ryan-crabbe-berri
21e9632713
test: add six ruff rules that catch tests which cannot fail ( #37709 )
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`assert False` inside a `try:` raises AssertionError, which the `except
Exception` right below it catches, so several tests reported green no matter
what the code did. `pytest.fail` raises Failed, a BaseException, and escapes.
A bare `a == b` statement is evaluated and discarded. Nine of those sat in
tests, and one was comparing against a model name the router never produces.
Selects B011, B015, B018, PT015, PLR0133 and PLW0127 in ruff-tests.toml
alongside F821, with all 50 existing violations fixed, so no budget file or
ratchet is needed. CI already runs this config over tests/.
2026-08-20 14:21:26 -07:00
Ishaan Jaff
bfceb7fc3f
feat(perplexity): add embedding support for pplx-embed-v1 models ( #22610 )
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* feat: add Perplexity embedding support (pplx-embed-v1)
Add support for Perplexity AI's embedding models via the LLM HTTP handler:
Models:
- pplx-embed-v1-0.6b (1024 dims, 32K context, $0.004/1M tokens)
- pplx-embed-v1-4b (2560 dims, 32K context, $0.03/1M tokens)
Implementation:
- PerplexityEmbeddingConfig in litellm/llms/perplexity/embedding/
- Registered in ProviderConfigManager, __init__.py lazy imports, main.py dispatch
- Model pricing added to model_prices_and_context_window.json
- Supports dimensions and encoding_format parameters
- Uses base_llm_http_handler.embedding() pattern
Tests:
- 19 unit tests covering transformation, params, URLs, provider config, model info
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* docs: add Perplexity AI embeddings documentation
- Create providers/perplexity_embedding.md with SDK and proxy usage examples
- Convert Perplexity from flat doc to category in sidebars.js
- Category includes existing chat/responses doc + new embeddings doc
- Covers pplx-embed-v1-0.6b and pplx-embed-v1-4b models
- Documents supported parameters (dimensions, encoding_format)
- Includes proxy config and curl examples
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* fix: decode Perplexity base64_int8 embeddings to OpenAI-format float arrays
Perplexity returns embeddings as base64-encoded signed int8 values by default,
not float arrays like OpenAI. This commit adds decoding in
transform_embedding_response so the proxy returns standard OpenAI-compatible
float arrays (normalized to [-1, 1]).
- Added _decode_base64_embedding() static method
- Handles both base64 strings (decoded) and float lists (passthrough)
- Added 3 new tests for base64 decoding + passthrough
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
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Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
2026-03-02 17:37:50 -08:00
