mirror of
https://github.com/tiennm99/DocsGPT.git
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483 lines
17 KiB
Python
483 lines
17 KiB
Python
"""Integration tests for LLM fallback behaviour.
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Verifies that when a primary model fails (immediately or mid-stream), the
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per-agent backup model is used before the global FALLBACK_* settings.
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"""
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from unittest.mock import MagicMock
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import pytest
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from application.llm.base import BaseLLM
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# ---------------------------------------------------------------------------
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# Concrete LLM stubs
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# ---------------------------------------------------------------------------
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class FakeLLM(BaseLLM):
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"""Minimal concrete BaseLLM for testing."""
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def __init__(self, responses=None, stream_chunks=None, fail_at=None, **kwargs):
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# Accept and discard api_key / user_api_key so LLMCreator.create_llm
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# signatures work without errors.
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kwargs.pop("api_key", None)
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kwargs.pop("user_api_key", None)
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super().__init__(**kwargs)
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self.responses = responses or ["fake response"]
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self.stream_chunks = stream_chunks or ["chunk1", "chunk2"]
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self.fail_at = fail_at # None = no failure, 0 = immediate, N = after N chunks
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self.user_api_key = None
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self.gen_called = False
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self.gen_stream_called = False
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self.last_model_received = None # tracks the model kwarg passed to gen/gen_stream
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def _raw_gen(self, baseself, model, messages, stream, tools=None, **kwargs):
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if self.fail_at is not None:
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raise RuntimeError("primary model unavailable")
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return self.responses[0]
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def _raw_gen_stream(self, baseself, model, messages, stream, tools=None, **kwargs):
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yielded = 0
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for chunk in self.stream_chunks:
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if self.fail_at is not None and yielded >= self.fail_at:
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raise RuntimeError("mid-stream failure")
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yield chunk
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yielded += 1
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# Wrap gen/gen_stream so we can track whether the fallback instance was used
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# and which model kwarg it received
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def gen(self, *args, **kwargs):
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self.gen_called = True
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self.last_model_received = kwargs.get("model")
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return super().gen(*args, **kwargs)
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def gen_stream(self, *args, **kwargs):
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self.gen_stream_called = True
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self.last_model_received = kwargs.get("model")
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return super().gen_stream(*args, **kwargs)
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# ---------------------------------------------------------------------------
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# Helpers
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# ---------------------------------------------------------------------------
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def _noop_decorator(func):
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"""Pass-through decorator that replaces cache / token-usage wrappers."""
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def wrapper(self_llm, model, messages, stream, tools=None, **kwargs):
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return func(self_llm, model, messages, stream, tools, **kwargs)
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return wrapper
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def _noop_stream_decorator(func):
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"""Pass-through generator decorator for streaming wrappers."""
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def wrapper(self_llm, model, messages, stream, tools=None, **kwargs):
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yield from func(self_llm, model, messages, stream, tools, **kwargs)
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return wrapper
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@pytest.fixture(autouse=True)
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def _patch_decorators(monkeypatch):
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"""Replace cache & token-usage decorators with no-ops so tests focus on
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fallback logic without needing Redis or token-counting infra."""
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monkeypatch.setattr("application.llm.base.gen_cache", _noop_decorator)
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monkeypatch.setattr("application.llm.base.gen_token_usage", _noop_decorator)
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monkeypatch.setattr("application.llm.base.stream_cache", _noop_stream_decorator)
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monkeypatch.setattr(
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"application.llm.base.stream_token_usage", _noop_stream_decorator
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)
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@pytest.fixture
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def patch_model_utils(monkeypatch):
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"""Patch model_utils functions used by fallback_llm property."""
