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feat：统一replyer在是否多模态下的表现，提高一致性和通用性，新增模型visual参数

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This commit is contained in:
SengokuCola
2026-04-11 16:41:00 +08:00
parent 3ea2bf1059
commit c0230fc313
20 changed files with 323 additions and 1802 deletions
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133
pytests/test_maisaka_monitor_protocol.py
View File

@@ -5,8 +5,7 @@ import pytest
from rich.panel import Panel
from rich.text import Text
from src.chat.replyer import maisaka_generator as legacy_replyer_module
from src.chat.replyer import maisaka_generator_multi as multimodal_replyer_module
from src.chat.replyer import maisaka_generator as replyer_module
from src.common.data_models.reply_generation_data_models import (
GenerationMetrics,
LLMCompletionResult,
@@ -37,8 +36,8 @@ class _FakeLegacyLLMServiceClient:
del args
del kwargs
async def generate_response(self, prompt: str) -> _FakeLLMResult:
assert prompt
async def generate_response_with_messages(self, *, message_factory: Callable[[object], list[Any]]) -> _FakeLLMResult:
assert message_factory(object())
return _FakeLLMResult()
@@ -54,13 +53,21 @@ class _FakeMultimodalLLMServiceClient:
@pytest.mark.asyncio
async def test_legacy_and_multimodal_replyer_monitor_detail_have_same_shape(monkeypatch: pytest.MonkeyPatch) -> None:
monkeypatch.setattr(legacy_replyer_module, "LLMServiceClient", _FakeLegacyLLMServiceClient)
monkeypatch.setattr(multimodal_replyer_module, "LLMServiceClient", _FakeMultimodalLLMServiceClient)
monkeypatch.setattr(legacy_replyer_module, "load_prompt", lambda *args, **kwargs: "legacy prompt")
monkeypatch.setattr(multimodal_replyer_module, "load_prompt", lambda *args, **kwargs: "multi prompt")
monkeypatch.setattr(replyer_module, "LLMServiceClient", _FakeLegacyLLMServiceClient)
monkeypatch.setattr(replyer_module, "load_prompt", lambda *args, **kwargs: "legacy prompt")
legacy_generator = legacy_replyer_module.MaisakaReplyGenerator(chat_stream=None, request_type="test_legacy")
multimodal_generator = multimodal_replyer_module.MaisakaReplyGenerator(chat_stream=None, request_type="test_multi")
legacy_generator = replyer_module.MaisakaReplyGenerator(
chat_stream=None,
request_type="test_legacy",
enable_visual_message=False,
)
multimodal_generator = replyer_module.MaisakaReplyGenerator(
chat_stream=None,
request_type="test_multi",
llm_client_cls=_FakeMultimodalLLMServiceClient,
load_prompt_func=lambda *args, **kwargs: "multi prompt",
enable_visual_message=True,
)
legacy_success, legacy_result = await legacy_generator.generate_reply_with_context(
stream_id="session-legacy",
@@ -84,6 +91,40 @@ async def test_legacy_and_multimodal_replyer_monitor_detail_have_same_shape(monk
assert legacy_result.monitor_detail["metrics"]["total_tokens"] == 19
def test_legacy_replyer_builds_message_sequence_like_multimodal() -> None:
legacy_generator = replyer_module.MaisakaReplyGenerator(
chat_stream=None,
request_type="test_legacy",
enable_visual_message=False,
)
legacy_prompt_loader = replyer_module.load_prompt
replyer_module.load_prompt = lambda *args, **kwargs: "legacy prompt"
try:
session_message = replyer_module.SessionBackedMessage(
raw_message=SimpleNamespace(),
visible_text="[Alice]你好\n[Bob]在吗",
timestamp=replyer_module.datetime.now(),
source_kind="user",
)
request_messages = legacy_generator._build_request_messages(
chat_history=[session_message],
reply_message=None,
reply_reason="测试原因",
stream_id="session-legacy",
)
finally:
replyer_module.load_prompt = legacy_prompt_loader
assert len(request_messages) == 4
assert request_messages[0].role.value == "system"
assert request_messages[1].role.value == "user"
assert request_messages[1].get_text_content() == "[Alice]你好"
assert request_messages[2].role.value == "user"
assert request_messages[2].get_text_content() == "[Bob]在吗"
assert request_messages[3].role.value == "user"
@pytest.mark.asyncio
async def test_reply_tool_puts_monitor_detail_into_metadata(monkeypatch: pytest.MonkeyPatch) -> None:
fake_monitor_detail = {
