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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>
220 lines
7.8 KiB
Python
220 lines
7.8 KiB
Python
import os
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import textwrap
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from typing import Final
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import pytest
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from tests.test_litellm_rust.support.child_interpreter import run_child_interpreter
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pytestmark = pytest.mark.requires_rust_extension
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_NATIVE_CONTRACT = textwrap.dedent(
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"""
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import os
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from litellm.rust_bridge import _native
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from litellm.rust_bridge.fork_guard import reserve_process_for_forking
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def native_route_error():
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import asyncio
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async def call():
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await _native.ResponsesWebSocketConnection.connect("ws://127.0.0.1:1", {}, 0.2)
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try:
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asyncio.run(call())
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except Exception as error:
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return f"{type(error).__name__}: {error}"
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return ""
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assert _native.process_state_started() is False
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reserve_process_for_forking("the test master")
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assert native_route_error().startswith("ProcessReservedForForking: ")
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assert _native.process_state_started() is False
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pid = os.fork()
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if pid == 0:
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error = native_route_error()
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started = _native.process_state_started()
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os._exit(0 if started and "reserved" not in error and "forked" not in error else 1)
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assert os.waitpid(pid, 0)[1] == 0
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pid = os.fork()
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if pid == 0:
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native_route_error()
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grandchild = os.fork()
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if grandchild == 0:
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os._exit(0 if native_route_error().startswith("ForkedAfterNativeRuntimeStarted: ") else 1)
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os._exit(os.waitpid(grandchild, 0)[1])
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assert os.waitpid(pid, 0)[1] == 0
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"""
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)
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@pytest.mark.skipif(not hasattr(os, "fork"), reason="fork only")
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def test_compiled_extension_forbids_the_master_and_frees_its_workers() -> None:
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env = {**os.environ, "OBJC_DISABLE_INITIALIZE_FORK_SAFETY": "YES"}
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result = run_child_interpreter(_NATIVE_CONTRACT, env=env, timeout=60)
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assert result.returncode == 0, result.stderr
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_SDK_CONTRACT = textwrap.dedent(
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"""
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import asyncio, json, multiprocessing, os, threading
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from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
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import litellm
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from litellm.rust_bridge.fork_guard import ForkedAfterNativeRuntimeStarted
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class Handler(BaseHTTPRequestHandler):
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def do_POST(self):
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self.rfile.read(int(self.headers["Content-Length"]))
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if self.headers.get("User-Agent", "").startswith("python-httpx"):
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self.send_response(418)
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self.end_headers()
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return
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body = json.dumps({
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"pages": [{"index": 0, "markdown": "native", "images": [], "dimensions": None}],
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"model": "mistral-ocr-latest",
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"usage_info": {"pages_processed": 1, "doc_size_bytes": 3},
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}).encode()
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self.send_response(200)
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self.send_header("Content-Type", "application/json")
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self.send_header("Content-Length", str(len(body)))
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self.end_headers()
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self.wfile.write(body)
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def log_message(self, *args):
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pass
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server = ThreadingHTTPServer(("127.0.0.1", 0), Handler)
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threading.Thread(target=server.serve_forever, daemon=True).start()
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arguments = {
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"model": "mistral/mistral-ocr-latest",
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"document": {"type": "document_url", "document_url": "data:application/pdf;base64,YWJj"},
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"api_key": "test-key",
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"api_base": f"http://127.0.0.1:{server.server_port}",
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"num_retries": 0,
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}
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litellm.rust(True)
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SERVED, REFUSED, OTHER = 0, 3, 4
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def outcome(asynchronous):
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try:
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response = asyncio.run(litellm.aocr(**arguments)) if asynchronous else litellm.ocr(**arguments)
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except ForkedAfterNativeRuntimeStarted:
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return REFUSED
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except Exception:
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return OTHER
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return SERVED if response.pages[0].markdown == "native" else OTHER
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def forked(asynchronous):
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pid = os.fork()
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if pid == 0:
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os._exit(outcome(asynchronous))
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return os.waitstatus_to_exitcode(os.waitpid(pid, 0)[1])
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def pooled(asynchronous):
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with multiprocessing.get_context("fork").Pool(1) as pool:
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return pool.apply(outcome, (asynchronous,))
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# Forking before the first native call is fine: the child starts its own runtime.
