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feat: 支持多语言提示词本地化和界面优化

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- 添加 prompt_locale 参数支持简体中文、繁体中文和英文提示词本地化
- 移除内置 agents 配置以简化系统架构
- 更新 ContextBuilder 使用动态提示词模板而非硬编码内容
- 在 AgentLoop、Web 接口和 AgentService 中传递 locale 参数
- 添加输出语言指令确保用户界面内容按指定语言生成
- 扩展前端 LanguageSwitcher 组件支持三种语言选项
- 优化 Header 和侧边栏组件的响应式布局和文本截断处理
- 更新测试用例验证不同语言环境下的提示词正确性
This commit is contained in:
steven_li
2026-06-10 16:11:05 +08:00
parent 9cc3334ea7
commit fc9fd93c36
51 changed files with 7493 additions and 619 deletions
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143
app-instance/backend/agents/registry.json
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@ -1,145 +1,4 @@
{
"agents": [
{
"agent_id": "researcher",
"capabilities": [
"research",
"analysis",
"source review",
"requirements"
],
"created_at": "2026-05-27T05:25:11.756341+00:00",
"description": "Finds facts, references, constraints, and implementation options.",
"display_name": "Researcher",
"metadata": {},
"model": null,
"name": "researcher",
"priority": 50,
"provider_name": null,
"role": "research",
"skill_names": [],
"source": "builtin",
"status": "active",
"system_prompt": "You are a research specialist. Gather concise evidence and tradeoffs for the parent task.",
"tags": [
"planning",
"research"
],
"tool_hints": [],
"updated_at": "2026-05-27T05:25:11.756349+00:00"
},
{
"agent_id": "implementer",
"capabilities": [
"implementation",
"coding",
"refactor",
"integration"
],
"created_at": "2026-05-27T05:25:11.756351+00:00",
"description": "Builds scoped implementation slices and proposes concrete changes.",
"display_name": "Implementer",
"metadata": {},
"model": null,
"name": "implementer",
"priority": 45,
"provider_name": null,
"role": "implementation",
"skill_names": [],
"source": "builtin",
"status": "active",
"system_prompt": "You are an implementation specialist. Produce practical, scoped implementation output.",
"tags": [
"coding",
"build"
],
"tool_hints": [],
"updated_at": "2026-05-27T05:25:11.756353+00:00"
},
{
"agent_id": "reviewer",
"capabilities": [
"review",
"quality",
"risk",
"verification"
],
"created_at": "2026-05-27T05:25:11.756355+00:00",
"description": "Reviews plans, code, outputs, and risks before final synthesis.",
"display_name": "Reviewer",
"metadata": {},
"model": null,
"name": "reviewer",
"priority": 45,
"provider_name": null,
"role": "review",
"skill_names": [],
"source": "builtin",
"status": "active",
"system_prompt": "You are a review specialist. Focus on defects, missing requirements, and risks.",
"tags": [
"review",
"quality"
],
"tool_hints": [],
"updated_at": "2026-05-27T05:25:11.756356+00:00"
},
{
"agent_id": "tester",
"capabilities": [
"testing",
"verification",
"regression",
"qa"
],
"created_at": "2026-05-27T05:25:11.756358+00:00",
"description": "Designs and executes verification checks for task outputs.",
"display_name": "Tester",
"metadata": {},
"model": null,
"name": "tester",
"priority": 40,
"provider_name": null,
"role": "testing",
"skill_names": [],
"source": "builtin",
"status": "active",
"system_prompt": "You are a testing specialist. Identify focused checks and report pass/fail evidence.",
"tags": [
"test",
"quality"
],
"tool_hints": [],
"updated_at": "2026-05-27T05:25:11.756358+00:00"
},
{
"agent_id": "documenter",
"capabilities": [
"documentation",
"explanation",
"migration notes",
"release notes"
],
"created_at": "2026-05-27T05:25:11.756360+00:00",
"description": "Writes and reconciles user-facing and internal documentation updates.",
"display_name": "Documenter",
"metadata": {},
"model": null,
"name": "documenter",
"priority": 35,
"provider_name": null,
"role": "documentation",
"skill_names": [],
"source": "builtin",
"status": "active",
"system_prompt": "You are a documentation specialist. Produce concise docs aligned with the implementation.",
"tags": [
"docs",
"communication"
],
"tool_hints": [],
"updated_at": "2026-05-27T05:25:11.756360+00:00"
}
],
"agents": [],
"version": 1
}

