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Daft

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chore(ai): drop the embed option defaults that never applied Both text embedder descriptors declared `batch_size=64, max_retries=3, on_error="raise"` through a `default_factory`, but a provider always passes `embed_options` explicitly - an empty dict when the caller supplied no options - and an explicitly passed argument wins over `default_factory`. The declaration was therefore unreachable through `embed_text` and only misled readers. With the input cap enforced in the embedder, nothing depends on it. Whether `embed_text` should ship a default UDF `batch_size` is a separate question: it changes the request count for every existing caller, so it wants throughput benchmarks rather than a default that silently starts applying.

FANNG1:fix/ai-embed-batch-size-default

11 hours ago

test(ai): hoist test imports to file scope Repository convention is file-scope imports; the stdlib and openai imports added for the base64 decoding test do not need the optional-package exception. Flagged by review on #7615.

FANNG1:fix/ai-embedding-base64-fast-path

16 hours ago

fix(ai): apply the declared embed option defaults on the provider path ## Changes Made - Merge `DEFAULT_EMBED_OPTIONS` into the descriptor instead of relying on the dataclass `default_factory`. Providers always pass `embed_options` explicitly (an empty dict when the caller gave no options), so the factory never ran on the public `embed_text` path and the declared `batch_size=64` silently became "whole morsel". - Apply the same merge to LM Studio. - Cover the default and an explicit override with a regression test. Beyond the declared/actual mismatch, the unbounded default produces requests the real API rejects: OpenAI caps an embeddings request at 2,048 inputs, and only the 300,000-token cap was enforced. Against a stub server, 5,000 rows went out as a single 5,000-input request before this change and as 79 requests of at most 64 after it. Verification: `DAFT_RUNNER=native pytest tests/ai/openai/test_openai_text_embedder.py tests/ai/test_lm_studio.py` (36 passed). ruff and mypy report no new findings against the HEAD baseline.

FANNG1:fix/ai-embed-batch-size-default

17 hours ago

fix(ai): stop disabling the OpenAI SDK base64 fast path in embeddings ## Changes Made - Add `encoding_format` to `EmbedTextOptions`, defaulting to base64. - Stop passing `encoding_format="float"` on every OpenAI-compatible embedding call, which disabled the SDK's base64 fast path and made it build one Python object per float (~15-19x slower response parsing on large batches). - Forward an explicit `"float"` only when the caller opts in, for servers whose base64 support is broken. - Apply the same behavior to the dimension probes and to LM Studio. - Drop `encoding_format="float"` from the contributor guide's sample implementation so it no longer teaches the slow path. - Cover the SDK's base64 decoding at the transport layer, which mocking `Embeddings.create` cannot reach. Verification: `DAFT_RUNNER=native pytest tests/ai/openai/test_openai_text_embedder.py tests/ai/test_lm_studio.py` (39 passed). ruff and mypy report no new findings against the HEAD baseline.

FANNG1:fix/ai-embedding-base64-fast-path

17 hours ago

fix(io): expose documented HTTPConfig properties (#7579) ## Changes Made Expose the five read-only `HTTPConfig` properties already declared in the Python stubs: bearer token, retry backoff, connection/read timeouts, and attempt count. Use the existing PyO3 getter pattern so readers can preserve caller HTTP settings when applying authentication. Credential representations remain redacted; serialization is unchanged. ## Validation Native extension rebuilt. Tests cover configured/default values, pickle round trips, and credential redaction. Cargo formatting passed. ## Related Issues Related to #5295.

main

17 hours ago

fix(sql): use signed 64-bit Iceberg snapshot IDs (#7590) ## Changes Made Use `Option<i64>` for SQL `read_iceberg` snapshot IDs and both scan-builder configurations, following the signedness decision in #7477. This removes pointer-width dependence and lets absent negative IDs reach Iceberg's snapshot lookup instead of failing unsigned-option parsing. Other unsigned table-function options retain their existing validation. Add deterministic SQL/Python parity tests for IDs above the 32-bit range and at `i64::MAX`, negative missing-snapshot diagnostics, and invalid literal rejection. Document the ID type. The general SQL number parser is unchanged, including its existing exact-`i64::MIN` literal limitation. AI disclosure: Codex generated the implementation and regression tests, reviewed the diff, and ran the baseline and post-fix checks above. A second agent independently reviewed the patch; test results described here are agent-run validation. ## Related Issues Closes #7477.

main

17 hours ago

test(huggingface): audit real datasets before release publication

everettVT/hf-release-audit

17 hours ago

fix(huggingface): distinguish feature tags from column names

everettVT/hf-image-features

17 hours ago

Latest Branches

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fix(ai): bound embedding requests by input count, not just tokens#7616

11 hours ago

552485d

FANNG1:fix/ai-embed-batch-size-default

0%

fix(ai): stop disabling the OpenAI SDK base64 fast path in embeddings#7615

16 hours ago

710f71f

FANNG1:fix/ai-embedding-base64-fast-path

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test(huggingface): audit real datasets before release publication#7583

13 days ago

d0502bf

everettVT/hf-release-audit

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