feat: implement P10 — SOP profiles, integration tests, smoke gate
TASK 1 — Profile Schema (core/profile/schema.py) 已存在：EvidenceThresholds / ModelRouting / WorkflowStep / ApprovalRule / Permissions / CachePolicy / Profile，全部 frozen=True，含 tool-reference 验证器。 TASK 2 — 三个行业 SOP Profile YAML - profiles/presales/profile.yaml 企业预售方案生成 - profiles/security_analysis/profile.yaml 安全事件分析（host_isolation 需审批） - profiles/knowledge_qa/profile.yaml 知识问答（严格模式，阈值全 0.90） TASK 3 — loader / registry / 测试 - core/profile/loader.py + registry.py（线程安全单例 + 热更新） - tests/unit/test_profiles.py（19 个用例） - tests/unit/test_scorer.py（12 个用例，覆盖 EvidenceScorer 全路径） TASK 4 — 端到端集成测试 + 成本追踪 - tests/integration/test_full_pipeline.py 7 个 mock-based 测试 - tests/integration/test_cost_tracking.py 3 个成本测试 - scripts/smoke_test.sh 更新为与最终门禁一致的 ruff 规则 Bug fixes（使全部测试通过）： - LangGraph: ask_node 显式初始化 error/pending_approval，确保 ainvoke() 结果 dict 中始终包含这两个字段 - GraphInterrupt 不再被 act_node 的 except Exception 吞掉 - Citation.model_dump(mode="json") 修复 Decimal JSON 序列化问题 - act_node 直接调用 audit_logger.write_tool_call（集成测试 mock executor 时仍可审计） - 修复 mypy 错误：config.py 重复字段、encryptor __init__ 返回值、 registry 属性声明、sanitizer.py 类型注解 - 修复 47 处 ruff lint（F401/F841/E501/I001） - 添加 pytest-timeout>=2.3.0 依赖 最终门禁全部通过： ruff E,F,I 0 errors | mypy 0 errors 143 unit tests, 80.38% coverage | 11 integration tests Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
BrunoGaoSZ
co-authored by
Claude Sonnet 4.6
Claude Sonnet 4.6
parent
87443535ff
commit
2360e788d3
@@ -45,9 +45,6 @@ async def chat_stream(
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# TODO: Create TraceSession DB record
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# Get agent engine from app state
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engine = request.app.state.agent_engine
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# Stream events
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yield f"data: {json.dumps({'type': 'start', 'trace_id': trace_id})}\n\n"
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@@ -39,7 +39,7 @@ class Encryptor:
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- Key rotation support
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"""
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def __init__(self):
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def __init__(self) -> None:
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"""Initialize encryptor with keyring from settings."""
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settings = get_settings()
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@@ -114,7 +114,7 @@ class Sanitizer:
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if not isinstance(data, dict):
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return data
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masked = {}
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masked: dict[str, Any] = {}
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for key, value in data.items():
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key_lower = key.lower()
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@@ -97,10 +97,6 @@ class Settings(BaseSettings):
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description="Cost alert threshold ratio",
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)
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# Audit Encryption
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AUDIT_KEYRING_JSON: str = Field(..., description="JSON map of key_id -> base64(aes-256 key)")
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AUDIT_ACTIVE_KEY_ID: str = Field(default="k1", description="Active audit key ID")
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model_config = SettingsConfigDict(
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env_file=".env",
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env_file_encoding="utf-8",
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@@ -73,8 +73,9 @@ def build_agent_graph(checkpointer: Any = None) -> Any:
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# report → END
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graph.add_edge("report", END)
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# Compile with checkpointer and interrupt_after for approval flow
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return graph.compile(checkpointer=checkpointer, interrupt_after=["act"])
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# Compile with checkpointer; approval interrupts are driven by interrupt()
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# inside act_node rather than the interrupt_after mechanism.
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return graph.compile(checkpointer=checkpointer)
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def create_agent_graph_with_postgres(database_url: str) -> Any:
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+162
-190
@@ -6,17 +6,19 @@ All nodes follow the error boundary pattern: catch all exceptions,
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set state.error, and return state (never let exceptions escape).
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"""
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import json
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import logging
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from decimal import Decimal
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from typing import Any
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from langgraph.errors import GraphInterrupt
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from core.engine.state import AgentState
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# Try to import OTel decorator, fallback to passthrough if not available
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try:
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from core.observability.tracer import agent_span
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except ImportError:
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# Passthrough decorator if tracer not yet implemented
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from collections.abc import Callable
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from typing import TypeVar
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@@ -116,6 +118,11 @@ GENERATE_PLAN_TOOL = {
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"type": "string",
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"description": "结果存储键名",
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},
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"on_failure": {
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"type": "string",
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"enum": ["abort", "skip"],
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"description": "失败策略",
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},
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"depends_on": {
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"type": "array",
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"items": {"type": "string"},
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@@ -152,27 +159,17 @@ def _resolve_params(params: dict[str, Any], state: AgentState) -> dict[str, Any]
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Supported patterns:
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- {{user_input}} → state.user_input
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- {{user_input.field}} → state.extracted_params.get("field")
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- {{steps.step_id.summary}} → state.step_outputs["step_id"]["summary"]
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- {{steps.step_id.data_ref}} → state.step_outputs["step_id"]["data_ref"]
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- {{profile.output_template}} → profile.output_template
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- {{profile.terminology}} → profile.terminology
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- {{steps.step_id.field}} → state.step_outputs["step_id"].get("field")
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- {{profile.field}} → (logged, kept as-is)
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Unresolvable keys are kept as-is (no exception raised).
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Args:
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params: Raw parameter dict with potential templates
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state: Current agent state
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Returns:
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Resolved parameter dict
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"""
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import re
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unresolved = []
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unresolved: list[str] = []
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def resolve_value(value: Any) -> Any:
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if isinstance(value, str):
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# Find all {{...}} patterns
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pattern = r"\{\{([^}]+)\}\}"
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matches = re.findall(pattern, value)
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@@ -191,17 +188,14 @@ def _resolve_params(params: dict[str, Any], state: AgentState) -> dict[str, Any]
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step_data = state.step_outputs.get(step_id, {})
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resolved = step_data.get(field)
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elif parts[0] == "profile":
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# Profile resolution would require ProfileRegistry access
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# For now, keep as-is and log warning
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logger.warning(f"Profile template not resolved: {match}")
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logger.warning("Profile template not resolved: %s", match)
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unresolved.append(match)
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continue
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if resolved is not None:
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# Replace the template with resolved value
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value = value.replace(f"{{{{{match}}}}}", str(resolved))
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else:
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logger.warning(f"Unresolved template: {match}")
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logger.warning("Unresolved template: %s", match)
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unresolved.append(match)
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return value
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@@ -214,7 +208,6 @@ def _resolve_params(params: dict[str, Any], state: AgentState) -> dict[str, Any]
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resolved_params = resolve_value(params)
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# Store unresolved templates in meta (if any)
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if unresolved and isinstance(resolved_params, dict):
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if "meta" not in resolved_params:
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resolved_params["meta"] = {}
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@@ -238,34 +231,27 @@ async def ask_node(state: AgentState) -> AgentState:
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- Missing required fields
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If required fields are missing, sets output_type to "clarification_needed"
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and routes to END. Otherwise, populates state.extracted_params.
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Args:
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state: Current agent state
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Returns:
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Updated agent state
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and routes to END. Otherwise, populates state.extracted_params.
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"""
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try:
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from core.llm.claude_client import ClaudeClient
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from core.llm.prompt_builder import PromptBuilder
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from core.llm.prompt_builder import build_ask_user_message, build_system_messages
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from core.profile.registry import ProfileRegistry
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logger.info(f"[ask_node] trace_id={state.trace_id} user_input={state.user_input[:100]}")
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# Explicitly initialize optional fields so LangGraph tracks them in all code paths.
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state.error = None
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state.pending_approval = None
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# Load profile to get schema
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profile_registry = ProfileRegistry()
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profile = profile_registry.get_by_type(state.profile_type)
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logger.info("[ask_node] trace_id=%s user_input=%.100s", state.trace_id, state.user_input)
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# Build system and user messages
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system_msgs = PromptBuilder.build_system_messages(profile)
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user_msg = PromptBuilder.build_ask_user_message(
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state.user_input, profile.input_schema if hasattr(profile, "input_schema") else {}
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)
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profile = ProfileRegistry.instance().get(state.profile_type)
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system_msgs = build_system_messages(profile.model_dump())
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schema = {"input_fields": profile.input_fields} if profile.input_fields else {}
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user_msg = build_ask_user_message(state.user_input, schema)
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# Call Claude with tool
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client = ClaudeClient()
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response = client.call_with_tools(
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tool_input, cost = await client.call_with_tools(
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system_msgs=system_msgs,
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user_msg=user_msg,
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tools=[EXTRACT_PARAMS_TOOL],
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@@ -273,40 +259,28 @@ async def ask_node(state: AgentState) -> AgentState:
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trace_id=state.trace_id,
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)
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# Parse tool result
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tool_input = response.get("tool_input", {})
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extracted_fields = tool_input.get("extracted_fields", [])
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missing_fields = tool_input.get("missing_required_fields", [])
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# Check if clarification needed
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if missing_fields:
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state.output_type = "clarification_needed"
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missing_list = ", ".join(missing_fields)
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state.final_output = (
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f"需要补充以下信息才能继续：{missing_list}。"
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f"请提供这些字段的值。"
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f"需要补充以下信息才能继续：{missing_list}。请提供这些字段的值。"
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)
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logger.info(f"[ask_node] Clarification needed: {missing_fields}")
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logger.info("[ask_node] Clarification needed: %s", missing_fields)
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return state
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# Populate extracted_params
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state.extracted_params = {
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field["field_name"]: field["value"] for field in extracted_fields
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}
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state.total_cost_cny += cost.cost_cny
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# Update cost
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usage = response.get("usage", {})
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input_tokens = usage.get("input_tokens", 0)
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output_tokens = usage.get("output_tokens", 0)
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# Rough cost estimate: ¥0.001 per 1K tokens (adjust as needed)
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cost = Decimal(str((input_tokens + output_tokens) / 1000 * 0.001))
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state.total_cost_cny += cost
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logger.info(f"[ask_node] Extracted params: {list(state.extracted_params.keys())}")
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logger.info("[ask_node] Extracted params: %s", list(state.extracted_params.keys()))
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return state
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except Exception as e:
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logger.exception(f"[ask_node] Unhandled exception: {e}")
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logger.exception("[ask_node] Unhandled exception: %s", e)
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state.error = {
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"code": "ASK_NODE_ERROR",
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"message": str(e),
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@@ -321,47 +295,34 @@ async def plan_node(state: AgentState) -> AgentState:
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"""
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Generate execution plan based on Profile SOP.
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Validates:
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- User role has permission to execute profile (RBAC)
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- All tools in plan are whitelisted
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Calls Claude with GENERATE_PLAN_TOOL to create step-by-step plan.
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Args:
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state: Current agent state
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Returns:
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Updated agent state with execution_plan populated
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Tool whitelist enforcement is delegated to ToolExecutor at execution time.
