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Python

"""Unit tests for application/llm/premai.py — PremAILLM.
Covers:
- Constructor
- _raw_gen: API call and return value
- _raw_gen_stream: streaming with delta content filtering
"""
import sys
import types
import pytest
# ---------------------------------------------------------------------------
# Fake premai module
# ---------------------------------------------------------------------------
class _FakeMessage:
def __init__(self, content):
self.message = {"content": content}
class _FakeDelta:
def __init__(self, content):
self.delta = {"content": content}
class _FakeChoice:
def __init__(self, content):
self.message = {"content": content}
class _FakeStreamChoice:
def __init__(self, content):
self.delta = {"content": content}
class _FakeResponse:
def __init__(self, content="result_text"):
self.choices = [_FakeChoice(content)]
class _FakeStreamLine:
def __init__(self, content):
self.choices = [_FakeStreamChoice(content)]
class _FakeChatCompletions:
def __init__(self):
self.last_kwargs = None
def create(self, **kwargs):
self.last_kwargs = kwargs
if kwargs.get("stream"):
return [
_FakeStreamLine("chunk1"),
_FakeStreamLine("chunk2"),
_FakeStreamLine(None), # None content should be filtered
]
return _FakeResponse()
class _FakeChat:
def __init__(self):
self.completions = _FakeChatCompletions()
class _FakePrem:
def __init__(self, api_key=None):
self.api_key = api_key
self.chat = _FakeChat()
@pytest.fixture(autouse=True)
def patch_premai(monkeypatch):
fake_mod = types.ModuleType("premai")
fake_mod.Prem = _FakePrem
sys.modules["premai"] = fake_mod
if "application.llm.premai" in sys.modules:
del sys.modules["application.llm.premai"]
yield
sys.modules.pop("premai", None)
if "application.llm.premai" in sys.modules:
del sys.modules["application.llm.premai"]
@pytest.fixture
def llm():
from application.llm.premai import PremAILLM
return PremAILLM(api_key="test-key")
# ---------------------------------------------------------------------------
# Constructor
# ---------------------------------------------------------------------------
@pytest.mark.unit
class TestPremAIConstructor:
def test_sets_api_key(self, llm):
assert llm.api_key == "test-key"
def test_sets_user_api_key_none(self, llm):
assert llm.user_api_key is None
def test_client_created(self, llm):
assert isinstance(llm.client, _FakePrem)
def test_project_id_from_settings(self, llm):
from application.core.settings import settings
assert llm.project_id == settings.PREMAI_PROJECT_ID
# ---------------------------------------------------------------------------
# _raw_gen
# ---------------------------------------------------------------------------
@pytest.mark.unit
class TestRawGen:
def test_returns_content(self, llm):
msgs = [{"role": "user", "content": "hi"}]
result = llm._raw_gen(llm, model="model-1", messages=msgs)
assert result == "result_text"
def test_passes_model_and_project_id(self, llm):
msgs = [{"role": "user", "content": "hi"}]
llm._raw_gen(llm, model="my-model", messages=msgs)
kwargs = llm.client.chat.completions.last_kwargs
assert kwargs["model"] == "my-model"
assert kwargs["project_id"] == llm.project_id
assert kwargs["stream"] is False
def test_passes_messages(self, llm):
msgs = [{"role": "user", "content": "hello"}]
llm._raw_gen(llm, model="m", messages=msgs)
kwargs = llm.client.chat.completions.last_kwargs
assert kwargs["messages"] == msgs
def test_extra_kwargs_forwarded(self, llm):
msgs = [{"role": "user", "content": "hi"}]
llm._raw_gen(llm, model="m", messages=msgs, temperature=0.5)
kwargs = llm.client.chat.completions.last_kwargs
assert kwargs["temperature"] == 0.5
# ---------------------------------------------------------------------------
# _raw_gen_stream
# ---------------------------------------------------------------------------
@pytest.mark.unit
class TestRawGenStream:
def test_yields_non_none_content(self, llm):
msgs = [{"role": "user", "content": "hi"}]
chunks = list(
llm._raw_gen_stream(llm, model="m", messages=msgs, stream=True)
)
assert chunks == ["chunk1", "chunk2"]
def test_filters_none_content(self, llm):
msgs = [{"role": "user", "content": "hi"}]
chunks = list(
llm._raw_gen_stream(llm, model="m", messages=msgs, stream=True)
)
assert None not in chunks
def test_passes_stream_true(self, llm):
msgs = [{"role": "user", "content": "hi"}]
list(llm._raw_gen_stream(llm, model="m", messages=msgs))
kwargs = llm.client.chat.completions.last_kwargs
assert kwargs["stream"] is True
def test_passes_extra_kwargs(self, llm):
msgs = [{"role": "user", "content": "hi"}]
list(
llm._raw_gen_stream(
llm, model="m", messages=msgs, max_tokens=100
)
)
kwargs = llm.client.chat.completions.last_kwargs
assert kwargs["max_tokens"] == 100