chore: import upstream snapshot with attribution
This commit is contained in:
wehub-resource-sync
@@ -0,0 +1,598 @@
|
||||
# SPDX-License-Identifier: Apache-2.0
|
||||
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
|
||||
"""Replay tests for engine parsers (holdback, skip-tool-parsing, adapters).
|
||||
|
||||
Replays dynamically built token sequences at different chunk sizes and
|
||||
holdback depths to verify chunk-size invariance and terminal-token hygiene.
|
||||
|
||||
Parser discovery is automatic: any ``ParserEngine`` subclass registered in
|
||||
``registered_adapters`` that also has a builder in ``trace_builder._BUILDERS``
|
||||
is picked up with zero manual wiring.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import dataclasses
|
||||
from typing import NamedTuple
|
||||
|
||||
import pytest
|
||||
|
||||
from tests.parser.engine.replay_harness import (
|
||||
DUMMY_TOOLS,
|
||||
MockTokenizer,
|
||||
Sample,
|
||||
_test_request,
|
||||
assert_no_terminal_leakage,
|
||||
assert_parse_output,
|
||||
collect_output,
|
||||
make_mock_tokenizer,
|
||||
parse_non_streaming,
|
||||
replay_streaming,
|
||||
replay_with_text_holdback,
|
||||
)
|
||||
from tests.parser.engine.trace_builder import _BUILDERS, build_samples
|
||||
from vllm.parser.engine import registered_adapters as _adapters_mod
|
||||
from vllm.parser.engine.parser_engine import ParserEngine
|
||||
from vllm.parser.engine.parser_engine_config import ParserState
|
||||
|
||||
# ── Parser discovery ─────────────────────────────────────────────────
|
||||
|
||||
|
||||
class _ParserInfo(NamedTuple):
|
||||
parser_cls: type[ParserEngine]
|
||||
name: str
|
||||
samples: tuple
|
||||
terminals: list[str]
|
||||
tool_end: str
|
||||
think_end: str
|
||||
tool_start: str
|
||||
|
||||
|
||||
def _discover_parsers() -> list[_ParserInfo]:
|
||||
"""Discover engine parsers from registered_adapters that have test builders.
|
||||
|
||||
Returns one ``_ParserInfo`` per parser, sorted by config name.
|
||||
Raises ``RuntimeError`` if any registered parser lacks a builder.
|
||||
"""
|
||||
bare_tok = MockTokenizer(vocab={}, tokens=[])
|
||||
found: list[_ParserInfo] = []
|
||||
missing_builders: list[str] = []
|
||||
for obj in vars(_adapters_mod).values():
|
||||
if not (
|
||||
isinstance(obj, type)
|
||||
and issubclass(obj, ParserEngine)
|
||||
and obj is not ParserEngine
|
||||
):
|
||||
continue
|
||||
cfg = obj(bare_tok, None).parser_engine_config
|
||||
if cfg.name not in _BUILDERS:
|
||||
missing_builders.append(f"{obj.__name__} (config.name={cfg.name!r})")
|
||||
continue
|
||||
tool_end = cfg.token_id_terminals.get("TOOL_END")
|
||||
if not tool_end:
|
||||
raise RuntimeError(
|
||||
f"{obj.__name__} config missing 'TOOL_END' in token_id_terminals"
|
||||
)
|
||||
all_vals = set(cfg.terminals.values()) | set(cfg.token_id_terminals.values())
|
||||
found.append(
|
||||
_ParserInfo(
|
||||
parser_cls=obj,
|
||||
name=cfg.name,
|
||||
samples=build_samples(cfg.name),
|
||||
terminals=sorted(v for v in all_vals if len(v) > 1),
|
||||
tool_end=tool_end,
|
||||
think_end=cfg.terminals.get("THINK_END", ""),
|
||||
tool_start=(
|
||||
cfg.terminals["TOOL_SECTION_START"]
|
||||
if (ParserState.CONTENT, "TOOL_SECTION_START") in cfg.transitions
|
||||
else cfg.terminals.get("TOOL_START", "")
|
||||
),
|
||||
)
|
||||
)
|
||||
if missing_builders:
|
||||
raise RuntimeError(
|
||||
f"Engine parsers in registered_adapters have no test builder "
|
||||
f"in trace_builder._BUILDERS: {', '.join(missing_builders)}. "
|
||||
f"Add a builder to _BUILDERS for each new parser."
