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ktx/python/ktx-daemon
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Andrey Avtomonov 394a985d2a
fix(snowflake): unblock multi-schema ingest and relationship discovery (#204) 
* feat(setup): drop redundant Snowflake schema prompt; fall back to free-text on listSchemas failure

Snowflake setup previously asked for a single schema as free text, then
ran a multiselect against the discovered schemas — two schema questions
back-to-back, with the first being only a session bootstrap. The SDK's
`schema` is optional, so the bootstrap step is unnecessary.

- Remove the free-text Snowflake schema prompt; only pass `schema` to
  snowflake-sdk when one is configured.
- When `listSchemas()` fails (e.g. role lacks SHOW SCHEMAS), prompt the
  user for a comma-separated list, persist it as `schema_names`, and use
  it as both the table-list filter and the multiselect default. Applies
  to every driver with a scope-discovery spec, not just Snowflake.
- Update docs to lead with `schema_names`; keep `schema_name` as a
  documented single-schema shorthand.

* fix(snowflake): keep introspecting when primary-key discovery is denied

The PK query joins INFORMATION_SCHEMA.TABLE_CONSTRAINTS and
INFORMATION_SCHEMA.KEY_COLUMN_USAGE, which require grants the
connection role may not have. Previously a 'SQL compilation error:
Object ANALYTICS.INFORMATION_SCHEMA.KEY_COLUMN_USAGE does not exist
or not authorized' aborted the entire introspect — schemas, columns,
and row counts were all discarded over a missing nice-to-have.

Wrap the constraint query in try/catch, log a one-line warning per
schema, and return an empty PK map. Columns end up with
primaryKey=false; relationship inference still has FK and profiling
to fall back on.

* fix(scan): unblock relationship discovery on Snowflake

Two adjacent bugs prevented the scan's relationship pipeline from producing
any joins on a Snowflake warehouse:

- relationship-profiling.ts fell through to a default `GROUP_CONCAT` branch
  for unknown drivers. Snowflake has no GROUP_CONCAT, so every per-table
  profile query failed with "Unknown function GROUP_CONCAT". Add an explicit
  Snowflake branch that uses LISTAGG with a literal '\x1f' delimiter
  (Snowflake requires the delimiter to be a constant, so CHR(31) is rejected).
- description-generation.ts destructured `connector.sampleTable` and
  `connector.sampleColumn` into bare locals, losing the `this` binding when
  the class-method connectors (Snowflake, Postgres, MySQL) were invoked.
  Every sample call threw "Cannot read properties of undefined (reading
  'assertConnection')" and degraded LLM descriptions to metadata-only
  prompts. Call the methods through the connector instead.

Without these, even after the primary-key probe is allowed to fail softly,
the scan ends up with 0 validated relationships and an empty `joins:` block
in every shard YAML.

* test(scan): cover table-ref helpers

* feat(scan): plumb tableScope through live-database introspection port

* feat(scan): apply tableScope during metadata fetch

* feat(scan): enforce table scope at fetch boundary

* feat(scan): pool Snowflake sessions and batch enrichment for faster ingest (#206)

* feat(cli): add RSA key-pair auth option to Snowflake setup wizard

Extends the interactive Snowflake setup flow with an authentication-method
prompt (password vs RSA/JWT key-pair). The RSA branch collects a private-key
path (env/file/absolute) and an optional passphrase; the resulting connection
config records `authMethod: 'rsa'` with `privateKey` and `passphrase` instead
of `password`.

* feat(scan): pool Snowflake sessions

* fix(scan): reuse structural snapshots and cleanup connectors

* feat(scan): parallelize relationship profiling

* feat(scan): batch table description generation

* docs: document Snowflake ingest concurrency knobs

* fix(scan): close Snowflake ingest perf verification gaps

* fix(scan): keep batched description failure bounded

* feat(scan): dispatch query-history probes by connection driver

Extract historic-sql dialect resolution into a shared helper so the
status-project readiness check and the local ingest factory agree on
which connections enable query history and which probe to run. The
status command now picks the postgres/snowflake/bigquery probe based on
the connection's driver instead of always reporting against postgres,
which previously caused snowflake connections with queryHistory.enabled
to surface a misleading "driver is snowflake" failure.

Also drops a noisy console.warn from Snowflake primary-key discovery —
INFORMATION_SCHEMA.KEY_COLUMN_USAGE is commonly ungranted for read-only
roles and the FK + profiling paths handle the empty PK map already.

* fix(llm): allow StructuredOutput tool and raise maxTurns for generateObject

The Claude Code agent SDK announces an internal pseudo-tool named
StructuredOutput in the system/init message whenever outputFormat is set
to { type: 'json_schema' }. The runtime's isolation check built its
allowedToolIds set only from MCP tool ids and treated StructuredOutput
as an unexpected host-injected tool, so every generateObject call threw
"Claude Code runtime isolation failed: tools=StructuredOutput ..." and
the table-descriptions and relationship-LLM-proposal enrichment stages
recorded null output across the board.

Whitelist StructuredOutput specifically in generateObject's
allowedToolIds — the check also enforces missing_tools symmetry, so
generateText and runAgentLoop, which do not see StructuredOutput, must
not require it.

generateObject also ran with maxTurns: 1, which the model intermittently
breached when it emitted thinking text before the structured response.
Raised to 5 to give the schema-bound call enough headroom without
allowing unbounded loops. The existing tests now exercise the path with
an init message that announces StructuredOutput so the regression cannot
slip back in.

* chore(scripts): add ktx-reset.sh project-cleanup helper

Convenience script for repeatable ingest testing: takes a project
directory and prunes everything except ktx.yaml and .ktx/secrets/, so
the next ktx setup or ktx ingest run starts from a known-clean state.
2026-05-23 10:41:30 +02:00
..
src/ktx_daemon fix(snowflake): unblock multi-schema ingest and relationship discovery (#204) 2026-05-23 10:41:30 +02:00
tests fix(snowflake): unblock multi-schema ingest and relationship discovery (#204) 2026-05-23 10:41:30 +02:00
pyproject.toml feat(telemetry): anonymous posthog usage telemetry across node cli and python daemon (#205) 2026-05-22 18:18:47 +02:00
README.md chore(workspace): gate dead-code with knip production mode (#196) 2026-05-21 15:28:58 +02:00

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/ktx CLI.
  • 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 /health
  • POST /database/introspect
  • POST /embeddings/compute
  • POST /embeddings/compute-bulk
  • POST /lookml/parse
  • POST /semantic-layer/generate-sources
  • POST /semantic-layer/query
  • POST /semantic-layer/validate
  • POST /code/execute when --enable-code-execution is 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.