchema,\n  summary: 'Query vectors',\n  description: 'Performs a similarity search on the vector index',\n  tags: ['Vectors'],\n  requiresAuth: true,\n  handler: async ({ mastra, vectorName, ...params }) => {\n    try {\n      const { indexName, queryVector, topK, filter, includeVector } = params;\n\n      if (!indexName || !queryVector || !Array.isArray(queryVector)) {\n        throw new HTTPException(400, {\n          message: 'Invalid request query. indexName and queryVector array are required.',\n        });\n      }\n\n      const vector = getVector(mastra, vectorName);\n      const results: QueryResult[] = await vector.query({ indexName, queryVector, topK, filter, includeVector });\n      return results;\n    } catch (error) {\n      return handleError(error, 'Error querying vectors');\n    }\n  },\n});\n\nexport const LIST_INDEXES_ROUTE = createRoute({\n  method: 'GET',\n  path: '/vector/:vectorName/indexes',\n  responseType: 'json',\n  pathParamSchema: vectorNamePathParams,\n  responseSchema: listIndexesResponseSchema,\n  summary: 'List indexes',\n  description: 'Returns a list of all indexes in the vector store',\n  tags: ['Vectors'],\n  requiresAuth: true,\n  handler: async ({ mastra, vectorName }) => {\n    try {\n      const vector = getVector(mastra, vectorName);\n      const indexes = await vector.listIndexes();\n      return indexes.filter(Boolean);\n    } catch (error) {\n      return handleError(error, 'Error listing indexes');\n    }\n  },\n});\n\nexport const DESCRIBE_INDEX_ROUTE = createRoute({\n  method: 'GET',\n  path: '/vector/:vectorName/indexes/:indexName',\n  responseType: 'json',\n  pathParamSchema: vectorIndexPathParams,\n  responseSchema: describeIndexResponseSchema,\n  summary: 'Describe index',\n  description: 'Returns statistics and metadata for a specific index',\n  tags: ['Vectors'],\n  requiresAuth: true,\n  handler: async ({ mastra, vectorName, indexName }) => {\n    try {\n      if (!indexName) {\n        throw new HTTPException(400, { message: 'Index name is required' });\n      }\n\n      const vector = getVector(mastra, vectorName);\n      const stats: IndexStats = await vector.describeIndex({ indexName: indexName });\n\n      return {\n        dimension: stats.dimension,\n        count: stats.count,\n        metric: stats.metric?.toLowerCase(),\n      };\n    } catch (error) {\n      return handleError(error, 'Error describing index');\n    }\n  },\n});\n\nexport const DELETE_INDEX_ROUTE = createRoute({\n  method: 'DELETE',\n  path: '/vector/:vectorName/indexes/:indexName',\n  responseType: 'json',\n  pathParamSchema: vectorIndexPathParams,\n  responseSchema: deleteIndexResponseSchema,\n  summary: 'Delete index',\n  description: 'Deletes a vector index and all its data',\n  tags: ['Vectors'],\n  requiresAuth: true,\n  handler: async ({ mastra, vectorName, indexName }) => {\n    try {\n      if (!indexName) {\n        throw new HTTPException(400, { message: 'Index name is required' });\n      }\n\n      const vector = getVector(mastra, vectorName);\n      await vector.deleteIndex({ indexName: indexName });\n      return { success: true };\n    } catch (error) {\n      return handleError(error, 'Error deleting index');\n    }\n  },\n});\n\nexport const LIST_VECTORS_ROUTE = createRoute({\n  method: 'GET',\n  path: '/vectors',\n  responseType: 'json',\n  responseSchema: listVectorsResponseSchema,\n  summary: 'List vector stores',\n  description: 'Returns a list of all configured vector stores',\n  tags: ['Vectors'],\n  requiresAuth: true,\n  handler: async ({ mastra }) => {\n    try {\n      const vectors = mastra.listVectors();\n      if (!vectors) {\n        return { vectors: [] };\n      }\n\n      // Convert to array and extract metadata\n      const vectorList = Object.entries(vectors).map(([name, vector]) => ({\n        id: vector.id || name, // Use the key as the ID since vectors might not have their own id property\n        name,\n        type: vector.constructor.name,\n      }));\n\n      return { vectors: vectorList };\n    } catch (error) {\n      return handleError(error, 'Error listing vector stores');\n    }\n  },\n});\n\nexport const LIST_EMBEDDERS_ROUTE = createRoute({\n  method: 'GET',\n  path: '/embedders',\n  responseType: 'json',\n  responseSchema: listEmbeddersResponseSchema,\n  summary: 'List available embedder models',\n  description: 'Returns a list of all available embedding models',\n  tags: ['Vectors'],\n  requiresAuth: true,\n  handler: async () => {\n    try {\n      const embeddersList = EMBEDDING_MODELS.map(model => ({\n        id: `${model.provider}/${model.id}`,\n        provider: model.provider,\n        name: model.id,\n        description: model.description || '',\n        dimensions: model.dimensions,\n        maxInputTokens: model.maxInputTokens,\n      }));\n\n      return { embedders: embeddersList };\n    } catch (error) {\n      return handleError(error, 'Error listing embedders');\n    }\n  },\n});\n"]}