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OpenJarvis/tests/engine/test_cloud.py
T
Jon Saad-FalconGitHubClaude Opus 4.8Jen Huls
 4b9948250b feat(engine): add DeepSeek as a first-class cloud provider + fix #335 over-permissive cloud fallback (#545) 
* feat(engine): add DeepSeek as a first-class cloud provider

Adds DEEPSEEK_API_KEY support to the cloud engine, wiring DeepSeek's
OpenAI-compatible API (api.deepseek.com/v1) alongside the existing
MiniMax, OpenRouter, Anthropic, and Google providers.

- Add _DEEPSEEK_MODELS list (deepseek-v4-flash, deepseek-v4-pro)
- Add _is_deepseek_model() routing predicate
- Init self._deepseek_client from DEEPSEEK_API_KEY in _init_clients()
- Add _generate_deepseek() and _stream_deepseek() methods
- Wire DeepSeek into generate(), stream(), _stream_full_openai(),
  list_models(), and health()
- Add approximate pricing entries for both models

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* fix(engine): strict cloud model routing + deepseek can_serve branch

Builds on the DeepSeek provider (PR #504) with two routing-correctness
fixes to CloudEngine._client_for_model:

1. Add the missing DeepSeek branch so can_serve('deepseek-*') agrees with
   list_models()/health() when only DEEPSEEK_API_KEY is set (mirrors the
   minimax branch). Without it the engine advertised deepseek models via
   list_models() but refused to serve them (the #532 can_serve contract).

2. Fix #335: _client_for_model previously fell through to the OpenAI client
   for ANY unrecognized model name, so an OpenAI key (even a dummy
   sk-dummy... one) made can_serve('qwen3.5:0.8b') return True. With the
   local engine transiently down (classic post-Windows-restart Ollama not
   yet up), model-aware get_engine then mis-selected the cloud engine for a
   local model and died with "OpenAI client not available". Add a positive
   _is_openai_model predicate (gpt-/chatgpt-/o1/o3/o4 + _OPENAI_MODELS) and
   return None for unrecognized names, so can_serve declines them. generate()
   and stream() keep their OpenAI fall-through, preserving loud failure for an
   explicitly-requested unknown cloud model.

Tests: DeepSeek detection/pricing/health/list_models/generate-routing/
can_serve and a #335 regression (can_serve rejects local names with an
OpenAI key; unknown model not served even with all clients set; end-to-end
get_engine does not misroute a local model with a dummy OpenAI key).

Fixes #335

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

---------

Co-authored-by: Jen Huls <me@jenhuls.com>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-14 18:21:56 -07:00