11
app-instance/backend/beaver/engine/context/builder.py
View File

@ -27,13 +27,7 @@ from dataclasses import dataclass, field
from typing import Any
from beaver.memory.curated.snapshot import MemorySnapshot
BEAVER_USER_ASSISTANT_IDENTITY_PROMPT = (
"You are 海狸 (Beaver), an AI assistant developed by 博维资讯系统有限公司. "
"When communicating with users, keep this identity consistent. "
"If users ask who you are, say that you are 海狸 (Beaver), 博维资讯系统有限公司研发的 AI 助手."
)
from beaver.prompts import get_main_agent_prompt
@dataclass(slots=True)
@ -113,6 +107,7 @@ class ContextBuildInput:
"""
base_system_prompt: str = ""
prompt_locale: str | None = None
history: list[dict[str, Any]] = field(default_factory=list)
current_user_input: str | list[dict[str, Any]] | None = None
memory_snapshot: MemorySnapshot | None = None
@ -171,7 +166,7 @@ class ContextBuilder:
- activated skill 正文放到显式消息里，避免 system prompt 持续膨胀
"""
sections: list[str] = [BEAVER_USER_ASSISTANT_IDENTITY_PROMPT]
sections: list[str] = [get_main_agent_prompt(build_input.prompt_locale)]
base_system_prompt = (build_input.base_system_prompt or "").strip()
if base_system_prompt:

4
app-instance/backend/beaver/engine/loop.py
View File

@ -224,6 +224,7 @@ class AgentLoop:
title: str | None = None,
execution_context: str | None = None,
skill_selection_context: str | None = None,
prompt_locale: str | None = None,
model: str | None = None,
provider_name: str | None = None,
api_key: str | None = None,
@ -275,6 +276,7 @@ class AgentLoop:
title=title,
execution_context=execution_context,
skill_selection_context=skill_selection_context,
prompt_locale=prompt_locale,
model=model,
provider_name=provider_name,
api_key=api_key,
@ -314,6 +316,7 @@ class AgentLoop:
title: str | None = None,
execution_context: str | None = None,
skill_selection_context: str | None = None,
prompt_locale: str | None = None,
model: str | None = None,
provider_name: str | None = None,
api_key: str | None = None,
@ -572,6 +575,7 @@ class AgentLoop:
build_input = ContextBuildInput(
base_system_prompt=self.profile.system_prompt,
prompt_locale=prompt_locale,
history=session_manager.get_history(
resolved_session_id,
max_messages=max(1, self.profile.max_context_messages),

2
app-instance/backend/beaver/interfaces/web/app.py
View File

@ -2463,6 +2463,7 @@ def create_app(
"user_id": payload.user_id,
"title": payload.title,
"execution_context": payload.execution_context,
"prompt_locale": payload.prompt_locale,
"model": payload.model,
"provider_name": payload.provider_name,
"embedding_model": payload.embedding_model,
@ -2578,6 +2579,7 @@ def create_app(
"user_id": _clean_text(payload.get("user_id")) or None,
"title": _clean_text(payload.get("title")) or None,
"execution_context": _clean_text(payload.get("execution_context")) or None,
"prompt_locale": _clean_text(payload.get("prompt_locale")) or None,
"model": _clean_text(payload.get("model")) or None,
"provider_name": _clean_text(payload.get("provider_name")) or None,
"embedding_model": _clean_text(payload.get("embedding_model")) or None,

1
app-instance/backend/beaver/interfaces/web/schemas/chat.py
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@ -55,6 +55,7 @@ class WebChatRequest(BaseModel):
user_id: str | None = None
title: str | None = None
execution_context: str | None = None
prompt_locale: str | None = None
model: str | None = None
provider_name: str | None = None
embedding_model: str | None = None