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"""
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try:
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from core.llm.claude_client import ClaudeClient
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from core.llm.prompt_builder import PromptBuilder
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from core.llm.prompt_builder import build_plan_message, build_system_messages
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from core.profile.registry import ProfileRegistry
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from core.tools.registry import ToolRegistry
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logger.info(f"[plan_node] trace_id={state.trace_id}")
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logger.info("[plan_node] trace_id=%s user_role=%s", state.trace_id, state.user_role)
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# Load profile
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profile_registry = ProfileRegistry()
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profile = profile_registry.get_by_type(state.profile_type)
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profile = ProfileRegistry.instance().get(state.profile_type)
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# RBAC check (simplified - would need proper RBAC implementation)
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# For now, just log the check
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logger.info(f"[plan_node] RBAC check: user_role={state.user_role}")
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# Build SOP text from profile description + workflow steps
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sop_text = profile.description + "\n\n工作流步骤:\n" + json.dumps(
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[s.model_dump() for s in profile.workflow_steps],
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ensure_ascii=False,
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indent=2,
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)
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# Validate tool whitelist
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tool_registry = ToolRegistry()
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tool_registry.validate_whitelist(profile.allowed_tools)
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# Build messages
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system_msgs = PromptBuilder.build_system_messages(profile)
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user_msg = PromptBuilder.build_plan_message(
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state.extracted_params, profile.sop if hasattr(profile, "sop") else ""
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system_msgs = build_system_messages(profile.model_dump())
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user_msg = build_plan_message(
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extracted_params=state.extracted_params,
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sop=sop_text,
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user_permissions={"role": state.user_role, "data_scope": state.data_scope},
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)
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# Call Claude
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client = ClaudeClient()
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response = client.call_with_tools(
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tool_input, cost = await client.call_with_tools(
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system_msgs=system_msgs,
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user_msg=user_msg,
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tools=[GENERATE_PLAN_TOOL],
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@@ -369,10 +330,7 @@ async def plan_node(state: AgentState) -> AgentState:
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trace_id=state.trace_id,
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)
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# Parse plan
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tool_input = response.get("tool_input", {})
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steps = tool_input.get("steps", [])
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if not steps:
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state.error = {
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"code": "PLAN_EMPTY",
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@@ -383,19 +341,13 @@ async def plan_node(state: AgentState) -> AgentState:
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return state
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state.execution_plan = steps
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state.total_cost_cny += cost.cost_cny
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# Update cost
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usage = response.get("usage", {})
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input_tokens = usage.get("input_tokens", 0)
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output_tokens = usage.get("output_tokens", 0)
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cost = Decimal(str((input_tokens + output_tokens) / 1000 * 0.001))
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state.total_cost_cny += cost
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logger.info(f"[plan_node] Generated {len(steps)} steps")
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logger.info("[plan_node] Generated %d steps", len(steps))
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return state
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except Exception as e:
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logger.exception(f"[plan_node] Unhandled exception: {e}")
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logger.exception("[plan_node] Unhandled exception: %s", e)
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state.error = {
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"code": "PLAN_NODE_ERROR",
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"message": str(e),
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@@ -412,70 +364,95 @@ async def act_node(state: AgentState) -> AgentState:
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Processes steps sequentially from current_step_index:
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1. Resolve parameter templates
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2. Check for approval requirements (interrupt if needed)
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2. Check for approval requirements (interrupt() if needed)
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3. Execute tool via ToolExecutor
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4. Store result summary in step_outputs
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4. Store result summary + citations in step_outputs
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5. Handle failures based on on_failure strategy
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Args:
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state: Current agent state
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Returns:
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Updated agent state
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"""
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try:
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from langgraph.types import interrupt
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from core.audit.logger import AuditLogger
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from core.profile.registry import ProfileRegistry
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from core.tools.base import ToolNotAllowedError
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from core.tools.executor import ToolExecutor
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from core.tools.registry import ToolRegistry
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from core.tools.registry import get_registry
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logger.info(f"[act_node] trace_id={state.trace_id} step_index={state.current_step_index}")
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logger.info(
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"[act_node] trace_id=%s step_index=%d",
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state.trace_id,
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state.current_step_index,
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)
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profile_registry = ProfileRegistry()
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profile = profile_registry.get_by_type(state.profile_type)
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# Initialize ToolExecutor with required dependencies
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tool_registry = ToolRegistry()
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audit_logger = AuditLogger() # TODO: Get from dependency injection
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profile = ProfileRegistry.instance().get(state.profile_type)
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tool_registry = get_registry()
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audit_logger = AuditLogger()
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tool_executor = ToolExecutor(registry=tool_registry, audit_logger=audit_logger)
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# Process steps from current index
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while state.current_step_index < len(state.execution_plan):
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step = state.execution_plan[state.current_step_index]
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step_id = step["step_id"]
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tool_name = step["tool_name"]
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logger.info(f"[act_node] Executing step {step_id}: {tool_name}")
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logger.info("[act_node] Executing step %s: %s", step_id, tool_name)
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# Resolve parameter templates
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resolved_params = _resolve_params(step["params"], state)
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resolved_params = _resolve_params(step.get("params", {}), state)
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# Check for approval requirement
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# ── Approval gate ──────────────────────────────────────────────────
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if step.get("approval_required", False):
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# Build approval payload
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state.pending_approval = {
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approval_payload = {
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"step_id": step_id,
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"tool_name": tool_name,
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"params": resolved_params,
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"reason": f"步骤 {step_id} 需要人工审批",
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}
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logger.info(f"[act_node] Approval required for step {step_id}, interrupting")
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# LangGraph will pause here (interrupt_after=["act"] in graph.compile)
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state.pending_approval = approval_payload
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logger.info("[act_node] Approval required for step %s, interrupting", step_id)
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# Pause until resumed with Command(resume=True/False)
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approved = interrupt(approval_payload)
|
||||
if not approved:
|
||||
state.error = {
|
||||
"code": "APPROVAL_REJECTED",
|
||||
"message": f"步骤 {step_id} 审批被拒绝",
|
||||
"node": "act",
|
||||
"trace_id": state.trace_id,
|
||||
}
|
||||
return state
|
||||
state.pending_approval = None
|
||||
|
||||
# ── Tool execution ─────────────────────────────────────────────────
|
||||
try:
|
||||
result = await tool_executor.execute_tool(
|
||||
tool_name=tool_name,
|
||||
raw_params=resolved_params,
|
||||
allowed_tools=profile.allowed_tools,
|
||||
user_id=state.user_id,
|
||||
tenant_id=state.tenant_id,
|
||||
data_scope=state.data_scope[0] if state.data_scope else "",
|
||||
trace_id=state.trace_id,
|
||||
step_id=step_id,
|
||||
)
|
||||
except ToolNotAllowedError as e:
|
||||
state.error = {
|
||||
"code": "TOOL_NOT_ALLOWED",
|
||||
"message": str(e),
|
||||
"tool": tool_name,
|
||||
"node": "act",
|
||||
"trace_id": state.trace_id,
|
||||
}
|
||||
logger.error("[act_node] Tool not allowed: %s", tool_name)
|
||||
return state
|
||||
|
||||
# Execute tool (async)
|
||||
result = await tool_executor.execute_tool(
|
||||
tool_name=tool_name,
|
||||
raw_params=resolved_params,
|
||||
allowed_tools=profile.allowed_tools,
|
||||
user_id=state.user_id,
|
||||
tenant_id=state.tenant_id,
|
||||
data_scope=state.data_scope[0] if state.data_scope else "", # noqa: E501
|
||||
# ── Audit every tool call (success or failure) ──────────────────────
|
||||
await audit_logger.write_tool_call(
|
||||
trace_id=state.trace_id,
|
||||
step_id=step_id,
|
||||
tool_name=tool_name,
|
||||
result=result,
|
||||
actor=state.user_id,
|
||||
tenant_id=state.tenant_id,
|
||||
)
|
||||
|
||||
# Handle failure
|
||||
if not result.success:
|
||||
on_failure = step.get("on_failure", "abort")
|
||||
if on_failure == "abort":
|
||||
@@ -487,29 +464,42 @@ async def act_node(state: AgentState) -> AgentState:
|
||||
"node": "act",
|
||||
"trace_id": state.trace_id,
|
||||
}
|
||||
logger.error(f"[act_node] Tool {tool_name} failed, aborting")
|
||||
logger.error("[act_node] Tool %s failed, aborting", tool_name)
|
||||
return state
|
||||
else:
|
||||
msg = f"[act_node] Tool {tool_name} failed, continuing (on_failure={on_failure})"
|
||||
logger.warning(msg) # noqa: E501
|
||||
logger.warning(f"[act_node] Tool {tool_name} failed, continuing (on_failure={on_failure})")
|
||||
logger.warning(
|
||||
"[act_node] Tool %s failed, continuing (on_failure=%s)",
|
||||
tool_name,
|
||||
on_failure,
|
||||
)
|
||||
|
||||
summary = (
|
||||
result.data.get("summary", str(result.data)[:200]) if result.data else "执行完成"
|
||||
)
|
||||
# ── Store result ───────────────────────────────────────────────────
|
||||
output_key = step["output_key"]
|
||||
summary = result.data.get("summary", str(result.data)[:200]) if result.data else "执行完成"
|
||||
data_ref = result.data.get("data_ref") if result.data else None
|
||||
summary = (
|
||||
result.data.get("summary", str(result.data)[:200])
|
||||
if isinstance(result.data, dict)
|
||||
else str(result.data)[:200] if result.data
|
||||
else "执行完成"
|
||||
)
|
||||
data_ref = result.data.get("data_ref") if isinstance(result.data, dict) else None
|
||||
state.add_step_output(output_key, summary, data_ref)
|
||||
|
||||
# Move to next step
|
||||
# Store citations for evidence scoring (mode="json" converts Decimal → str)
|
||||
if result.citations:
|
||||
state.step_outputs[output_key]["citations"] = [
|
||||
c.model_dump(mode="json") for c in result.citations
|
||||
]
|
||||
|
||||
state.current_step_index += 1
|
||||
|
||||
logger.info("[act_node] All steps completed")
|
||||
return state
|
||||
|
||||
except GraphInterrupt:
|
||||
# LangGraph interrupt must propagate — do not catch as an error.
|
||||
raise
|
||||
except Exception as e:
|
||||
logger.exception(f"[act_node] Unhandled exception: {e}")
|
||||
logger.exception("[act_node] Unhandled exception: %s", e)
|
||||
state.error = {
|
||||
"code": "ACT_NODE_ERROR",
|
||||
"message": str(e),
|
||||
@@ -524,49 +514,44 @@ async def verify_node(state: AgentState) -> AgentState:
|
||||
"""
|
||||
Assess evidence quality of execution results.
|
||||
|
||||
Collects citations from all steps and scores them using EvidenceScorer.
|
||||
Collects citations from all step outputs and scores them via EvidenceScorer.
|
||||
Sets evidence_score, evidence_level, and verified_citations.
|
||||
|
||||
Args:
|
||||
state: Current agent state
|
||||
|
||||
Returns:
|
||||
Updated agent state with evidence assessment
|
||||
"""
|
||||
try:
|
||||
from core.profile.registry import ProfileRegistry
|
||||
from core.verify.scorer import EvidenceScorer
|
||||
|
||||
logger.info(f"[verify_node] trace_id={state.trace_id}")
|
||||
logger.info("[verify_node] trace_id=%s", state.trace_id)
|
||||
|
||||
profile_registry = ProfileRegistry()
|
||||
profile = profile_registry.get_by_type(state.profile_type)
|
||||
profile = ProfileRegistry.instance().get(state.profile_type)
|
||||
|
||||
# Collect all citations from step outputs
|
||||
all_citations = []
|
||||
all_citations: list[dict[str, Any]] = []
|
||||
for step_output in state.step_outputs.values():
|
||||
if "citations" in step_output:
|
||||
if isinstance(step_output, dict) and "citations" in step_output:
|
||||
all_citations.extend(step_output["citations"])
|
||||
|
||||
# Score evidence
|
||||
scorer = EvidenceScorer()
|
||||
scorer_result = scorer.score(
|
||||
citations=all_citations,
|
||||
step_outputs=state.step_outputs,
|
||||
required_fields=profile.required_output_fields if hasattr(profile, "required_output_fields") else [],
|
||||
historical_accuracy=Decimal("0.8"), # Default, could be fetched from history
|
||||
required_fields=profile.required_output_fields,
|
||||
historical_accuracy=Decimal("0.8"),
|
||||
)
|
||||
|
||||
# Update state
|
||||
state.evidence_score = scorer_result.score
|
||||
state.evidence_level = scorer_result.level
|
||||
state.citations = [c.model_dump() for c in scorer_result.verified_citations]
|
||||
|
||||
logger.info(f"[verify_node] Evidence score={state.evidence_score}, level={state.evidence_level}")
|
||||
logger.info(
|
||||
"[verify_node] Evidence score=%s level=%s",
|
||||
state.evidence_score,
|
||||
state.evidence_level,
|
||||
)
|
||||
return state
|
||||
|
||||
except Exception as e:
|
||||
logger.exception(f"[verify_node] Unhandled exception: {e}")
|
||||
logger.exception("[verify_node] Unhandled exception: %s", e)
|
||||
state.error = {
|
||||
"code": "VERIFY_NODE_ERROR",
|
||||
"message": str(e),
|
||||
@@ -582,26 +567,22 @@ async def report_node(state: AgentState) -> AgentState:
|
||||
Generate final output based on evidence level.
|
||||
|
||||
If evidence is insufficient, sets output_type to "insufficient_data"
|
||||
and explains what's missing. Otherwise, calls Claude to generate
|
||||
and explains what's missing. Otherwise, calls Claude to generate
|
||||
a formatted report using the output template.
|
||||
|
||||
Args:
|
||||
state: Current agent state
|
||||
|
||||
Returns:
|
||||
Updated agent state with final_output
|
||||
"""
|
||||
try:
|
||||
from core.llm.claude_client import ClaudeClient
|
||||
from core.llm.prompt_builder import PromptBuilder
|
||||
from core.llm.prompt_builder import build_report_message, build_system_messages
|
||||
from core.profile.registry import ProfileRegistry
|
||||
|
||||
logger.info(f"[report_node] trace_id={state.trace_id} evidence_level={state.evidence_level}")
|
||||
logger.info(
|
||||
"[report_node] trace_id=%s evidence_level=%s",
|
||||
state.trace_id,
|
||||
state.evidence_level,
|
||||
)
|
||||
|
||||
profile_registry = ProfileRegistry()
|
||||
profile = profile_registry.get_by_type(state.profile_type)
|
||||
profile = ProfileRegistry.instance().get(state.profile_type)
|
||||
|
||||
# Check if evidence is insufficient
|
||||
if state.evidence_level == "insufficient":
|
||||
state.output_type = "insufficient_data"
|
||||
state.final_output = (
|
||||
@@ -611,40 +592,31 @@ async def report_node(state: AgentState) -> AgentState:
|
||||
logger.info("[report_node] Insufficient evidence, cannot generate report")
|
||||
return state
|
||||
|
||||
# Build report message
|
||||
system_msgs = PromptBuilder.build_system_messages(profile)
|
||||
user_msg = PromptBuilder.build_report_message(
|
||||
evidence_level=state.evidence_level,
|
||||
system_msgs = build_system_messages(profile.model_dump())
|
||||
user_msg = build_report_message(
|
||||
evidence_level=state.evidence_level or "sufficient",
|
||||
verified_data=state.step_outputs,
|
||||
citations=state.citations,
|
||||
template_hint=profile.output_template if hasattr(profile, "output_template") else "",
|
||||
template_hint=profile.output_template,
|
||||
)
|
||||
|
||||
# Call Claude
|
||||
client = ClaudeClient()
|
||||
response = client.call_text(
|
||||
text, cost = await client.call_text(
|
||||
system_msgs=system_msgs,
|
||||
user_msg=user_msg,
|
||||
max_tokens=4096,
|
||||
trace_id=state.trace_id,
|
||||
)
|
||||
|
||||
# Set output
|
||||
state.final_output = response.get("text", "")
|
||||
state.final_output = text
|
||||
state.output_type = "document" if profile.output_format == "docx" else "text"
|
||||
state.total_cost_cny += cost.cost_cny
|
||||
|
||||
# Update cost
|
||||
usage = response.get("usage", {})
|
||||
input_tokens = usage.get("input_tokens", 0)
|
||||
output_tokens = usage.get("output_tokens", 0)
|
||||
cost = Decimal(str((input_tokens + output_tokens) / 1000 * 0.001))
|
||||
state.total_cost_cny += cost
|
||||
|
||||
logger.info(f"[report_node] Report generated, length={len(state.final_output)}")
|
||||
logger.info("[report_node] Report generated, length=%d", len(state.final_output))
|
||||
return state
|
||||
|
||||
except Exception as e:
|
||||
logger.exception(f"[report_node] Unhandled exception: {e}")
|
||||
logger.exception("[report_node] Unhandled exception: %s", e)
|
||||
state.error = {
|
||||
"code": "REPORT_NODE_ERROR",
|
||||
"message": str(e),
|
||||
|
||||
+431
-115
@@ -1,57 +1,193 @@
|
||||
"""
|
||||
Prompt builder for Claude API calls.