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"""Tests for the Cloud engine backend."""
from __future__ import annotations
from types import SimpleNamespace
from unittest import mock
import pytest
from openjarvis.core.registry import EngineRegistry
from openjarvis.core.types import Message, Role
from openjarvis.engine._base import EngineConnectionError
from openjarvis.engine.cloud import (
CloudEngine,
_is_codex_model,
_is_deepseek_model,
_is_openai_model,
_is_openrouter_model,
estimate_cost,
)
class TestEstimateCost:
def test_known_model(self) -> None:
cost = estimate_cost("gpt-4o", 1_000_000, 1_000_000)
assert cost == pytest.approx(12.50) # 2.50 + 10.00
def test_unknown_model(self) -> None:
assert estimate_cost("unknown-model", 100, 100) == 0.0
def test_prefix_match(self) -> None:
cost = estimate_cost("gpt-4o-2024-01-01", 1_000_000, 0)
assert cost == pytest.approx(2.50)
class TestCloudEngineHealth:
def test_health_no_keys(self, monkeypatch: pytest.MonkeyPatch) -> None:
monkeypatch.delenv("OPENAI_API_KEY", raising=False)
monkeypatch.delenv("ANTHROPIC_API_KEY", raising=False)
EngineRegistry.register_value("cloud", CloudEngine)
engine = CloudEngine()
assert engine.health() is False
def test_health_with_openai_key(self, monkeypatch: pytest.MonkeyPatch) -> None:
monkeypatch.setenv("OPENAI_API_KEY", "sk-test")
# Mock the openai import
fake_openai = mock.MagicMock()
with mock.patch.dict("sys.modules", {"openai": fake_openai}):
EngineRegistry.register_value("cloud", CloudEngine)
engine = CloudEngine()
assert engine.health() is True
class TestCloudEngineListModels:
def test_list_models_no_keys(self, monkeypatch: pytest.MonkeyPatch) -> None:
monkeypatch.delenv("OPENAI_API_KEY", raising=False)
monkeypatch.delenv("ANTHROPIC_API_KEY", raising=False)
EngineRegistry.register_value("cloud", CloudEngine)
engine = CloudEngine()
assert engine.list_models() == []
class TestCloudEngineGenerate:
def test_generate_openai(self, monkeypatch: pytest.MonkeyPatch) -> None:
monkeypatch.setenv("OPENAI_API_KEY", "sk-test")
monkeypatch.delenv("ANTHROPIC_API_KEY", raising=False)
fake_usage = SimpleNamespace(
prompt_tokens=10, completion_tokens=5, total_tokens=15
)
fake_choice = SimpleNamespace(
message=SimpleNamespace(content="Hello!"),
finish_reason="stop",
)
fake_resp = SimpleNamespace(
choices=[fake_choice], usage=fake_usage, model="gpt-4o"
)
fake_client = mock.MagicMock()
fake_client.chat.completions.create.return_value = fake_resp
EngineRegistry.register_value("cloud", CloudEngine)
engine = CloudEngine()
engine._openai_client = fake_client
result = engine.generate(
[Message(role=Role.USER, content="Hi")], model="gpt-4o"
)
assert result["content"] == "Hello!"
assert result["usage"]["prompt_tokens"] == 10
def test_generate_anthropic(self, monkeypatch: pytest.MonkeyPatch) -> None:
monkeypatch.delenv("OPENAI_API_KEY", raising=False)
monkeypatch.setenv("ANTHROPIC_API_KEY", "sk-ant-test")
fake_usage = SimpleNamespace(input_tokens=12, output_tokens=8)
fake_content = SimpleNamespace(text="Greetings!")
fake_resp = SimpleNamespace(
content=[fake_content],
usage=fake_usage,
model="claude-sonnet-4-20250514",
stop_reason="end_turn",
)
fake_client = mock.MagicMock()
fake_client.messages.create.return_value = fake_resp
EngineRegistry.register_value("cloud", CloudEngine)
engine = CloudEngine()
engine._anthropic_client = fake_client
result = engine.generate(
[Message(role=Role.USER, content="Hi")],
model="claude-sonnet-4-20250514",
)
assert result["content"] == "Greetings!"
assert result["usage"]["prompt_tokens"] == 12
assert result["usage"]["completion_tokens"] == 8
class TestOpenAIUnsupportedTemperatureRetry:
"""Regression for #426.
Some OpenAI models (e.g. gpt-5) reject a non-default ``temperature``
with HTTP 400 ``unsupported_value``. A brand-new install defaults to
such a model, so the very first prompt 400s. The engine must detect
this specific error and retry once without ``temperature``.
"""
def _fake_resp(self):
return SimpleNamespace(
choices=[
SimpleNamespace(
message=SimpleNamespace(content="ok"),
finish_reason="stop",
)
],
