| 1 |
"""Teacher selector parsing and runtime wrappers for Sprint 43.""" |
| 2 |
|
| 3 |
from __future__ import annotations |
| 4 |
|
| 5 |
import builtins |
| 6 |
import json |
| 7 |
import sys |
| 8 |
import urllib.error |
| 9 |
from pathlib import Path |
| 10 |
from types import ModuleType, SimpleNamespace |
| 11 |
from typing import Any, Literal |
| 12 |
|
| 13 |
import pytest |
| 14 |
|
| 15 |
import dlm.synth.teachers as teachers_mod |
| 16 |
from dlm.synth import ( |
| 17 |
AnthropicTeacher, |
| 18 |
HfTeacher, |
| 19 |
InvalidTeacherSpecError, |
| 20 |
OpenAiTeacher, |
| 21 |
SelfTeacher, |
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TeacherInvocationError, |
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TeacherUnavailableError, |
| 24 |
VllmServerTeacher, |
| 25 |
build_teacher, |
| 26 |
parse_teacher_ref, |
| 27 |
) |
| 28 |
|
| 29 |
|
| 30 |
def _module(name: str, **attrs: object) -> ModuleType: |
| 31 |
module = ModuleType(name) |
| 32 |
for key, value in attrs.items(): |
| 33 |
setattr(module, key, value) |
| 34 |
return module |
| 35 |
|
| 36 |
|
| 37 |
class TestTeacherSelectorParsing: |
| 38 |
@pytest.mark.parametrize( |
| 39 |
("raw", "kind", "target"), |
| 40 |
[ |
| 41 |
("self", "self", None), |
| 42 |
("hf:Qwen/Qwen2.5-1.5B-Instruct", "hf", "Qwen/Qwen2.5-1.5B-Instruct"), |
| 43 |
("openai:gpt-4o-mini", "openai", "gpt-4o-mini"), |
| 44 |
("anthropic:claude-3-5-haiku-latest", "anthropic", "claude-3-5-haiku-latest"), |
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("vllm-server:http://127.0.0.1:8000", "vllm-server", "http://127.0.0.1:8000"), |
| 46 |
], |
| 47 |
) |
| 48 |
def test_parse_teacher_ref(self, raw: str, kind: str, target: str | None) -> None: |
| 49 |
ref = parse_teacher_ref(raw) |
| 50 |
assert ref.kind == kind |
| 51 |
assert ref.target == target |
| 52 |
|
| 53 |
def test_empty_selector_refused(self) -> None: |
| 54 |
with pytest.raises(InvalidTeacherSpecError, match="must not be empty"): |
| 55 |
parse_teacher_ref(" ") |
| 56 |
|
| 57 |
def test_unknown_selector_refused(self) -> None: |
| 58 |
with pytest.raises(InvalidTeacherSpecError, match="unknown teacher selector"): |
| 59 |
parse_teacher_ref("mystery:thing") |
| 60 |
|
| 61 |
@pytest.mark.parametrize( |
| 62 |
("raw", "message"), |
| 63 |
[ |
| 64 |
("hf: ", "hf teacher selector must include a model id"), |
| 65 |
("openai: ", "openai teacher selector must include a model id"), |
| 66 |
("anthropic: ", "anthropic teacher selector must include a model id"), |
| 67 |
("vllm-server: ", "vllm-server teacher selector must include a URL"), |
| 68 |
], |
| 69 |
) |
| 70 |
def test_missing_selector_targets_are_refused(self, raw: str, message: str) -> None: |
| 71 |
with pytest.raises(InvalidTeacherSpecError, match=message): |
| 72 |
parse_teacher_ref(raw) |
| 73 |
|
| 74 |
|
| 75 |
class TestBuildTeacher: |
| 76 |
def test_self_requires_dlm_path(self) -> None: |
| 77 |
with pytest.raises(TeacherUnavailableError, match="requires the .dlm path context"): |
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build_teacher("self") |
| 79 |
|
| 80 |
def test_build_teacher_dispatches(self, tmp_path: Path) -> None: |
| 81 |
self_teacher = build_teacher("self", dlm_path=tmp_path / "doc.dlm") |
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assert isinstance(self_teacher, SelfTeacher) |
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assert self_teacher.backend == "pytorch" |
| 84 |
assert isinstance(build_teacher("hf:foo/bar"), HfTeacher) |
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assert isinstance(build_teacher("openai:gpt-4o-mini"), OpenAiTeacher) |
| 86 |
assert isinstance(build_teacher("anthropic:claude"), AnthropicTeacher) |
| 87 |
assert isinstance( |
| 88 |
build_teacher("vllm-server:http://127.0.0.1:8000"), |
| 89 |
VllmServerTeacher, |
| 90 |
) |
| 91 |
|
| 92 |
|
| 93 |
class TestSelfTeacher: |
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def test_self_teacher_uses_loader_once_and_forwards_kwargs(self, tmp_path: Path) -> None: |
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calls: list[tuple[str, dict[str, Any]]] = [] |
| 96 |
loaded_paths: list[tuple[Path, str]] = [] |
| 97 |
|
| 98 |
class _Backend: |
| 99 |
def generate(self, prompt: str, **gen_kwargs: Any) -> str: |
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calls.append((prompt, gen_kwargs)) |
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return " synthesized answer " |
| 102 |
|
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def _loader(path: Path, backend: str) -> _Backend: |
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loaded_paths.append((path, backend)) |
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return _Backend() |
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|
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teacher = SelfTeacher(tmp_path / "doc.dlm", loader=_loader) |
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out1 = teacher.generate( |
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"system text", |
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"user text", |
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max_new_tokens=33, |
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temperature=0.7, |
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top_p=0.9, |
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seed=7, |
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) |
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out2 = teacher.generate("system text", "user text") |
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|
