mirror of
https://github.com/BerriAI/litellm.git
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* ci: benchmark and gate an installed release wheel Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * ci: simplify installed-wheel benchmark check Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * feat(rust): add native tokenizer codec Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * refactor(tokenizer): route Python tokenization through the Rust extension Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * style(lint): format tokenizer call Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(packaging): restore runtime dependencies and native images Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(tokenizer): preserve Python SDK behavior with Rust tokenizers * fix(tokenizer): restore compatibility paths Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * refactor(tokenizer): count custom tokenizers directly Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(tokenizer): preserve caller-supplied Python tokenizer counts * fix(tokenizer): reuse packaged vocabularies in the native wheel * refactor(rust_bridge): route token counting through the catalog as RUST_OPT_IN Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(spend_tracking): compare tokenizer groups by value Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * chore(deps): re-resolve filelock under the <4.0 pin Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(llms): align transformation override signatures with base configs Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * build(rust): use fat LTO to keep the native wheel under the 35 MB limit Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * feat(tokenizer): preserve Python defaults with opt-in Rust dispatch * test(proxy): tolerate missing litellm.utils.Tokenizer when patching it Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(proxy): patch the tokenizer dispatch function instead of the removed alias Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * feat(tokenizer): give the Rust wrappers the tiktoken and tokenizers surface Callers of litellm.encoding and litellm.create_tokenizer must see the same read-only API whichever backend the catalog selects. - OpenAIEncoding mirrors tiktoken.Encoding: n_vocab, max_token_value, token_byte_values, encode_single_token, encode_with_unstable, encode_to_numpy, decode_with_offsets, is_special_token, repr; the Rust tiktoken crate keeps a Vocabulary beside each CoreBPE and reports the requested encoding name (gpt2 stays gpt2). - HuggingFaceTokenizer mirrors the read-only tokenizers.Tokenizer surface (token_to_id, id_to_token, get_vocab, get_vocab_size, get_added_tokens_decoder, num_special_tokens_to_add, padding, truncation, encode_special_tokens, from_buffer); HuggingFaceEncoding gains the char/word/token lookups, pad, truncate, set_sequence_id and merge. Mutators stay on the Python tokenizer. - from_json/from_pretrained claim the fork gate only when the huggingface feature is compiled in; the surrogate fallback matches on the Codec. - Tokenizer caching is keyed on the same catalog Context the dispatch runs on; rust_tokenizer reads the encoding name without loading an encoding; LITELLM_RUST parsing is cached. - Drop the unused tiktoken_encoding_for_model export and Error::Download. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com> * fix(tokenizer): close the exhaustive matches with assert_never CodeQL reads a `match` over a Literal with no default arm as an implicit `None` return. `assert_never` makes the exhaustiveness explicit for both the HuggingFace tokenizer loader and the Rust token-counter factory. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com> * feat(tokenizer): derive the fast counter from the shared tokenizer The count-only counter (`fast` feature) and the codec each parsed the same artifact: TokenCounter took the Anthropic JSON and the tiktoken rank files from Python while Tokenizer loaded them again. One parse now serves both. - FastTokenizer builds from a model another loader holds: `from_shared` takes the Arc<tokenizers::Tokenizer> the HF codec keeps, and `from_*_pairs` take the ranks the tiktoken vocabulary already parsed. - `FastCounter::fast_counter` in the core crate derives it from either codec; encodings the fast scanner does not reproduce are refused. - Native `Tokenizer.count(text, fast=False)` opts into that counter, built once per tokenizer on first use; `TokenCounter.from_tokenizer(tokenizer, fast=False)` replaces the JSON and rank-file constructors. - The Python route counts over the native tokenizers the codec path shares (`native_encoding`, `native_anthropic`) and no longer reads rank files; the packaged Anthropic tokenizer has one loader, `tokenizer_dispatch.anthropic`. - Public wrappers gain `count(text, fast=False)`. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com> --------- Co-authored-by: Yujong Lee <yujong@berri.ai> Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> Co-authored-by: Claude Fable 5.1 <noreply@anthropic.com>
100 lines
3.1 KiB
YAML
100 lines
3.1 KiB
YAML
name: CodSpeed Benchmarks
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on:
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push:
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branches:
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- main
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- litellm_internal_staging
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paths:
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- "litellm/**"
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- "tests/benchmarks/**"
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- "pyproject.toml"
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- "uv.lock"
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- ".github/workflows/codspeed.yml"
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- ".github/actions/setup-uv-with-retries/**"
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- ".github/actions/cache-cargo-build/**"
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- ".github/scripts/uv_sync_with_retries.sh"
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pull_request:
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branches:
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- main
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- litellm_internal_staging
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paths:
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- "litellm/**"
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- "tests/benchmarks/**"
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- "pyproject.toml"
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- "uv.lock"
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- ".github/workflows/codspeed.yml"
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- ".github/actions/setup-uv-with-retries/**"
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- ".github/actions/cache-cargo-build/**"
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- ".github/scripts/uv_sync_with_retries.sh"
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# Allow CodSpeed to trigger backtest performance analysis
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# in order to generate initial data
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workflow_dispatch:
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permissions:
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contents: read
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id-token: write
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concurrency:
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group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
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cancel-in-progress: true
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jobs:
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benchmarks:
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runs-on: ubuntu-24.04
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timeout-minutes: 60
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steps:
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- uses: actions/checkout@08eba0b27e820071cde6df949e0beb9ba4906955 # v4.3.0
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with:
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persist-credentials: false
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- name: Set up Python
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uses: actions/setup-python@a26af69be951a213d495a4c3e4e4022e16d87065 # v5.6.0
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with:
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python-version: "3.12"
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- name: Set up uv
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uses: ./.github/actions/setup-uv-with-retries
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with:
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version: "0.10.9"
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- name: Cache the Rust build
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uses: ./.github/actions/cache-cargo-build
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with:
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profile: release
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# Build the wheel and resolve every dependency outside the CodSpeed
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# runner: the same maturin build took 42 minutes inside `codspeed run`
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# versus under 3 minutes as a plain step (LIT-6183)
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- name: Build the release wheel
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run: uv build --wheel --out-dir dist
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- name: Install the wheel into the benchmark environment
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run: |
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UV_PROJECT_ENVIRONMENT="${RUNNER_TEMP}/benchmark-venv" .github/scripts/uv_sync_with_retries.sh --frozen --no-default-groups --group benchmarks --no-install-project --python 3.12
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uv pip install --python "${RUNNER_TEMP}/benchmark-venv/bin/python" --no-deps dist/*.whl
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- name: Collect benchmarks
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env:
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PYTEST_DISABLE_PLUGIN_AUTOLOAD: "1"
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LITELLM_REQUIRE_INSTALLED_WHEEL: "1"
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run: >
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"${RUNNER_TEMP}/benchmark-venv/bin/python" -I -m pytest
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--import-mode=importlib
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-p pytest_codspeed.plugin
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tests/benchmarks/
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--codspeed
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--collect-only -q
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- name: Run benchmarks
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uses: CodSpeedHQ/action@1c8ae4843586d3ba879736b7f6b7b0c990757fab # v4.12.1
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with:
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mode: simulation
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run: >
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env PYTEST_DISABLE_PLUGIN_AUTOLOAD=1 LITELLM_REQUIRE_INSTALLED_WHEEL=1
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"${RUNNER_TEMP}/benchmark-venv/bin/python" -I -m pytest
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--import-mode=importlib
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-p pytest_codspeed.plugin
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tests/benchmarks/
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--codspeed
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