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Neo4j GraphRAG integration for Anvia.","maintainers":[{"name":"indrazm","email":"me@indrazm.com"}],"readme":"# @anvia/neo4j\n\nSchema-first local GraphRAG for Neo4j 2026.01 and newer.\n\nProvider-neutral schemas from `@anvia/graph` are accepted alongside the compatibility\n`defineNeo4jGraphSchema()` API. Registered graphs expose `graph.retrieve()`, and the shared\n`createGraphSearchTool()` factory gives Neo4j and Memgraph the same Agent tool API.\n\n## Installation\n\n```sh\npnpm add @anvia/graph @anvia/neo4j @anvia/core\n```\n\n## Managed knowledge graph\n\n```ts\nimport { Agent } from \"@anvia/core/agent\";\nimport { createGraphSearchTool, ingestGraphText } from \"@anvia/graph\";\nimport { Neo4jClient, defineNeo4jGraphSchema } from \"@anvia/neo4j\";\nimport { z } from \"zod\";\n\nconst schema = defineNeo4jGraphSchema({\n  nodes: {\n    Product: {\n      description: \"A product or service.\",\n      identity: [\"id\"],\n      properties: z.strictObject({ id: z.string(), name: z.string() }),\n    },\n    Incident: {\n      description: \"An operational incident.\",\n      identity: [\"id\"],\n      properties: z.strictObject({ id: z.string(), title: z.string() }),\n    },\n  },\n  relationships: {\n    AFFECTS: {\n      description: \"An incident affects a product.\",\n      from: \"Incident\",\n      to: \"Product\",\n      properties: z.strictObject({ severity: z.enum([\"low\", \"high\"]) }),\n    },\n  },\n});\n\nawait using client = new Neo4jClient({\n  uri: process.env.NEO4J_URI!,\n  auth: {\n    username: process.env.NEO4J_USERNAME!,\n    password: process.env.NEO4J_PASSWORD!,\n  },\n});\nconst graph = client.managedKnowledgeGraph({\n  name: \"support\",\n  schema,\n  resources: {\n    labels: { document: \"SupportDocument\", chunk: \"SupportChunk\", entity: \"SupportEntity\" },\n    indexes: {\n      chunks: {\n        vector: { name: \"support_chunks_vector\", dimensions: 1536, similarity: \"cosine\" },\n        fulltext: { name: \"support_chunks_text\" },\n      },\n      entities: {\n        vector: { name: \"support_entities_vector\", dimensions: 1536, similarity: \"cosine\" },\n        fulltext: { name: \"support_entities_text\", properties: [\"id\", \"name\", \"title\"] },\n      },\n    },\n  },\n});\n\nawait graph.ensure({ indexTimeoutMs: 60_000 });\n\nconst ingestion = await ingestGraphText({\n  graph,\n  document: { id: \"incident-42\", text },\n  extractionModel,\n  embeddingModel,\n  chunking: {\n    strategy: \"recursive\",\n    maxSize: 1_000,\n    overlap: 100,\n    separators: [\"\\n\\n\", \"\\n\", \" \"],\n  },\n  conflict: \"error\",\n  orphanEntities: \"delete\",\n});\nconsole.log(ingestion.write);\n\nconst searchGraph = createGraphSearchTool({\n  name: \"search_support_graph\",\n  description: \"Search connected support incidents and products.\",\n  graph,\n  model: embeddingModel,\n  search: {\n    type: \"hybrid\",\n    seeds: [\"chunks\", \"entities\"],\n    topK: 8,\n    candidatesPerSeed: 20,\n    rrfK: 60,\n  },\n  traversal: {\n    relationships: [\"AFFECTS\"],\n    direction: \"both\",\n    maxDepth: 2,\n    maxNodes: 40,\n    maxRelationships: 80,\n  },\n  evidence: { type: \"chunks\", maxChunks: 12 },\n});\n\nconst agent = new Agent({ id: \"support\", model: chatModel, tools: [searchGraph] });\n```\n\nCall `ensure()` once during application startup or deployment initialization, then reuse the graph\nhandle in jobs. It is idempotent, but calling it for every ingestion job adds version, schema, and\nindex checks to the hot path. Call `validate()` for readiness checks that must never provision.\n\n## Tenant namespaces\n\nReuse the same labels, indexes, and Qdrant collection across tenants without constructing resource\nnames from user input:\n\n```ts\nconst tenant = client.tenant(userId);\nconst graph = tenant.managedKnowledgeGraph({ name: \"support\", schema, resources });\n\nconst qdrantTenant = qdrant.tenant(userId);\nconst vectors = qdrantTenant.vectorStore({\n  collectionName: \"support_documents\",\n  dimensions: 1536,\n});\n```\n\nBoth adapters hash the tenant ID using the same deterministic namespace. Neo4j includes that\nnamespace in managed uniqueness constraints, indexed vector filtering, writes, retrieval,\ntraversal, evidence, deletion, and exploration. Do not mix namespaced and non-namespaced handles\nwith the same Neo4j resource definitions; `validate()` reports the incompatible constraint or\nindex so it can be migrated explicitly.\n\nTenant handles scope Anvia's managed lifecycle, retrieval, and exploration APIs; they are not a\ndatabase authorization boundary. `graph.query()` and `client.nativeDriver()` intentionally expose\nraw Cypher access. Use separate Neo4j credentials or databases when untrusted callers require a\nhard security boundary.\n\nThe application owns file discovery, reading, model loading, retry policy, and Agent lifecycle.