mirror of
https://github.com/jxxghp/MoviePilot.git
synced 2026-08-09 23:44:20 +08:00
116 lines
4.1 KiB
Python
116 lines
4.1 KiB
Python
import unittest
|
|
|
|
from langchain_core.messages import AIMessage, HumanMessage, ToolMessage
|
|
|
|
from app.agent.llm import helper as llm_module
|
|
|
|
|
|
def _build_tool_call(name: str = "search", arguments: str = "{}"):
|
|
return [
|
|
{
|
|
"id": "call_1",
|
|
"type": "tool_call",
|
|
"name": name,
|
|
"args": {},
|
|
}
|
|
]
|
|
|
|
|
|
class _FakeChatDeepSeek:
|
|
def __init__(self, model_name: str, model_kwargs: dict | None = None):
|
|
self.model_name = model_name
|
|
self.model_kwargs = model_kwargs or {}
|
|
|
|
def _convert_input(self, input_):
|
|
return type("_FakeInput", (), {"to_messages": lambda _self: input_})()
|
|
|
|
def _get_request_payload(self, input_, *, stop=None, **kwargs):
|
|
messages = []
|
|
for message in input_:
|
|
payload_message = {
|
|
"role": message.type,
|
|
"content": message.content,
|
|
}
|
|
if message.type == "human":
|
|
payload_message["role"] = "user"
|
|
elif message.type == "ai":
|
|
payload_message["role"] = "assistant"
|
|
tool_calls = getattr(message, "tool_calls", None)
|
|
if tool_calls:
|
|
payload_message["tool_calls"] = tool_calls
|
|
elif message.type == "tool":
|
|
payload_message["role"] = "tool"
|
|
payload_message["tool_call_id"] = message.tool_call_id
|
|
messages.append(payload_message)
|
|
return {"messages": messages}
|
|
|
|
|
|
_ORIGINAL_GET_REQUEST_PAYLOAD = _FakeChatDeepSeek._get_request_payload
|
|
|
|
|
|
class DeepSeekCompatPatchTest(unittest.TestCase):
|
|
def setUp(self):
|
|
_FakeChatDeepSeek._get_request_payload = _ORIGINAL_GET_REQUEST_PAYLOAD
|
|
if hasattr(_FakeChatDeepSeek, "_moviepilot_reasoning_content_patched"):
|
|
delattr(_FakeChatDeepSeek, "_moviepilot_reasoning_content_patched")
|
|
llm_module._patch_interleaved_reasoning_request_support(
|
|
_FakeChatDeepSeek,
|
|
patch_marker="_moviepilot_reasoning_content_patched",
|
|
thinking_filter=lambda model_name, extra_body: (
|
|
llm_module._is_deepseek_thinking_enabled(model_name, extra_body)
|
|
),
|
|
normalize_deepseek_messages=True,
|
|
inject_missing_as_empty=True,
|
|
)
|
|
|
|
def test_injects_reasoning_content_for_assistant_tool_calls(self):
|
|
llm = _FakeChatDeepSeek("deepseek-v4-pro")
|
|
messages = [
|
|
HumanMessage(content="天气如何？"),
|
|
AIMessage(
|
|
content="",
|
|
tool_calls=_build_tool_call(),
|
|
additional_kwargs={"reasoning_content": "先调用天气工具"},
|
|
),
|
|
ToolMessage(content="晴天", tool_call_id="call_1"),
|
|
]
|
|
|
|
payload = llm._get_request_payload(messages)
|
|
|
|
self.assertEqual(
|
|
payload["messages"][1]["reasoning_content"],
|
|
"先调用天气工具",
|
|
)
|
|
|
|
def test_falls_back_to_empty_reasoning_content_when_missing(self):
|
|
llm = _FakeChatDeepSeek("deepseek-v4-flash")
|
|
messages = [
|
|
HumanMessage(content="天气如何？"),
|
|
AIMessage(content="", tool_calls=_build_tool_call()),
|
|
ToolMessage(content="晴天", tool_call_id="call_1"),
|
|
]
|
|
|
|
payload = llm._get_request_payload(messages)
|
|
|
|
self.assertIn("reasoning_content", payload["messages"][1])
|
|
self.assertEqual(payload["messages"][1]["reasoning_content"], "")
|
|
|
|
def test_skips_injection_when_thinking_is_disabled(self):
|
|
llm = _FakeChatDeepSeek(
|
|
"deepseek-v4-pro",
|
|
model_kwargs={"extra_body": {"thinking": {"type": "disabled"}}},
|
|
)
|
|
messages = [
|
|
HumanMessage(content="天气如何？"),
|
|
AIMessage(
|
|
content="",
|
|
tool_calls=_build_tool_call(),
|
|
additional_kwargs={"reasoning_content": "先调用天气工具"},
|
|
),
|
|
ToolMessage(content="晴天", tool_call_id="call_1"),
|
|
]
|
|
|
|
payload = llm._get_request_payload(messages)
|
|
|
|
self.assertNotIn("reasoning_content", payload["messages"][1])
|