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def _apply(get_provider=None, get_api_key=None, create_llm=None):
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if get_provider:
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monkeypatch.setattr(
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"application.core.model_utils.get_provider_from_model_id",
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get_provider,
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)
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if get_api_key:
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monkeypatch.setattr(
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"application.core.model_utils.get_api_key_for_provider",
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get_api_key,
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)
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if create_llm:
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monkeypatch.setattr(
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"application.llm.llm_creator.LLMCreator.create_llm",
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create_llm,
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)
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return _apply
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CALL_ARGS = dict(model="test-model", messages=[{"role": "user", "content": "hi"}])
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# ---------------------------------------------------------------------------
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# Tests — fallback_llm property resolution
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# ---------------------------------------------------------------------------
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@pytest.mark.integration
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class TestFallbackLLMResolution:
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def test_backup_model_preferred_over_global_fallback(self, patch_model_utils):
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"""When agent has backup models configured, the first valid one is used
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as fallback — not the global FALLBACK_* settings."""
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backup_llm = FakeLLM(responses=["backup response"])
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patch_model_utils(
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get_provider=lambda mid: "openai",
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get_api_key=lambda prov: "fake-key",
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create_llm=lambda type, **kw: backup_llm,
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)
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primary = FakeLLM(backup_models=["backup-model-id"])
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fallback = primary.fallback_llm
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assert fallback is backup_llm
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def test_global_fallback_used_when_no_backup_models(
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self, monkeypatch, patch_model_utils
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):
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"""When no per-agent backup models exist, global FALLBACK_* is used."""
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global_fallback = FakeLLM(responses=["global fallback"])
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patch_model_utils(
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create_llm=lambda type, **kw: global_fallback,
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)
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monkeypatch.setattr(
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"application.llm.base.settings",
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MagicMock(
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FALLBACK_LLM_PROVIDER="openai",
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FALLBACK_LLM_NAME="gpt-4o",
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FALLBACK_LLM_API_KEY="key",
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API_KEY="key",
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),
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)
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primary = FakeLLM(backup_models=[])
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fallback = primary.fallback_llm
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assert fallback is global_fallback
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def test_skips_unresolvable_backup_model_tries_next(self, patch_model_utils):
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"""If the first backup model can't be resolved, skip it and try the next."""
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good_backup = FakeLLM(responses=["good backup"])
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call_count = {"n": 0}
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def fake_get_provider(model_id):
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call_count["n"] += 1
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if model_id == "bad-model":
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return None # unresolvable
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return "openai"
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patch_model_utils(
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get_provider=fake_get_provider,
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get_api_key=lambda prov: "key",
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create_llm=lambda type, **kw: good_backup,
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)
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primary = FakeLLM(backup_models=["bad-model", "good-model"])
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fallback = primary.fallback_llm
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assert fallback is good_backup
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assert call_count["n"] == 2 # tried both
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def test_no_fallback_when_nothing_configured(self, monkeypatch):
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"""No backup models + no global FALLBACK_* → fallback_llm is None."""
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monkeypatch.setattr(
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"application.llm.base.settings",
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MagicMock(FALLBACK_LLM_PROVIDER=None),
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)
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primary = FakeLLM(backup_models=[])
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assert primary.fallback_llm is None
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# ---------------------------------------------------------------------------
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# Tests — non-streaming fallback (gen)
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# ---------------------------------------------------------------------------
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@pytest.mark.integration
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class TestNonStreamingFallback:
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def test_primary_success_no_fallback(self):
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"""When primary succeeds, fallback is never touched."""
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primary = FakeLLM(responses=["primary ok"])
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result = primary.gen(**CALL_ARGS)
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assert result == "primary ok"
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def test_primary_fails_uses_backup_model(self, patch_model_utils):
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"""Primary fails immediately → backup model from agent config is used."""
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backup = FakeLLM(responses=["backup ok"])
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patch_model_utils(
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get_provider=lambda mid: "openai",
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get_api_key=lambda p: "k",
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create_llm=lambda type, **kw: backup,
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)
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primary = FakeLLM(fail_at=0, backup_models=["backup-model"])
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result = primary.gen(**CALL_ARGS)
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assert result == "backup ok"
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assert backup.gen_called
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def test_no_fallback_raises(self, monkeypatch):
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"""Primary fails and no fallback configured → exception propagates."""
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monkeypatch.setattr(
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"application.llm.base.settings",
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MagicMock(FALLBACK_LLM_PROVIDER=None),
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)
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primary = FakeLLM(fail_at=0, backup_models=[])
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with pytest.raises(RuntimeError, match="primary model unavailable"):
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primary.gen(**CALL_ARGS)
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# ---------------------------------------------------------------------------
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# Tests — streaming fallback (gen_stream)
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# ---------------------------------------------------------------------------
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@pytest.mark.integration
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class TestStreamingFallback:
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def test_stream_primary_success(self):
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"""Full stream completes without triggering fallback."""