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assert out1 == "synthesized answer" |
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assert out2 == "synthesized answer" |
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assert loaded_paths == [(tmp_path / "doc.dlm", "auto")] |
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assert "system text" in calls[0][0] |
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assert "user text" in calls[0][0] |
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assert calls[0][1] == { |
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"max_new_tokens": 33, |
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"temperature": 0.7, |
| 126 |
"top_p": 0.9, |
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} |
| 128 |
|
| 129 |
|
| 130 |
class TestHfTeacher: |
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def test_blank_hf_id_refused(self) -> None: |
| 132 |
with pytest.raises(InvalidTeacherSpecError, match="must include a model id"): |
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HfTeacher(" ") |
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|
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def test_hf_teacher_uses_loader_and_runner(self) -> None: |
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seen: dict[str, Any] = {} |
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|
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def _loader(hf_id: str, device: str) -> teachers_mod._LoadedHfTeacher: |
| 139 |
seen["loader"] = (hf_id, device) |
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return teachers_mod._LoadedHfTeacher(model="model", tokenizer="tok", device=device) |
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|
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def _runner( |
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model: Any, |
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tokenizer: Any, |
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prompt: str, |
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*, |
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max_new_tokens: int, |
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temperature: float, |
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top_p: float | None, |
| 150 |
seed: int | None, |
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) -> str: |
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seen["runner"] = (model, tokenizer, prompt, max_new_tokens, temperature, top_p, seed) |
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return " hf output " |
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|
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teacher = HfTeacher("Qwen/Qwen2.5-1.5B-Instruct", loader=_loader, runner=_runner) |
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out = teacher.generate( |
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"system", "user", max_new_tokens=21, temperature=0.5, top_p=0.8, seed=11 |
| 158 |
) |
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assert out == "hf output" |
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assert seen["loader"] == ( |
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"Qwen/Qwen2.5-1.5B-Instruct", |
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teachers_mod._resolve_generation_device("auto"), |
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) |
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assert seen["runner"][3:] == (21, 0.5, 0.8, 11) |
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|
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def test_hf_teacher_reuses_loaded_bundle(self) -> None: |
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loads: list[tuple[str, str]] = [] |
| 168 |
|
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def _loader(hf_id: str, device: str) -> teachers_mod._LoadedHfTeacher: |
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loads.append((hf_id, device)) |
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return teachers_mod._LoadedHfTeacher(model="model", tokenizer="tok", device=device) |
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|
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teacher = HfTeacher( |
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"Qwen/Qwen2.5-1.5B-Instruct", |
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loader=_loader, |
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runner=lambda *_args, **_kwargs: "ok", |
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) |
| 178 |
|
| 179 |
assert teacher.generate("system", "user") == "ok" |
| 180 |
assert teacher.generate("system", "user") == "ok" |
| 181 |
assert loads == [ |
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("Qwen/Qwen2.5-1.5B-Instruct", teachers_mod._resolve_generation_device("auto")) |
| 183 |
] |
| 184 |
|
| 185 |
|
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class TestOpenAiTeacher: |
| 187 |
def test_blank_model_refused(self) -> None: |
| 188 |
with pytest.raises(InvalidTeacherSpecError, match="must include a model id"): |
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OpenAiTeacher(" ") |
| 190 |
|
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def test_missing_api_key_refused(self, monkeypatch: pytest.MonkeyPatch) -> None: |
| 192 |
monkeypatch.delenv("OPENAI_API_KEY", raising=False) |
| 193 |
teacher = OpenAiTeacher("gpt-4o-mini") |
| 194 |
with pytest.raises(TeacherUnavailableError, match="OPENAI_API_KEY"): |
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teacher.generate("system", "user") |
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|
| 197 |