|
||||
)
|
||||
found.sort(key=lambda p: p.name)
|
||||
return found
|
||||
|
||||
|
||||
_PARSERS = _discover_parsers()
|
||||
|
||||
|
||||
def _make_parser(parser_cls: type[ParserEngine], tokenizer, sample: Sample, **extra):
|
||||
kwargs = dict(extra)
|
||||
if sample.chat_template_kwargs:
|
||||
kwargs["chat_template_kwargs"] = sample.chat_template_kwargs
|
||||
return parser_cls(tokenizer, sample.tools, **kwargs)
|
||||
|
||||
|
||||
_ENGINE_PARSERS: dict[str, type[ParserEngine]] = {
|
||||
f"{p.name}_engine": p.parser_cls for p in _PARSERS
|
||||
}
|
||||
|
||||
# ── Parametrize sample lists ─────────────────────────────────────────
|
||||
|
||||
HOLDBACK_CONFIGS = [6, 12, 24]
|
||||
|
||||
_REPLAY_SAMPLES = [(p.parser_cls, s, p.terminals) for p in _PARSERS for s in p.samples]
|
||||
|
||||
|
||||
@pytest.mark.parametrize("holdback", HOLDBACK_CONFIGS, ids=lambda h: f"holdback{h}")
|
||||
@pytest.mark.parametrize("chunk_size", [3, 5, 10], ids=lambda c: f"chunk{c}")
|
||||
@pytest.mark.parametrize(
|
||||
"parser_cls,sample,terminals",
|
||||
_REPLAY_SAMPLES,
|
||||
ids=lambda v: v.id if hasattr(v, "id") else "",
|
||||
)
|
||||
class TestReplayWithHoldback:
|
||||
"""Replay all parsers with simulated detokenizer holdback."""
|
||||
|
||||
def test_replay(self, parser_cls, sample, terminals, chunk_size, holdback):
|
||||
tokenizer = make_mock_tokenizer(sample)
|
||||
parser = _make_parser(parser_cls, tokenizer, sample)
|
||||
deltas = replay_streaming(
|
||||
parser,
|
||||
sample.tokens,
|
||||
chunk_size=chunk_size,
|
||||
holdback_chars=holdback,
|
||||
prompt_token_ids=sample.prompt_token_ids,
|
||||
)
|
||||
output = collect_output(deltas)
|
||||
|
||||
assert_parse_output(output, sample)
|
||||
assert_no_terminal_leakage(
|
||||
output,
|
||||
terminals,
|
||||
context=f"chunk_size={chunk_size}, holdback={holdback}",
|
||||
)
|
||||
|
||||
|
||||
TEXT_HOLDBACK_DELAYS = [1, 2, 3]
|
||||
|
||||
|
||||
@pytest.mark.parametrize("delay", TEXT_HOLDBACK_DELAYS, ids=lambda d: f"delay{d}")
|
||||
@pytest.mark.parametrize(
|
||||
"parser_cls,sample,terminals",
|
||||
_REPLAY_SAMPLES,
|
||||
ids=lambda v: v.id if hasattr(v, "id") else "",
|
||||
)
|
||||
class TestTextHoldback:
|
||||
"""Replay with production-like text/token-ID misalignment.
|
||||
|
||||
In production the detokenizer sends token IDs immediately but holds
|
||||
back text by N tokens. This exercises the TokenIDScanner deferred
|
||||
terminal path that aligned-holdback tests do not cover.
|
||||
"""
|
||||
|
||||
def test_replay(self, parser_cls, sample, terminals, delay):
|
||||
tokenizer = make_mock_tokenizer(sample)
|
||||
parser = _make_parser(parser_cls, tokenizer, sample)
|
||||
deltas = replay_with_text_holdback(
|
||||
parser,
|
||||
sample.tokens,
|
||||
text_delay=delay,
|
||||
prompt_token_ids=sample.prompt_token_ids,
|
||||
)
|
||||
output = collect_output(deltas)
|
||||
|
||||
assert_parse_output(output, sample)
|
||||
assert_no_terminal_leakage(
|
||||
output,
|
||||
terminals,
|
||||
context=f"text_delay={delay}",
|
||||
)
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"chunk_size", [1, 2, 3, 5, 10, 19, 20, None], ids=lambda c: f"chunk{c}"
|
||||
)
|
||||
@pytest.mark.parametrize(
|
||||
"parser_cls,sample,terminals",
|
||||
_REPLAY_SAMPLES,
|
||||
ids=lambda v: v.id if hasattr(v, "id") else "",
|
||||
)
|
||||
class TestReplay:
|
||||
"""Replay all parsers at varied chunk sizes without holdback."""