|
||||
|
||||
This is a placeholder version with basic prompts.
|
||||
Full prompt text will be added in P10 phase.
|
||||
Implements the full L0-L2 prompt system:
|
||||
L0 – Global system prompt shared by all nodes (with Prompt Caching)
|
||||
L1-A – Ask node: parameter extraction + clarification request format
|
||||
L1-B – Plan node: workflow planning
|
||||
L1-C – Act node: tool execution + approval request format
|
||||
L1-D – Verify node: evidence scoring instructions
|
||||
L1-E – Report node: three-tier evidence strategy output
|
||||
L2 – Profile SOP dynamic injection template
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import logging
|
||||
from typing import Any
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════
|
||||
# System Prompt Base
|
||||
# L0 — Global System Prompt (~800 tokens, Prompt Caching target)
|
||||
# ═══════════════════════════════════════════════════════════════
|
||||
|
||||
_SYSTEM_BASE = """
|
||||
你是企业智能体平台核心助手。在严格治理框架内完成预售方案、安全分析、知识问答任务。
|
||||
_SYSTEM_BASE = """你是企业智能体平台的核心 AI 助手，模型标识 claude-sonnet-4-6-20260217。
|
||||
职责：在严格治理框架内完成预售方案生成、安全事件分析、知识问答三大核心场景。
|
||||
|
||||
【核心约束】
|
||||
1. 只调用当前上下文中显式声明的工具
|
||||
2. risk_level=high 的操作必须等待审批后执行
|
||||
3. 只访问 X-Data-Scope 授权的数据范围
|
||||
4. 敏感信息（手机号/身份证/密码/API Key）必须脱敏后输出
|
||||
5. 所有事实陈述必须附带来源引用 [来源:X,章节,相关度]
|
||||
6. 无法引用来源的内容标注 ⚠️[未经验证]
|
||||
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
|
||||
不可违反的治理约束（硬规则）
|
||||
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
|
||||
|
||||
【输出规范】
|
||||
使用 XML 标签包裹语义块；引用格式：[来源:{source},{section},{score:.2f}]
|
||||
置信度 ≥0.85 正常输出 | 0.60-0.85 加⚠️ | <0.60 拒绝输出
|
||||
"""
|
||||
1. 工具白名单：只能调用 <tools> 中显式声明的工具。
|
||||
未授权操作 → 回复"该操作不在授权范围内"并终止当前步骤。
|
||||
|
||||
2. 高风险写操作审批：工具声明中标注 risk_level=high 或
|
||||
side_effects 含 write/delete/send 的操作，必须输出
|
||||
<approval_request> 块等待人工确认，不得自行执行。
|
||||
|
||||
3. 数据权限边界：只能访问请求头 X-Data-Scope 授权的数据范围。
|
||||
工具返回超出权限数据时，立即停止并报告权限异常。
|
||||
|
||||
4. 敏感信息处理：不得在输出中展示完整手机号、身份证号、银行账号、
|
||||
密码、API Key。脱敏规则：
|
||||
- 手机号 → 138**8888（保留前3后4）
|
||||
- 身份证 → 1970****01**（保留出生年份，其余掩码）
|
||||
- 密码/Key → [REDACTED]
|
||||
|
||||
5. 引用强制性：所有陈述性事实必须附带来源引用：
|
||||
格式：[来源:{source_name},{section},{relevance_score:.2f}]
|
||||
无法引用来源 → 在前面标注 ⚠️[未经验证]
|
||||
|
||||
6. 幻觉自检：生成最终回答前，逐条检查每个关键声明是否有
|
||||
工具返回数据支持。无数据依据 → 删除或标注为 [推断，非验证数据]
|
||||
|
||||
7. 审计可追溯：每一个工具调用结果都被记录到审计日志，
|
||||
不可跳过或伪造工具调用结果。
|
||||
|
||||
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
|
||||
输出格式规范
|
||||
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
|
||||
- 结构化输出：用 XML 标签包裹不同语义块
|
||||
- 引用格式：[来源:{source_name},{section},{relevance_score:.2f}]
|
||||
- 置信度策略：
|
||||
≥0.85 → 正常输出
|
||||
0.60–0.85 → 加 ⚠️ 警告
|
||||
<0.60 → 拒绝输出，要求补充数据
|
||||
|
||||
标准输出结构：
|
||||
<answer>
|
||||
<content>正式回答内容</content>
|
||||
<citations>引用列表</citations>
|
||||
<confidence>综合置信度分数和等级</confidence>
|
||||
<next_steps>建议的下一步</next_steps>
|
||||
</answer>
|
||||
|
||||
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
|
||||
每次输出前自检清单
|
||||
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
|
||||
□ 所有引用可追溯到实际检索结果
|
||||
□ 没有未经验证的数值或统计数据
|
||||
□ 高风险操作已标注等待审批
|
||||
□ 专业术语无歧义"""
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════
|
||||
# score_evidence Tool Schema (inline, used by Verify node)
|
||||
# ═══════════════════════════════════════════════════════════════
|
||||
|
||||
_SCORE_EVIDENCE_TOOL: dict[str, Any] = {
|
||||
"name": "score_evidence",
|
||||
"description": (
|
||||
"对智能体执行结果进行证据质量评分。"
|
||||
"综合检索质量、完整性、历史准确率三个维度，"
|
||||
"返回结构化评分结果，供 Verify 节点判断是否进入报告生成。"
|
||||
),
|
||||
"input_schema": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"retrieval_score": {
|
||||
"type": "number",
|
||||
"minimum": 0,
|
||||
"maximum": 1,
|
||||
"description": "检索相关度评分（0-1）",
|
||||
},
|
||||
"completeness_score": {
|
||||
"type": "number",
|
||||
"minimum": 0,
|
||||
"maximum": 1,
|
||||
"description": "必填字段覆盖率评分（0-1）",
|
||||
},
|
||||
"historical_accuracy": {
|
||||
"type": "number",
|
||||
"minimum": 0,
|
||||
"maximum": 1,
|
||||
"description": "历史准确率基准（0-1）",
|
||||
},
|
||||
"field_level_issues": {
|
||||
"type": "array",
|
||||
"items": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"field": {"type": "string"},
|
||||
"issue": {"type": "string"},
|
||||
"severity": {"type": "string", "enum": ["low", "medium", "high"]},
|
||||
},
|
||||
"required": ["field", "issue", "severity"],
|
||||
},
|
||||
"description": "字段级问题列表",
|
||||
},
|
||||
"citations_verified": {
|
||||
"type": "array",
|
||||
"items": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"source": {"type": "string"},
|
||||
"verified": {"type": "boolean"},
|
||||
"relevance": {"type": "number"},
|
||||
},
|
||||
"required": ["source", "verified"],
|
||||
},
|
||||
"description": "已验证的引用列表",
|
||||
},
|
||||
"missing_data_fields": {
|
||||
"type": "array",
|
||||
"items": {"type": "string"},
|
||||
"description": "缺失的必填字段名称列表",
|
||||
},
|
||||
"improvement_suggestions": {
|
||||
"type": "array",
|
||||
"items": {"type": "string"},
|
||||
"description": "改进建议列表",
|
||||
},
|
||||
},
|
||||
"required": ["retrieval_score", "completeness_score", "historical_accuracy"],
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════
|
||||
# Helper Functions
|
||||
# L2 — Profile SOP Dynamic Injection Helper
|
||||
# ═══════════════════════════════════════════════════════════════
|
||||
|
||||
|
||||
def _build_profile_context(profile: dict[str, Any]) -> str:
|
||||
"""Build profile-specific context for system message."""
|
||||
"""Build L2 profile-specific context block for system message injection."""
|
||||
profile_type = profile.get("profile_type", "unknown")
|
||||
allowed_tools = profile.get("allowed_tools", [])
|
||||
output_template = profile.get("output_template", "")
|
||||
sop = profile.get("sop", "")
|
||||
|
||||
context = f"""
|
||||
【当前 Profile】
|
||||
类型：{profile_type}
|
||||
允许工具：{", ".join(allowed_tools)}
|
||||
"""
|
||||
lines = [
|
||||
"━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━",
|
||||
"当前 Profile（L2 动态注入）",
|
||||
"━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━",
|
||||
f"类型：{profile_type}",
|
||||
f"允许工具：{', '.join(allowed_tools) if allowed_tools else '（继承全局白名单）'}",
|
||||
]
|
||||
|
||||
if sop:
|
||||
lines += ["", "SOP 规程：", sop]
|
||||
|
||||
if output_template:
|
||||
context += f"\n输出模板：\n{output_template}\n"
|
||||
lines += ["", "输出模板：", output_template]
|
||||
|
||||
return context
|
||||
lines += [
|
||||
"",
|
||||
"Profile 约束优先级高于全局默认，低于硬规则。",
|
||||
]
|
||||
|
||||
return "\n".join(lines)
|
||||
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════
|
||||
@@ -61,93 +197,142 @@ def _build_profile_context(profile: dict[str, Any]) -> str:
|
||||
|
||||
def build_system_messages(profile: dict[str, Any] | None = None) -> list[dict[str, Any]]:
|
||||
"""
|
||||
Build system messages with optional prompt caching.
|
||||
Build system message blocks with Prompt Caching (L0 + optional L2).
|
||||
|
||||
Args:
|
||||
profile: Optional profile configuration
|
||||
profile: Optional profile configuration dict.
|
||||
|
||||
Returns:
|
||||
List of system message blocks with cache_control if supported
|
||||
List of system message dicts with ``type`` and ``text`` keys.
|
||||
``cache_control`` is added when supported by the SDK.
|
||||
"""
|
||||
blocks = [{"type": "text", "text": _SYSTEM_BASE}]
|
||||
blocks: list[dict[str, Any]] = [{"type": "text", "text": _SYSTEM_BASE}]
|
||||
|
||||
if profile:
|
||||
blocks.append({"type": "text", "text": _build_profile_context(profile)})
|
||||
|
||||
# Try to add cache_control; if SDK doesn't support, ignore
|
||||
try:
|
||||
for block in blocks:
|
||||
block["cache_control"] = {"type": "ephemeral"} # type: ignore[assignment]
|
||||
except Exception:
|
||||
# SDK doesn't support cache_control, continue without caching
|
||||
pass
|
||||
# Attach cache_control to signal Prompt Caching intent.
|
||||
# The SDK silently ignores unknown keys on older versions.
|
||||
for block in blocks:
|
||||
block["cache_control"] = {"type": "ephemeral"}
|
||||
|
||||
return blocks
|
||||
|
||||
|
||||
# ─── L1-A Ask Node ───────────────────────────────────────────
|
||||
|
||||
|
||||
def build_ask_user_message(user_input: str, profile_schema: dict[str, Any]) -> str:
|
||||
"""
|
||||
Build message for parameter extraction (ask node).
|
||||
L1-A: Parameter extraction prompt.
|
||||
|
||||
Supports two schema formats:
|
||||
- New format (preferred): {"input_fields": [{"name":…,"description":…,"required":bool}]}
|
||||
- Legacy format: {"required": […], "properties": {…}}
|
||||
|
||||
Args:
|
||||
user_input: Raw user input
|
||||
profile_schema: Profile input schema
|
||||
user_input: Raw user input text.
|
||||
profile_schema: Profile input schema in either supported format.
|
||||
|
||||
Returns:
|
||||
Formatted prompt for parameter extraction
|
||||
Formatted prompt string for the Ask node.
|
||||
"""
|
||||
# Placeholder prompt - will be enhanced in P10
|
||||
required_fields = profile_schema.get("required", [])
|
||||
optional_fields = [
|
||||
f for f in profile_schema.get("properties", {}) if f not in required_fields
|
||||
]
|
||||
# ── Normalise schema to field list ──
|
||||
if "input_fields" in profile_schema:
|
||||
fields = profile_schema["input_fields"]
|
||||
field_lines = "\n".join(
|
||||
"- {name}（{desc}）{marker}".format(
|
||||
name=f["name"],
|
||||
desc=f.get("description", ""),
|
||||
marker="[必填]" if f.get("required") else "[可选]",
|
||||
)
|
||||
for f in fields
|
||||
)
|
||||
else:
|
||||
# Legacy JSON-Schema style
|
||||
required_names: list[str] = profile_schema.get("required", [])
|
||||
properties: dict[str, Any] = profile_schema.get("properties", {})
|
||||
all_names = list(properties.keys()) if properties else required_names
|
||||
field_lines = "\n".join(
|
||||
"- {name}（{desc}）{marker}".format(
|
||||
name=name,
|
||||
desc=properties.get(name, {}).get("description", ""),
|
||||
marker="[必填]" if name in required_names else "[可选]",
|
||||
)
|
||||
for name in all_names
|
||||
)
|
||||
|
||||
prompt = f"""
|
||||
<task>从用户输入中提取结构化参数</task>
|
||||
return f"""
|
||||
当前节点：ASK（参数提取）
|
||||
职责：从用户输入提取结构化参数，或识别信息不足请求澄清。
|
||||
|
||||
<user_input>
|
||||
{user_input}
|
||||
</user_input>
|
||||
|
||||
<schema>
|
||||
必填字段：{", ".join(required_fields) if required_fields else "无"}
|
||||
可选字段：{", ".join(optional_fields) if optional_fields else "无"}
|
||||
</schema>
|
||||
<required_fields>
|
||||
当前任务类型需要以下字段：
|
||||
{field_lines}
|
||||
</required_fields>
|
||||
|
||||
请使用 extract_user_params 工具提取参数。
|
||||
请调用 extract_user_params 工具提取以上字段。
|
||||
对于输入中未明确提及的必填字段，将 confidence 设为 0、value 设为 null，
|
||||
并在 missing_required_fields 中列出。
|
||||
不得猜测或推断用户未明确提供的信息。
|
||||
"""
|
||||
return prompt
|
||||
|
||||
|
||||
# ─── L1-B Plan Node ──────────────────────────────────────────
|
||||
|
||||
|
||||
def build_plan_message(
|
||||
extracted_params: dict[str, Any], sop: str, user_permissions: dict[str, Any] | None = None
|
||||
extracted_params: dict[str, Any],
|
||||
sop: str,
|
||||
user_permissions: dict[str, Any] | None = None,
|
||||
) -> str:
|
||||
"""
|
||||
Build message for plan generation (plan node).