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assert [forked(False), forked(True)] == [SERVED, SERVED]
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assert outcome(False) == SERVED
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# After it, a forked child is told so instead of hanging on threads that do not exist.
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assert [forked(False), forked(True)] == [REFUSED, REFUSED]
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assert [pooled(False), pooled(True)] == [REFUSED, REFUSED]
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# The parent is not poisoned by any of it.
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assert [outcome(False), outcome(True)] == [SERVED, SERVED]
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"""
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)
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@pytest.mark.skipif(not hasattr(os, "fork"), reason="fork only")
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def test_sdk_call_in_a_child_forked_after_native_use_raises_instead_of_hanging() -> None:
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env = {
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**os.environ,
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"OBJC_DISABLE_INITIALIZE_FORK_SAFETY": "YES",
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"LITELLM_RUST": "1",
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"LITELLM_LOCAL_MODEL_COST_MAP": "True",
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}
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result = run_child_interpreter(_SDK_CONTRACT, env=env, timeout=120)
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assert result.returncode == 0, result.stderr
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@pytest.mark.skipif(not hasattr(os, "fork"), reason="fork only")
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@pytest.mark.parametrize("warm_fast_counter", (False, True))
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def test_tokenizers_share_the_native_process_guard(warm_fast_counter: bool) -> None:
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script: Final = """
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import asyncio
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import os
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import litellm
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from litellm.proxy.spend_tracking.input_tokens import count_input_tokens
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from litellm.rust_bridge import _native
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from litellm.litellm_core_utils.tokenizer import HuggingFaceTokenizer
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from litellm.utils import claude_json_str
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litellm.anthropic_models = {*litellm.anthropic_models, "tokenizer-fork-fixture"}
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_native.reserve_process_for_forking()
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for create in (
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lambda: _native.Tokenizer.from_tiktoken("cl100k_base"),
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lambda: _native.Tokenizer.from_json(claude_json_str),
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lambda: litellm.token_counter(model="tokenizer-fork-fixture", text="hello"),
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):
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try:
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create()
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except _native.ProcessReservedForForking:
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pass
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else:
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raise AssertionError("reserved parent ran a native tokenizer")
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assert not _native.process_state_started()
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pid = os.fork()
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if pid == 0:
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tokenizer = HuggingFaceTokenizer.from_str(claude_json_str)
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encoding = _native.Tokenizer.from_tiktoken("cl100k_base")
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if os.environ["WARM_FAST_COUNTER"] == "True":
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_native.TokenCounter.from_tokenizer(encoding, fast=True)
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expected = [item.ids for item in tokenizer.encode_batch(["hello", "world"])]
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assert _native.process_state_started()
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grandchild = os.fork()
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if grandchild == 0:
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for call in (
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lambda: tokenizer.encode_batch(["hello", "world"]),
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lambda: tokenizer.encode("hello"),
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lambda: encoding.count("hello"),
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lambda: encoding.count("hello", fast=True),
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lambda: _native.TokenCounter.from_tokenizer(encoding),
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lambda: _native.TokenCounter.from_tokenizer(encoding, fast=True),
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lambda: _native.Tokenizer.from_tiktoken("cl100k_base"),
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lambda: asyncio.run(count_input_tokens({"prompt": "hello"}, b'{"prompt": "hello"}', ("counter-fork-fixture",))),
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):
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try:
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call()
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except _native.ForkedAfterNativeRuntimeStarted:
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pass
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else:
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os._exit(1)
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os._exit(0)
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assert os.waitpid(grandchild, 0)[1] == 0
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assert [item.ids for item in tokenizer.encode_batch(["hello", "world"])] == expected
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os._exit(0)
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assert os.waitpid(pid, 0)[1] == 0
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"""
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result: Final = run_child_interpreter(
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script,
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env={
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**os.environ,
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"OBJC_DISABLE_INITIALIZE_FORK_SAFETY": "YES",
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"LITELLM_LOCAL_MODEL_COST_MAP": "True",
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"WARM_FAST_COUNTER": str(warm_fast_counter),
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},
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timeout=30,
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)
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assert result.returncode == 0, result.stderr
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