|
||||
|
||||
def test_replay(self, parser_cls, sample, terminals, chunk_size):
|
||||
tokenizer = make_mock_tokenizer(sample)
|
||||
parser = _make_parser(parser_cls, tokenizer, sample)
|
||||
deltas = replay_streaming(
|
||||
parser,
|
||||
sample.tokens,
|
||||
chunk_size=chunk_size,
|
||||
prompt_token_ids=sample.prompt_token_ids,
|
||||
)
|
||||
output = collect_output(deltas)
|
||||
|
||||
assert_parse_output(output, sample)
|
||||
assert_no_terminal_leakage(output, terminals)
|
||||
|
||||
|
||||
_DEFERRAL_SAMPLES = [
|
||||
(p.parser_cls, s, p.tool_end)
|
||||
for p in _PARSERS
|
||||
for s in p.samples
|
||||
if s.expected_tool_calls
|
||||
]
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"parser_cls,sample,tool_end_text",
|
||||
_DEFERRAL_SAMPLES,
|
||||
ids=lambda v: v.id if hasattr(v, "id") else getattr(v, "__name__", ""),
|
||||
)
|
||||
class TestDeferralFinish:
|
||||
"""Test that parse_delta(finished=True) resolves deferred scanner state.
|
||||
|
||||
Simulates a production failure where delta_text is missing the
|
||||
tool-call-end text but delta_token_ids has the token, causing the
|
||||
scanner to defer it. Without finish(), the deferred state is lost
|
||||
and tool call arguments are empty.
|
||||
"""
|
||||
|
||||
def test_misaligned_last_delta_with_finish(self, parser_cls, sample, tool_end_text):
|
||||
tokenizer = make_mock_tokenizer(sample)
|
||||
parser = _make_parser(parser_cls, tokenizer, sample)
|
||||
|
||||
request = _test_request()
|
||||
|
||||
all_ids = [tid for tid, _ in sample.tokens]
|
||||
all_texts = [text for _, text in sample.tokens]
|
||||
|
||||
tool_end_id = sample.vocab.get(tool_end_text)
|
||||
split_idx = None
|
||||
for i in range(len(all_ids) - 1, -1, -1):
|
||||
if all_ids[i] == tool_end_id:
|
||||
split_idx = i
|
||||
break
|
||||
|
||||
if split_idx is None:
|
||||
pytest.skip(f"no {tool_end_text} token found")
|
||||
|
||||
first_ids = all_ids[:split_idx]
|
||||
first_text = "".join(all_texts[:split_idx])
|
||||
|
||||
last_ids = all_ids[split_idx:]
|
||||
last_text_missing = "".join(all_texts[split_idx:]).replace(tool_end_text, "")
|
||||
|
||||
result1 = parser.parse_delta(
|
||||
first_text,
|
||||
first_ids,
|
||||
request,
|
||||
prompt_token_ids=[],
|
||||
finished=False,
|
||||
)
|
||||
result2 = parser.parse_delta(
|
||||
last_text_missing, last_ids, request, finished=True
|
||||
)
|
||||
|
||||
output = collect_output([result1, result2])
|
||||
|
||||
tool_calls_only = dataclasses.replace(
|
||||
sample, expected_reasoning=None, expected_content=None
|
||||
)
|
||||
assert_parse_output(output, tool_calls_only)
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"parser_cls,sample",
|
||||
[(p.parser_cls, p.samples[0]) for p in _PARSERS],
|
||||
ids=[p.name for p in _PARSERS],
|
||||
)
|
||||
class TestParserEngineAdjustRequest:
|
||||
"""Verify ParserEngine and its adapters set skip_special_tokens=False."""
|
||||
|
||||
def test_adjust_request_disables_skip_special_tokens(self, parser_cls, sample):
|
||||
tokenizer = make_mock_tokenizer(sample)
|
||||
parser = parser_cls(tokenizer, sample.tools)
|
||||
request = _test_request()
|
||||
assert request.skip_special_tokens is True
|
||||
adjusted = parser.adjust_request(request)
|
||||
assert adjusted.skip_special_tokens is False
|
||||
|
||||
|
||||
_TOOL_CALL_SAMPLES = [
|
||||
(p.parser_cls, s, p.think_end, p.tool_start)
|
||||
for p in _PARSERS
|
||||
for s in p.samples
|
||||
if s.expected_tool_calls and s.expected_reasoning
|
||||
]
|
||||
|
||||
|
||||
def _tool_suppression_expectations(
|
||||
sample, think_end: str, tool_start: str, *, include_tool_block: bool
|
||||
) -> tuple[str, str]:
|
||||
"""Expected (reasoning, content) when tool calls are not extracted.
