Skip to content

This release adds 3 notable features for engineering teams evaluating rollout.

✓ No known CVEs patched
Read the diff → Tool health → What is this tool? →

✓ No known CVEs patched in this version

Topics

semantic-layer

Summary

AI summary

Snowflake and BigQuery become Tier 1 dialects with new auth config and connection handling.

Changes in this release

Feature Medium

Adds Snowflake as a Tier-1 dialect with live integration tests.

Adds Snowflake as a Tier-1 dialect with live integration tests.

Source: llm_adapter@2026-06-14

Confidence: high

Feature Medium

Adds BigQuery as a Tier-1 dialect via the `bigquery://` driver.

Adds BigQuery as a Tier-1 dialect via the `bigquery://` driver.

Source: llm_adapter@2026-06-14

Confidence: high

Feature Low

Adds public `truncate_text_for_model` helper for downstream callers.

Adds public `truncate_text_for_model` helper for downstream callers.

Source: llm_adapter@2026-06-14

Confidence: high

Feature Low

Supports two authentication shapes for Snowflake: sentinel URL and full `snowflake-sqlalchemy` URL with typed config fields.

Supports two authentication shapes for Snowflake: sentinel URL and full `snowflake-sqlalchemy` URL with typed config fields.

Source: granite4.1:30b@2026-06-14-audit

Confidence: low

Feature Low

Reapplies configured session state on every Snowflake query to avoid stale settings.

Reapplies configured session state on every Snowflake query to avoid stale settings.

Source: granite4.1:30b@2026-06-14-audit

Confidence: low

Feature Low

Handles statement timeouts and Snowflake-specific timestamp types in queries.

Handles statement timeouts and Snowflake-specific timestamp types in queries.

Source: granite4.1:30b@2026-06-14-audit

Confidence: low

Feature Low

Uses Google Application Default Credentials with `GCP_PROJECT_ID` for BigQuery billing.

Uses Google Application Default Credentials with `GCP_PROJECT_ID` for BigQuery billing.

Source: granite4.1:30b@2026-06-14-audit

Confidence: low

Feature Low

Provides a live BigQuery example in `examples/bigquery/` against the public dataset.

Provides a live BigQuery example in `examples/bigquery/` against the public dataset.

Source: granite4.1:30b@2026-06-14-audit

Confidence: low

Bugfix Medium

Prevents encoder crash when `<|endoftext|>` appears in memory content.

Prevents encoder crash when `<|endoftext|>` appears in memory content.

Source: llm_adapter@2026-06-14

Confidence: high

Bugfix Medium

Logs truncation warnings with SHA‑256 prefix instead of content snippets.

Logs truncation warnings with SHA‑256 prefix instead of content snippets.

Source: llm_adapter@2026-06-14

Confidence: high

Bugfix Medium

Invokes demo data generator with the current Python interpreter for consistent installs.

Invokes demo data generator with the current Python interpreter for consistent installs.

Source: llm_adapter@2026-06-14

Confidence: high

Bugfix Medium

Surfaces actionable errors for empty or truncated YAML model files.

Surfaces actionable errors for empty or truncated YAML model files.

Source: llm_adapter@2026-06-14

Confidence: high

Bugfix Medium

Improves `embed_batch` to pre-truncate inputs and retry on `BadRequestError`.

Improves `embed_batch` to pre-truncate inputs and retry on `BadRequestError`.

Source: llm_adapter@2026-06-14

Confidence: low

Bugfix Low

Pre-truncates each input to the model's token cap before sending in `embed_batch`.

Pre-truncates each input to the model's token cap before sending in `embed_batch`.

Source: granite4.1:30b@2026-06-14-audit

Confidence: low

Bugfix Low

Adds per-input retry on `BadRequestError` in `embed_batch` so good inputs survive.

Adds per-input retry on `BadRequestError` in `embed_batch` so good inputs survive.

Source: granite4.1:30b@2026-06-14-audit

Confidence: low

Refactor Low

Removes "Reachable via joins" section from `inspect_model` output.

Removes "Reachable via joins" section from `inspect_model` output.

Source: llm_adapter@2026-06-14

Confidence: high

Refactor Low

Keeps one-hop joins in the `## Joins` table; multi-hop discovery uses the `search` tool.

Keeps one-hop joins in the `## Joins` table; multi-hop discovery uses the `search` tool.

Source: granite4.1:30b@2026-06-14-audit

Confidence: low

Full changelog

0.7.4

Two new Tier-1 dialects (Snowflake and BigQuery), a slimmer inspect_model,, and some hardening of the embedding pipeline.

Snowflake

Snowflake is now Tier 1 with live integration tests. Install the new snowflake extra. Auth supports two shapes: the sentinel URL snowflake://?connection_name=<profile> (looked up in ~/.snowflake/connections.toml via the official connector), or a full snowflake-sqlalchemy URL plus the new typed DatasourceConfig fields connection_name, warehouse, role (alongside the existing database / schema_name). Configured session state is reapplied on every query, so a connection never inherits stale settings from a previous user. Statement timeouts and Snowflake-specific timestamp types are handled.

BigQuery

BigQuery is also Tier 1 now, via the bigquery:// driver (install the sqlalchemy-bigquery extra). Auth uses Google Application Default Credentials with GCP_PROJECT_ID for the billing project. A live example lives in examples/bigquery/ against the public thelook_ecommerce dataset.

inspect_model

The "Reachable via joins" section is gone. It BFS-walked the join graph and blew through the context window on densely-joined real-world schemas. One-hop joins still appear in the ## Joins table; for multi-hop discovery, use the search tool.

Embeddings

embed_batch now pre-truncates each input to the model's token cap before sending, and falls back to per-input retry on BadRequestError so good inputs survive when one over-cap text trips a batch. A user-controlled <|endoftext|> literal inside memory content no longer crashes the encoder. Truncation warnings log a sha256 prefix rather than a content snippet, so application logs don't retain embedded user content. There's a new public truncate_text_for_model helper for downstream callers.

Smaller fixes

The demo data generator is now invoked via the current Python interpreter, so uv tool install and pipx installs work. Empty or truncated YAML model files surface actionable errors instead of opaque parse failures.

Weekly OSS security release digest.

The CVE patches and breaking changes that affected production tools this week. One email, every Sunday.

No spam, unsubscribe anytime.

Share this release

Track SLayer, a semantic layer maintained by your agent

Get notified when new releases ship.

Sign up free

About SLayer, a semantic layer maintained by your agent

All releases →

Related context

Earlier breaking changes

  • v0.7.1 Changes `search()` response to a single flat `results` list capped by `max_results`, removing separate `memories`, `example_queries`, and `entities` buckets.
  • v0.7.1 Changes `search()` to return a single flat `results` list, removing per‑bucket caps.
  • v0.6.3 Datasource names now reject dots, slashes, nulls, empty/whitespace; existing names containing '.' will fail validation on upgrade.
  • v0.6.0 recall_memories surface entirely removed with no deprecation shim.
  • v0.5.1 Two-mode reference semantics enforced: SQL mode accepts arbitrary SQL; DSL mode strictly resolves identifiers.

Beta — feedback welcome: [email protected]