def test_openai_teacher_extracts_message_text(self, monkeypatch: pytest.MonkeyPatch) -> None: |
| 198 |
monkeypatch.setenv("OPENAI_API_KEY", "secret") |
| 199 |
|
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payloads: list[dict[str, Any]] = [] |
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factories: list[str] = [] |
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|
| 203 |
def _create(**kwargs: Any) -> Any: |
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payloads.append(kwargs) |
| 205 |
return SimpleNamespace( |
| 206 |
choices=[SimpleNamespace(message=SimpleNamespace(content=" generated "))] |
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) |
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|
| 209 |
def _factory(api_key: str) -> Any: |
| 210 |
factories.append(api_key) |
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return client |
| 212 |
|
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client = SimpleNamespace( |
| 214 |
chat=SimpleNamespace( |
| 215 |
completions=SimpleNamespace(create=_create), |
| 216 |
) |
| 217 |
) |
| 218 |
|
| 219 |
teacher = OpenAiTeacher( |
| 220 |
"gpt-4o-mini", |
| 221 |
client_factory=_factory, |
| 222 |
) |
| 223 |
out = teacher.generate("sys", "usr", max_new_tokens=17, temperature=0.3, top_p=0.7, seed=5) |
| 224 |
second = teacher.generate("sys", "usr") |
| 225 |
assert out == "generated" |
| 226 |
assert second == "generated" |
| 227 |
assert payloads[0]["model"] == "gpt-4o-mini" |
| 228 |
assert payloads[0]["seed"] == 5 |
| 229 |
assert factories == ["secret"] |
| 230 |
|
| 231 |
def test_openai_teacher_wraps_request_failures(self, monkeypatch: pytest.MonkeyPatch) -> None: |
| 232 |
monkeypatch.setenv("OPENAI_API_KEY", "secret") |
| 233 |
|
| 234 |
def _create(**_kwargs: Any) -> Any: |
| 235 |
raise RuntimeError("boom") |
| 236 |
|
| 237 |
client = SimpleNamespace( |
| 238 |
chat=SimpleNamespace( |
| 239 |
completions=SimpleNamespace(create=_create), |
| 240 |
) |
| 241 |
) |
| 242 |
teacher = OpenAiTeacher("gpt-4o-mini", client_factory=lambda _api_key: client) |
| 243 |
|
| 244 |
with pytest.raises(TeacherInvocationError, match="openai:gpt-4o-mini request failed: boom"): |
| 245 |
teacher.generate("sys", "usr") |
| 246 |
|
| 247 |
|
| 248 |
class TestAnthropicTeacher: |
| 249 |
def test_blank_model_refused(self) -> None: |
| 250 |
with pytest.raises(InvalidTeacherSpecError, match="must include a model id"): |
| 251 |
AnthropicTeacher(" ") |
| 252 |
|
| 253 |
def test_missing_api_key_refused(self, monkeypatch: pytest.MonkeyPatch) -> None: |
| 254 |
monkeypatch.delenv("ANTHROPIC_API_KEY", raising=False) |
| 255 |
teacher = AnthropicTeacher("claude-3-5-haiku-latest") |
| 256 |
with pytest.raises(TeacherUnavailableError, match="ANTHROPIC_API_KEY"): |
| 257 |
teacher.generate("system", "user") |
| 258 |
|
| 259 |
def test_anthropic_teacher_extracts_text_blocks(self, monkeypatch: pytest.MonkeyPatch) -> None: |
| 260 |
monkeypatch.setenv("ANTHROPIC_API_KEY", "secret") |
| 261 |
captured: dict[str, Any] = {} |
| 262 |
factories: list[str] = [] |
| 263 |
|
| 264 |
class _Messages: |
| 265 |
@staticmethod |
| 266 |
def create(**kwargs: Any) -> Any: |
| 267 |
captured["payload"] = kwargs |
| 268 |
return SimpleNamespace( |
| 269 |
content=[ |
| 270 |
SimpleNamespace(type="image", text="ignored"), |
| 271 |
SimpleNamespace(type="text", text=" first "), |
| 272 |
SimpleNamespace(type="text", text=" second "), |
| 273 |
] |
| 274 |
) |
| 275 |
|
| 276 |
class _Client: |
| 277 |
messages = _Messages() |
| 278 |
|
| 279 |
def _factory(api_key: str) -> _Client: |
| 280 |
factories.append(api_key) |
| 281 |
return _Client() |
| 282 |
|
| 283 |
teacher = AnthropicTeacher( |
| 284 |
"claude-3-5-haiku-latest", |
| 285 |
client_factory=_factory, |
| 286 |
) |
| 287 |
out = teacher.generate("sys", "usr", max_new_tokens=19, temperature=0.2, top_p=0.6) |
| 288 |
second = teacher.generate("sys", "usr") |
| 289 |
assert out == "first\nsecond" |
| 290 |
assert second == "first\nsecond" |
| 291 |
assert captured["payload"]["model"] == "claude-3-5-haiku-latest" |
| 292 |
assert factories == ["secret"] |
| 293 |
|
| 294 |
def test_anthropic_teacher_wraps_request_failures( |
| 295 |
self, monkeypatch: pytest.MonkeyPatch |
| 296 |
) -> None: |
| 297 |
monkeypatch.setenv("ANTHROPIC_API_KEY", "secret") |
| 298 |
|
| 299 |
class _Messages: |
| 300 |
@staticmethod |
| 301 |
def create(**_kwargs: Any) -> Any: |
| 302 |
raise RuntimeError("boom") |
| 303 |
|
| 304 |
class _Client: |
| 305 |
messages = _Messages() |
| 306 |
|
| 307 |
teacher = AnthropicTeacher( |
| 308 |
"claude-3-5-haiku-latest", |
| 309 |
client_factory=lambda _api_key: _Client(), |
| 310 |
) |
| 311 |
|
| 312 |
with pytest.raises( |
| 313 |
TeacherInvocationError, |
| 314 |
match="anthropic:claude-3-5-haiku-latest request failed: boom", |
| 315 |
): |
| 316 |
teacher.generate("sys", "usr") |
| 317 |
|
| 318 |
|
| 319 |
class TestVllmServerTeacher: |
| 320 |
def test_blank_url_refused(self) -> None: |
| 321 |
with pytest.raises(InvalidTeacherSpecError, match="must include a URL"): |
| 322 |
VllmServerTeacher(" ") |
| 323 |
|
| 324 |
def test_invalid_url_refused(self) -> None: |
| 325 |
with pytest.raises(InvalidTeacherSpecError, match="http\\(s\\)"): |
| 326 |
VllmServerTeacher("localhost:8000") |
| 327 |
|
| 328 |
def test_vllm_teacher_queries_model_and_completion( |
| 329 |
self, monkeypatch: pytest.MonkeyPatch |
| 330 |
) -> None: |
| 331 |
model_calls: list[tuple[str, float]] = [] |
| 332 |
completion_calls: list[tuple[Any, ...]] = [] |
| 333 |
|
| 334 |
def _fake_models(base_url: str, *, request_timeout: float) -> str | None: |
| 335 |