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primary = FakeLLM(stream_chunks=["a", "b", "c"])
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chunks = list(primary.gen_stream(**CALL_ARGS))
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assert chunks == ["a", "b", "c"]
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def test_stream_immediate_failure_uses_backup(self, patch_model_utils):
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"""Primary fails before yielding anything → entire backup stream returned."""
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backup = FakeLLM(stream_chunks=["fallback1", "fallback2"])
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patch_model_utils(
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get_provider=lambda m: "openai",
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get_api_key=lambda p: "k",
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create_llm=lambda type, **kw: backup,
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)
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primary = FakeLLM(
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stream_chunks=["x", "y"],
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fail_at=0, # fail before first chunk
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backup_models=["backup-model"],
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)
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chunks = list(primary.gen_stream(**CALL_ARGS))
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assert chunks == ["fallback1", "fallback2"]
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assert backup.gen_stream_called
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def test_stream_mid_stream_failure_uses_backup(self, patch_model_utils):
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"""Primary yields some chunks then fails → backup stream follows partial output."""
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backup = FakeLLM(stream_chunks=["recovery1", "recovery2"])
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patch_model_utils(
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get_provider=lambda m: "openai",
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get_api_key=lambda p: "k",
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create_llm=lambda type, **kw: backup,
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)
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primary = FakeLLM(
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stream_chunks=["ok1", "ok2", "ok3"],
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fail_at=2, # yields ok1, ok2, then fails before ok3
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backup_models=["backup-model"],
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)
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chunks = list(primary.gen_stream(**CALL_ARGS))
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# First two from primary, then full backup stream
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assert chunks == ["ok1", "ok2", "recovery1", "recovery2"]
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def test_stream_no_fallback_raises(self, monkeypatch):
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"""Primary stream fails and no fallback → exception propagates."""
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monkeypatch.setattr(
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"application.llm.base.settings",
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MagicMock(FALLBACK_LLM_PROVIDER=None),
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)
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primary = FakeLLM(stream_chunks=["x"], fail_at=0, backup_models=[])
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with pytest.raises(RuntimeError, match="mid-stream failure"):
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list(primary.gen_stream(**CALL_ARGS))
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# ---------------------------------------------------------------------------
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# Tests — backup model priority over global fallback
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# ---------------------------------------------------------------------------
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@pytest.mark.integration
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class TestBackupModelPriority:
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def test_agent_backup_tried_before_global_on_gen_failure(self, patch_model_utils):
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"""On gen() failure, agent's backup model is used — not the global fallback."""
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backup = FakeLLM(responses=["agent backup"])
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created_models = []
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def fake_create_llm(type, **kw):
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created_models.append(kw.get("model_id"))
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return backup
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patch_model_utils(
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get_provider=lambda m: "openai",
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get_api_key=lambda p: "k",
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create_llm=fake_create_llm,
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)
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primary = FakeLLM(fail_at=0, backup_models=["agent-backup-model"])
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result = primary.gen(**CALL_ARGS)
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assert result == "agent backup"
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assert "agent-backup-model" in created_models
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def test_agent_backup_tried_before_global_on_stream_failure(
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self, patch_model_utils
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):
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"""On gen_stream() failure, agent's backup model is used — not the global."""
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backup = FakeLLM(stream_chunks=["agent-stream"])
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created_models = []
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def fake_create_llm(type, **kw):
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created_models.append(kw.get("model_id"))
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return backup
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patch_model_utils(
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get_provider=lambda m: "openai",
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get_api_key=lambda p: "k",
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create_llm=fake_create_llm,
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)
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primary = FakeLLM(
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stream_chunks=["x"], fail_at=0, backup_models=["agent-backup-model"]
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)
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chunks = list(primary.gen_stream(**CALL_ARGS))
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assert chunks == ["agent-stream"]
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assert "agent-backup-model" in created_models
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def test_global_fallback_used_when_all_backup_models_fail(
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self, monkeypatch, patch_model_utils
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):
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"""If every agent backup model fails to initialize, fall through to global."""