\n`ingestGraphText()` and `ingestGraphDocuments()` provide the convenient end-to-end path. Advanced\ncallers can compose `prepareGraphDocuments()`, `extractGraphFacts()`, `embedDocuments()`, and\n`replaceDocuments()` directly when they need custom orchestration.\n\nGraph property schemas must use `z.strictObject()` and must not coerce, default, transform,\npreprocess, catch, trim, or otherwise overwrite values. This keeps extraction, comparison, and\nstored Neo4j properties exact.\n\nRe-ingestion is document-scoped. `replaceDocuments()` removes the old chunks and their provenance\nbefore inserting the new representation. Facts supported by other documents remain. Use\n`deleteDocuments({ documentIds, orphanEntities })` for explicit removal.\n\nBoth write operations return exact logical before-and-after counts for documents, chunks, entities,\nrelationships, and mentions. A resource is `created`, `updated`, `deleted`, or `unchanged` by its\nstable public identity; the result is produced inside the same transaction as the mutation.\n\nRetrieval always requires an explicit evidence mode. `{ type: \"none\" }` performs no evidence read.\nManaged graphs can use `{ type: \"chunks\", maxChunks }` to hydrate exact source chunks in ranked\nprovenance order. Seeds, nodes, and relationships refer to those records through `sourceChunkIds`.\n\n## Existing graph\n\n```ts\nconst graph = client.knowledgeGraph({\n  schema,\n  seeds: {\n    incidents: {\n      nodeTypes: [\"Incident\"],\n      vectorIndex: {\n        name: \"existing_incident_vectors\",\n        property: \"embedding\",\n        dimensions: 1536,\n        similarity: \"cosine\",\n      },\n      fulltextIndex: {\n        name: \"existing_incident_text\",\n        properties: [\"title\"],\n      },\n    },\n    products: {\n      nodeTypes: [\"Product\"],\n      vectorIndex: {\n        name: \"existing_product_vectors\",\n        property: \"embedding\",\n        dimensions: 1536,\n        similarity: \"cosine\",\n      },\n      fulltextIndex: {\n        name: \"existing_product_text\",\n        properties: [\"name\"],\n      },\n    },\n  },\n});\n\nawait graph.validate();\n```\n\n## Graph explorer\n\nManaged and existing graph registrations implement the shared `GraphExplorer` contract:\n\n```ts\nconst overview = await graph.explore({ mode: \"overview\", maxNodes: 100 });\nconst neighborhood = await graph.explore({\n  mode: \"expand\",\n  nodeIds: [overview.nodes[0]!.id],\n  maxDepth: 1,\n});\n```\n\nPass `includeProvenance: true` to expose supported source document and chunk IDs on explorer nodes\nand relationships. This can drive article-to-entity UI links without a separate identity mapping\ntable; Neo4j element IDs remain opaque expansion cursors.\n\n## Production ingestion workflow\n\nFor a queue worker (including BullMQ), use stable document IDs, attach a monotonic revision, and\ncall `ingestGraphTextToStores({ graph, vectorStore, ... })`. Persist its receipt as the job result.\nRetry extraction/provider failures as a whole. If `GraphIngestionStageError.stage === \"vector\"`,\nthe graph transaction already committed; re-run the idempotent job with `conflict: \"overwrite\"`.\nRefresh by replacing the same document ID;\ndelete from both stores and record each completed stage. Pass the queue cancellation signal through\n`abortSignal`, create tenant-scoped handles before processing user-owned jobs, and request explorer\nprovenance for source attribution.\n\nThe explorer returns Neo4j element IDs as opaque strings, limits every query, and omits embeddings\nand other `__anvia_*` properties. Use stable graph identity properties for application logic; use the\nopaque IDs only to expand the current view.\n\nExisting registrations are read-only and expose no provisioning or write methods. Use\n`client.nativeDriver()` for application-owned Cypher.\n\nExisting graph registrations do not own Anvia document and chunk resources, so their retrieval and\ntool registrations accept only `evidence: { type: \"none\" }`.\n\nEach existing seed describes exactly one indexed node type and the complete expected vector and\nfull-text index definitions. Register additional node types as separate seeds and fuse them with\nhybrid retrieval.\n\nPackage operations use explicit transactions and do not invoke Neo4j's managed retry APIs. Abort\nsignals roll back the active transaction. Applications decide whether and how to retry an entire\noperation.\n\n`Neo4jClient` supports `await using` and closes a driver that it creates from `uri` and `auth`.\nWhen a caller supplies `driver`, that driver remains caller-owned; closing or disposing the client\nonly closes the Anvia client handle.\n\nThe public property boundary is intentionally JSON-safe. Unsafe Neo4j integers, temporal and\nspatial objects, nodes, relationships, paths, maps, and heterogeneous property arrays are rejected\ninstead of being coerced.\n\n## Development\n\n```sh\npnpm --filter @anvia/neo4j typecheck\npnpm --filter @anvia/neo4j test\npnpm --filter @anvia/neo4j build\n```\n","readmeFilename":"README.md"}