model_calls.append((base_url, request_timeout)) |
| 336 |
return "demo-model" |
| 337 |
|
| 338 |
def _fake_completion( |
| 339 |
base_url: str, |
| 340 |
*, |
| 341 |
model_id: str | None, |
| 342 |
messages: list[dict[str, str]], |
| 343 |
max_new_tokens: int, |
| 344 |
temperature: float, |
| 345 |
top_p: float | None, |
| 346 |
seed: int | None, |
| 347 |
request_timeout: float, |
| 348 |
) -> str: |
| 349 |
completion_calls.append( |
| 350 |
( |
| 351 |
base_url, |
| 352 |
model_id, |
| 353 |
messages, |
| 354 |
max_new_tokens, |
| 355 |
temperature, |
| 356 |
top_p, |
| 357 |
seed, |
| 358 |
request_timeout, |
| 359 |
) |
| 360 |
) |
| 361 |
return " served " |
| 362 |
|
| 363 |
monkeypatch.setattr(teachers_mod, "_fetch_openai_compat_model_id", _fake_models) |
| 364 |
monkeypatch.setattr(teachers_mod, "_request_openai_compat_completion", _fake_completion) |
| 365 |
|
| 366 |
teacher = VllmServerTeacher("http://127.0.0.1:8000") |
| 367 |
out = teacher.generate("sys", "usr", max_new_tokens=29, temperature=0.4, top_p=0.75, seed=9) |
| 368 |
second = teacher.generate("sys", "usr") |
| 369 |
|
| 370 |
assert out == "served" |
| 371 |
assert second == "served" |
| 372 |
assert model_calls == [("http://127.0.0.1:8000", 30.0)] |
| 373 |
assert completion_calls[0][1] == "demo-model" |
| 374 |
assert completion_calls[0][3:] == (29, 0.4, 0.75, 9, 30.0) |
| 375 |
|
| 376 |
|
| 377 |
class TestTeacherHelpers: |
| 378 |
def test_flatten_teacher_prompt_handles_partial_inputs(self) -> None: |
| 379 |
assert teachers_mod._flatten_teacher_prompt("system", "user").startswith("System:\n") |
| 380 |
assert teachers_mod._flatten_teacher_prompt("", "user") == "user" |
| 381 |
assert teachers_mod._flatten_teacher_prompt("system", "") == "system" |
| 382 |
|
| 383 |
def test_require_non_empty_teacher_output_refuses_blank_text(self) -> None: |
| 384 |
with pytest.raises(TeacherInvocationError, match="self returned empty output"): |
| 385 |
teachers_mod._require_non_empty_teacher_output(" ", teacher="self") |
| 386 |
|
| 387 |
def test_extract_openai_message_text_handles_list_content_and_errors(self) -> None: |
| 388 |
response = { |
| 389 |
"choices": [ |
| 390 |
{ |
| 391 |
"message": { |
| 392 |
"content": [ |
| 393 |
{"text": " first "}, |
| 394 |
{"text": " second "}, |
| 395 |
] |
| 396 |
} |
| 397 |
} |
| 398 |
] |
| 399 |
} |
| 400 |
assert teachers_mod._extract_openai_message_text(response) == "first\nsecond" |
| 401 |
|
| 402 |
with pytest.raises(TeacherInvocationError, match="missing choices"): |
| 403 |
teachers_mod._extract_openai_message_text({}) |
| 404 |
|
| 405 |
with pytest.raises(TeacherInvocationError, match="missing choices\\[0\\]\\.message"): |
| 406 |
teachers_mod._extract_openai_message_text({"choices": [{}]}) |
| 407 |
|
| 408 |
with pytest.raises(TeacherInvocationError, match="missing non-empty message content"): |
| 409 |
teachers_mod._extract_openai_message_text({"choices": [{"message": {"content": None}}]}) |
| 410 |
|
| 411 |
def test_extract_anthropic_text_handles_errors(self) -> None: |
| 412 |
with pytest.raises(TeacherInvocationError, match="missing content blocks"): |
| 413 |
teachers_mod._extract_anthropic_text({}) |
| 414 |
|
| 415 |
with pytest.raises(TeacherInvocationError, match="missing non-empty text blocks"): |
| 416 |
teachers_mod._extract_anthropic_text( |
| 417 |
{"content": [{"type": "image", "text": "ignored"}, {"type": "text", "text": " "}]} |
| 418 |
) |
| 419 |
|
| 420 |
def test_normalize_chat_content_and_obj_get_helpers(self) -> None: |
| 421 |
assert teachers_mod._normalize_chat_content(" hello ") == "hello" |
| 422 |
assert ( |
| 423 |
teachers_mod._normalize_chat_content([{"text": " one "}, {"text": " two "}]) |
| 424 |
== "one\ntwo" |
| 425 |
) |
| 426 |
assert teachers_mod._normalize_chat_content([{"text": " "}]) is None |
| 427 |
assert teachers_mod._normalize_chat_content(123) is None |
| 428 |
assert teachers_mod._obj_get({"name": "value"}, "name") == "value" |
| 429 |
assert teachers_mod._obj_get(SimpleNamespace(name="value"), "name") == "value" |
| 430 |
|
| 431 |
def test_openai_compat_url_helpers_normalize_suffixes(self) -> None: |
| 432 |
assert ( |
| 433 |
teachers_mod._normalize_openai_compat_base_url( |
| 434 |
"http://127.0.0.1:8000/v1/chat/completions" |
| 435 |
) |
| 436 |
== "http://127.0.0.1:8000" |
| 437 |
) |
| 438 |
assert ( |
| 439 |
teachers_mod._normalize_openai_compat_base_url("http://127.0.0.1:8000/chat/completions") |
| 440 |
== "http://127.0.0.1:8000" |
| 441 |
) |
| 442 |
assert teachers_mod._openai_compat_models_url("http://127.0.0.1:8000/v1") == ( |
| 443 |
"http://127.0.0.1:8000/v1/models" |
| 444 |
) |
| 445 |
assert teachers_mod._openai_compat_models_url("http://127.0.0.1:8000") == ( |
| 446 |
"http://127.0.0.1:8000/v1/models" |
| 447 |
) |
| 448 |
assert teachers_mod._openai_compat_chat_url("http://127.0.0.1:8000/v1") == ( |
| 449 |
"http://127.0.0.1:8000/v1/chat/completions" |
| 450 |
) |
| 451 |
assert teachers_mod._openai_compat_chat_url("http://127.0.0.1:8000") == ( |
| 452 |
"http://127.0.0.1:8000/v1/chat/completions" |
| 453 |
) |
| 454 |
|
| 455 |
|
| 456 |
class TestTeacherRuntimeHelpers: |
| 457 |
def test_resolve_generation_device_prefers_requested_or_detected_backends( |
| 458 |
self, |
| 459 |
monkeypatch: pytest.MonkeyPatch, |
| 460 |
) -> None: |
| 461 |
assert teachers_mod._resolve_generation_device("mps") == "mps" |
| 462 |
|
| 463 |
monkeypatch.delitem(sys.modules, "torch", raising=False) |
| 464 |
real_import = builtins.__import__ |
| 465 |
|
| 466 |
def _missing_torch( |
| 467 |
name: str, |
| 468 |
globals: dict[str, object] | None = None, |
| 469 |
locals: dict[str, object] | None = None, |