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global_fallback = FakeLLM(responses=["global ok"])
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call_order = []
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def fake_get_provider(mid):
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if mid == "broken-backup":
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return "nonexistent_provider"
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return "openai"
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def fake_create_llm(type, **kw):
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model_id = kw.get("model_id")
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call_order.append(model_id)
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if model_id == "broken-backup":
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raise ValueError("provider init failed")
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return global_fallback
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patch_model_utils(
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get_provider=fake_get_provider,
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get_api_key=lambda p: "k",
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create_llm=fake_create_llm,
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)
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monkeypatch.setattr(
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"application.llm.base.settings",
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MagicMock(
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FALLBACK_LLM_PROVIDER="openai",
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FALLBACK_LLM_NAME="global-model",
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FALLBACK_LLM_API_KEY="gk",
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API_KEY="gk",
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),
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)
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primary = FakeLLM(fail_at=0, backup_models=["broken-backup"])
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result = primary.gen(**CALL_ARGS)
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assert result == "global ok"
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# Tried broken-backup first, then fell through to global-model
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assert call_order == ["broken-backup", "global-model"]
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# ---------------------------------------------------------------------------
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# Tests — fallback uses its own model_id, not the primary's
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# ---------------------------------------------------------------------------
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@pytest.mark.integration
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class TestFallbackModelIdOverride:
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"""The fallback LLM must be called with its own model_id — not the
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primary's. Otherwise providers like Groq receive an unknown model name
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(e.g. a Qwen model_id) and return 404."""
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def test_gen_fallback_receives_own_model_id(self, patch_model_utils):
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"""Non-streaming: fallback.gen() is called with fallback.model_id."""
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backup = FakeLLM(
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responses=["backup ok"], model_id="groq-gpt-oss-120b"
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)
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patch_model_utils(
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get_provider=lambda m: "groq",
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get_api_key=lambda p: "k",
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create_llm=lambda type, **kw: backup,
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)
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primary = FakeLLM(
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fail_at=0,
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model_id="qwen/qwen3-4b-2507",
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backup_models=["groq-gpt-oss-120b"],
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)
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result = primary.gen(**CALL_ARGS)
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assert result == "backup ok"
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assert backup.last_model_received == "groq-gpt-oss-120b"
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def test_gen_stream_fallback_receives_own_model_id(self, patch_model_utils):
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"""Streaming: fallback.gen_stream() is called with fallback.model_id."""
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backup = FakeLLM(
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stream_chunks=["ok"], model_id="groq-gpt-oss-120b"
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)
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patch_model_utils(
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get_provider=lambda m: "groq",
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get_api_key=lambda p: "k",
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create_llm=lambda type, **kw: backup,
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)
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primary = FakeLLM(
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stream_chunks=["x"],
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fail_at=0,
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model_id="qwen/qwen3-4b-2507",
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backup_models=["groq-gpt-oss-120b"],
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)
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chunks = list(primary.gen_stream(**CALL_ARGS))
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assert chunks == ["ok"]
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assert backup.last_model_received == "groq-gpt-oss-120b"
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def test_mid_stream_fallback_receives_own_model_id(self, patch_model_utils):
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"""Mid-stream failure: fallback still gets its own model_id, not the
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primary's that was already partially streaming."""
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backup = FakeLLM(
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stream_chunks=["recovered"], model_id="groq-gpt-oss-120b"
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)
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patch_model_utils(
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get_provider=lambda m: "groq",
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get_api_key=lambda p: "k",
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create_llm=lambda type, **kw: backup,
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)
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primary = FakeLLM(
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stream_chunks=["partial1", "partial2", "boom"],
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fail_at=2,
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model_id="qwen/qwen3-4b-2507",
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backup_models=["groq-gpt-oss-120b"],
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)
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chunks = list(primary.gen_stream(**CALL_ARGS))
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assert chunks == ["partial1", "partial2", "recovered"]
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assert backup.last_model_received == "groq-gpt-oss-120b"
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