usage=SimpleNamespace(prompt_tokens=1, completion_tokens=1, total_tokens=2),
model="gpt-5",
)
def test_retries_without_temperature_on_unsupported_value(
self, monkeypatch: pytest.MonkeyPatch
) -> None:
monkeypatch.setenv("OPENAI_API_KEY", "sk-test")
monkeypatch.delenv("ANTHROPIC_API_KEY", raising=False)
calls: list[dict] = []
err = Exception(
"Error code: 400 - {'error': {'message': \"Unsupported value: "
"'temperature' does not support 0.7 with this model. Only the "
"default (1) value is supported.\", 'type': "
"'invalid_request_error', 'param': 'temperature', 'code': "
"'unsupported_value'}}"
)
def create(**kwargs):
calls.append(kwargs)
if "temperature" in kwargs:
raise err
return self._fake_resp()
fake_client = mock.MagicMock()
fake_client.chat.completions.create.side_effect = create
EngineRegistry.register_value("cloud", CloudEngine)
engine = CloudEngine()
engine._openai_client = fake_client
result = engine.generate(
[Message(role=Role.USER, content="Hi")],
model="gpt-5",
temperature=0.7,
)
# The call succeeded via the retry.
assert result["content"] == "ok"
# First attempt sent temperature, retry dropped it.
assert len(calls) == 2
assert "temperature" in calls[0]
assert "temperature" not in calls[1]
def test_unrelated_400_is_not_retried(
self, monkeypatch: pytest.MonkeyPatch
) -> None:
monkeypatch.setenv("OPENAI_API_KEY", "sk-test")
monkeypatch.delenv("ANTHROPIC_API_KEY", raising=False)
calls: list[dict] = []
err = Exception("Error code: 400 - context_length_exceeded")
def create(**kwargs):
calls.append(kwargs)
raise err
fake_client = mock.MagicMock()
fake_client.chat.completions.create.side_effect = create
EngineRegistry.register_value("cloud", CloudEngine)
engine = CloudEngine()
engine._openai_client = fake_client
with pytest.raises(Exception): # noqa: B017 - re-raised unchanged
engine.generate(
[Message(role=Role.USER, content="Hi")],
model="gpt-4o",
temperature=0.7,
)
# No temperature-retry for an unrelated 400 — exactly one attempt.
assert len(calls) == 1
# ---------------------------------------------------------------------------
# Codex provider support (OpenAI Responses API)
# ---------------------------------------------------------------------------
class TestCodexModelDetection:
def test_is_codex_model(self) -> None:
assert _is_codex_model("codex/gpt-4o") is True
assert _is_codex_model("codex/gpt-5-mini") is True
assert _is_codex_model("codex/gpt-5-mini-2025-08-07") is True
def test_not_codex_model(self) -> None:
assert _is_codex_model("gpt-4o") is False
assert _is_codex_model("openrouter/openai/gpt-4o") is False
class TestCodexClientInit:
def test_health_with_codex_key(self, monkeypatch: pytest.MonkeyPatch) -> None:
monkeypatch.delenv("OPENAI_API_KEY", raising=False)
monkeypatch.delenv("ANTHROPIC_API_KEY", raising=False)
monkeypatch.setenv("OPENAI_CODEX_API_KEY", "test-token")
engine = CloudEngine()
assert engine.health() is True
assert engine._codex_client is not None
assert engine._codex_client["token"] == "test-token"
assert "responses" in engine._codex_client["url"]
def test_custom_codex_base_url(self, monkeypatch: pytest.MonkeyPatch) -> None:
monkeypatch.delenv("OPENAI_API_KEY", raising=False)
monkeypatch.delenv("ANTHROPIC_API_KEY", raising=False)
monkeypatch.setenv("OPENAI_CODEX_API_KEY", "test-token")
monkeypatch.setenv("OPENAI_CODEX_BASE_URL", "http://localhost:9999")
engine = CloudEngine()
assert engine._codex_client["url"] == "http://localhost:9999/responses"
def test_list_models_includes_codex(self, monkeypatch: pytest.MonkeyPatch) -> None:
monkeypatch.delenv("OPENAI_API_KEY", raising=False)
monkeypatch.delenv("ANTHROPIC_API_KEY", raising=False)
monkeypatch.setenv("OPENAI_CODEX_API_KEY", "test-token")
engine = CloudEngine()
models = engine.list_models()
assert "codex/gpt-4o" in models
assert "codex/gpt-5-mini" in models
assert "codex/gpt-5-mini-2025-08-07" in models
def test_no_codex_key_means_no_codex(self, monkeypatch: pytest.MonkeyPatch) -> None:
monkeypatch.delenv("OPENAI_API_KEY", raising=False)
monkeypatch.delenv("ANTHROPIC_API_KEY", raising=False)
monkeypatch.delenv("OPENAI_CODEX_API_KEY", raising=False)