| 470 |
fromlist: tuple[str, ...] = (), |
| 471 |
level: int = 0, |
| 472 |
) -> object: |
| 473 |
if name == "torch": |
| 474 |
raise ImportError("no torch") |
| 475 |
return real_import(name, globals, locals, fromlist, level) |
| 476 |
|
| 477 |
monkeypatch.setattr(builtins, "__import__", _missing_torch) |
| 478 |
assert teachers_mod._resolve_generation_device("auto") == "cpu" |
| 479 |
|
| 480 |
monkeypatch.setattr(builtins, "__import__", real_import) |
| 481 |
monkeypatch.setitem( |
| 482 |
sys.modules, |
| 483 |
"torch", |
| 484 |
SimpleNamespace( |
| 485 |
cuda=SimpleNamespace(is_available=lambda: True), |
| 486 |
backends=SimpleNamespace(mps=SimpleNamespace(is_available=lambda: False)), |
| 487 |
), |
| 488 |
) |
| 489 |
assert teachers_mod._resolve_generation_device("auto") == "cuda" |
| 490 |
|
| 491 |
monkeypatch.setitem( |
| 492 |
sys.modules, |
| 493 |
"torch", |
| 494 |
SimpleNamespace( |
| 495 |
cuda=SimpleNamespace(is_available=lambda: False), |
| 496 |
backends=SimpleNamespace(mps=SimpleNamespace(is_available=lambda: True)), |
| 497 |
), |
| 498 |
) |
| 499 |
assert teachers_mod._resolve_generation_device("auto") == "mps" |
| 500 |
|
| 501 |
monkeypatch.setitem( |
| 502 |
sys.modules, |
| 503 |
"torch", |
| 504 |
SimpleNamespace( |
| 505 |
cuda=SimpleNamespace(is_available=lambda: False), |
| 506 |
backends=SimpleNamespace(mps=SimpleNamespace(is_available=lambda: False)), |
| 507 |
), |
| 508 |
) |
| 509 |
assert teachers_mod._resolve_generation_device("auto") == "cpu" |
| 510 |
|
| 511 |
def test_default_openai_client_validates_import_surface( |
| 512 |
self, |
| 513 |
monkeypatch: pytest.MonkeyPatch, |
| 514 |
) -> None: |
| 515 |
def _raise_import(name: str) -> object: |
| 516 |
raise ImportError(name) |
| 517 |
|
| 518 |
monkeypatch.setattr("dlm.synth.teachers.importlib.import_module", _raise_import) |
| 519 |
with pytest.raises(TeacherUnavailableError, match="requires the openai package"): |
| 520 |
teachers_mod._default_openai_client("secret") |
| 521 |
|
| 522 |
monkeypatch.setattr( |
| 523 |
"dlm.synth.teachers.importlib.import_module", lambda _name: SimpleNamespace() |
| 524 |
) |
| 525 |
with pytest.raises(TeacherUnavailableError, match="does not expose OpenAI client"): |
| 526 |
teachers_mod._default_openai_client("secret") |
| 527 |
|
| 528 |
captured: list[str] = [] |
| 529 |
|
| 530 |
class _OpenAI: |
| 531 |
def __init__(self, *, api_key: str) -> None: |
| 532 |
captured.append(api_key) |
| 533 |
|
| 534 |
monkeypatch.setattr( |
| 535 |
"dlm.synth.teachers.importlib.import_module", |
| 536 |
lambda _name: SimpleNamespace(OpenAI=_OpenAI), |
| 537 |
) |
| 538 |
client = teachers_mod._default_openai_client("secret") |
| 539 |
assert isinstance(client, _OpenAI) |
| 540 |
assert captured == ["secret"] |
| 541 |
|
| 542 |
def test_default_anthropic_client_validates_import_surface( |
| 543 |
self, |
| 544 |
monkeypatch: pytest.MonkeyPatch, |
| 545 |
) -> None: |
| 546 |
def _raise_import(name: str) -> object: |
| 547 |
raise ImportError(name) |
| 548 |
|
| 549 |
monkeypatch.setattr("dlm.synth.teachers.importlib.import_module", _raise_import) |
| 550 |
with pytest.raises(TeacherUnavailableError, match="requires the anthropic package"): |
| 551 |
teachers_mod._default_anthropic_client("secret") |
| 552 |
|
| 553 |
monkeypatch.setattr( |
| 554 |
"dlm.synth.teachers.importlib.import_module", lambda _name: SimpleNamespace() |
| 555 |
) |
| 556 |
with pytest.raises(TeacherUnavailableError, match="does not expose Anthropic client"): |
| 557 |
teachers_mod._default_anthropic_client("secret") |
| 558 |
|
| 559 |
captured: list[str] = [] |
| 560 |
|
| 561 |
class _Anthropic: |
| 562 |
def __init__(self, *, api_key: str) -> None: |
| 563 |
captured.append(api_key) |
| 564 |
|
| 565 |
monkeypatch.setattr( |
| 566 |
"dlm.synth.teachers.importlib.import_module", |
| 567 |
lambda _name: SimpleNamespace(Anthropic=_Anthropic), |
| 568 |
) |
| 569 |
client = teachers_mod._default_anthropic_client("secret") |
| 570 |
assert isinstance(client, _Anthropic) |
| 571 |
assert captured == ["secret"] |
| 572 |
|
| 573 |
def test_fetch_openai_compat_model_id_handles_success_empty_and_errors( |
| 574 |
self, |
| 575 |
monkeypatch: pytest.MonkeyPatch, |
| 576 |
) -> None: |
| 577 |
class _Response: |
| 578 |
def __init__(self, payload: object) -> None: |
| 579 |
self._payload = payload |
| 580 |
|
| 581 |
def __enter__(self) -> _Response: |
| 582 |
return self |
| 583 |
|
| 584 |
def __exit__(self, *_args: object) -> Literal[False]: |
| 585 |
return False |
| 586 |
|
| 587 |
def read(self) -> bytes: |
| 588 |
return json.dumps(self._payload).encode("utf-8") |
| 589 |
|
| 590 |
monkeypatch.setattr( |
| 591 |
"dlm.synth.teachers.urllib.request.urlopen", |
| 592 |
lambda *_args, **_kwargs: _Response({"data": [{"id": "demo-model"}]}), |
| 593 |
) |
| 594 |
assert ( |
| 595 |
teachers_mod._fetch_openai_compat_model_id( |
| 596 |
"http://127.0.0.1:8000", |
| 597 |
request_timeout=1.0, |
| 598 |
) |
| 599 |
== "demo-model" |
| 600 |
) |
| 601 |
|
| 602 |
monkeypatch.setattr( |
| 603 |
"dlm.synth.teachers.urllib.request.urlopen", |
| 604 |
lambda *_args, **_kwargs: _Response({"data": []}), |
| 605 |
) |
| 606 |
assert ( |
| 607 |
teachers_mod._fetch_openai_compat_model_id( |
| 608 |
"http://127.0.0.1:8000", |
| 609 |
request_timeout=1.0, |
| 610 |
) |
| 611 |
is None |
| 612 |
) |
| 613 |
|
| 614 |
monkeypatch.setattr( |
| 615 |
"dlm.synth.teachers.urllib.request.urlopen", |
| 616 |
lambda *_args, **_kwargs: _Response({"data": [{"id": " "}]}), |
| 617 |
) |
| 618 |
assert ( |
| 619 |
teachers_mod._fetch_openai_compat_model_id( |
| 620 |
"http://127.0.0.1:8000", |
| 621 |