5
app-instance/backend/beaver/prompts/__init__.py Normal file
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@ -0,0 +1,5 @@
"""Prompt templates used by Beaver runtime components."""
from .main_agent import get_main_agent_prompt
__all__ = ["get_main_agent_prompt"]

55
app-instance/backend/beaver/prompts/main_agent.py Normal file
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@ -0,0 +1,55 @@
"""Locale-aware main agent prompt loading."""
from __future__ import annotations
from functools import lru_cache
from pathlib import Path
DEFAULT_MAIN_AGENT_PROMPT_LOCALE = "zh-Hans"
_PROMPT_FILES = {
"zh-Hans": "zh-Hans.md",
"zh-Hant": "zh-Hant.md",
"en": "en.md",
}
_LOCALE_ALIASES = {
"zh": "zh-Hans",
"zh-cn": "zh-Hans",
"zh-hans": "zh-Hans",
"zh-sg": "zh-Hans",
"zh-hant": "zh-Hant",
"zh-tw": "zh-Hant",
"zh-hk": "zh-Hant",
"zh-mo": "zh-Hant",
"en": "en",
"en-us": "en",
"en-gb": "en",
}
def get_main_agent_prompt(locale: str | None = None) -> str:
"""Return the main-agent identity prompt for a prompt locale."""
prompt_locale = normalize_main_agent_prompt_locale(locale)
return _load_main_agent_prompt(prompt_locale)
def normalize_main_agent_prompt_locale(locale: str | None = None) -> str:
cleaned = (locale or DEFAULT_MAIN_AGENT_PROMPT_LOCALE).strip()
if not cleaned:
return DEFAULT_MAIN_AGENT_PROMPT_LOCALE
normalized = _LOCALE_ALIASES.get(cleaned.lower())
if normalized:
return normalized
return cleaned if cleaned in _PROMPT_FILES else DEFAULT_MAIN_AGENT_PROMPT_LOCALE
@lru_cache(maxsize=len(_PROMPT_FILES))
def _load_main_agent_prompt(locale: str) -> str:
filename = _PROMPT_FILES.get(locale, _PROMPT_FILES[DEFAULT_MAIN_AGENT_PROMPT_LOCALE])
path = Path(__file__).with_name("main_agent") / filename
if not path.exists():
fallback_path = Path(__file__).with_name("main_agent") / _PROMPT_FILES[DEFAULT_MAIN_AGENT_PROMPT_LOCALE]
return fallback_path.read_text(encoding="utf-8").strip()
return path.read_text(encoding="utf-8").strip()

7
app-instance/backend/beaver/prompts/main_agent/en.md Normal file
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@ -0,0 +1,7 @@
You are Beaver, an AI assistant developed by Boway Information Systems Co., Ltd.
When communicating with users, keep this identity consistent. If users ask who you are, say that you are Beaver, an AI assistant developed by Boway Information Systems Co., Ltd.
# Language
Use English for user-facing replies, task titles, summaries, plans, and final reports while this prompt is active. If the user explicitly asks for another language, follow that request.

7
app-instance/backend/beaver/prompts/main_agent/zh-Hans.md Normal file
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@ -0,0 +1,7 @@
你是海狸 (Beaver)，博维资讯系统有限公司研发的 AI 助手。
与用户沟通时，保持这个身份一致。用户问你是谁时，说明你是海狸 (Beaver)，博维资讯系统有限公司研发的 AI 助手。
# 语言
使用简体中文进行面向用户的回复、任务标题、摘要、计划和最终报告。若用户明确要求其他语言，则按用户要求执行。

7
app-instance/backend/beaver/prompts/main_agent/zh-Hant.md Normal file
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@ -0,0 +1,7 @@
你是海狸 (Beaver)，博維資訊系統有限公司研發的 AI 助手。
與使用者溝通時，保持這個身份一致。使用者問你是誰時，說明你是海狸 (Beaver)，博維資訊系統有限公司研發的 AI 助手。
# 語言
使用繁體中文進行面向使用者的回覆、任務標題、摘要、計劃和最終報告。若使用者明確要求其他語言，則按使用者要求執行。