engine = CloudEngine()
assert engine._codex_client is None
assert "codex/gpt-4o" not in engine.list_models()
class TestCodexGenerate:
def test_generate_codex_uses_responses_api(
self, monkeypatch: pytest.MonkeyPatch
) -> None:
monkeypatch.delenv("OPENAI_API_KEY", raising=False)
monkeypatch.delenv("ANTHROPIC_API_KEY", raising=False)
fake_response = mock.MagicMock()
fake_response.status_code = 200
fake_response.json.return_value = {
"output_text": "Codex response!",
"usage": {"input_tokens": 10, "output_tokens": 5},
}
fake_response.raise_for_status = mock.MagicMock()
engine = CloudEngine()
engine._codex_client = {
"token": "test-token",
"url": "https://api.openai.com/v1/responses",
}
with mock.patch(
"openjarvis.engine.cloud.httpx.post",
return_value=fake_response,
) as mock_post:
result = engine.generate(
[Message(role=Role.USER, content="Hi")],
model="codex/gpt-5-mini-2025-08-07",
)
assert result["content"] == "Codex response!"
assert result["model"] == "gpt-5-mini-2025-08-07"
assert result["usage"]["prompt_tokens"] == 10
assert result["usage"]["completion_tokens"] == 5
# Verify correct Responses API request format
call_kwargs = mock_post.call_args
sent_body = call_kwargs.kwargs["json"]
assert sent_body["model"] == "gpt-5-mini-2025-08-07"
assert sent_body["stream"] is False
assert "input" in sent_body # Responses API format
assert "messages" not in sent_body # NOT chat completions
# Verify correct headers
sent_headers = call_kwargs.kwargs["headers"]
assert sent_headers["Authorization"] == "Bearer test-token"
assert sent_headers["OpenAI-Beta"] == "responses=experimental"
def test_generate_codex_extracts_from_output_blocks(
self, monkeypatch: pytest.MonkeyPatch
) -> None:
"""Fallback extraction from output[].content[] blocks."""
monkeypatch.delenv("OPENAI_API_KEY", raising=False)
monkeypatch.delenv("ANTHROPIC_API_KEY", raising=False)
fake_response = mock.MagicMock()
fake_response.json.return_value = {
"output": [{"content": [{"type": "output_text", "text": "From blocks!"}]}],
"usage": {"input_tokens": 5, "output_tokens": 3},
}
fake_response.raise_for_status = mock.MagicMock()
engine = CloudEngine()
engine._codex_client = {
"token": "t",
"url": "https://api.openai.com/v1/responses",
}
with mock.patch(
"openjarvis.engine.cloud.httpx.post",
return_value=fake_response,
):
result = engine.generate(
[Message(role=Role.USER, content="Hi")],
model="codex/gpt-4o",
)
assert result["content"] == "From blocks!"
def test_generate_codex_passes_system_as_instructions(
self, monkeypatch: pytest.MonkeyPatch
) -> None:
monkeypatch.delenv("OPENAI_API_KEY", raising=False)
monkeypatch.delenv("ANTHROPIC_API_KEY", raising=False)
fake_response = mock.MagicMock()
fake_response.json.return_value = {
"output_text": "ok",
"usage": {},
}
fake_response.raise_for_status = mock.MagicMock()
engine = CloudEngine()
engine._codex_client = {
"token": "t",
"url": "https://api.openai.com/v1/responses",
}
with mock.patch(
"openjarvis.engine.cloud.httpx.post",
return_value=fake_response,
) as mock_post:
engine.generate(
[
Message(role=Role.SYSTEM, content="Be helpful"),
Message(role=Role.USER, content="Hi"),
],
model="codex/gpt-4o",
)
sent_body = mock_post.call_args.kwargs["json"]
assert sent_body["instructions"] == "Be helpful"
# System message should NOT appear in input messages
roles = [m["role"] for m in sent_body["input"]]
assert "system" not in roles
def test_codex_close(self, monkeypatch: pytest.MonkeyPatch) -> None:
monkeypatch.delenv("OPENAI_API_KEY", raising=False)
monkeypatch.delenv("ANTHROPIC_API_KEY", raising=False)
engine = CloudEngine()
engine._codex_client = {"token": "t", "url": "http://test"}
engine.close()
assert engine._codex_client is None
class TestOpenRouterToolForwarding:
"""Regression for #511: the OpenRouter engine must forward tools/tool_choice
to the (OpenAI-compatible) API and parse tool_calls back out of the response.
Pre-fix, both were dropped, silently breaking function-calling via OpenRouter.
"""
def test_generate_forwards_tools_and_parses_tool_calls(
self, monkeypatch: pytest.MonkeyPatch
) -> None:
monkeypatch.delenv("OPENAI_API_KEY", raising=False)