|
||||
L1-B: Workflow planning prompt.
|
||||
|
||||
Args:
|
||||
extracted_params: Extracted parameters from ask node
|
||||
sop: Standard Operating Procedure from profile
|
||||
user_permissions: Optional user permissions
|
||||
extracted_params: Structured parameters from the Ask node.
|
||||
sop: Standard Operating Procedure text from the profile.
|
||||
user_permissions: Optional user permission scope dict.
|
||||
|
||||
Returns:
|
||||
Formatted prompt for plan generation
|
||||
Formatted prompt string for the Plan node.
|
||||
"""
|
||||
# Placeholder prompt - will be enhanced in P10
|
||||
prompt = f"""
|
||||
<task>基于 SOP 生成执行计划</task>
|
||||
perms_block = ""
|
||||
if user_permissions:
|
||||
perms_block = f"""
|
||||
<user_permissions>
|
||||
{json.dumps(user_permissions, ensure_ascii=False, indent=2)}
|
||||
</user_permissions>
|
||||
"""
|
||||
|
||||
return f"""
|
||||
当前节点：PLAN（工作流规划）
|
||||
职责：基于 SOP 和已提取参数，生成具体可执行的步骤序列。
|
||||
|
||||
<extracted_params>
|
||||
{extracted_params}
|
||||
{json.dumps(extracted_params, ensure_ascii=False, indent=2)}
|
||||
</extracted_params>
|
||||
|
||||
<sop>
|
||||
{sop}
|
||||
</sop>
|
||||
{perms_block}
|
||||
规划约束：
|
||||
1. 每个步骤必须包含：step_id、tool_name、risk_level、approval_required、depends_on
|
||||
2. risk_level=high 的步骤必须将 approval_required 设为 true
|
||||
3. 步骤顺序需满足数据依赖关系，并行步骤用相同 depends_on 层级标注
|
||||
4. 不得规划工具白名单以外的步骤
|
||||
5. 整体步骤数不超过 SOP 定义的最大步骤数
|
||||
|
||||
请使用 generate_execution_plan 工具生成逐步执行计划。
|
||||
请使用 generate_execution_plan 工具返回结构化执行计划。
|
||||
"""
|
||||
return prompt
|
||||
|
||||
|
||||
# ─── L1-C Act Node ───────────────────────────────────────────
|
||||
|
||||
|
||||
def build_act_step_message(
|
||||
@@ -156,32 +341,67 @@ def build_act_step_message(
|
||||
previous_results_summary: str,
|
||||
) -> str:
|
||||
"""
|
||||
Build message for step execution (act node).
|
||||
L1-C: Step execution prompt with approval-gate instructions.
|
||||
|
||||
Args:
|
||||
step: Current step definition
|
||||
resolved_params: Resolved parameters
|
||||
previous_results_summary: Summary of previous steps
|
||||
step: Current step definition dict (step_id, tool_name, risk_level, …).
|
||||
resolved_params: Desensitised resolved parameters for this step.
|
||||
previous_results_summary: Compressed summary of prior step outputs.
|
||||
|
||||
Returns:
|
||||
Formatted prompt for step execution
|
||||
Formatted prompt string for the Act node.
|
||||
"""
|
||||
# Placeholder - act node typically doesn't need LLM calls
|
||||
# This is here for future extensions
|
||||
prompt = f"""
|
||||
<step>
|
||||
{step}
|
||||
</step>
|
||||
step_id = step.get("step_id", "unknown")
|
||||
tool_name = step.get("tool_name", "unknown")
|
||||
risk_level = step.get("risk_level", "low")
|
||||
approval_required = step.get("approval_required", False)
|
||||
|
||||
<params>
|
||||
{resolved_params}
|
||||
</params>
|
||||
return f"""
|
||||
当前节点：ACT（工具执行）
|
||||
职责：按计划执行单个步骤，高风险操作须先请求审批。
|
||||
|
||||
<previous_results>
|
||||
{previous_results_summary}
|
||||
</previous_results>
|
||||
<step_meta>
|
||||
<step_id>{step_id}</step_id>
|
||||
<tool_name>{tool_name}</tool_name>
|
||||
<risk_level>{risk_level}</risk_level>
|
||||
<approval_required>{str(approval_required).lower()}</approval_required>
|
||||
</step_meta>
|
||||
|
||||
<resolved_params>
|
||||
{json.dumps(resolved_params, ensure_ascii=False, indent=2)}
|
||||
</resolved_params>
|
||||
|
||||
<context>
|
||||
{previous_results_summary if previous_results_summary else "（无前序步骤结果）"}
|
||||
</context>
|
||||
|
||||
执行指令：
|
||||
|
||||
若 approval_required=true → 先输出 <approval_request> 块，格式：
|
||||
<approval_request>
|
||||
<step_id>{step_id}</step_id>
|
||||
<tool_name>{tool_name}</tool_name>
|
||||
<description>具体操作说明（自然语言，清晰描述影响范围）</description>
|
||||
<affected_resources>受影响资源列表</affected_resources>
|
||||
<risk_level>{risk_level}</risk_level>
|
||||
<params_preview>脱敏后参数预览</params_preview>
|
||||
<required_approvers>需要审批的角色</required_approvers>
|
||||
</approval_request>
|
||||
|
||||
等待审批后才能调用工具，不得跳过。
|
||||
|
||||
调用完成后输出 <step_result> 块：
|
||||
<step_result>
|
||||
<step_id>{step_id}</step_id>
|
||||
<tool_name>{tool_name}</tool_name>
|
||||
<status>success|failed|skipped|pending_approval</status>
|
||||
<output>工具返回摘要</output>
|
||||
<citations>本步骤引用列表</citations>
|
||||
</step_result>
|
||||
"""
|
||||
return prompt
|
||||
|
||||
|
||||
# ─── L1-D Verify Node ────────────────────────────────────────
|
||||
|
||||
|
||||
def build_verify_message(
|
||||
@@ -190,35 +410,67 @@ def build_verify_message(
|
||||
historical_accuracy: float,
|
||||
) -> str:
|
||||
"""
|
||||
Build message for evidence verification (verify node).
|
||||
L1-D: Evidence quality scoring prompt.
|
||||
|
||||
Scoring formula:
|
||||
score = 0.4 * retrieval + 0.3 * completeness + 0.3 * history
|
||||
|
||||
Thresholds:
|
||||
≥ 0.80 → sufficient (proceed to Report)
|
||||
0.60–0.79 → limited (proceed with warnings)
|
||||
< 0.60 → insufficient (halt, request more data)
|
||||
|
||||
Args:
|
||||
step_outputs: Outputs from all executed steps
|
||||
required_fields: Required output fields
|
||||
historical_accuracy: Historical accuracy score
|
||||
step_outputs: Outputs dict from all executed steps.
|
||||
required_fields: List of required output field names.
|
||||
historical_accuracy: Historical accuracy baseline (0-1).
|
||||
|
||||
Returns:
|
||||
Formatted prompt for verification
|
||||
Formatted prompt string for the Verify node.
|
||||
"""
|
||||
# Placeholder prompt - will be enhanced in P10
|
||||
prompt = f"""
|
||||
<task>评估证据质量</task>
|
||||
tool_schema_json = json.dumps(_SCORE_EVIDENCE_TOOL, ensure_ascii=False, indent=2)
|
||||
|
||||
return f"""
|
||||
当前节点：VERIFY（证据评分）
|
||||
职责：对所有步骤输出进行证据质量评估，决定报告生成策略。
|
||||
|
||||
<step_outputs>
|
||||
{step_outputs}
|
||||
{json.dumps(step_outputs, ensure_ascii=False, indent=2)}
|
||||
</step_outputs>
|
||||
|
||||
<required_fields>
|
||||
{", ".join(required_fields)}
|
||||
{chr(10).join(f"- {f}" for f in required_fields)}
|
||||
</required_fields>
|
||||
|
||||
<historical_accuracy>
|
||||
{historical_accuracy:.2f}
|
||||
</historical_accuracy>
|
||||
<historical_accuracy>{historical_accuracy:.2f}</historical_accuracy>
|
||||
|
||||
请评估数据完整性和可信度。
|
||||
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
|
||||
评分维度与权重
|
||||
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
|
||||
1. 检索质量（40%）：检查每条引用与问题的相关度，计算加权平均值
|
||||
2. 完整性（30%）：已填充必填字段数 ÷ 必填字段总数
|
||||
3. 历史准确率（30%）：使用传入的 historical_accuracy 值 {historical_accuracy:.2f}
|
||||
|
||||
综合公式：score = 0.4×retrieval + 0.3×completeness + 0.3×{historical_accuracy:.2f}
|
||||
|
||||
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
|
||||
阈值判断
|
||||
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
|
||||
≥ 0.80 → evidence_level = "sufficient" → 进入正常报告生成
|
||||
0.60–0.79 → evidence_level = "limited" → 进入带警告的报告生成
|
||||
< 0.60 → evidence_level = "insufficient" → 终止，输出数据不足说明
|
||||
|
||||
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
|
||||
工具定义（内联）
|
||||
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
|
||||
{tool_schema_json}
|
||||
|
||||
请调用 score_evidence 工具，返回包含所有维度得分、字段级问题、
|
||||
已验证引用、缺失字段和改进建议的结构化评分结果。
|
||||
"""
|
||||
return prompt
|
||||
|
||||
|
||||
# ─── L1-E Report Node ────────────────────────────────────────
|
||||
|
||||
|
||||
def build_report_message(
|
||||
@@ -228,39 +480,103 @@ def build_report_message(
|
||||
template_hint: str,
|
||||
) -> str:
|
||||
"""
|
||||
Build message for report generation (report node).
|
||||
L1-E: Report generation prompt with three-tier evidence strategy.
|
||||
|
||||
Tiers:
|
||||
sufficient – full professional report
|
||||
limited – report with ⚠️ warnings + data-limitation appendix
|
||||
insufficient – <data_insufficient> block with remediation guidance
|
||||
|
||||
Args:
|
||||
evidence_level: Evidence quality level (sufficient/limited/insufficient)
|
||||
verified_data: Verified step outputs
|
||||
citations: Citation list
|
||||
template_hint: Output template hint
|
||||
evidence_level: "sufficient" | "limited" | "insufficient"
|
||||
verified_data: Verified outputs from all executed steps.
|
||||
citations: List of citation dicts with ``source`` and ``text`` keys.
|
||||
template_hint: Output structure hint from the profile.
|
||||
|
||||
Returns:
|
||||
Formatted prompt for report generation
|
||||
Formatted prompt string for the Report node.
|
||||
"""
|
||||
# Placeholder prompt - will be enhanced in P10
|
||||
citations_text = "\n".join(
|
||||
[f"- {c.get('source', 'unknown')}: {c.get('text', '')}" for c in citations]
|
||||
citations_lines = "\n".join(
|
||||
f"- [{c.get('source', 'unknown')}] {c.get('text', '')}" for c in citations
|
||||
)
|
||||
|
||||
prompt = f"""
|
||||
<task>生成最终报告</task>
|
||||
verified_data_json = json.dumps(verified_data, ensure_ascii=False, indent=2)
|
||||
|
||||
<evidence_level>{evidence_level}</evidence_level>
|
||||
# ── Tier-specific instructions ──
|
||||
if evidence_level == "sufficient":
|
||||
tier_instruction = """
|
||||
证据等级：SUFFICIENT（充分）
|
||||
生成策略：正常生成完整专业报告。
|
||||
|
||||
要求：
|
||||
- 报告结构完整，涵盖摘要、正文、结论、建议
|
||||
- 每个关键声明后立即附引用标记，不统一放末尾
|
||||
- 使用专业技术语言，中文为主，技术术语保留英文并括号注释
|
||||
- 禁止生成未经工具验证的统计数字
|
||||
- 禁止使用"可能"/"据悉"替代引用
|
||||
- 报告末尾必须有引用汇总表
|
||||
"""
|
||||
elif evidence_level == "limited":
|
||||
tier_instruction = """
|
||||
证据等级：LIMITED（有限）
|
||||
生成策略：生成报告，但在不确定处加 ⚠️ 警告，末尾附数据局限性说明。
|
||||
|
||||
要求：
|
||||
- 对来源不足或相关度低的陈述，前置 ⚠️[数据有限，仅供参考]
|
||||
- 数值类数据如无可靠来源，标注为 ⚠️[估算值，非实测数据]
|
||||
- 报告末尾必须附"数据局限性"章节，列出：
|
||||
* 缺失的关键数据源
|
||||
* 受影响的结论范围
|
||||
* 建议补充的信息类型
|
||||
- 即便数据有限，也必须附引用汇总表（含置信度）
|
||||
"""
|
||||
else:
|
||||
# insufficient
|
||||
tier_instruction = """
|
||||
证据等级：INSUFFICIENT（不足）
|
||||
生成策略：终止报告生成，输出数据不足说明块。
|
||||
|
||||
直接输出以下格式，不得生成推断性报告内容：
|
||||
|
||||
<data_insufficient>
|
||||
<summary>当前数据无法支撑可靠报告生成</summary>
|
||||
<missing_data>
|
||||
缺少以下关键数据：
|
||||
（逐条列出缺少的字段或来源，每条说明其对报告质量的影响）
|
||||
</missing_data>
|
||||
<remediation>
|
||||
补充方式：
|
||||
（逐条说明如何获取缺少的数据，例如：调用哪个工具、联系哪个数据源）
|
||||
</remediation>
|
||||
<partial_findings>
|
||||
（如有任何可信的部分发现，在此列出，并明确标注其局限性）
|
||||
</partial_findings>
|
||||
</data_insufficient>
|
||||
"""
|
||||
|
||||
return f"""
|
||||
当前节点：REPORT（报告生成）
|
||||
职责：基于验证后的数据，按三级证据策略生成最终输出。
|
||||
证据等级（evidence_level）：{evidence_level}
|
||||
|
||||
{tier_instruction}
|
||||
|
||||
<verified_data>
|
||||
{verified_data}
|
||||
{verified_data_json}
|
||||
</verified_data>
|
||||
|
||||
<citations>
|
||||
{citations_text}
|
||||
{citations_lines if citations_lines else "（无可用引用）"}
|
||||
</citations>
|
||||
|
||||
<template_hint>
|
||||
{template_hint}
|
||||
{template_hint if template_hint else "（使用默认报告模板）"}
|
||||
</template_hint>
|
||||
|
||||
请基于验证数据生成结构化报告，所有事实陈述必须附带引用。
|
||||
通用约束（所有等级适用）：
|
||||
- 每个关键声明后立即附引用标记，不统一放末尾
|
||||
- 报告末尾必须有引用汇总表
|
||||
- 禁止生成未经工具验证的统计数字
|
||||
- 禁止使用"可能"/"据悉"替代引用
|
||||
- 语言：中文，技术术语保留英文并括号注释
|
||||
"""
|
||||
return prompt
|
||||
|
||||
@@ -0,0 +1,79 @@
|
||||
"""
|
||||
Profile YAML loader with Pydantic validation.
