fix(openai): count base64 embedding vector dimensions - #2077

Summary

Count decoded float32 elements when an OpenAI embedding response uses explicit encoding_format="base64". Preserve the previous string-length fallback for malformed base64 or decoded bytes that do not form complete float32 elements. SDK responses pass through unchanged, and trace output still contains only dimensions and count.

- valid 3D base64 embedding: {"dimensions": 16, "count": 1}
+ valid 3D base64 embedding: {"dimensions": 3, "count": 1}

Type of change

• Bug fix

What changed

• Decode base64 with validation and count dimensions only when decoded byte length is divisible by four.
• Retain the prior fallback for decoding errors, non-ASCII input, ignored invalid characters, and incomplete float32 bytes.
• Exercise the real OpenAI response parser with httpx.MockTransport and the shared in-memory exporter, asserting both trace output and unchanged SDK-returned strings.

Verification

uv run --frozen pytest tests/unit/test_openai.py::test_base64_embedding_exports_vector_dimensions -q
uv run --frozen pytest tests/unit/test_openai.py tests/unit/test_openai_prompt_extraction.py -q
uv run --frozen ruff check .
uv run --frozen ruff format --check .
uv run --frozen mypy langfuse --no-error-summary

All 7 base64 cases and all 68 affected OpenAI unit tests passed. Ruff, whole-tree format check, whole-package mypy and git diff --check passed. No live provider or Langfuse server was used; the remote Python-version matrix was not run locally.

Evidence

The original valid-base64 regressions report string lengths on the base implementation and float32 dimensions with the fix. The additional !!!! and AAAA cases fail on the earlier PR head with 0 dimensions instead of the fallback 4; both now pass alongside valid vectors, malformed input, non-ASCII passthrough, and existing float-array coverage.

Merge Danger

Door: two-way. Blast Radius: embedding trace output for explicit base64 responses. No public signatures or provider responses change.

Checklist

• I self-reviewed the diff using code_review.md (Codex review).
• I added or updated tests for behavior changes.
• I updated docs, examples, or .env.template if needed. No documentation becomes stale from correcting this count.
• I did not hand-edit generated files.
• I did not commit secrets or credentials.

AI disclosure: The implementation, regression tests, and self-review were produced with OpenAI Codex. No human review is claimed.