|
||||
|
||||
With ``include_tool_block=True`` (skip_tool_parsing / reasoning
|
||||
adapter first pass), tool terminal text is preserved as content so
|
||||
a second-pass parser can see it.
|
||||
|
||||
With ``include_tool_block=False`` (_suppress_tool_calls /
|
||||
tool_choice='none'), the state machine consumes tool blocks and
|
||||
only non-tool content survives.
|
||||
"""
|
||||
full_text = "".join(text for _, text in sample.tokens)
|
||||
reasoning = sample.expected_reasoning
|
||||
idx = full_text.find(reasoning)
|
||||
if idx < 0:
|
||||
return (full_text, "")
|
||||
after_reasoning = full_text[idx + len(reasoning) :]
|
||||
if think_end:
|
||||
pos = after_reasoning.find(think_end)
|
||||
if pos >= 0:
|
||||
if include_tool_block:
|
||||
return (reasoning, after_reasoning[pos + len(think_end) :])
|
||||
after_reasoning = after_reasoning[pos + len(think_end) :]
|
||||
if tool_start:
|
||||
pos = after_reasoning.find(tool_start)
|
||||
if pos >= 0:
|
||||
if include_tool_block:
|
||||
return (reasoning, after_reasoning[pos:])
|
||||
return (reasoning, after_reasoning[:pos])
|
||||
if include_tool_block:
|
||||
return (full_text, "")
|
||||
return (reasoning, after_reasoning)
|
||||
|
||||
|
||||
@pytest.mark.parametrize("chunk_size", [1, 5, None], ids=lambda c: f"chunk{c}")
|
||||
@pytest.mark.parametrize(
|
||||
"mode",
|
||||
["skip_tool_parsing", "suppress_tool_calls"],
|
||||
ids=["skip_tool_parsing", "suppress_tool_calls"],
|
||||
)
|
||||
@pytest.mark.parametrize(
|
||||
"parser_cls,sample,think_end,tool_start",
|
||||
_TOOL_CALL_SAMPLES,
|
||||
ids=lambda v: v.id if hasattr(v, "id") else getattr(v, "__name__", ""),
|
||||
)
|
||||
class TestToolCallFilteringReplay:
|
||||
"""Replay with tool calls not extracted, in both filtering modes.
|
||||
|
||||
``skip_tool_parsing`` (reasoning adapter first pass): tool terminal
|
||||
text is preserved as content for a second-pass tool parser.
|
||||
|
||||
``suppress_tool_calls`` (tool_choice='none'): tool call blocks are
|
||||
consumed by the state machine and do not leak into content.
|
||||
"""
|
||||
|
||||
def test_replay(self, parser_cls, sample, think_end, tool_start, mode, chunk_size):
|
||||
tokenizer = make_mock_tokenizer(sample)
|
||||
kwargs = {}
|
||||
if sample.chat_template_kwargs:
|
||||
kwargs["chat_template_kwargs"] = sample.chat_template_kwargs
|
||||
parser = parser_cls(tokenizer, **kwargs)
|
||||
|
||||
request = _test_request()
|
||||
request.tools = DUMMY_TOOLS
|
||||
if mode == "skip_tool_parsing":
|
||||
parser.skip_tool_parsing = True
|
||||
else:
|
||||
request.tool_choice = "none"
|
||||
|
||||
all_ids = [tid for tid, _ in sample.tokens]
|
||||
all_texts = [text for _, text in sample.tokens]
|
||||
if chunk_size is None:
|
||||
chunk_size = len(all_ids)
|
||||
|
||||
results = []
|
||||
chunks = list(range(0, len(all_ids), chunk_size))
|
||||
for i, start in enumerate(chunks):
|
||||
end = min(start + chunk_size, len(all_ids))
|
||||
is_last = i == len(chunks) - 1
|
||||
result = parser.parse_delta(
|
||||
"".join(all_texts[start:end]),
|
||||
all_ids[start:end],
|
||||
request,
|
||||
prompt_token_ids=(sample.prompt_token_ids or [])
|
||||
if start == 0
|
||||
else None,
|
||||
finished=is_last,
|
||||
)
|
||||
results.append(result)
|
||||
|
||||
output = collect_output(results)
|
||||
|
||||
include_block = mode == "skip_tool_parsing"
|
||||
expected_reasoning, expected_content = _tool_suppression_expectations(
|
||||
sample, think_end, tool_start, include_tool_block=include_block
|
||||
)
|
||||
|
||||
assert output.reasoning == expected_reasoning, (
|
||||
f"Reasoning mismatch (mode={mode}):\n"
|
||||
f" expected: {expected_reasoning!r}\n"