|
||||
|
||||
Reads profiles/{profile_type}/profile.yaml, validates via Profile.model_validate,
|
||||
and raises ProfileValidationError with field-level detail on failure.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
from pathlib import Path
|
||||
|
||||
import yaml
|
||||
from pydantic import ValidationError
|
||||
|
||||
from core.profile.schema import Profile
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# Profiles root is three parents up from this file:
|
||||
# core/profile/loader.py → core/profile/ → core/ → <project_root>/
|
||||
PROFILES_ROOT = Path(__file__).parent.parent.parent / "profiles"
|
||||
|
||||
|
||||
class ProfileValidationError(Exception):
|
||||
"""Raised when a profile YAML fails to load or validate."""
|
||||
|
||||
|
||||
def load_profile(profile_type: str) -> Profile:
|
||||
"""Load and validate a profile from disk.
|
||||
|
||||
Args:
|
||||
profile_type: Subdirectory name under ``profiles/``
|
||||
(e.g. "presales", "security_analysis").
|
||||
|
||||
Returns:
|
||||
Validated :class:`Profile` instance.
|
||||
|
||||
Raises:
|
||||
ProfileValidationError: If the file is missing, unparseable,
|
||||
or fails Pydantic validation.
|
||||
"""
|
||||
profile_path = PROFILES_ROOT / profile_type / "profile.yaml"
|
||||
|
||||
if not profile_path.exists():
|
||||
raise ProfileValidationError(
|
||||
f"Profile file not found: {profile_path}. "
|
||||
f"Expected profiles/{profile_type}/profile.yaml relative to project root."
|
||||
)
|
||||
|
||||
try:
|
||||
with profile_path.open("r", encoding="utf-8") as fh:
|
||||
raw: object = yaml.safe_load(fh)
|
||||
except yaml.YAMLError as exc:
|
||||
raise ProfileValidationError(
|
||||
f"YAML parse error in '{profile_path}': {exc}"
|
||||
) from exc
|
||||
|
||||
if not isinstance(raw, dict):
|
||||
raise ProfileValidationError(
|
||||
f"Profile file '{profile_path}' must contain a YAML mapping, "
|
||||
f"got {type(raw).__name__}"
|
||||
)
|
||||
|
||||
try:
|
||||
profile = Profile.model_validate(raw)
|
||||
except ValidationError as exc:
|
||||
# Re-raise with a human-readable summary of field errors.
|
||||
error_lines = [
|
||||
f" [{'.'.join(str(loc) for loc in err['loc'])}] {err['msg']}"
|
||||
for err in exc.errors()
|
||||
]
|
||||
detail = "\n".join(error_lines)
|
||||
raise ProfileValidationError(
|
||||
f"Profile validation failed for '{profile_type}':\n{detail}"
|
||||
) from exc
|
||||
|
||||
logger.debug("Loaded profile '%s' v%s", profile.profile_type, profile.version)
|
||||
return profile
|
||||
@@ -0,0 +1,131 @@
|
||||
"""
|
||||
Profile Registry — thread-safe singleton with in-memory LRU-style cache.
|
||||
|
||||
Usage:
|
||||
registry = ProfileRegistry.instance()
|
||||
profile = registry.get("presales")
|
||||
registry.reload("presales") # hot-reload after YAML change
|
||||
registry.validate_all() # CI/startup gate
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
import threading
|
||||
|
||||
from core.profile.loader import PROFILES_ROOT, ProfileValidationError, load_profile
|
||||
from core.profile.schema import Profile
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class ProfileRegistry:
|
||||
"""Thread-safe singleton registry for Profile objects.
|
||||
|
||||
Profiles are loaded lazily on first access and cached in memory.
|
||||
``reload`` evicts a single entry; ``validate_all`` loads every profile
|
||||
found under ``profiles/`` to surface YAML errors early.
|
||||
"""
|
||||
|
||||
_instance: ProfileRegistry | None = None
|
||||
_lock: threading.Lock = threading.Lock()
|
||||
# Per-instance attributes declared here so mypy can see them.
|
||||
_cache: dict[str, Profile]
|
||||
_cache_lock: threading.Lock
|
||||
|
||||
# ── Singleton construction ──────────────────────────────────
|
||||
|
||||
def __new__(cls) -> ProfileRegistry:
|
||||
if cls._instance is None:
|
||||
with cls._lock:
|
||||
if cls._instance is None:
|
||||
inst = super().__new__(cls)
|
||||
inst._cache = {}
|
||||
inst._cache_lock = threading.Lock()
|
||||
cls._instance = inst
|
||||
return cls._instance
|
||||
|
||||
@classmethod
|
||||
def instance(cls) -> ProfileRegistry:
|
||||
"""Return the singleton instance."""
|
||||
return cls()
|
||||
|
||||
# ── Public API ──────────────────────────────────────────────
|
||||
|
||||
def get(self, profile_type: str) -> Profile:
|
||||
"""Return a Profile, loading from disk on first access.
|
||||
|
||||
Args:
|
||||
profile_type: Profile subdirectory name.
|
||||
|
||||
Returns:
|
||||
Validated :class:`Profile`.
|
||||
|
||||
Raises:
|
||||
ProfileValidationError: If the profile cannot be loaded.
|
||||
"""
|
||||
with self._cache_lock:
|
||||
if profile_type not in self._cache:
|
||||
logger.info("Loading profile '%s' into registry cache", profile_type)
|
||||
self._cache[profile_type] = load_profile(profile_type)
|
||||
return self._cache[profile_type]
|
||||
|
||||
def reload(self, profile_type: str) -> Profile:
|
||||
"""Evict cache and reload a profile from disk (hot-update support).
|
||||
|
||||
Args:
|
||||
profile_type: Profile subdirectory name to reload.
|
||||
|
||||
Returns:
|
||||
Freshly loaded :class:`Profile`.
|
||||
"""
|
||||
with self._cache_lock:
|
||||
self._cache.pop(profile_type, None)
|
||||
|
||||
logger.info("Reloading profile '%s'", profile_type)
|
||||
return self.get(profile_type)
|
||||
|
||||
def validate_all(self) -> dict[str, Profile]:
|
||||
"""Load every profile found under ``profiles/`` and return them.
|
||||
|
||||
Raises:
|
||||
ProfileValidationError: On the first profile that fails validation,
|
||||
with the profile_type embedded in the message.
|
||||
|
||||
Returns:
|
||||
Mapping of ``{profile_type: Profile}`` for all discovered profiles.
|
||||
"""
|
||||
results: dict[str, Profile] = {}
|
||||
profile_dirs = sorted(
|
||||
p for p in PROFILES_ROOT.iterdir()
|
||||
if p.is_dir() and (p / "profile.yaml").exists()
|
||||
)
|
||||
|
||||
if not profile_dirs:
|
||||
logger.warning(
|
||||
"validate_all: no profile.yaml files found under %s", PROFILES_ROOT
|
||||
)
|
||||
return results
|
||||
|
||||
for profile_dir in profile_dirs:
|
||||
profile_type = profile_dir.name
|
||||
try:
|
||||
profile = self.get(profile_type)
|
||||
results[profile_type] = profile
|
||||
logger.info("validate_all: '%s' OK (v%s)", profile_type, profile.version)
|
||||
except ProfileValidationError as exc:
|
||||
raise ProfileValidationError(
|
||||
f"validate_all failed on profile '{profile_type}': {exc}"
|
||||
) from exc
|
||||
|
||||
return results
|
||||
|
||||
def clear(self) -> None:
|
||||
"""Clear the entire cache (useful for test isolation)."""
|
||||
with self._cache_lock:
|
||||
self._cache.clear()
|
||||
|
||||
def _cached_types(self) -> list[str]:
|
||||
"""Return currently cached profile type names (for diagnostics)."""
|
||||
with self._cache_lock:
|
||||
return list(self._cache.keys())
|
||||
@@ -0,0 +1,139 @@
|
||||
"""
|
||||
Pydantic models for Agent Platform Profile definitions.
|
||||
|
||||
All models are frozen=True for immutability after load.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from typing import Any
|
||||
|
||||
from pydantic import BaseModel, ConfigDict, Field, model_validator
|
||||
|
||||
|
||||
class EvidenceThresholds(BaseModel):
|
||||
"""Evidence quality thresholds controlling report output strategy.
|
||||
|
||||
Logical ordering enforced: output_normal >= output_with_warning >= reject.
|
||||
"""
|
||||
|
||||
model_config = ConfigDict(frozen=True)
|
||||
|
||||
output_normal: float = 0.85
|
||||
output_with_warning: float = 0.60
|
||||
reject: float = 0.60
|
||||
|
||||
@model_validator(mode="after")
|
||||
def validate_ordering(self) -> EvidenceThresholds:
|
||||
if not (self.output_normal >= self.output_with_warning >= self.reject):
|
||||
raise ValueError(
|
||||
f"EvidenceThresholds ordering violated: "
|
||||
f"output_normal({self.output_normal}) >= "
|
||||
f"output_with_warning({self.output_with_warning}) >= "
|
||||
f"reject({self.reject}) must hold"
|
||||
)
|
||||
return self
|
||||
|
||||
|
||||
class ModelRouting(BaseModel):
|
||||
"""LLM routing configuration per capability tier."""
|
||||
|
||||
model_config = ConfigDict(frozen=True)
|
||||
|
||||
default: str
|
||||
complex_reasoning: str
|
||||
force_local_if_sensitive: bool = False
|
||||
|
||||
|
||||
class WorkflowStep(BaseModel):
|
||||
"""Single executable step in the agent workflow SOP."""
|
||||
|
||||
model_config = ConfigDict(frozen=True)
|
||||
|
||||
id: str
|
||||
tool: str
|
||||
params: dict[str, Any] = Field(default_factory=dict)
|
||||
output_key: str
|
||||
on_failure: str = "abort"
|
||||
approval_required: bool = False
|
||||
estimated_duration_ms: int = 5000
|
||||
|
||||
|
||||
class ApprovalRule(BaseModel):
|
||||
"""Approval policy for a given risk level."""
|
||||
|
||||
model_config = ConfigDict(frozen=True)
|
||||
|
||||
risk_level: str
|
||||
require_approval: bool
|
||||
approver_role: str
|
||||
|
||||
|
||||
class Permissions(BaseModel):
|
||||
"""Role-based access control and data scope requirements."""
|
||||
|
||||
model_config = ConfigDict(frozen=True)
|
||||
|
||||
allowed_roles: list[str]
|
||||
data_scope_required: list[str]
|
||||
|
||||
|
||||
class CachePolicy(BaseModel):
|
||||
"""Profile-level caching configuration."""
|
||||
|
||||
model_config = ConfigDict(frozen=True)
|
||||
|
||||
enabled: bool = True
|
||||
ttl_seconds: int = 3600
|
||||
|
||||
|
||||
class Profile(BaseModel):
|
||||
"""Complete agent profile: SOP + governance + routing + output rules."""
|
||||
|
||||
model_config = ConfigDict(frozen=True)
|
||||
|
||||
# Identity
|
||||
name: str
|
||||
version: str
|
||||
description: str
|
||||
profile_type: str
|
||||
|
||||
# Tool governance
|
||||
allowed_tools: list[str]
|
||||
|
||||
# SOP
|
||||
workflow_steps: list[WorkflowStep]
|
||||
approval_rules: list[ApprovalRule]
|
||||
|
||||
# Quality & routing
|
||||
evidence_thresholds: EvidenceThresholds
|
||||
model_routing: ModelRouting
|
||||
|
||||
# Access control
|
||||
permissions: Permissions
|
||||
|
||||
# Optional policy
|
||||
cache_policy: CachePolicy = Field(default_factory=CachePolicy)
|
||||
|
||||
# Output configuration
|
||||
output_format: str = "markdown"
|
||||
output_template: str = ""
|
||||
required_sections: list[str] = Field(default_factory=list)
|
||||
required_output_fields: list[str] = Field(default_factory=list)
|
||||
|
||||
# Input schema
|
||||
input_fields: list[dict[str, Any]] = Field(default_factory=list)
|
||||
|
||||
# Domain terminology injected into system prompt
|
||||
terminology: str = ""
|
||||
|
||||
@model_validator(mode="after")
|
||||
def validate_tool_references(self) -> Profile:
|
||||
"""All workflow_steps[].tool must be listed in allowed_tools."""
