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https://github.com/trustgraph-ai/trustgraph.git
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c545213224
Wire up the query and retrieval side of the pipeline so the agent can answer questions from stored knowledge: - Triples query service (FalkorDB) — all SPO pattern queries via NATS - Graph embeddings query service (Qdrant) — entity vector similarity - Document embeddings query service (Qdrant) — chunk vector similarity - Graph RAG service — full concept→entity→traverse→score→synthesize pipeline - Document RAG service — embed→find chunks→synthesize pipeline - Runner scripts for chunker, extractor, embeddings (missing from Phase 5) - Add DocumentEmbeddingsRequest/Response schema types - Add RAG prompt templates (extract-concepts, edge-scoring, synthesize) - Add graph/doc embeddings query topics to seed config + flow manager - Add all pipeline/query/retrieval services to docker-compose - 8 new runner scripts, 8 new pnpm script aliases Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
6 lines
164 B
TypeScript
6 lines
164 B
TypeScript
import { run } from "../packages/flow/src/embeddings/ollama.js";
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run().catch((err) => {
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console.error("Embeddings service failed:", err);
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process.exit(1);
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});
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