|
||||
f" actual: {output.reasoning!r}"
|
||||
)
|
||||
assert output.tool_calls == [], (
|
||||
f"Expected no tool calls (mode={mode}) but got {output.tool_calls}"
|
||||
)
|
||||
assert output.content == expected_content, (
|
||||
f"Content mismatch (mode={mode}):\n"
|
||||
f" expected: {expected_content!r}\n"
|
||||
f" actual: {output.content!r}"
|
||||
)
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"parser_cls,sample,think_end,tool_start",
|
||||
_TOOL_CALL_SAMPLES,
|
||||
ids=lambda v: v.id if hasattr(v, "id") else getattr(v, "__name__", ""),
|
||||
)
|
||||
class TestToolCallFilteringNonStreaming:
|
||||
"""Non-streaming parse() with tool_choice='none' must suppress tool
|
||||
calls and not leak special tokens into content."""
|
||||
|
||||
def test_parse(self, parser_cls, sample, think_end, tool_start):
|
||||
tokenizer = make_mock_tokenizer(sample)
|
||||
kwargs = {}
|
||||
if sample.chat_template_kwargs:
|
||||
kwargs["chat_template_kwargs"] = sample.chat_template_kwargs
|
||||
parser = parser_cls(tokenizer, **kwargs)
|
||||
|
||||
request = _test_request()
|
||||
request.tools = DUMMY_TOOLS
|
||||
request.tool_choice = "none"
|
||||
|
||||
output = parse_non_streaming(parser, sample, request)
|
||||
|
||||
expected_reasoning, expected_content = _tool_suppression_expectations(
|
||||
sample, think_end, tool_start, include_tool_block=False
|
||||
)
|
||||
assert output.reasoning == expected_reasoning, (
|
||||
f"Reasoning mismatch:\n"
|
||||
f" expected: {expected_reasoning!r}\n"
|
||||
f" actual: {output.reasoning!r}"
|
||||
)
|
||||
assert output.tool_calls == [], (
|
||||
f"Expected no tool calls but got {output.tool_calls}"
|
||||
)
|
||||
assert output.content == expected_content, (
|
||||
f"Content mismatch:\n"
|
||||
f" expected: {expected_content!r}\n"
|
||||
f" actual: {output.content!r}"
|
||||
)
|
||||
|
||||
|
||||
_WS_TOOL_SAMPLES = [(t[0], t[1]) for t in _TOOL_CALL_SAMPLES if "whitespace" in t[1].id]
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"parser_cls,sample",
|
||||
_WS_TOOL_SAMPLES,
|
||||
ids=lambda v: v.id if hasattr(v, "id") else getattr(v, "__name__", ""),
|
||||
)
|
||||
class TestToolChoiceNoneStreamingParity:
|
||||
"""Streaming and non-streaming must return the same content
|
||||
when tool_choice='none' suppresses tool calls."""
|
||||
|
||||
def test_content_matches(self, parser_cls, sample):
|
||||
tokenizer = make_mock_tokenizer(sample)
|
||||
kwargs = {}
|
||||
if sample.chat_template_kwargs:
|
||||
kwargs["chat_template_kwargs"] = sample.chat_template_kwargs
|
||||
request = _test_request()
|
||||
request.tools = DUMMY_TOOLS
|
||||
request.tool_choice = "none"
|
||||
|
||||
ns_output = parse_non_streaming(
|
||||
parser_cls(tokenizer, **kwargs),
|
||||
sample,
|
||||
request,
|
||||
)
|
||||
|
||||
s_parser = parser_cls(tokenizer, **kwargs)
|
||||
results = []
|
||||
for i, (tid, text) in enumerate(sample.tokens):
|
||||
is_last = i == len(sample.tokens) - 1
|
||||
results.append(
|
||||
s_parser.parse_delta(
|
||||
text,
|
||||
[tid],
|
||||
request,
|
||||
prompt_token_ids=(sample.prompt_token_ids or [])
|
||||
if i == 0
|
||||
else None,
|
||||
finished=is_last,
|
||||
)
|
||||
)
|
||||
s_output = collect_output(results)
|
||||
|
||||
assert ns_output.content == s_output.content, (
|
||||
f"Streaming/non-streaming content mismatch:\n"
|
||||
f" streaming: {s_output.content!r}\n"
|
||||
f" non-streaming: {ns_output.content!r}"
|
||||
)
|
||||
|
||||
|
||||
_DROP_TOKENS = {"<bos>": 99990, "<eos>": 99991}
|
||||
|
||||
|
||||
def _inject_drop_tokens(sample):
|
||||
"""Insert <bos> at stream start and <eos> between the first two tokens."""