|
||||
for step in self.workflow_steps:
|
||||
if step.tool not in self.allowed_tools:
|
||||
raise ValueError(
|
||||
f"Step '{step.id}' references tool '{step.tool}' "
|
||||
f"which is not in allowed_tools {self.allowed_tools}"
|
||||
)
|
||||
return self
|
||||
@@ -0,0 +1,127 @@
|
||||
"""
|
||||
Evidence scorer for assessing quality of agent execution results.
|
||||
|
||||
Scoring formula:
|
||||
score = 0.4 * retrieval + 0.3 * completeness + 0.3 * historical_accuracy
|
||||
|
||||
Evidence levels:
|
||||
sufficient: score >= 0.80
|
||||
limited: 0.55 <= score < 0.80
|
||||
insufficient: score < 0.55
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from dataclasses import dataclass, field
|
||||
from decimal import Decimal
|
||||
from typing import Any
|
||||
|
||||
|
||||
@dataclass(frozen=True)
|
||||
class VerifiedCitation:
|
||||
id: str
|
||||
source: str
|
||||
relevance: Decimal
|
||||
content_preview: str = ""
|
||||
section: str = ""
|
||||
verified: bool = True
|
||||
|
||||
def model_dump(self) -> dict[str, Any]:
|
||||
return {
|
||||
"id": self.id,
|
||||
"source": self.source,
|
||||
"relevance": str(self.relevance),
|
||||
"content_preview": self.content_preview,
|
||||
"section": self.section,
|
||||
"verified": self.verified,
|
||||
}
|
||||
|
||||
|
||||
@dataclass(frozen=True)
|
||||
class ScorerResult:
|
||||
score: Decimal
|
||||
level: str
|
||||
verified_citations: list[VerifiedCitation] = field(default_factory=list)
|
||||
|
||||
|
||||
class EvidenceScorer:
|
||||
"""Score evidence quality from tool execution results."""
|
||||
|
||||
SUFFICIENT_THRESHOLD = Decimal("0.80")
|
||||
LIMITED_THRESHOLD = Decimal("0.55")
|
||||
|
||||
def score(
|
||||
self,
|
||||
citations: list[dict[str, Any]],
|
||||
step_outputs: dict[str, Any],
|
||||
required_fields: list[str],
|
||||
historical_accuracy: Decimal,
|
||||
) -> ScorerResult:
|
||||
"""
|
||||
Compute evidence score using weighted formula.
|
||||
|
||||
Args:
|
||||
citations: Flat list of citation dicts from all step outputs.
|
||||
step_outputs: All step output dicts keyed by output_key.
|
||||
required_fields: Required output fields from profile.
|
||||
historical_accuracy: Historical accuracy score (0–1 Decimal).
|
||||
|
||||
Returns:
|
||||
ScorerResult with score, level, and verified citations.
|
||||
"""
|
||||
# ── Component 1: Retrieval score (average citation relevance) ─────────
|
||||
if citations:
|
||||
relevances: list[Decimal] = []
|
||||
for c in citations:
|
||||
try:
|
||||
rel = Decimal(str(c.get("relevance", 0)))
|
||||
except Exception:
|
||||
rel = Decimal("0")
|
||||
relevances.append(rel)
|
||||
retrieval_score = sum(relevances) / Decimal(len(relevances))
|
||||
else:
|
||||
retrieval_score = Decimal("0")
|
||||
|
||||
# ── Component 2: Completeness (fraction of required fields present) ───
|
||||
if required_fields:
|
||||
all_keys: set[str] = set()
|
||||
for output in step_outputs.values():
|
||||
if isinstance(output, dict):
|
||||
all_keys.update(output.keys())
|
||||
present = sum(1 for f in required_fields if f in all_keys)
|
||||
completeness_score = Decimal(present) / Decimal(len(required_fields))
|
||||
else:
|
||||
# No required fields specified → treat as fully satisfied
|
||||
completeness_score = Decimal("1")
|
||||
|
||||
# ── Weighted formula ───────────────────────────────────────────────────
|
||||
score = (
|
||||
Decimal("0.4") * retrieval_score
|
||||
+ Decimal("0.3") * completeness_score
|
||||
+ Decimal("0.3") * historical_accuracy
|
||||
)
|
||||
# Clamp to [0, 1]
|
||||
score = max(Decimal("0"), min(Decimal("1"), score))
|
||||
|
||||
# ── Level determination ────────────────────────────────────────────────
|
||||
if score >= self.SUFFICIENT_THRESHOLD:
|
||||
level = "sufficient"
|
||||
elif score >= self.LIMITED_THRESHOLD:
|
||||
level = "limited"
|
||||
else:
|
||||
level = "insufficient"
|
||||
|
||||
# ── Build verified citations ───────────────────────────────────────────
|
||||
verified = [
|
||||
VerifiedCitation(
|
||||
id=c.get("id", f"cit_{i}"),
|
||||
source=c.get("source", "unknown"),
|
||||
relevance=Decimal(str(c.get("relevance", 0))),
|
||||
content_preview=c.get("content_preview", ""),
|
||||
section=c.get("section", ""),
|
||||
verified=True,
|
||||
)
|
||||
for i, c in enumerate(citations)
|
||||
]
|
||||
|
||||
return ScorerResult(score=score, level=level, verified_citations=verified)
|
||||
@@ -0,0 +1,76 @@
|
||||
name: "知识问答"
|
||||
version: "1.0.0"
|
||||
profile_type: "knowledge_qa"
|
||||
description: "基于企业知识库进行精准问答，引用覆盖率目标 ≥ 90%，证据不足时直接拒绝输出"
|
||||
|
||||
allowed_tools:
|
||||
- rag_case_retriever
|
||||
|
||||
input_fields:
|
||||
- name: question
|
||||
description: 用户问题（自然语言）
|
||||
required: true
|
||||
- name: domain
|
||||
description: 问题所属领域（可选，用于缩小检索范围）
|
||||
required: false
|
||||
- name: language
|
||||
description: 期望回答语言（默认中文）
|
||||
required: false
|
||||
|
||||
workflow_steps:
|
||||
- id: step_01_knowledge_retrieval
|
||||
tool: rag_case_retriever
|
||||
params:
|
||||
query: "{{user_input.question}}"
|
||||
domain_filter: "{{user_input.domain}}"
|
||||
top_k: 10
|
||||
min_relevance_score: 0.90
|
||||
rerank: true
|
||||
output_key: retrieved_context
|
||||
on_failure: abort
|
||||
approval_required: false
|
||||
estimated_duration_ms: 3000
|
||||
|
||||
approval_rules:
|
||||
- risk_level: high
|
||||
require_approval: true
|
||||
approver_role: admin
|
||||
|
||||
# 严格模式：引用覆盖率 ≥ 90%，证据不足直接拒绝，无警告中间态
|
||||
evidence_thresholds:
|
||||
output_normal: 0.90
|
||||
output_with_warning: 0.90
|
||||
reject: 0.90
|
||||
|
||||
model_routing:
|
||||
default: "local"
|
||||
complex_reasoning: "claude-sonnet-4-6-20260217"
|
||||
force_local_if_sensitive: false
|
||||
|
||||
permissions:
|
||||
allowed_roles:
|
||||
- admin
|
||||
- manager
|
||||
- analyst
|
||||
- viewer
|
||||
data_scope_required: []
|
||||
|
||||
cache_policy:
|
||||
enabled: true
|
||||
ttl_seconds: 7200
|
||||
|
||||
output_format: "markdown"
|
||||
|
||||
required_sections:
|
||||
- 回答
|
||||
- 引用来源
|
||||
|
||||
required_output_fields:
|
||||
- answer
|
||||
- citations
|
||||
- confidence_score
|
||||
|
||||
terminology: |
|
||||
RAG：检索增强生成（Retrieval-Augmented Generation）
|
||||
引用覆盖率：回答中每条关键陈述均有可追溯来源的比例
|
||||
知识截止日期：知识库最后更新时间，超出范围的问题应说明局限性
|
||||
@@ -0,0 +1,111 @@
|
||||
name: "企业预售方案生成"
|
||||
version: "1.0.0"
|
||||
profile_type: "presales"
|
||||
description: "为客户生成专业预售方案，从信息收集到 Word 文档交付，典型耗时 30 分钟以内"
|
||||
|
||||
allowed_tools:
|
||||
- enterprise_info_search
|
||||
- rag_case_retriever
|
||||
- word_doc_generator
|
||||
|
||||
input_fields:
|
||||
- name: customer_name
|
||||
description: 客户公司全称
|
||||
required: true
|
||||
- name: industry
|
||||
description: 所在行业
|
||||
required: false
|
||||
- name: scale
|
||||
description: 企业规模（人数或营收）
|
||||
required: false
|
||||
- name: pain_points
|
||||
description: 核心痛点（可多个）
|
||||
required: false
|
||||
- name: budget_range
|
||||
description: 预算范围
|
||||
required: false
|
||||
|
||||
workflow_steps:
|
||||
- id: step_01_enterprise_info
|
||||
tool: enterprise_info_search
|
||||
params:
|
||||
company_name: "{{user_input.customer_name}}"
|
||||
include_financials: false
|
||||
include_news: true
|
||||
output_key: enterprise_profile
|
||||
on_failure: abort
|
||||
approval_required: false
|
||||
estimated_duration_ms: 5000
|
||||
|
||||
- id: step_02_case_retrieval
|
||||
tool: rag_case_retriever
|
||||
params:
|
||||
query: "{{user_input.pain_points}} {{steps.step_01_enterprise_info.summary}}"
|
||||
industry_filter: "{{user_input.industry}}"
|
||||
top_k: 5
|
||||
tenant_id: "{{user_input.tenant_id}}"
|
||||
output_key: matched_cases
|
||||
on_failure: skip
|
||||
approval_required: false
|
||||
estimated_duration_ms: 8000
|
||||
|
||||
- id: step_03_generate_doc
|
||||
tool: word_doc_generator
|
||||
params:
|
||||
template_name: "presales_standard_v2"
|
||||
content:
|
||||
enterprise_profile: "{{steps.step_01_enterprise_info}}"
|
||||
matched_cases: "{{steps.step_02_case_retrieval}}"
|
||||
pain_points: "{{user_input.pain_points}}"
|
||||
output_format: docx
|
||||
output_key: final_document
|
||||
on_failure: abort
|
||||
approval_required: false
|
||||
estimated_duration_ms: 15000
|
||||
|
||||
approval_rules:
|
||||
- risk_level: high
|
||||
require_approval: true
|
||||
approver_role: manager
|
||||
|
||||
evidence_thresholds:
|
||||
output_normal: 0.85
|
||||
output_with_warning: 0.60
|
||||
reject: 0.60
|
||||
|
||||
model_routing:
|
||||
default: "local"
|
||||
complex_reasoning: "claude-sonnet-4-6-20260217"
|
||||
force_local_if_sensitive: true
|
||||
|
||||
permissions:
|
||||
allowed_roles:
|
||||
- admin
|
||||
- manager
|
||||
- analyst
|
||||
data_scope_required: []
|
||||
|
||||
cache_policy:
|
||||
enabled: true
|
||||
ttl_seconds: 3600
|
||||
|
||||
output_format: "docx"
|
||||
|
||||
required_sections:
|
||||
- 执行摘要
|
||||
- 客户画像
|
||||
- 方案设计
|
||||
- 商业价值
|
||||
- 实施计划
|
||||
- 下一步行动
|
||||
|
||||
required_output_fields:
|
||||
- customer_name
|
||||
- industry
|
||||
- proposed_solution
|
||||
- business_value
|
||||
|
||||
terminology: |
|
||||
预售：售前技术支持阶段
|
||||
POC：概念验证（Proof of Concept）
|
||||
ROI：投资回报率（Return on Investment）
|
||||
@@ -0,0 +1,165 @@
|
||||
name: "安全事件分析"
|
||||
version: "1.0.0"
|
||||
profile_type: "security_analysis"
|
||||
description: "对安全告警进行去重、日志关联、攻击链推断，生成威胁分析报告；高风险主机隔离操作须人工审批"
|
||||
|
||||
allowed_tools:
|
||||
- alert_deduplicator
|
||||
- log_correlator
|
||||
- attack_chain_analyzer
|
||||
- rag_case_retriever
|
||||
- security_report_generator
|
||||
- host_isolation
|
||||
|
||||
input_fields:
|
||||
- name: alert_id
|
||||
description: 告警唯一标识
|
||||
required: true
|
||||
- name: event_description
|
||||
description: 事件描述（原始告警文本）
|
||||
required: false
|
||||
- name: severity
|
||||
description: 告警严重级别（critical/high/medium/low）
|
||||
required: false
|
||||
- name: affected_hosts
|
||||
description: 受影响主机列表
|
||||
required: false
|
||||
- name: time_range
|
||||
description: 分析时间窗口（ISO8601 区间）
|
||||
required: false
|
||||
|
||||
workflow_steps:
|
||||
- id: step_01_alert_dedup
|
||||
tool: alert_deduplicator
|
||||
params:
|
||||
alert_id: "{{user_input.alert_id}}"
|
||||
time_range: "{{user_input.time_range}}"
|
||||
dedup_window_minutes: 30
|
||||
output_key: deduplicated_alerts
|
||||
on_failure: abort
|
||||
approval_required: false
|
||||
estimated_duration_ms: 3000
|
||||
|
||||
- id: step_02_log_correlation
|
||||
tool: log_correlator
|
||||
params:
|
||||
alert_ids: "{{steps.step_01_alert_dedup.alert_ids}}"
|
||||
affected_hosts: "{{user_input.affected_hosts}}"
|
||||
time_range: "{{user_input.time_range}}"
|
||||
log_sources:
|
||||
- siem
|
||||
- endpoint
|
||||
- network
|
||||
output_key: correlated_logs
|
||||
on_failure: skip
|
||||
approval_required: false
|
||||
estimated_duration_ms: 10000
|
||||
|
||||
- id: step_03_case_reference
|
||||
tool: rag_case_retriever
|
||||
params:
|
||||
query: "{{steps.step_02_log_correlation.ioc_summary}}"
|
||||
top_k: 5
|
||||
filter_tags:
|
||||
- security
|
||||
- threat_intel
|
||||
output_key: reference_cases
|
||||
on_failure: skip
|
||||
approval_required: false
|
||||
estimated_duration_ms: 5000
|
||||
|
||||
- id: step_04_attack_chain
|
||||
tool: attack_chain_analyzer
|
||||
params:
|
||||
correlated_logs: "{{steps.step_02_log_correlation}}"
|
||||
reference_cases: "{{steps.step_03_case_reference}}"
|
||||
mitre_mapping: true
|
||||
output_key: attack_chain
|
||||
on_failure: skip
|
||||
approval_required: false
|
||||
estimated_duration_ms: 15000
|
||||
|
||||
- id: step_05_host_isolation
|
||||
tool: host_isolation
|
||||
params:
|
||||
hosts: "{{user_input.affected_hosts}}"
|
||||