request_timeout=1.0, |
| 622 |
) |
| 623 |
is None |
| 624 |
) |
| 625 |
|
| 626 |
def _raise_url_error(*_args: object, **_kwargs: object) -> object: |
| 627 |
raise urllib.error.URLError("boom") |
| 628 |
|
| 629 |
monkeypatch.setattr("dlm.synth.teachers.urllib.request.urlopen", _raise_url_error) |
| 630 |
with pytest.raises(TeacherUnavailableError, match="could not query models"): |
| 631 |
teachers_mod._fetch_openai_compat_model_id( |
| 632 |
"http://127.0.0.1:8000", |
| 633 |
request_timeout=1.0, |
| 634 |
) |
| 635 |
|
| 636 |
def test_request_openai_compat_completion_handles_success_and_failures( |
| 637 |
self, |
| 638 |
monkeypatch: pytest.MonkeyPatch, |
| 639 |
) -> None: |
| 640 |
class _Response: |
| 641 |
def __init__(self, payload: object) -> None: |
| 642 |
self._payload = payload |
| 643 |
|
| 644 |
def __enter__(self) -> _Response: |
| 645 |
return self |
| 646 |
|
| 647 |
def __exit__(self, *_args: object) -> Literal[False]: |
| 648 |
return False |
| 649 |
|
| 650 |
def read(self) -> bytes: |
| 651 |
return json.dumps(self._payload).encode("utf-8") |
| 652 |
|
| 653 |
monkeypatch.setattr( |
| 654 |
"dlm.synth.teachers.urllib.request.urlopen", |
| 655 |
lambda *_args, **_kwargs: _Response( |
| 656 |
{"choices": [{"message": {"content": [{"text": " served "}]}}]} |
| 657 |
), |
| 658 |
) |
| 659 |
assert ( |
| 660 |
teachers_mod._request_openai_compat_completion( |
| 661 |
"http://127.0.0.1:8000", |
| 662 |
model_id="demo-model", |
| 663 |
messages=[{"role": "user", "content": "hello"}], |
| 664 |
max_new_tokens=11, |
| 665 |
temperature=0.2, |
| 666 |
top_p=0.8, |
| 667 |
seed=5, |
| 668 |
request_timeout=1.0, |
| 669 |
) |
| 670 |
== "served" |
| 671 |
) |
| 672 |
|
| 673 |
monkeypatch.setattr( |
| 674 |
"dlm.synth.teachers.urllib.request.urlopen", |
| 675 |
lambda *_args, **_kwargs: _Response({"choices": []}), |
| 676 |
) |
| 677 |
with pytest.raises(TeacherInvocationError, match="response missing choices"): |
| 678 |
teachers_mod._request_openai_compat_completion( |
| 679 |
"http://127.0.0.1:8000", |
| 680 |
model_id=None, |
| 681 |
messages=[{"role": "user", "content": "hello"}], |
| 682 |
max_new_tokens=11, |
| 683 |
temperature=0.2, |
| 684 |
top_p=None, |
| 685 |
seed=None, |
| 686 |
request_timeout=1.0, |
| 687 |
) |
| 688 |
|
| 689 |
monkeypatch.setattr( |
| 690 |
"dlm.synth.teachers.urllib.request.urlopen", |
| 691 |
lambda *_args, **_kwargs: _Response({"choices": [{}]}), |
| 692 |
) |
| 693 |
with pytest.raises( |
| 694 |
TeacherInvocationError, match="response missing choices\\[0\\]\\.message" |
| 695 |
): |
| 696 |
teachers_mod._request_openai_compat_completion( |
| 697 |
"http://127.0.0.1:8000", |
| 698 |
model_id=None, |
| 699 |
messages=[{"role": "user", "content": "hello"}], |
| 700 |
max_new_tokens=11, |
| 701 |
temperature=0.2, |
| 702 |
top_p=None, |
| 703 |
seed=None, |
| 704 |
request_timeout=1.0, |
| 705 |
) |
| 706 |
|
| 707 |
monkeypatch.setattr( |
| 708 |
"dlm.synth.teachers.urllib.request.urlopen", |
| 709 |
lambda *_args, **_kwargs: _Response( |
| 710 |
{"choices": [{"message": {"content": [{"text": " "}]}}]} |
| 711 |
), |
| 712 |
) |
| 713 |
with pytest.raises(TeacherInvocationError, match="missing non-empty message content"): |
| 714 |
teachers_mod._request_openai_compat_completion( |
| 715 |
"http://127.0.0.1:8000", |
| 716 |
model_id=None, |
| 717 |
messages=[{"role": "user", "content": "hello"}], |
| 718 |
max_new_tokens=11, |
| 719 |
temperature=0.2, |
| 720 |
top_p=None, |
| 721 |
seed=None, |
| 722 |
request_timeout=1.0, |
| 723 |
) |
| 724 |
|
| 725 |
def _raise_url_error(*_args: object, **_kwargs: object) -> object: |
| 726 |
raise urllib.error.URLError("boom") |
| 727 |
|
| 728 |
monkeypatch.setattr("dlm.synth.teachers.urllib.request.urlopen", _raise_url_error) |
| 729 |
with pytest.raises(TeacherInvocationError, match="request to http://127.0.0.1:8000 failed"): |
| 730 |
teachers_mod._request_openai_compat_completion( |
| 731 |
"http://127.0.0.1:8000", |
| 732 |
model_id=None, |
| 733 |
messages=[{"role": "user", "content": "hello"}], |
| 734 |
max_new_tokens=11, |
| 735 |
temperature=0.2, |
| 736 |
top_p=None, |
| 737 |
seed=None, |
| 738 |
request_timeout=1.0, |
| 739 |
) |
| 740 |
|
| 741 |
|
| 742 |
def _install_self_loader_modules( |
| 743 |
monkeypatch: pytest.MonkeyPatch, |
| 744 |
*, |
| 745 |
manifest_exists: bool = True, |
| 746 |
license_acceptance: object | None = "accepted", |
| 747 |
load_manifest_error: str | None = None, |
| 748 |
resolve_error: str | None = None, |
| 749 |
select_error: str | None = None, |
| 750 |
backend_load_error: str | None = None, |
| 751 |
) -> dict[str, object]: |
| 752 |
calls: dict[str, object] = {} |
| 753 |
spec = object() |
| 754 |
caps = object() |
| 755 |
parsed = SimpleNamespace( |
| 756 |
frontmatter=SimpleNamespace( |
| 757 |
dlm_id="01KPQ9X1000000000000000000", |
| 758 |
base_model="smollm2-135m", |
| 759 |
) |
| 760 |
) |
| 761 |
manifest = SimpleNamespace(exists=lambda: manifest_exists) |
| 762 |
store = SimpleNamespace(manifest=manifest) |
| 763 |
|
| 764 |
class GatedModelError(Exception): |
| 765 |
pass |
| 766 |
|
| 767 |
class AdapterNotFoundError(Exception): |
| 768 |
pass |
| 769 |
|
| 770 |
class UnsupportedBackendError(Exception): |
| 771 |
pass |
| 772 |
|
| 773 |
class ManifestCorruptError(Exception): |
| 774 |
pass |
| 775 |
|
| 776 |
class _Backend: |
| 777 |
def load(self, spec_arg: object, store_arg: object) -> None: |
| 778 |
calls["load"] = (spec_arg, store_arg) |
| 779 |
if backend_load_error is not None: |
| 780 |
raise AdapterNotFoundError(backend_load_error) |
| 781 |
|
| 782 |
backend = _Backend() |
| 783 |
|
| 784 |