29
app-instance/backend/beaver/services/agent_service.py
View File

@ -22,6 +22,7 @@ from beaver.engine import AgentLoop, AgentProfile, AgentRunResult, EngineLoader
from beaver.engine.providers import make_provider_bundle
from beaver.foundation.events import InboundMessage, OutboundMessage
from beaver.foundation.models import CronJob, CronRunRecord
from beaver.prompts.main_agent import normalize_main_agent_prompt_locale
from beaver.tasks import (
EvidenceBuilder,
MainAgentRouter,
@ -622,6 +623,7 @@ class AgentService:
session_id=session_id,
description=message,
metadata={
"prompt_locale": normalize_main_agent_prompt_locale(kwargs.get("prompt_locale")),
"router_reason": decision.reason,
**({"short_title": decision.short_title} if decision.short_title else {}),
},
@ -749,6 +751,8 @@ class AgentService:
session_manager = self._require_loaded(loaded, "session_manager")
base_execution_context = kwargs.get("execution_context")
prompt_locale = kwargs.get("prompt_locale") or task.metadata.get("prompt_locale")
output_language_instruction = self._output_language_instruction(prompt_locale)
provider_bundle = kwargs.get("provider_bundle") or self._make_provider_bundle_for_task(loaded, kwargs)
kwargs = dict(kwargs)
team_provider_bundle_factory = kwargs.pop("team_provider_bundle_factory", None)
@ -843,8 +847,11 @@ class AgentService:
"allow_candidate_generation": False,
}
)
if team_execution_context:
attempt_kwargs["execution_context"] = self._join_context(base_execution_context, team_execution_context)
attempt_kwargs["execution_context"] = self._join_context(
base_execution_context,
output_language_instruction,
team_execution_context,
)
if plan.is_team and team_execution_context:
attempt_kwargs["include_tools"] = False
attempt_kwargs["max_tool_iterations"] = 0
@ -979,6 +986,24 @@ class AgentService:
"short_title": decision.short_title,
}
@staticmethod
def _output_language_instruction(prompt_locale: str | None) -> str:
locale = normalize_main_agent_prompt_locale(prompt_locale)
if locale == "en":
return (
"Output language: English. Use English for user-facing task titles, summaries, plans, "
"and final answers unless the user explicitly requests another language."
)
if locale == "zh-Hant":
return (
"輸出語言：繁體中文。除非使用者明確要求其他語言，所有面向使用者的任務標題、摘要、"
"計劃與最終回答都使用繁體中文。"
)
return (
"输出语言：简体中文。除非用户明确要求其他语言，所有面向用户的任务标题、摘要、"
"计划与最终回答都使用简体中文。"
)
@staticmethod
def _skill_names_for_run(loaded: Any, run_id: str) -> list[str]:
store = getattr(loaded, "run_memory_store", None)

23
app-instance/backend/tests/unit/test_context_builder.py
View File

@ -26,3 +26,26 @@ def test_context_builder_injects_current_date_and_time() -> None:
assert "Local UTC offset: +08:00" in system_prompt
assert '"today", "tomorrow", "now", "this week", and "next month"' in system_prompt
assert result.messages[-1] == {"role": "user", "content": "今天几号？"}
def test_context_builder_uses_simplified_main_agent_prompt_by_default() -> None:
system_prompt = ContextBuilder().build_system_prompt(ContextBuildInput())
assert "你是海狸 (Beaver)" in system_prompt
assert "博维资讯系统有限公司研发的 AI 助手" in system_prompt
assert "使用简体中文进行面向用户的回复" in system_prompt
def test_context_builder_uses_traditional_main_agent_prompt_for_zh_hant() -> None:
system_prompt = ContextBuilder().build_system_prompt(ContextBuildInput(prompt_locale="zh-Hant"))
assert "你是海狸 (Beaver)" in system_prompt
assert "博維資訊系統有限公司研發的 AI 助手" in system_prompt
assert "使用繁體中文進行面向使用者的回覆" in system_prompt
def test_context_builder_uses_english_main_agent_prompt_for_en() -> None:
system_prompt = ContextBuilder().build_system_prompt(ContextBuildInput(prompt_locale="en"))
assert "You are Beaver, an AI assistant developed by Boway Information Systems Co., Ltd." in system_prompt
assert "Use English for user-facing replies" in system_prompt