@@ -324,7 +365,7 @@ def test_reasoning_engine_build_tool_monitor_result_keeps_non_reply_tool_without
def test_runtime_build_tool_detail_panels_renders_reply_monitor_detail() -> None:
runtime = object.__new__(MaisakaHeartFlowChatting)
runtime.session_id = "session-1"
panels = runtime._build_tool_detail_panels(
panels = runtime._build_tool_detail_cards(
[
{
"tool_call_id": "call-reply-1",
@@ -348,7 +389,8 @@ def test_runtime_build_tool_detail_panels_renders_reply_monitor_detail() -> None
},
},
}
]
],
stage_title="工具调用",
)
assert len(panels) == 1
@@ -387,7 +429,7 @@ def test_runtime_build_tool_detail_panels_uses_prompt_access_panel(monkeypatch:
_fake_build_text_access_panel,
)
panels = runtime._build_tool_detail_panels(
panels = runtime._build_tool_detail_cards(
[
{
"tool_call_id": "call-reply-2",
@@ -401,7 +443,8 @@ def test_runtime_build_tool_detail_panels_uses_prompt_access_panel(monkeypatch:
"output_text": "reply output",
},
}
]
],
stage_title="工具调用",
)
assert len(panels) == 1
@@ -425,7 +468,7 @@ def test_runtime_build_tool_detail_panels_uses_emotion_prompt_access_panel(monke
_fake_build_text_access_panel,
)
panels = runtime._build_tool_detail_panels(
panels = runtime._build_tool_detail_cards(
[
{
"tool_call_id": "call-emoji-1",
@@ -439,7 +482,8 @@ def test_runtime_build_tool_detail_panels_uses_emotion_prompt_access_panel(monke
"output_text": '{"emoji_index": 1}',
},
}
]
],
stage_title="工具调用",
)
assert len(panels) == 1
@@ -448,6 +492,63 @@ def test_runtime_build_tool_detail_panels_uses_emotion_prompt_access_panel(monke
assert captured["kwargs"]["request_kind"] == "emotion"
def test_runtime_build_tool_detail_cards_uses_structured_prompt_messages_with_images(
monkeypatch: pytest.MonkeyPatch,
) -> None:
runtime = object.__new__(MaisakaHeartFlowChatting)
runtime.session_id = "session-image"
captured: dict[str, Any] = {}
def _fake_build_prompt_access_panel(messages: list[Any], **kwargs: Any) -> str:
captured["messages"] = messages
captured["kwargs"] = kwargs
return "IMAGE_PROMPT_LINK"
def _fake_build_text_access_panel(content: str, **kwargs: Any) -> str:
captured["text_content"] = content
captured["text_kwargs"] = kwargs
return "TEXT_PROMPT_LINK"
monkeypatch.setattr(
"src.maisaka.runtime.PromptCLIVisualizer.build_prompt_access_panel",
_fake_build_prompt_access_panel,
)
monkeypatch.setattr(
"src.maisaka.runtime.PromptCLIVisualizer.build_text_access_panel",
_fake_build_text_access_panel,
)
panels = runtime._build_tool_detail_cards(
[
{
"tool_call_id": "call-reply-image-1",
"tool_name": "reply",
"tool_args": {"msg_id": "m3"},
"success": True,
"duration_ms": 22.0,
"summary": "- reply [成功]: 已回复",
"detail": {
"prompt_text": "reply prompt image",
"request_messages": [
{
"role": "user",
"content": ["前缀文本", ["png", "ZmFrZQ=="]],
}
],
"output_text": "reply output",
},
}
],
stage_title="工具调用",
)
assert len(panels) == 1
assert "messages" in captured
assert "text_content" not in captured
assert captured["kwargs"]["chat_id"] == "session-image"
assert captured["kwargs"]["request_kind"] == "replyer"
def test_runtime_render_context_usage_panel_merges_timing_and_planner(monkeypatch: pytest.MonkeyPatch) -> None:
runtime = object.__new__(MaisakaHeartFlowChatting)
runtime.session_id = "session-merged"

18
pytests/test_prompt_message_roundtrip.py Normal file
View File

@@ -0,0 +1,18 @@
from src.llm_models.payload_content.message import MessageBuilder, RoleType
from src.plugin_runtime.hook_payloads import deserialize_prompt_messages, serialize_prompt_messages
def test_prompt_messages_roundtrip_preserves_image_parts() -> None:
messages = [
MessageBuilder().set_role(RoleType.User).add_text_content("你好").add_image_content("png", "ZmFrZQ==").build(),
]
serialized_messages = serialize_prompt_messages(messages)
restored_messages = deserialize_prompt_messages(serialized_messages)
assert len(restored_messages) == 1
assert restored_messages[0].role == RoleType.User
assert restored_messages[0].get_text_content() == "你好"
assert len(restored_messages[0].parts) == 2
assert restored_messages[0].parts[1].image_format == "png"
assert restored_messages[0].parts[1].image_base64 == "ZmFrZQ=="