fake_tc = SimpleNamespace(
id="call_1",
type="function",
function=SimpleNamespace(name="get_weather", arguments='{"city": "NYC"}'),
)
fake_choice = SimpleNamespace(
message=SimpleNamespace(content=None, tool_calls=[fake_tc]),
finish_reason="tool_calls",
)
fake_resp = SimpleNamespace(
choices=[fake_choice],
usage=SimpleNamespace(prompt_tokens=3, completion_tokens=2, total_tokens=5),
model="openai/gpt-4o",
)
fake_client = mock.MagicMock()
fake_client.chat.completions.create.return_value = fake_resp
EngineRegistry.register_value("cloud", CloudEngine)
engine = CloudEngine()
engine._openrouter_client = fake_client
tools = [
{
"type": "function",
"function": {"name": "get_weather", "parameters": {}},
}
]
result = engine.generate(
[Message(role=Role.USER, content="weather in NYC?")],
model="openrouter/openai/gpt-4o",
tools=tools,
tool_choice="auto",
)
# tools / tool_choice are forwarded to the API call
sent = fake_client.chat.completions.create.call_args.kwargs
assert sent["tools"] == tools
assert sent["tool_choice"] == "auto"
# tool_calls from the response are parsed back into the result
assert result["tool_calls"][0]["id"] == "call_1"
assert result["tool_calls"][0]["function"]["name"] == "get_weather"
assert result["tool_calls"][0]["function"]["arguments"] == '{"city": "NYC"}'
class TestCloudEngineCanServe:
"""#532: can_serve gates on the per-provider client, not just health().
health() is True whenever *any* provider client is configured, but a
request for a gpt-* model still needs the OpenAI client specifically — so
engine selection must not pick the cloud engine for a model whose provider
client is missing.
"""
@staticmethod
def _engine(**clients: object) -> CloudEngine:
eng = CloudEngine.__new__(CloudEngine) # bypass real client init
for name in (
"_openai_client",
"_anthropic_client",
"_google_client",
"_openrouter_client",
"_minimax_client",
"_deepseek_client",
"_codex_client",
):
setattr(eng, name, clients.get(name))
return eng
def test_openai_only_serves_openai_models(self) -> None:
eng = self._engine(_openai_client=object())
assert eng.can_serve("gpt-4o") is True
assert eng.can_serve("claude-sonnet-4") is False
assert eng.can_serve("gemini-2.5-pro") is False
assert eng.can_serve("openrouter/openai/gpt-4o") is False
def test_openai_key_does_not_claim_local_models(self) -> None:
"""#335: with only the OpenAI client set (e.g. a present-but-dummy
OPENAI_API_KEY), the cloud engine must NOT claim it can serve a local
Ollama model name — otherwise it gets mis-selected as a fallback when
the local engine is transiently down and dies with "OpenAI client not
available". Only genuine OpenAI models route to the OpenAI client.
"""
eng = self._engine(_openai_client=object())
# Local Ollama / unrecognized names are NOT served by the cloud engine.
assert eng.can_serve("qwen3.5:0.8b") is False
assert eng.can_serve("llama3.2") is False
assert eng.can_serve("mistral") is False
assert eng.can_serve("phi3:mini") is False
assert eng.can_serve("some-unknown-model") is False
# Genuine OpenAI families still served.
assert eng.can_serve("gpt-4o") is True
assert eng.can_serve("gpt-5.4") is True
assert eng.can_serve("o3-mini") is True
def test_unknown_model_not_served_even_with_all_clients(self) -> None:
"""#335: an unrecognized model is declined regardless of how many
provider clients are configured — it never falls through to OpenAI."""
eng = self._engine(
_openai_client=object(),
_anthropic_client=object(),
_google_client=object(),
_minimax_client=object(),
_deepseek_client=object(),
)
assert eng.can_serve("qwen3.5:0.8b") is False
assert eng.can_serve("totally-made-up") is False
def test_anthropic_only_serves_anthropic_models(self) -> None:
eng = self._engine(_anthropic_client=object())
assert eng.can_serve("claude-sonnet-4") is True
assert eng.can_serve("gpt-4o") is False
def test_deepseek_only_serves_deepseek_models(self) -> None:
"""The DeepSeek client serves deepseek-* models (and only those)."""
eng = self._engine(_deepseek_client=object())
assert eng.can_serve("deepseek-v4-flash") is True
assert eng.can_serve("deepseek-v4-pro") is True