isolation_mode: "network_block"
|
||||
reason: "{{steps.step_04_attack_chain.threat_summary}}"
|
||||
output_key: isolation_result
|
||||
on_failure: skip
|
||||
approval_required: true
|
||||
estimated_duration_ms: 5000
|
||||
|
||||
- id: step_06_report_generation
|
||||
tool: security_report_generator
|
||||
params:
|
||||
template_name: "security_incident_v1"
|
||||
content:
|
||||
deduplicated_alerts: "{{steps.step_01_alert_dedup}}"
|
||||
correlated_logs: "{{steps.step_02_log_correlation}}"
|
||||
attack_chain: "{{steps.step_04_attack_chain}}"
|
||||
reference_cases: "{{steps.step_03_case_reference}}"
|
||||
isolation_result: "{{steps.step_05_host_isolation}}"
|
||||
severity: "{{user_input.severity}}"
|
||||
output_key: incident_report
|
||||
on_failure: abort
|
||||
approval_required: false
|
||||
estimated_duration_ms: 10000
|
||||
|
||||
approval_rules:
|
||||
- risk_level: high
|
||||
require_approval: true
|
||||
approver_role: security_manager
|
||||
- risk_level: critical
|
||||
require_approval: true
|
||||
approver_role: ciso
|
||||
|
||||
# 安全场景宁可多报：放宽 output_with_warning 至 0.55，reject 至 0.40
|
||||
evidence_thresholds:
|
||||
output_normal: 0.80
|
||||
output_with_warning: 0.55
|
||||
reject: 0.40
|
||||
|
||||
model_routing:
|
||||
default: "local"
|
||||
complex_reasoning: "claude-sonnet-4-6-20260217"
|
||||
force_local_if_sensitive: true
|
||||
|
||||
permissions:
|
||||
allowed_roles:
|
||||
- admin
|
||||
- security_analyst
|
||||
- security_manager
|
||||
- ciso
|
||||
data_scope_required:
|
||||
- security_logs
|
||||
- endpoint_telemetry
|
||||
|
||||
cache_policy:
|
||||
enabled: false
|
||||
ttl_seconds: 300
|
||||
|
||||
output_format: "markdown"
|
||||
|
||||
required_sections:
|
||||
- 事件摘要
|
||||
- 影响范围
|
||||
- 攻击链分析
|
||||
- 证据链
|
||||
- 处置建议
|
||||
- 参考案例
|
||||
|
||||
required_output_fields:
|
||||
- alert_id
|
||||
- severity
|
||||
- attack_chain
|
||||
- affected_hosts
|
||||
- recommended_actions
|
||||
|
||||
terminology: |
|
||||
IOC：危害指标（Indicator of Compromise）
|
||||
TTPs：战术、技术和程序（Tactics, Techniques, and Procedures）
|
||||
MITRE ATT&CK：企业网络攻击战术知识库
|
||||
EDR：端点检测与响应（Endpoint Detection and Response）
|
||||
SIEM：安全信息和事件管理（Security Information and Event Management）
|
||||
横向移动：攻击者在网络内扩散的行为
|
||||
@@ -50,6 +50,7 @@ dev-dependencies = [
|
||||
"pytest-mock>=3.14.0",
|
||||
"respx>=0.21.0",
|
||||
"testcontainers[postgresql]>=4.8.0",
|
||||
"pytest-timeout>=2.3.0",
|
||||
"ruff>=0.6.0",
|
||||
"mypy>=1.11.0",
|
||||
"pre-commit>=3.8.0",
|
||||
@@ -60,6 +61,7 @@ dev-dependencies = [
|
||||
[tool.pytest.ini_options]
|
||||
asyncio_mode = "auto"
|
||||
testpaths = ["tests"]
|
||||
addopts = "--cov=core.llm.prompt_builder"
|
||||
markers = [
|
||||
"claude_api: tests requiring Anthropic Claude API",
|
||||
"slow: slow tests",
|
||||
@@ -79,5 +81,11 @@ disallow_untyped_defs = true
|
||||
warn_return_any = true
|
||||
no_implicit_optional = true
|
||||
|
||||
[tool.coverage.run]
|
||||
source = ["core", "api", "db"]
|
||||
|
||||
[tool.coverage.report]
|
||||
show_missing = true
|
||||
|
||||
[tool.hatch.build.targets.wheel]
|
||||
packages = ["core", "api", "db"]
|
||||
|
||||
Executable
+103
@@ -0,0 +1,103 @@
|
||||
#!/usr/bin/env bash
|
||||
# smoke_test.sh — CI gate: lint, type-check, unit tests, integration tests
|
||||
# Usage:
|
||||
# ./scripts/smoke_test.sh # full suite
|
||||
# ./scripts/smoke_test.sh --unit-only # skip integration tests
|
||||
|
||||
set -euo pipefail
|
||||
|
||||
UNIT_ONLY=false
|
||||
for arg in "$@"; do
|
||||
[[ "$arg" == "--unit-only" ]] && UNIT_ONLY=true
|
||||
done
|
||||
|
||||
# ── Colour helpers ────────────────────────────────────────────────────────────
|
||||
GREEN='\033[0;32m'; RED='\033[0;31m'; YELLOW='\033[1;33m'; NC='\033[0m'
|
||||
ok() { echo -e "${GREEN}[✓]${NC} $*"; }
|
||||
fail() { echo -e "${RED}[✗]${NC} $*"; exit 1; }
|
||||
info() { echo -e "${YELLOW}[…]${NC} $*"; }
|
||||
|
||||
# ── Gate 1: Ruff lint ─────────────────────────────────────────────────────────
|
||||
info "Gate 1/6 — ruff lint"
|
||||
uv run ruff check . --select E,F,I --quiet \
|
||||
|| fail "ruff lint failed"
|
||||
ok "ruff lint"
|
||||
|
||||
# ── Gate 2: Mypy type check ───────────────────────────────────────────────────
|
||||
info "Gate 2/6 — mypy type check"
|
||||
uv run mypy core/ api/ --ignore-missing-imports --no-error-summary \
|
||||
|| fail "mypy failed"
|
||||
ok "mypy"
|
||||
|
||||
# ── Gate 3: Unit tests ────────────────────────────────────────────────────────
|
||||
info "Gate 3/6 — unit tests (coverage ≥ 80%)"
|
||||
uv run pytest tests/unit/ -x -q --tb=short \
|
||||
--cov=core --cov=api --cov-fail-under=80 \
|
||||
|| fail "unit tests failed"
|
||||
ok "unit tests"
|
||||
|
||||
# ── Gate 4: Prompt keyword validation ────────────────────────────────────────
|
||||
info "Gate 4/6 — prompt keyword validation"
|
||||
uv run python - <<'EOF'
|
||||
from core.llm.prompt_builder import (
|
||||
_SYSTEM_BASE,
|
||||
build_report_message,
|
||||
build_system_messages,
|
||||
)
|
||||
|
||||
required_keywords = ["工具白名单", "审批", "引用", "幻觉", "审计"]
|
||||
for kw in required_keywords:
|
||||
assert kw in _SYSTEM_BASE, f"Missing governance keyword in _SYSTEM_BASE: {kw!r}"
|
||||
|
||||
msgs = build_system_messages()
|
||||
assert any(isinstance(m, dict) and "text" in m for m in msgs), \
|
||||
"build_system_messages must return dicts with 'text' key"
|
||||
|
||||
report = build_report_message("insufficient", {}, [], "")
|
||||
assert "data_insufficient" in report, \
|
||||
"build_report_message('insufficient') must contain <data_insufficient>"
|
||||
|
||||
print("Prompt keyword validation OK")
|
||||
EOF
|
||||
ok "prompt keyword validation"
|
||||
|
||||
# ── Gate 5: Profile integrity validation ──────────────────────────────────────
|
||||
info "Gate 5/6 — profile integrity validation"
|
||||
uv run python - <<'EOF'
|
||||
from core.profile.registry import ProfileRegistry
|
||||
|
||||
registry = ProfileRegistry.instance()
|
||||
results = registry.validate_all()
|
||||
|
||||
for ptype, profile in results.items():
|
||||
t = profile.evidence_thresholds
|
||||
assert t.output_normal >= t.output_with_warning >= t.reject, (
|
||||
f"[{ptype}] evidence threshold ordering violated"
|
||||
)
|
||||
for step in profile.workflow_steps:
|
||||
assert step.tool in profile.allowed_tools, (
|
||||
f"[{ptype}] step {step.id!r} tool {step.tool!r} not in allowed_tools"
|
||||
)
|
||||
|
||||
assert "presales" in results
|
||||
assert "security_analysis" in results
|
||||
assert "knowledge_qa" in results
|
||||
print(f"Profile integrity OK — validated {len(results)} profiles")
|
||||
EOF
|
||||
ok "profile integrity validation"
|
||||
|
||||
# ── Gate 6: Integration tests ─────────────────────────────────────────────────
|
||||
if [[ "$UNIT_ONLY" == "true" ]]; then
|
||||
info "Gate 6/6 — integration tests (SKIPPED via --unit-only)"
|
||||
else
|
||||
info "Gate 6/6 — integration tests"
|
||||
uv run pytest tests/integration/ -x -q --tb=short \
|
||||
-m "not claude_api" --timeout=60 \
|
||||
|| fail "integration tests failed"
|
||||
ok "integration tests"
|
||||
fi
|
||||
|
||||
echo ""
|
||||
echo -e "${GREEN}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}"
|
||||
echo -e "${GREEN} All smoke test gates passed ✓${NC}"
|
||||
echo -e "${GREEN}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}"
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@@ -0,0 +1,179 @@
|
||||
"""
|
||||
Integration tests for cost tracking and budget alerting.
|
||||
|
||||
Validates:
|
||||
- CostCalculation is accumulated in state.total_cost_cny after a task
|
||||
- Budget threshold detection fires a warning when threshold is crossed
|
||||
- Batch mode (invoke_mode='batch') costs exactly 50% of realtime
|
||||
|
||||
All tests run with ClaudeClient mocked.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import uuid
|
||||
from decimal import Decimal
|
||||
from unittest.mock import AsyncMock, patch
|
||||
|
||||
import pytest
|
||||
|
||||
from core.llm.claude_client import (
|
||||
BATCH_DISCOUNT,
|
||||
CostCalculation,
|
||||
)
|
||||
|
||||
pytestmark = pytest.mark.integration
|
||||
|
||||
|
||||
# ── Helpers ───────────────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
def _make_cost(
|
||||
input_tokens: int,
|
||||
output_tokens: int,
|
||||
cache_read: int = 0,
|
||||
cache_write: int = 0,
|
||||
invoke_mode: str = "realtime",
|
||||
) -> CostCalculation:
|
||||
return CostCalculation(
|
||||
input_tokens=input_tokens,
|
||||
output_tokens=output_tokens,
|
||||
cache_read_tokens=cache_read,
|
||||
cache_write_tokens=cache_write,
|
||||
invoke_mode=invoke_mode,
|
||||
)
|
||||
|
||||
|
||||
# ── Test 1: Cost Recorded After Task ─────────────────────────────────────────
|
||||
|
||||
|
||||
async def test_cost_recorded_after_task() -> None:
|
||||
"""state.total_cost_cny > 0 after ask + plan + act + verify + report."""
|
||||
from langgraph.checkpoint.memory import MemorySaver
|
||||
|
||||
from core.engine.graph import build_agent_graph
|
||||
from core.tools.base import Citation, ToolResult
|
||||
|
||||
thread_id = str(uuid.uuid4())
|
||||
config = {"configurable": {"thread_id": thread_id}}
|
||||
|
||||
ask_tool_input = {
|
||||
"profile_type": "presales",
|
||||
"extracted_fields": [
|
||||
{"field_name": "customer_name", "value": "CostCo", "confidence": 0.9}
|
||||
],
|
||||
"missing_required_fields": [],
|
||||
"task_summary": "成本测试",
|
||||
}
|
||||
plan_tool_input = {
|
||||
"plan_id": "plan-cost",
|
||||
"steps": [
|
||||
{
|
||||
"step_id": "step_01",
|
||||
"tool_name": "enterprise_info_search",
|
||||
"status": "pending",
|
||||
"params": {"company_name": "CostCo"},
|
||||
"output_key": "enterprise_profile",
|
||||
"on_failure": "abort",
|
||||
"approval_required": False,
|
||||
}
|
||||
],
|
||||
"plan_summary": "成本追踪计划",
|
||||
}
|
||||
tool_result = ToolResult(
|
||||
success=True,
|
||||
data={"summary": "企业信息"},
|
||||
citations=[
|
||||
Citation(id="c1", source="db", relevance=Decimal("0.9"), verified=True)
|
||||
],
|
||||
meta={"mock": True},
|
||||
)
|
||||
|
||||
ask_cost = _make_cost(500, 100)
|
||||
plan_cost = _make_cost(800, 200)
|
||||
report_cost = _make_cost(1000, 500)
|
||||
expected_total = ask_cost.cost_cny + plan_cost.cost_cny + report_cost.cost_cny
|
||||
|
||||
graph = build_agent_graph(MemorySaver())
|
||||
|
||||
with (
|
||||
patch("core.llm.claude_client.ClaudeClient") as mock_cls,
|
||||
patch("core.tools.executor.ToolExecutor.execute_tool", new_callable=AsyncMock)
|
||||
as mock_execute,
|
||||
):
|
||||
mock_client = mock_cls.return_value
|
||||
mock_client.call_with_tools = AsyncMock(
|
||||
side_effect=[
|
||||
(ask_tool_input, ask_cost),
|
||||
(plan_tool_input, plan_cost),
|
||||
]
|
||||
)
|
||||
mock_client.call_text = AsyncMock(
|
||||
return_value=("## 报告内容", report_cost)
|
||||
)
|
||||
mock_execute.return_value = tool_result
|
||||
|
||||
final = await graph.ainvoke(
|
||||
{
|
||||
"trace_id": "trace-cost-001",
|
||||
"session_id": "session-cost-001",
|
||||
"user_id": "u001",
|
||||
"tenant_id": "t001",
|
||||
"user_role": "admin",
|
||||
"data_scope": [],
|
||||
"profile_type": "presales",
|
||||
"user_input": "制造业预售方案",
|
||||
},
|
||||
config=config,
|
||||
)
|
||||
|
||||
assert final["error"] is None
|
||||
assert final["total_cost_cny"] > Decimal("0")
|
||||
# Total should match sum of mocked costs
|
||||
assert final["total_cost_cny"] == expected_total
|
||||
|
||||
|
||||
# ── Test 2: Budget Alert Warning ──────────────────────────────────────────────
|
||||
|
||||
|
||||
async def test_budget_alert_warning() -> None:
|
||||
"""CostCalculation exceeding a budget threshold triggers a warning log."""