def _resolve(base_model: str, *, accept_license: bool) -> object: |
| 785 |
calls["resolve"] = (base_model, accept_license) |
| 786 |
if resolve_error is not None: |
| 787 |
raise GatedModelError(resolve_error) |
| 788 |
return spec |
| 789 |
|
| 790 |
def _load_manifest(_path: object) -> object: |
| 791 |
calls["load_manifest"] = True |
| 792 |
if load_manifest_error is not None: |
| 793 |
raise ManifestCorruptError(load_manifest_error) |
| 794 |
return SimpleNamespace(license_acceptance=license_acceptance) |
| 795 |
|
| 796 |
def _select_backend(backend_name: str, capabilities: object) -> str: |
| 797 |
calls["select_backend"] = (backend_name, capabilities) |
| 798 |
if select_error is not None: |
| 799 |
raise UnsupportedBackendError(select_error) |
| 800 |
return "stub-backend" |
| 801 |
|
| 802 |
def _build_backend(name: str, capabilities: object) -> object: |
| 803 |
calls["build_backend"] = (name, capabilities) |
| 804 |
return backend |
| 805 |
|
| 806 |
monkeypatch.setitem( |
| 807 |
sys.modules, "dlm.base_models", _module("dlm.base_models", resolve=_resolve) |
| 808 |
) |
| 809 |
monkeypatch.setitem( |
| 810 |
sys.modules, |
| 811 |
"dlm.base_models.errors", |
| 812 |
_module("dlm.base_models.errors", GatedModelError=GatedModelError), |
| 813 |
) |
| 814 |
monkeypatch.setitem( |
| 815 |
sys.modules, |
| 816 |
"dlm.doc.parser", |
| 817 |
_module("dlm.doc.parser", parse_file=lambda _path: parsed), |
| 818 |
) |
| 819 |
monkeypatch.setitem( |
| 820 |
sys.modules, |
| 821 |
"dlm.hardware", |
| 822 |
_module("dlm.hardware", doctor=lambda: SimpleNamespace(capabilities=caps)), |
| 823 |
) |
| 824 |
monkeypatch.setitem( |
| 825 |
sys.modules, |
| 826 |
"dlm.inference", |
| 827 |
_module("dlm.inference", AdapterNotFoundError=AdapterNotFoundError), |
| 828 |
) |
| 829 |
monkeypatch.setitem( |
| 830 |
sys.modules, |
| 831 |
"dlm.inference.backends", |
| 832 |
_module( |
| 833 |
"dlm.inference.backends", build_backend=_build_backend, select_backend=_select_backend |
| 834 |
), |
| 835 |
) |
| 836 |
monkeypatch.setitem( |
| 837 |
sys.modules, |
| 838 |
"dlm.inference.backends.select", |
| 839 |
_module("dlm.inference.backends.select", UnsupportedBackendError=UnsupportedBackendError), |
| 840 |
) |
| 841 |
monkeypatch.setitem( |
| 842 |
sys.modules, |
| 843 |
"dlm.store.errors", |
| 844 |
_module("dlm.store.errors", ManifestCorruptError=ManifestCorruptError), |
| 845 |
) |
| 846 |
monkeypatch.setitem( |
| 847 |
sys.modules, |
| 848 |
"dlm.store.manifest", |
| 849 |
_module("dlm.store.manifest", load_manifest=_load_manifest), |
| 850 |
) |
| 851 |
monkeypatch.setitem( |
| 852 |
sys.modules, |
| 853 |
"dlm.store.paths", |
| 854 |
_module("dlm.store.paths", for_dlm=lambda _dlm_id: store), |
| 855 |
) |
| 856 |
|
| 857 |
calls["caps"] = caps |
| 858 |
calls["store"] = store |
| 859 |
calls["spec"] = spec |
| 860 |
calls["errors"] = { |
| 861 |
"gated": GatedModelError, |
| 862 |
"adapter": AdapterNotFoundError, |
| 863 |
"unsupported": UnsupportedBackendError, |
| 864 |
"manifest": ManifestCorruptError, |
| 865 |
} |
| 866 |
return calls |
| 867 |
|
| 868 |
|
| 869 |
class TestTeacherLoaderHelpers: |
| 870 |
def test_load_self_backend_wraps_import_error(self, monkeypatch: pytest.MonkeyPatch) -> None: |
| 871 |
real_import = builtins.__import__ |
| 872 |
|
| 873 |
def _raise_on_base_models( |
| 874 |
name: str, |
| 875 |
globals: dict[str, object] | None = None, |
| 876 |
locals: dict[str, object] | None = None, |
| 877 |
fromlist: tuple[str, ...] = (), |
| 878 |
level: int = 0, |
| 879 |
) -> object: |
| 880 |
if name.startswith("dlm.base_models"): |
| 881 |
raise ImportError("boom") |
| 882 |
return real_import(name, globals, locals, fromlist, level) |
| 883 |
|
| 884 |
monkeypatch.setattr(builtins, "__import__", _raise_on_base_models) |
| 885 |
with pytest.raises(TeacherUnavailableError, match="requires the local inference stack"): |
| 886 |
teachers_mod._load_self_backend(Path("/tmp/doc.dlm"), "auto") |
| 887 |
|
| 888 |
def test_load_self_backend_uses_recorded_license_acceptance( |
| 889 |
self, |
| 890 |
monkeypatch: pytest.MonkeyPatch, |
| 891 |
) -> None: |
| 892 |
calls = _install_self_loader_modules(monkeypatch, license_acceptance="accepted") |
| 893 |
|
| 894 |
backend = teachers_mod._load_self_backend(Path("/tmp/doc.dlm"), "auto") |
| 895 |
|
| 896 |
assert backend is not None |
| 897 |
assert calls["resolve"] == ("smollm2-135m", True) |
| 898 |
assert calls["select_backend"] == ("auto", calls["caps"]) |
| 899 |
assert calls["build_backend"] == ("stub-backend", calls["caps"]) |
| 900 |
assert calls["load"] == (calls["spec"], calls["store"]) |
| 901 |
|
| 902 |
def test_load_self_backend_tolerates_manifest_read_failure( |
| 903 |
self, |
| 904 |
monkeypatch: pytest.MonkeyPatch, |
| 905 |
) -> None: |
| 906 |
calls = _install_self_loader_modules( |
| 907 |
monkeypatch, |
| 908 |
load_manifest_error="bad manifest", |
| 909 |
) |
| 910 |
|
| 911 |
teachers_mod._load_self_backend(Path("/tmp/doc.dlm"), "auto") |
| 912 |
|
| 913 |
assert calls["resolve"] == ("smollm2-135m", False) |
| 914 |
|
| 915 |
def test_load_self_backend_wraps_gated_backend_and_adapter_failures( |
| 916 |
self, |
| 917 |
monkeypatch: pytest.MonkeyPatch, |
| 918 |
) -> None: |
| 919 |
_install_self_loader_modules(monkeypatch, resolve_error="gated") |
| 920 |
with pytest.raises(TeacherUnavailableError, match="cannot resolve gated base"): |
| 921 |
teachers_mod._load_self_backend(Path("/tmp/doc.dlm"), "auto") |
| 922 |
|
| 923 |
_install_self_loader_modules(monkeypatch, select_error="unsupported backend") |
| 924 |
with pytest.raises(TeacherUnavailableError, match="unsupported backend"): |
| 925 |
