wehub-resource-sync
332 lines
12 KiB
Python
332 lines
12 KiB
Python
import os
|
|
|
|
import pytest
|
|
|
|
os.environ.setdefault("OPENAI_API_KEY", "test-key")
|
|
|
|
from yuxi.models.providers.builtin import BUILTIN_PROVIDERS
|
|
from yuxi.models.providers.service import (
|
|
check_credential_status,
|
|
_normalize_payload,
|
|
_normalize_remote_model,
|
|
fetch_remote_models,
|
|
)
|
|
|
|
|
|
def test_normalize_payload_accepts_enabled_chat_model():
|
|
payload = _normalize_payload(
|
|
{
|
|
"provider_id": "openrouter-local",
|
|
"display_name": "OpenRouter Local",
|
|
"base_url": "https://openrouter.ai/api/v1",
|
|
"enabled_models": [{"id": "anthropic/claude-sonnet-4.5", "type": "chat"}],
|
|
}
|
|
)
|
|
|
|
assert payload["provider_id"] == "openrouter-local"
|
|
assert payload["provider_type"] == "openai"
|
|
assert "models_endpoint" not in payload
|
|
assert "embedding_models_endpoint" not in payload
|
|
assert payload["enabled_models"][0]["display_name"] == "anthropic/claude-sonnet-4.5"
|
|
|
|
|
|
def test_normalize_payload_accepts_anthropic_provider_type():
|
|
payload = _normalize_payload(
|
|
{
|
|
"provider_id": "xiaomi-token-plan",
|
|
"display_name": "Xiaomi Token Plan",
|
|
"provider_type": "anthropic",
|
|
"base_url": "https://token-plan-cn.xiaomimimo.com/anthropic",
|
|
"capabilities": ["chat"],
|
|
"enabled_models": [{"id": "mimo-v2.5-pro", "type": "chat", "source": "manual"}],
|
|
}
|
|
)
|
|
|
|
assert payload["provider_type"] == "anthropic"
|
|
assert payload["enabled_models"][0]["id"] == "mimo-v2.5-pro"
|
|
|
|
|
|
def test_normalize_payload_rejects_unknown_enabled_model_type():
|
|
with pytest.raises(ValueError, match="type 必须是"):
|
|
_normalize_payload(
|
|
{
|
|
"provider_id": "openrouter-local",
|
|
"display_name": "OpenRouter Local",
|
|
"base_url": "https://openrouter.ai/api/v1",
|
|
"enabled_models": [{"id": "unknown-model", "type": "unknown"}],
|
|
}
|
|
)
|
|
|
|
|
|
def test_normalize_payload_allows_embedding_without_dimension():
|
|
"""embedding 模型的 dimension 是可选字段，不提供也不会报错。"""
|
|
payload = _normalize_payload(
|
|
{
|
|
"provider_id": "embedding-local",
|
|
"display_name": "Embedding Local",
|
|
"base_url": "https://example.com/v1",
|
|
"capabilities": ["embedding"],
|
|
"embedding_base_url": "https://example.com/v1/embeddings",
|
|
"enabled_models": [{"id": "text-embedding", "type": "embedding"}],
|
|
}
|
|
)
|
|
assert payload["provider_id"] == "embedding-local"
|
|
assert payload["enabled_models"][0].get("dimension") is None
|
|
|
|
|
|
def test_normalize_remote_model_preserves_detailed_model_config():
|
|
model = _normalize_remote_model(
|
|
{
|
|
"id": "xiaomi/mimo-v2-omni",
|
|
"name": "Xiaomi: MiMo-V2-Omni",
|
|
"context_length": 262144,
|
|
"architecture": {
|
|
"input_modalities": ["text", "audio", "image", "video"],
|
|
"output_modalities": ["text"],
|
|
},
|
|
"top_provider": {"max_completion_tokens": 65536},
|
|
"supported_parameters": ["temperature", "tools"],
|
|
}
|
|
)
|
|
|
|
assert model["id"] == "xiaomi/mimo-v2-omni"
|
|
assert model["display_name"] == "Xiaomi: MiMo-V2-Omni"
|
|
assert model["type"] == "chat"
|
|
assert model["input_modalities"] == ["text", "audio", "image", "video"]
|
|
assert model["max_completion_tokens"] == 65536
|
|
assert model["raw_metadata"]["supported_parameters"] == ["temperature", "tools"]
|
|
|
|
|
|
def test_normalize_remote_model_uses_endpoint_model_type():
|
|
model = _normalize_remote_model({"id": "BAAI/bge-m3", "object": "model"}, "embedding")
|
|
|
|
assert model["id"] == "BAAI/bge-m3"
|
|
assert model["type"] == "embedding"
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_fetch_remote_models_loads_embedding_only_when_capability_enabled(monkeypatch):
|
|
calls = []
|
|
|
|
