Fast mode (the ktx ingest --fast/--deep database-ingest depth toggle) is removed.
ktx ingest now always builds the full enriched ("deep") context. There is no
structural fallback: a database connection without a configured model and
embeddings fails the enrichment-readiness preflight before any work runs, with
a 'Run ktx setup to configure a model and embeddings' hint.
- Remove --fast/--deep flags, the per-connection context.depth field, and the
ktx setup depth prompt (delete setup-database-context-depth.ts).
- Rename ingest-depth.ts -> connection-drivers.ts; ingest always requests scan
mode 'enriched'; readiness gate (enrichmentReadinessGaps) runs for every
database target.
- Drop the database-context-depth telemetry step (Node + Python schema mirrors
regenerated).
- Update CLI, setup, context-build view, docs, the public ktx skill, and the
release-smoke / artifacts scripts (now assert the no-LLM guard failure).
ktx status --fast (a separate network-probe flag) is unchanged.
Follow-ups: KLO-726 (live progress for ktx ingest --all), KLO-727 (restore
credentialed successful-ingest release smoke coverage).
|
||
|---|---|---|
| .. | ||
| src/ktx_daemon | ||
| tests | ||
| pyproject.toml | ||
| README.md | ||
ktx-daemon
ktx-daemon is the portable Python compute package for KTX.
It supports portable compute in two modes:
- One-shot commands, used by default by the
@kaelio/ktxCLI. - An explicit HTTP server for long-running local MCP sessions.
One-shot semantic query
printf '%s\n' '{"sources":[],"query":{"measures":[],"dimensions":[]},"dialect":"postgres"}' \
| ktx-daemon semantic-query
One-shot source generation
Generate semantic-layer sources from schema scan data:
printf '%s\n' '{"tables":[{"name":"orders","db":"public","columns":[{"name":"id","type":"integer","primary_key":true}]}],"links":[],"dialect":"postgres"}' \
| ktx-daemon semantic-generate-sources
One-shot database introspection
Introspect a Postgres database schema:
printf '%s\n' '{"connection_id":"warehouse","driver":"postgres","url":"postgresql://readonly@example.test/warehouse","schemas":["public"]}' \
| ktx-daemon database-introspect
One-shot LookML parsing
Parse LookML projects into resolved, KSL-ready structures:
printf '%s\n' '{"files":[{"path":"views/orders.view.lkml","content":"view: orders { sql_table_name: public.orders ;; measure: order_count { type: count } }"}],"dialect":"postgres"}' \
| ktx-daemon lookml-parse
One-shot embeddings
Compute text embeddings locally:
printf '%s\n' '{"text":"hello"}' \
| ktx-daemon embedding-compute
Compute text embeddings locally in bulk:
printf '%s\n' '{"texts":["hello","world"]}' \
| ktx-daemon embedding-compute-bulk
One-shot code execution
Execute Python code with the current in-process boundary:
printf '%s\n' '{"code":"result = 1 + 2"}' \
| ktx-daemon code-execute
HTTP compute server
Start the HTTP compute server with code execution disabled:
ktx-daemon serve-http --host 127.0.0.1 --port 8765
Enable HTTP code execution explicitly:
ktx-daemon serve-http --host 127.0.0.1 --port 8765 --enable-code-execution
Available HTTP endpoints:
GET /healthPOST /database/introspectPOST /embeddings/computePOST /embeddings/compute-bulkPOST /lookml/parsePOST /semantic-layer/generate-sourcesPOST /semantic-layer/queryPOST /semantic-layer/validatePOST /code/executewhen--enable-code-executionis passed
The HTTP server exposes Postgres database introspection, LookML parsing, local
embedding compute, and semantic-layer compute for source generation, query
compilation, and validation.
Code execution is off by default. When enabled, it runs Python exec in the
daemon process with the same in-process boundary as the one-shot
code-execute command and does not provide OS-level sandboxing.
HTTP code execution uses the standalone KTX boundary. It does not forward caller authorization headers to a host app and does not connect scratchpad or visualization helpers to host application APIs.