teachers_mod._load_self_backend(Path("/tmp/doc.dlm"), "auto") |
| 926 |
|
| 927 |
_install_self_loader_modules(monkeypatch, backend_load_error="missing adapter") |
| 928 |
with pytest.raises(TeacherUnavailableError, match="requires a trained adapter"): |
| 929 |
teachers_mod._load_self_backend(Path("/tmp/doc.dlm"), "auto") |
| 930 |
|
| 931 |
def test_default_hf_loader_wraps_import_error(self, monkeypatch: pytest.MonkeyPatch) -> None: |
| 932 |
real_import = builtins.__import__ |
| 933 |
|
| 934 |
def _raise_transformers( |
| 935 |
name: str, |
| 936 |
globals: dict[str, object] | None = None, |
| 937 |
locals: dict[str, object] | None = None, |
| 938 |
fromlist: tuple[str, ...] = (), |
| 939 |
level: int = 0, |
| 940 |
) -> object: |
| 941 |
if name == "transformers": |
| 942 |
raise ImportError("boom") |
| 943 |
return real_import(name, globals, locals, fromlist, level) |
| 944 |
|
| 945 |
monkeypatch.setattr(builtins, "__import__", _raise_transformers) |
| 946 |
with pytest.raises(TeacherUnavailableError, match="requires transformers"): |
| 947 |
teachers_mod._default_hf_loader("hf/model", "cpu") |
| 948 |
|
| 949 |
def test_default_hf_loader_moves_model_and_sets_eval( |
| 950 |
self, |
| 951 |
monkeypatch: pytest.MonkeyPatch, |
| 952 |
) -> None: |
| 953 |
seen: dict[str, object] = {} |
| 954 |
|
| 955 |
class _Model: |
| 956 |
def to(self, device: str) -> _Model: |
| 957 |
seen["device"] = device |
| 958 |
return self |
| 959 |
|
| 960 |
def eval(self) -> None: |
| 961 |
seen["eval"] = True |
| 962 |
|
| 963 |
model = _Model() |
| 964 |
|
| 965 |
class AutoModelForCausalLM: |
| 966 |
@staticmethod |
| 967 |
def from_pretrained(hf_id: str) -> _Model: |
| 968 |
seen["model_id"] = hf_id |
| 969 |
return model |
| 970 |
|
| 971 |
class AutoTokenizer: |
| 972 |
@staticmethod |
| 973 |
def from_pretrained(hf_id: str) -> str: |
| 974 |
seen["tokenizer_id"] = hf_id |
| 975 |
return "tok" |
| 976 |
|
| 977 |
monkeypatch.setitem( |
| 978 |
sys.modules, |
| 979 |
"transformers", |
| 980 |
_module( |
| 981 |
"transformers", |
| 982 |
AutoModelForCausalLM=AutoModelForCausalLM, |
| 983 |
AutoTokenizer=AutoTokenizer, |
| 984 |
), |
| 985 |
) |
| 986 |
|
| 987 |
loaded = teachers_mod._default_hf_loader("hf/model", "cuda") |
| 988 |
|
| 989 |
assert loaded.model is model |
| 990 |
assert loaded.tokenizer == "tok" |
| 991 |
assert loaded.device == "cuda" |
| 992 |
assert seen == { |
| 993 |
"model_id": "hf/model", |
| 994 |
"tokenizer_id": "hf/model", |
| 995 |
"device": "cuda", |
| 996 |
"eval": True, |
| 997 |
} |
| 998 |
|
| 999 |
def test_default_hf_generate_seeds_torch_and_calls_runner( |
| 1000 |
self, |
| 1001 |
monkeypatch: pytest.MonkeyPatch, |
| 1002 |
) -> None: |
| 1003 |
manual: list[int] = [] |
| 1004 |
manual_all: list[int] = [] |
| 1005 |
calls: dict[str, object] = {} |
| 1006 |
|
| 1007 |
def _generate( |
| 1008 |
model: object, |
| 1009 |
tokenizer: object, |
| 1010 |
prompt: str, |
| 1011 |
*, |
| 1012 |
max_new_tokens: int, |
| 1013 |
temperature: float, |
| 1014 |
top_p: float | None, |
| 1015 |
) -> str: |
| 1016 |
calls["args"] = (model, tokenizer, prompt, max_new_tokens, temperature, top_p) |
| 1017 |
return "ok" |
| 1018 |
|
| 1019 |
monkeypatch.setitem( |
| 1020 |
sys.modules, |
| 1021 |
"dlm.inference.generate", |
| 1022 |
_module("dlm.inference.generate", generate=_generate), |
| 1023 |
) |
| 1024 |
monkeypatch.setitem( |
| 1025 |
sys.modules, |
| 1026 |
"torch", |
| 1027 |
SimpleNamespace( |
| 1028 |
manual_seed=lambda seed: manual.append(seed), |
| 1029 |
cuda=SimpleNamespace( |
| 1030 |
is_available=lambda: True, |
| 1031 |
manual_seed_all=lambda seed: manual_all.append(seed), |
| 1032 |
), |
| 1033 |
), |
| 1034 |
) |
| 1035 |
|
| 1036 |
out = teachers_mod._default_hf_generate( |
| 1037 |
"model", |
| 1038 |
"tokenizer", |
| 1039 |
"prompt", |
| 1040 |
max_new_tokens=17, |
| 1041 |
temperature=0.3, |
| 1042 |
top_p=0.8, |
| 1043 |
seed=7, |
| 1044 |
) |
| 1045 |
|
| 1046 |
assert out == "ok" |
| 1047 |
assert manual == [7] |
| 1048 |
assert manual_all == [7] |
| 1049 |
assert calls["args"] == ("model", "tokenizer", "prompt", 17, 0.3, 0.8) |
| 1050 |
|
| 1051 |
def test_default_hf_generate_tolerates_missing_torch_when_seeding( |
| 1052 |
self, |
| 1053 |
monkeypatch: pytest.MonkeyPatch, |
| 1054 |
) -> None: |
| 1055 |
real_import = builtins.__import__ |
| 1056 |
|
| 1057 |
def _generate( |
| 1058 |
model: object, |
| 1059 |
tokenizer: object, |
| 1060 |
prompt: str, |
| 1061 |
*, |
| 1062 |
max_new_tokens: int, |
| 1063 |
temperature: float, |
| 1064 |
top_p: float | None, |
| 1065 |
) -> str: |
| 1066 |
_ = model, tokenizer, prompt, max_new_tokens, temperature, top_p |
| 1067 |
return "ok" |
| 1068 |
|
| 1069 |
def _raise_torch( |
| 1070 |
name: str, |
| 1071 |
globals: dict[str, object] | None = None, |
| 1072 |
locals: dict[str, object] | None = None, |
| 1073 |
fromlist: tuple[str, ...] = (), |
| 1074 |
level: int = 0, |
| 1075 |
) -> object: |
| 1076 |
if name == "torch": |
| 1077 |
raise ImportError("no torch") |
| 1078 |
return real_import(name, globals, locals, fromlist, level) |
| 1079 |
|
| 1080 |
monkeypatch.setitem( |
| 1081 |
sys.modules, |
| 1082 |
"dlm.inference.generate", |
| 1083 |
_module("dlm.inference.generate", generate=_generate), |
| 1084 |
) |
| 1085 |
monkeypatch.delitem(sys.modules, "torch", raising=False) |
| 1086 |
monkeypatch.setattr(builtins, "__import__", _raise_torch) |
| 1087 |
|
| 1088 |
out = teachers_mod._default_hf_generate( |
| 1089 |
"model", |
| 1090 |
"tokenizer", |
| 1091 |
"prompt", |
| 1092 |
max_new_tokens=17, |
| 1093 |
temperature=0.3, |
| 1094 |
top_p=0.8, |
| 1095 |
seed=7, |
| 1096 |
) |
| 1097 |
|
| 1098 |
assert out == "ok" |