service-slm graph store migration
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enrich wikilinks: documentation services body (EN+ES) batch 2
@@ -16,7 +16,7 @@ short_description: "service-slm migrated its graph store from LadybugDB to SQLit cites: [] --- The `service-slm` graph store is a live property graph of named business entities extracted nightly from an operator's data corpus — the entity layer that `service-content` uses to inject structured business context into every inference request without sending proprietary data to an external model. The graph is stored in LadybugDB and rebuilt on a nightly schedule by the DataGraph rebuild script, which runs as Phase 1 of the Elastic Compute nightly window before the model-training phase claims the GPU. The [[service-slm]] graph store is a live property graph of named business entities extracted nightly from an operator's data corpus — the entity layer that [[service-content]] uses to inject structured business context into every inference request without sending proprietary data to an external model. The graph is stored in LadybugDB and rebuilt on a nightly schedule by the DataGraph rebuild script, which runs as Phase 1 of the Elastic Compute nightly window before the model-training phase claims the GPU. Each night, the DataGraph rebuild script processes the operator data corpus and writes extracted named entities to a property graph stored in @@ -37,12 +37,12 @@ Location (offices, sites, and operational addresses). These entities are extracted from three document streams: meeting transcript markdown files from the minutebook asset directory, research and background YAML and markdown files from the service-agents directory, and contact source JSON records from the service-people directory. the [[service-people]] directory. ## What the nightly rebuild does For each unprocessed document, the rebuild script calls `POST :9080/v1/chat/completions` through the Doorman endpoint, passing the `POST :9080/v1/chat/completions` through the [[doorman-protocol|Doorman]] endpoint, passing the document text with a JSON Schema grammar constraint. The language model — OLMo 3 32B Think running on Elastic Compute #1 via vLLM — returns a structured JSON array of entity objects. Each object carries the entity name, classification, @@ -78,7 +78,7 @@ that real callers would never exercise. ## Idempotency The script tracks processed documents using a local ledger at The script tracks processed documents using a local [[worm-ledger-design|ledger]] at `$DEPLOYMENT_ROOT/data/datagraph-processed.txt`. Each document is identified by a hash of its file content, prefixed with a source tag (`mk-` for minutebook, `ag-` for service-agents, `sp-` for service-people). Before processing any