48
app-instance/backend/tests/unit/test_task_mode_feedback.py
View File

@ -15,6 +15,7 @@ class StubProvider(LLMProvider):
def __init__(self, responses: list[LLMResponse]) -> None:
super().__init__()
self._responses = list(responses)
self.seen_messages: list[list[dict]] = []
async def chat(
self,
@ -26,6 +27,7 @@ class StubProvider(LLMProvider):
) -> LLMResponse:
if not self._responses:
raise AssertionError("No stubbed provider responses left")
self.seen_messages.append(messages)
return self._responses.pop(0)
def get_default_model(self) -> str:
@ -99,6 +101,52 @@ def test_task_run_records_evidence_and_waits_for_acceptance(tmp_path: Path) -> N
assert "validated" not in event_types
def test_task_mode_injects_prompt_locale_output_language(tmp_path: Path) -> None:
service = AgentService(
loader=EngineLoader(
workspace=tmp_path,
task_execution_planner=StubTaskExecutionPlanner(),
)
)
main_provider = StubProvider(
[
LLMResponse(
content="Done",
finish_reason="stop",
provider_name="stub",
model="stub-model",
)
]
)
bundle = ProviderBundle(
main_runtime=SimpleNamespace(model="stub-model", provider_name="stub"),
main_provider=main_provider,
auxiliary_runtime=SimpleNamespace(model="stub-model", provider_name="stub"),
auxiliary_provider=StubProvider([_route_response("new_task", "Product summary")]),
)
result = asyncio.run(
service.process_direct(
"Summarize the uploaded report in English",
session_id="web:locale-task",
prompt_locale="en",
provider_bundle=bundle,
)
)
assert result.task_id
assert main_provider.seen_messages
system_prompt = main_provider.seen_messages[-1][0]["content"]
assert "Use English for user-facing replies" in system_prompt
assert "Output language: English." in system_prompt
task_service = service.create_loop().boot().task_service
assert task_service is not None
task = task_service.get_task(result.task_id)
assert task is not None
assert task.metadata["prompt_locale"] == "en"
def test_unrelated_simple_chat_auto_accepts_active_task(tmp_path: Path) -> None:
service = AgentService(
loader=EngineLoader(

9
app-instance/backend/tests/unit/test_websocket_chat.py
View File

@ -73,6 +73,7 @@ def test_websocket_message_returns_chat_metadata_and_session_updated() -> None:
{
"type": "message",
"content": "hello",
"prompt_locale": "zh-Hant",
"metadata": {"source": "test"},
"attachments": [{"file_id": "file-1", "name": "a.txt"}],
}
@ -89,6 +90,7 @@ def test_websocket_message_returns_chat_metadata_and_session_updated() -> None:
"user_id": None,
"title": None,
"execution_context": None,
"prompt_locale": "zh-Hant",
"model": None,
"provider_name": None,
"embedding_model": None,
@ -134,6 +136,7 @@ def test_websocket_message_uses_direct_processing_when_loop_is_not_running() ->
"user_id": None,
"title": None,
"execution_context": None,
"prompt_locale": None,
"model": None,
"provider_name": None,
"embedding_model": None,
@ -149,7 +152,10 @@ def test_rest_chat_uses_direct_processing_when_loop_is_not_running() -> None:
app = create_app(service=service, manage_service_lifecycle=False)
with TestClient(app) as client:
response = client.post("/api/chat", json={"session_id": "web:alpha", "message": "hello"})
response = client.post(
"/api/chat",
json={"session_id": "web:alpha", "message": "hello", "prompt_locale": "en"},
)
assert response.status_code == 200
assert service.calls == [
@ -160,6 +166,7 @@ def test_rest_chat_uses_direct_processing_when_loop_is_not_running() -> None:
"user_id": None,
"title": None,
"execution_context": None,
"prompt_locale": "en",
"model": None,
"provider_name": None,
"embedding_model": None,