|
||||
new_vocab = {**sample.vocab, **_DROP_TOKENS}
|
||||
tokens = list(sample.tokens)
|
||||
tokens.insert(0, (99990, "<bos>"))
|
||||
if len(tokens) >= 3:
|
||||
tokens.insert(2, (99991, "<eos>"))
|
||||
else:
|
||||
tokens.append((99991, "<eos>"))
|
||||
return dataclasses.replace(sample, vocab=new_vocab, tokens=tokens)
|
||||
|
||||
|
||||
class TestDropTokenReplay:
|
||||
"""Verify unconfigured special tokens are silently dropped across
|
||||
all parsers and chunk sizes."""
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"parser_info",
|
||||
_PARSERS,
|
||||
ids=[p.name for p in _PARSERS],
|
||||
)
|
||||
@pytest.mark.parametrize("chunk_size", [1, 3, None])
|
||||
def test_drop_tokens_removed_from_output(self, parser_info, chunk_size):
|
||||
for sample in parser_info.samples:
|
||||
injected = _inject_drop_tokens(sample)
|
||||
tokenizer = make_mock_tokenizer(injected)
|
||||
parser = _make_parser(parser_info.parser_cls, tokenizer, sample)
|
||||
|
||||
results = replay_streaming(
|
||||
parser,
|
||||
injected.tokens,
|
||||
chunk_size=chunk_size,
|
||||
tools=sample.tools,
|
||||
prompt_token_ids=sample.prompt_token_ids,
|
||||
)
|
||||
output = collect_output(results)
|
||||
|
||||
assert_no_terminal_leakage(
|
||||
output,
|
||||
list(_DROP_TOKENS.keys()),
|
||||
context=f"parser={parser_info.name}, chunk={chunk_size}",
|
||||
)
|
||||
assert_parse_output(output, sample)
|
||||
|
||||
|
||||
class TestDropTokenNonStreaming:
|
||||
"""Non-streaming parse() must also strip unconfigured special tokens."""
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"parser_info",
|
||||
_PARSERS,
|
||||
ids=[p.name for p in _PARSERS],
|
||||
)
|
||||
def test_drop_tokens_removed_from_output(self, parser_info):
|
||||
for sample in parser_info.samples:
|
||||
injected = _inject_drop_tokens(sample)
|
||||
tokenizer = make_mock_tokenizer(injected)
|
||||
parser = _make_parser(parser_info.parser_cls, tokenizer, sample)
|
||||
|
||||
request = _test_request(tools=sample.tools)
|
||||
output = parse_non_streaming(parser, injected, request)
|
||||
|
||||
assert_no_terminal_leakage(
|
||||
output,
|
||||
list(_DROP_TOKENS.keys()),
|
||||
context=f"parser={parser_info.name}",
|
||||
)
|
||||
|
||||
|
||||
class TestAdapterReferences:
|
||||
"""Verify make_adapters sets reasoning/tool parser class refs on parser engine
|
||||
parser classes so the serving layer finds them and calls adjust_request."""
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"parser_name",
|
||||
list(_ENGINE_PARSERS.keys()),
|
||||
)
|
||||
def test_adapter_cls_refs_set(self, parser_name):
|
||||
parser_cls = _ENGINE_PARSERS[parser_name]
|
||||
assert parser_cls.reasoning_parser_cls is not None, (
|
||||
f"{parser_name}: reasoning_parser_cls is None"
|
||||
)
|
||||
assert parser_cls.tool_parser_cls is not None, (
|
||||
f"{parser_name}: tool_parser_cls is None"
|
||||
)
|
||||
Reference in New Issue
Block a user