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Niyaz Almufti a92fb1e078
Fix Gemini batch embedding for gemini-embedding-2* models (#745) 
* Fix Gemini batch embedding for gemini-embedding-2* models

The google-genai SDK treats embed_content(contents=[list_of_strings]) as a
single multi-part document for gemini-embedding-2* models, silently returning
exactly 1 embedding regardless of input count. This caused a zip(...,
strict=True) ValueError in _process_batch.

Wrap each text in genai_types.Content(parts=[genai_types.Part(text=...)])
so the SDK treats each string as a separate content item. This matches the
workaround used by pydantic-ai (#4873) and graphiti (#1474).

Upstream SDK issue: googleapis/python-genai#2523
Fixes plastic-labs/honcho#744

* test(embedding): live embedding coverage for every Gemini and OpenAI model

Adds tests/live_llm/test_live_embeddings.py plus an env-driven embedding
matrix alongside the existing LLM one. Covers single embed, batched embed,
batch-vs-single alignment, chunk-to-id mapping, and the batch-split path.

Only a live call catches the gemini-embedding-2* collapse: the SDK folds a
list of bare strings into one document and returns a single embedding.
Reverting the Content wrapping fails all four batch tests for
gemini-embedding-2-preview and gemini-embedding-2 with the reported
`zip() argument 2 is shorter than argument 1`, while gemini-embedding-001
and text-embedding-3-small stay green.

Also makes the concatenation in the conclusions semantic-search validation
message explicit, so the repo-wide basedpyright pre-push hook passes.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

* test(embedding): drop the preview twin from the default embedding matrix

gemini-embedding-2 is the GA release of gemini-embedding-2-preview and
behaves identically, so running both by default doubles the Gemini cost for
no extra coverage. The preview stays reachable through
LIVE_EMBEDDING_GEMINI_MODELS.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

---------

Co-authored-by: Aakash Kattelu <aakash@plasticlabs.ai>
Co-authored-by: Claude Opus 5 <noreply@anthropic.com>
 		2026-08-11 17:50:40 -04:00
..
README.md Fix Gemini batch embedding for gemini-embedding-2* models (#745) 2026-08-11 17:50:40 -04:00
__init__.py Refactor clients.py to add modern features and more flexible configuration (#459) 2026-04-20 02:46:37 -04:00
conftest.py Fix Gemini batch embedding for gemini-embedding-2* models (#745) 2026-08-11 17:50:40 -04:00
embedding_matrix.py Fix Gemini batch embedding for gemini-embedding-2* models (#745) 2026-08-11 17:50:40 -04:00
model_matrix.py feat: add model config option for json_object mode (#820) 2026-06-23 10:42:03 -04:00
test_live_anthropic.py Refactor clients.py to add modern features and more flexible configuration (#459) 2026-04-20 02:46:37 -04:00
test_live_embeddings.py Fix Gemini batch embedding for gemini-embedding-2* models (#745) 2026-08-11 17:50:40 -04:00
test_live_gemini.py Refactor clients.py to add modern features and more flexible configuration (#459) 2026-04-20 02:46:37 -04:00
test_live_openai.py feat(llm backend): enable combined tool calling + structured output in the LLM backend transport layer (#907) 2026-07-15 11:47:49 -04:00
test_live_structured_output_unions.py feat(dialectic): optional structured outputs with limited schema for Dialectic calls (#896) 2026-07-20 18:46:49 -04:00
test_live_timeouts.py fix(llm): support per-request provider timeouts (#832) 2026-08-04 12:43:00 -04:00
test_live_tools_structured_output.py feat(llm backend): enable combined tool calling + structured output in the LLM backend transport layer (#907) 2026-07-15 11:47:49 -04:00

README.md

Live LLM Tests

These tests call real provider APIs and are disabled by default.

Run them with:

uv run pytest tests/live_llm -n 0 --live-llm --no-header -q

Required API key env vars:

  • LLM_ANTHROPIC_API_KEY
  • LLM_OPENAI_API_KEY
  • LLM_GEMINI_API_KEY

Model-family env vars:

  • LIVE_LLM_ANTHROPIC_45_PLUS_MODELS
  • LIVE_LLM_OPENAI_GPT4_MODELS
  • LIVE_LLM_OPENAI_GPT5_MODELS
  • LIVE_LLM_OPENAI_OPENROUTER_NON_REASONING_MODELS (OpenAI-transport → OpenRouter-served non-reasoning models)
  • LIVE_LLM_GEMINI_25_MODELS
  • LIVE_LLM_GEMINI_30_MODELS
  • LIVE_LLM_GEMINI_31_MODELS

Embedding-model env vars:

  • LIVE_EMBEDDING_GEMINI_MODELS (default: gemini-embedding-001,gemini-embedding-2; add gemini-embedding-2-preview to cover the preview twin)
  • LIVE_EMBEDDING_OPENAI_MODELS (default: text-embedding-3-small)

Each model env var accepts a comma-separated list of bare model ids or provider-qualified ids.

Examples:

export LIVE_LLM_ANTHROPIC_45_PLUS_MODELS="claude-sonnet-4-5,claude-sonnet-4-6"
export LIVE_LLM_OPENAI_GPT4_MODELS="gpt-4.1"
export LIVE_LLM_OPENAI_GPT5_MODELS="gpt-5,gpt-5.4,gpt-5.4-mini"
export LIVE_LLM_OPENAI_OPENROUTER_NON_REASONING_MODELS="inception/mercury-2"
export LIVE_LLM_GEMINI_25_MODELS="gemini-2.5-flash,gemini-2.5-pro"
export LIVE_LLM_GEMINI_30_MODELS="gemini-3-flash-preview"
export LIVE_LLM_GEMINI_31_MODELS="gemini-3.1-pro-preview"

OpenRouter-routed models require additional env for the proxy endpoint:

export OPENROUTER_API_KEY="sk-or-v1-..."
# Per-feature config example:
#   DERIVER_MODEL_CONFIG__TRANSPORT=openai
#   DERIVER_MODEL_CONFIG__MODEL=inception/mercury-2
#   DERIVER_MODEL_CONFIG__OVERRIDES__BASE_URL=https://openrouter.ai/api/v1
#   DERIVER_MODEL_CONFIG__OVERRIDES__API_KEY_ENV=OPENROUTER_API_KEY

Coverage by provider:

  • Anthropic: structured output path, prompt caching metrics, thinking blocks, multi-turn tool replay
  • OpenAI GPT-4 class: structured outputs, prompt caching
  • OpenAI GPT-5 class (incl. gpt-5.x point-releases): structured outputs, prompt caching, reasoning_effort, max_completion_tokens routing
  • OpenAI transport → OpenRouter non-reasoning models (e.g. inception/mercury-2): non-chat / diffusion architectures must stay on max_tokens, no reasoning_effort, tool-calling parameter-schema compatibility is the canary for exotic OR-served providers
  • Gemini 2.5/3.0 classes: structured outputs, cached-content reuse, thought signatures, multi-turn tool replay
  • Gemini 3.1 class: thinking and tool replay coverage by default; structured-output/caching coverage should only be added once Google documents support for that path
  • Embeddings (test_live_embeddings.py): single embed, batched embed, batch-vs-single alignment, and chunk-to-id mapping for every configured embedding model. gemini-embedding-2* is the reason this exists — those models collapse a list of bare strings into one document (#745), and only a live call catches it