@gravityai-dev/pinecone
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Pinecone vector database nodes for GravityWorkflow - knowledge management and vector operations
55 lines • 1.94 kB
JavaScript
;
/**
* Pinecone Query Service
* Handles vector similarity search operations
*/
Object.defineProperty(exports, "__esModule", { value: true });
exports.executeQuery = executeQuery;
const platform_1 = require("../../shared/platform");
const pineconeClient_1 = require("../../shared/pineconeClient");
const logger = (0, platform_1.createLogger)("PineconeQueryService");
/**
* Execute Pinecone query with text
*/
async function executeQuery(config) {
try {
// Build credential context
const credentialContext = {
workflowId: config.context.workflow?.id || "unknown",
executionId: config.context.executionId || "unknown",
nodeId: config.context.nodeId,
nodeType: "PineconeQuery",
credentials: config.context.credentials || {},
};
logger.info("Starting Pinecone query", {
queryLength: config.query.length,
queryPreview: config.query.substring(0, 100),
indexName: config.indexName,
namespace: config.namespace,
});
// Initialize Pinecone client
const pinecone = await (0, pineconeClient_1.initializePineconeClient)(credentialContext);
const index = pinecone.index(config.indexName);
// For now, return a simple mock response
// TODO: Implement actual query logic with embedding generation
const results = [];
const topResult = null;
logger.info("Query completed", {
resultsCount: results.length,
topScore: topResult?.score || 0,
});
return {
results,
topResult,
usedReranking: false,
};
}
catch (error) {
logger.error("Failed to execute Pinecone query", {
error: error.message,
indexName: config.indexName,
});
throw error;
}
}
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