async def fake_fetch(client, provider, headers, endpoint, model_type):
|
|
calls.append((endpoint, model_type))
|
|
return [{"id": f"{model_type}-model", "type": model_type}]
|
|
|
|
monkeypatch.setattr("yuxi.models.providers.service._fetch_models_from_endpoint", fake_fetch)
|
|
|
|
class Provider:
|
|
base_url = "https://example.com/v1"
|
|
api_key = None
|
|
api_key_env = None
|
|
headers_json = {}
|
|
capabilities = ["chat", "embedding", "rerank"]
|
|
models_endpoint = "/models"
|
|
embedding_models_endpoint = "/embeddings/models"
|
|
rerank_models_endpoint = None
|
|
|
|
models = await fetch_remote_models(Provider())
|
|
|
|
assert calls == [("/models", "chat"), ("/embeddings/models", "embedding")]
|
|
assert [model["type"] for model in models] == ["chat", "embedding"]
|
|
|
|
|
|
def test_normalize_payload_rejects_ollama_provider_type():
|
|
with pytest.raises(ValueError, match="provider_type 必须是"):
|
|
_normalize_payload(
|
|
{
|
|
"provider_id": "ollama-local",
|
|
"display_name": "Ollama Local",
|
|
"provider_type": "ollama",
|
|
"base_url": "http://localhost:11434",
|
|
}
|
|
)
|
|
|
|
|
|
def test_builtin_provider_templates_default_to_openai_provider_type():
|
|
assert len(BUILTIN_PROVIDERS) >= 16
|
|
provider_types = {
|
|
_normalize_payload(
|
|
{
|
|
"provider_id": provider["provider_id"],
|
|
"display_name": provider["display_name"],
|
|
"base_url": provider["base_url"],
|
|
"provider_type": provider.get("provider_type"),
|
|
}
|
|
)["provider_type"]
|
|
for provider in BUILTIN_PROVIDERS
|
|
}
|
|
assert provider_types == {"openai"}
|
|
assert all("ollama" not in provider["provider_id"] for provider in BUILTIN_PROVIDERS)
|
|
|
|
|
|
def test_builtin_siliconflow_provider_includes_default_runnable_models():
|
|
provider = next(item for item in BUILTIN_PROVIDERS if item["provider_id"] == "siliconflow-cn")
|
|
models = {model["id"]: model for model in provider["enabled_models"]}
|
|
|
|
assert provider["capabilities"] == ["chat", "embedding", "rerank"]
|
|
assert provider["embedding_base_url"] == "https://api.siliconflow.cn/v1/embeddings"
|
|
assert provider["rerank_base_url"] == "https://api.siliconflow.cn/v1/rerank"
|
|
assert models["Pro/BAAI/bge-m3"]["type"] == "embedding"
|
|
assert models["Pro/BAAI/bge-m3"]["dimension"] == 1024
|
|
assert "base_url_override" not in models["Pro/BAAI/bge-m3"]
|
|
assert models["Pro/BAAI/bge-reranker-v2-m3"]["type"] == "rerank"
|
|
assert "base_url_override" not in models["Pro/BAAI/bge-reranker-v2-m3"]
|
|
|
|
|
|
def test_builtin_dashscope_provider_includes_default_embedding_and_rerank_models():
|
|
provider = next(item for item in BUILTIN_PROVIDERS if item["provider_id"] == "alibaba")
|
|
models = {model["id"]: model for model in provider["enabled_models"]}
|
|
|
|
assert provider["capabilities"] == ["chat", "embedding", "rerank"]
|
|
assert provider["embedding_base_url"] == "https://dashscope.aliyuncs.com/compatible-mode/v1/embeddings"
|
|
assert provider["rerank_base_url"] == "https://dashscope.aliyuncs.com/compatible-api/v1/reranks"
|
|
assert "embedding_models_endpoint" not in provider
|
|
assert "rerank_models_endpoint" not in provider
|
|
assert models["text-embedding-v4"]["type"] == "embedding"
|
|
assert models["text-embedding-v4"]["dimension"] == 1024
|
|
assert models["qwen3-rerank"]["type"] == "rerank"
|
|
|
|
|
|
def testcheck_credential_status_disabled_provider_always_ok():
|
|
"""未启用的 provider 无论凭证如何配置，状态始终为 ok。"""
|
|
|
|
class Provider:
|
|
is_enabled = False
|
|
api_key = None
|
|
api_key_env = None
|
|
|
|
assert check_credential_status(Provider()) == "ok"
|
|
|
|
|
|
def testcheck_credential_status_direct_api_key_ok():
|
|
"""直接配置了 api_key 的启用 provider 状态为 ok。"""
|
|
|
|
class Provider:
|
|
is_enabled = True
|
|