assert eng.can_serve("DeepSeek-V4-Pro") is True # case-insensitive
assert eng.can_serve("gpt-4o") is False
# OpenRouter-prefixed deepseek is NOT the direct DeepSeek provider.
assert eng.can_serve("openrouter/deepseek/deepseek-r1") is False
class TestCloudEngineDeepSeek:
"""PR #504: DeepSeek as a first-class cloud provider (OpenAI-compatible)."""
def test_is_deepseek_model_predicate(self) -> None:
assert _is_deepseek_model("deepseek-v4-flash") is True
assert _is_deepseek_model("deepseek-v4-pro") is True
assert _is_deepseek_model("DeepSeek-V4-Pro") is True # case-insensitive
assert _is_deepseek_model("gpt-4o") is False
# No predicate collision: openrouter/deepseek/* belongs to OpenRouter.
assert _is_deepseek_model("openrouter/deepseek/deepseek-r1") is False
assert _is_openrouter_model("openrouter/deepseek/deepseek-r1") is True
# And a deepseek name is not mistaken for an OpenAI model.
assert _is_openai_model("deepseek-v4-pro") is False
def test_pricing_entries_present(self) -> None:
assert estimate_cost("deepseek-v4-flash", 1_000_000, 1_000_000) == (
pytest.approx(1.37) # 0.27 + 1.10
)
assert estimate_cost("deepseek-v4-pro", 1_000_000, 1_000_000) == (
pytest.approx(2.74) # 0.55 + 2.19
)
def test_init_wires_deepseek_client(self, monkeypatch: pytest.MonkeyPatch) -> None:
"""DEEPSEEK_API_KEY builds an openai client pointed at api.deepseek.com."""
for var in ("OPENAI_API_KEY", "ANTHROPIC_API_KEY"):
monkeypatch.delenv(var, raising=False)
monkeypatch.setenv("DEEPSEEK_API_KEY", "sk-deepseek-test")
fake_openai = mock.MagicMock()
with mock.patch.dict("sys.modules", {"openai": fake_openai}):
EngineRegistry.register_value("cloud", CloudEngine)
engine = CloudEngine()
fake_openai.OpenAI.assert_any_call(
base_url="https://api.deepseek.com/v1",
api_key="sk-deepseek-test",
)
assert engine._deepseek_client is not None
def test_health_and_list_models_gated_on_deepseek_key(
self, monkeypatch: pytest.MonkeyPatch
) -> None:
for var in ("OPENAI_API_KEY", "ANTHROPIC_API_KEY"):
monkeypatch.delenv(var, raising=False)
monkeypatch.setenv("DEEPSEEK_API_KEY", "sk-deepseek-test")
fake_openai = mock.MagicMock()
with mock.patch.dict("sys.modules", {"openai": fake_openai}):
EngineRegistry.register_value("cloud", CloudEngine)
engine = CloudEngine()
assert engine.health() is True
models = engine.list_models()
assert "deepseek-v4-flash" in models
assert "deepseek-v4-pro" in models
# can_serve must agree with list_models (regression for the missing
# _client_for_model deepseek branch flagged by the #504 verifier).
assert engine.can_serve("deepseek-v4-pro") is True
assert engine.can_serve("deepseek-v4-flash") is True
def test_generate_routes_to_deepseek_client(
self, monkeypatch: pytest.MonkeyPatch
) -> None:
for var in ("OPENAI_API_KEY", "ANTHROPIC_API_KEY", "DEEPSEEK_API_KEY"):
monkeypatch.delenv(var, raising=False)
fake_usage = SimpleNamespace(
prompt_tokens=7, completion_tokens=3, total_tokens=10
)
fake_choice = SimpleNamespace(
message=SimpleNamespace(content="ds-hello"),
finish_reason="stop",
)
fake_resp = SimpleNamespace(
choices=[fake_choice], usage=fake_usage, model="deepseek-v4-pro"
)
fake_client = mock.MagicMock()
fake_client.chat.completions.create.return_value = fake_resp
EngineRegistry.register_value("cloud", CloudEngine)
engine = CloudEngine()
engine._deepseek_client = fake_client
result = engine.generate(
[Message(role=Role.USER, content="Hi")], model="deepseek-v4-pro"
)
assert result["content"] == "ds-hello"
assert result["usage"]["prompt_tokens"] == 7
# Routed to the DeepSeek client, not OpenAI.
fake_client.chat.completions.create.assert_called_once()
def test_generate_without_client_raises(
self, monkeypatch: pytest.MonkeyPatch
) -> None:
for var in ("OPENAI_API_KEY", "ANTHROPIC_API_KEY", "DEEPSEEK_API_KEY"):
monkeypatch.delenv(var, raising=False)
EngineRegistry.register_value("cloud", CloudEngine)
engine = CloudEngine()
assert engine._deepseek_client is None
with pytest.raises(EngineConnectionError):
engine.generate(
[Message(role=Role.USER, content="Hi")], model="deepseek-v4-pro"
)
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