api_key = "sk-test"
|
|
api_key_env = None
|
|
|
|
assert check_credential_status(Provider()) == "ok"
|
|
|
|
|
|
def testcheck_credential_status_env_key_exists_ok(monkeypatch):
|
|
"""api_key_env 对应的环境变量存在时状态为 ok。"""
|
|
monkeypatch.setenv("TEST_API_KEY", "exists")
|
|
|
|
class Provider:
|
|
is_enabled = True
|
|
api_key = None
|
|
api_key_env = "TEST_API_KEY"
|
|
|
|
assert check_credential_status(Provider()) == "ok"
|
|
|
|
|
|
def testcheck_credential_status_env_key_missing_warning(monkeypatch):
|
|
"""api_key_env 对应的环境变量不存在时状态为 warning。"""
|
|
monkeypatch.delenv("MISSING_KEY", raising=False)
|
|
|
|
class Provider:
|
|
is_enabled = True
|
|
api_key = None
|
|
api_key_env = "MISSING_KEY"
|
|
|
|
assert check_credential_status(Provider()) == "warning"
|
|
|
|
|
|
def testcheck_credential_status_both_empty_warning():
|
|
"""api_key 和 api_key_env 都未配置时状态为 warning。"""
|
|
|
|
class Provider:
|
|
is_enabled = True
|
|
api_key = None
|
|
api_key_env = None
|
|
|
|
assert check_credential_status(Provider()) == "warning"
|
|
|
|
|
|
# ==================== 手动添加模型 / source 字段 ====================
|
|
|
|
|
|
def test_normalize_payload_default_model_source_is_remote():
|
|
"""未显式指定 source 时，规范化后默认填入 remote，向后兼容旧数据。"""
|
|
payload = _normalize_payload(
|
|
{
|
|
"provider_id": "openrouter-local",
|
|
"display_name": "OpenRouter Local",
|
|
"base_url": "https://openrouter.ai/api/v1",
|
|
"enabled_models": [{"id": "anthropic/claude-sonnet-4.5", "type": "chat"}],
|
|
}
|
|
)
|
|
|
|
assert payload["enabled_models"][0]["source"] == "remote"
|
|
|
|
|
|
def test_normalize_payload_accepts_manual_source():
|
|
"""source=manual 表示管理员手动添加的模型，规范化保留该标签。"""
|
|
payload = _normalize_payload(
|
|
{
|
|
"provider_id": "custom-local",
|
|
"display_name": "Custom Local",
|
|
"base_url": "https://example.com/v1",
|
|
"capabilities": ["chat"],
|
|
"enabled_models": [{"id": "my-chat-model", "type": "chat", "source": "manual"}],
|
|
}
|
|
)
|
|
|
|
assert payload["enabled_models"][0]["source"] == "manual"
|
|
|
|
|
|
def test_normalize_payload_rejects_invalid_source():
|
|
"""source 仅允许 manual 或 remote，其他取值视为非法。"""
|
|
with pytest.raises(ValueError, match="source 必须是"):
|
|
_normalize_payload(
|
|
{
|
|
"provider_id": "custom-local",
|
|
"display_name": "Custom Local",
|
|
"base_url": "https://example.com/v1",
|
|
"enabled_models": [{"id": "x", "type": "chat", "source": "custom"}],
|
|
}
|
|
)
|
|
|
|
|
|
def test_normalize_payload_rejects_model_type_not_in_capabilities():
|
|
"""provider 仅声明 chat 能力时，不允许写入 embedding 类型的模型。"""
|
|
with pytest.raises(ValueError, match="不在 provider 能力"):
|
|
_normalize_payload(
|
|
{
|
|
"provider_id": "chat-only",
|
|
"display_name": "Chat Only",
|
|
"base_url": "https://example.com/v1",
|
|
"capabilities": ["chat"],
|
|
"enabled_models": [{"id": "rogue-embedding", "type": "embedding", "dimension": 1024}],
|
|
}
|
|
)
|
|
|
|
|
|
def test_normalize_payload_allows_model_type_within_capabilities():
|
|
"""provider 同时声明 chat + embedding 时，两类模型均可正常写入。"""
|
|
payload = _normalize_payload(
|
|
{
|
|
"provider_id": "multi-cap",
|
|
"display_name": "Multi Cap",
|
|
"base_url": "https://example.com/v1",
|
|
"capabilities": ["chat", "embedding"],
|
|
"embedding_base_url": "https://example.com/v1/embeddings",
|
|
"embedding_models_endpoint": "/embeddings/models",
|
|
"enabled_models": [
|
|
{"id": "chat-1", "type": "chat", "source": "manual"},
|
|
{
|
|
"id": "embed-1",
|
|
"type": "embedding",
|
|
"source": "manual",
|
|
"dimension": 1024,
|
|
},
|
|
],
|
|
}
|
|
)
|
|
|
|
types = [model["type"] for model in payload["enabled_models"]]
|
|
sources = [model["source"] for model in payload["enabled_models"]]
|
|
assert types == ["chat", "embedding"]
|
|
assert sources == ["manual", "manual"]
|