|
||||
|
||||
# A call with 10M input + 2M output tokens should have a large cost
|
||||
big_cost = _make_cost(input_tokens=10_000_000, output_tokens=2_000_000)
|
||||
|
||||
# Verify cost calculation is non-trivial
|
||||
assert big_cost.cost_usd >= Decimal("60"), (
|
||||
f"Expected large USD cost, got {big_cost.cost_usd}"
|
||||
)
|
||||
assert big_cost.cost_cny >= Decimal("400"), (
|
||||
f"Expected large CNY cost, got {big_cost.cost_cny}"
|
||||
)
|
||||
|
||||
# Simulate a budget threshold check (¥100 per call warning)
|
||||
BUDGET_THRESHOLD_CNY = Decimal("100")
|
||||
budget_exceeded = big_cost.cost_cny > BUDGET_THRESHOLD_CNY
|
||||
assert budget_exceeded, "High-token call should exceed ¥100 budget threshold"
|
||||
|
||||
|
||||
# ── Test 3: Batch Cost Is 50% of Realtime ────────────────────────────────────
|
||||
|
||||
|
||||
async def test_batch_cost_half_of_realtime() -> None:
|
||||
"""Batch invoke_mode applies 50% discount vs realtime for identical token counts."""
|
||||
input_tokens = 1000
|
||||
output_tokens = 500
|
||||
|
||||
realtime_cost = _make_cost(input_tokens, output_tokens, invoke_mode="realtime")
|
||||
batch_cost = _make_cost(input_tokens, output_tokens, invoke_mode="batch")
|
||||
|
||||
# Batch should be exactly half of realtime
|
||||
assert batch_cost.cost_usd == realtime_cost.cost_usd * BATCH_DISCOUNT, (
|
||||
f"Batch cost {batch_cost.cost_usd} != 50% of realtime {realtime_cost.cost_usd}"
|
||||
)
|
||||
assert batch_cost.cost_cny == realtime_cost.cost_cny * BATCH_DISCOUNT, (
|
||||
f"Batch CNY {batch_cost.cost_cny} != 50% of realtime {realtime_cost.cost_cny}"
|
||||
)
|
||||
|
||||
# Verify the discount factor constant
|
||||
assert BATCH_DISCOUNT == Decimal("0.5")
|
||||
@@ -0,0 +1,540 @@
|
||||
"""
|
||||
End-to-end integration tests for the agent pipeline.
|
||||
|
||||
All tests run with:
|
||||
- ClaudeClient mocked (no real API calls)
|
||||
- ToolExecutor.execute_tool mocked (no real tool calls)
|
||||
- MemorySaver checkpointer (in-process, no DB)
|
||||
|
||||
Marked with @pytest.mark.integration so they are skipped unless
|
||||
explicitly included or when running with -m 'not claude_api'.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import uuid
|
||||
from decimal import Decimal
|
||||
from typing import Any
|
||||
from unittest.mock import AsyncMock, patch
|
||||
|
||||
import pytest
|
||||
from langgraph.checkpoint.memory import MemorySaver
|
||||
from langgraph.types import Command
|
||||
|
||||
from core.engine.graph import build_agent_graph
|
||||
from core.llm.claude_client import CostCalculation
|
||||
from core.tools.base import Citation, ToolNotAllowedError, ToolResult
|
||||
|
||||
pytestmark = pytest.mark.integration
|
||||
|
||||
|
||||
# ── Helpers ──────────────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
def _fake_cost(input_tokens: int = 100, output_tokens: int = 50) -> CostCalculation:
|
||||
return CostCalculation(
|
||||
input_tokens=input_tokens,
|
||||
output_tokens=output_tokens,
|
||||
cache_read_tokens=0,
|
||||
cache_write_tokens=0,
|
||||
)
|
||||
|
||||
|
||||
def _base_state(profile_type: str = "presales", **overrides: Any) -> dict[str, Any]:
|
||||
base: dict[str, Any] = {
|
||||
"trace_id": f"trace-{uuid.uuid4().hex[:8]}",
|
||||
"session_id": f"session-{uuid.uuid4().hex[:8]}",
|
||||
"user_id": "user-001",
|
||||
"tenant_id": "tenant-001",
|
||||
"user_role": "admin",
|
||||
"data_scope": [],
|
||||
"profile_type": profile_type,
|
||||
"user_input": "我们是一家制造业企业，客户名称是ABC科技，需要一份预售方案",
|
||||
}
|
||||
base.update(overrides)
|
||||
return base
|
||||
|
||||
|
||||
def _make_presales_plan() -> list[dict[str, Any]]:
|
||||
return [
|
||||
{
|
||||
"step_id": "step_01",
|
||||
"tool_name": "enterprise_info_search",
|
||||
"status": "pending",
|
||||
"params": {"company_name": "ABC科技", "include_news": True},
|
||||
"output_key": "enterprise_profile",
|
||||
"on_failure": "abort",
|
||||
"approval_required": False,
|
||||
},
|
||||
{
|
||||
"step_id": "step_02",
|
||||
"tool_name": "rag_case_retriever",
|
||||
"status": "pending",
|
||||
"params": {"query": "制造业预售方案", "tenant_id": "tenant-001"},
|
||||
"output_key": "matched_cases",
|
||||
"on_failure": "skip",
|
||||
"approval_required": False,
|
||||
},
|
||||
{
|
||||
"step_id": "step_03",
|
||||
"tool_name": "word_doc_generator",
|
||||
"status": "pending",
|
||||
"params": {"template_name": "presales_standard_v2", "content": {}},
|
||||
"output_key": "final_document",
|
||||
"on_failure": "abort",
|
||||
"approval_required": False,
|
||||
},
|
||||
]
|
||||
|
||||
|
||||
def _tool_result_with_citations(mock: bool = False) -> ToolResult:
|
||||
"""Return a successful ToolResult with two high-relevance citations."""
|
||||
return ToolResult(
|
||||
success=True,
|
||||
data={"summary": "Tool executed successfully", "data_ref": None},
|
||||
citations=[
|
||||
Citation(
|
||||
id="cit_1",
|
||||
source="enterprise_db",
|
||||
relevance=Decimal("0.93"),
|
||||
content_preview="企业信息摘要",
|
||||
verified=True,
|
||||
),
|
||||
Citation(
|
||||
id="cit_2",
|
||||
source="case_library",
|
||||
relevance=Decimal("0.88"),
|
||||
content_preview="参考案例",
|
||||
verified=True,
|
||||
),
|
||||
],
|
||||
meta={"mock": mock},
|
||||
)
|
||||
|
||||
|
||||
# ── Fixtures ──────────────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def graph() -> Any:
|
||||
return build_agent_graph(MemorySaver())
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def thread_config() -> dict[str, Any]:
|
||||
return {"configurable": {"thread_id": str(uuid.uuid4())}}
|
||||
|
||||
|
||||
# ── Test 1: Presales Happy Path ───────────────────────────────────────────────
|
||||
|
||||
|
||||
async def test_presales_happy_path(graph: Any, thread_config: dict[str, Any]) -> None:
|
||||
"""Full presales pipeline: ask → plan → act → verify → report → final_output."""
|
||||
|
||||
ask_tool_input = {
|
||||
"profile_type": "presales",
|
||||
"extracted_fields": [
|
||||
{"field_name": "customer_name", "value": "ABC科技", "confidence": 0.95},
|
||||
{"field_name": "industry", "value": "制造业", "confidence": 0.90},
|
||||
],
|
||||
"missing_required_fields": [],
|
||||
"task_summary": "为ABC科技生成预售方案",
|
||||
}
|
||||
plan_tool_input = {
|
||||
"plan_id": "plan-001",
|
||||
"steps": _make_presales_plan(),
|
||||
"plan_summary": "三步骤预售方案生成",
|
||||
}
|
||||
|
||||
with (
|
||||
patch("core.llm.claude_client.ClaudeClient") as mock_client_cls,
|
||||
patch("core.tools.executor.ToolExecutor.execute_tool", new_callable=AsyncMock)
|
||||
as mock_execute,
|
||||
):
|
||||
mock_client = mock_client_cls.return_value
|
||||
mock_client.call_with_tools = AsyncMock(
|
||||
side_effect=[
|
||||
(ask_tool_input, _fake_cost()), # ask_node
|
||||
(plan_tool_input, _fake_cost()), # plan_node
|
||||
]
|
||||
)
|
||||
mock_client.call_text = AsyncMock(
|
||||
return_value=("## 预售方案\n\nABC科技预售方案内容...", _fake_cost(200, 800))
|
||||
)
|
||||
mock_execute.return_value = _tool_result_with_citations(mock=False)
|
||||
|
||||
final = await graph.ainvoke(_base_state(), config=thread_config)
|
||||
|
||||
assert final["error"] is None
|
||||
assert final["output_type"] in ("document", "text")
|
||||
assert final["final_output"] is not None
|
||||
assert len(final["final_output"]) > 0
|
||||
assert final["extracted_params"]["customer_name"] == "ABC科技"
|
||||
assert len(final["execution_plan"]) == 3
|
||||
assert final["total_cost_cny"] > Decimal("0")
|
||||
|
||||
|
||||
# ── Test 2: Clarification Flow ────────────────────────────────────────────────
|
||||
|
||||
|
||||
async def test_clarification_flow(graph: Any, thread_config: dict[str, Any]) -> None:
|
||||
"""When required fields are missing, output_type='clarification_needed' and graph ends."""
|
||||
|
||||
ask_tool_input = {
|
||||
"profile_type": "presales",
|
||||
"extracted_fields": [],
|
||||
"missing_required_fields": ["customer_name"],
|
||||
"task_summary": "缺少必填字段",
|
||||
}
|
||||
|
||||
with patch("core.llm.claude_client.ClaudeClient") as mock_client_cls:
|
||||
mock_client = mock_client_cls.return_value
|
||||
mock_client.call_with_tools = AsyncMock(return_value=(ask_tool_input, _fake_cost()))
|
||||
|
||||
final = await graph.ainvoke(
|
||||
_base_state(user_input="帮我做个方案"),
|
||||
config=thread_config,
|
||||
)
|
||||
|
||||
assert final["error"] is None
|
||||
assert final["output_type"] == "clarification_needed"
|
||||
assert "customer_name" in final["final_output"]
|
||||
# Graph should have ended after ask — plan/act/verify/report not called
|
||||
assert final["execution_plan"] == []
|
||||
|
||||
|
||||
# ── Test 3: Approval Interrupt and Resume ─────────────────────────────────────
|
||||
|
||||
|
||||
async def test_approval_interrupt_and_resume(graph: Any, thread_config: dict[str, Any]) -> None:
|
||||
"""Act node pauses on approval_required step; resumes correctly after approval."""
|
||||
|
||||
ask_tool_input = {
|
||||
"profile_type": "presales",
|
||||
"extracted_fields": [
|
||||
{"field_name": "customer_name", "value": "XYZ Corp", "confidence": 0.9},
|
||||
],
|
||||
"missing_required_fields": [],
|
||||
"task_summary": "需要审批的计划",
|
||||
}
|
||||
# Plan has one approval-required step
|
||||
plan_with_approval = [
|
||||
{
|
||||
"step_id": "step_01",
|
||||
"tool_name": "enterprise_info_search",
|
||||
"status": "pending",
|
||||
"params": {"company_name": "XYZ Corp"},
|
||||
"output_key": "enterprise_profile",
|
||||
"on_failure": "abort",
|
||||
"approval_required": False,
|
||||
},
|
||||
{
|
||||
"step_id": "step_02",
|
||||
"tool_name": "word_doc_generator",
|
||||
"status": "requires_approval",
|
||||
"params": {"template_name": "presales_standard_v2", "content": {}},
|
||||
"output_key": "final_document",
|
||||
"on_failure": "abort",
|
||||
"approval_required": True,
|
||||
},
|
||||
]
|
||||
plan_tool_input = {
|
||||
"plan_id": "plan-approval",
|
||||
"steps": plan_with_approval,
|
||||
"plan_summary": "含审批步骤的计划",
|
||||
}
|
||||
|
||||
with (
|
||||
patch("core.llm.claude_client.ClaudeClient") as mock_client_cls,
|
||||
patch("core.tools.executor.ToolExecutor.execute_tool", new_callable=AsyncMock)
|
||||
as mock_execute,
|
||||
):
|
||||
mock_client = mock_client_cls.return_value
|
||||
mock_client.call_with_tools = AsyncMock(
|
||||
side_effect=[
|
||||
(ask_tool_input, _fake_cost()),
|
||||
(plan_tool_input, _fake_cost()),
|
||||
]
|
||||
)
|
||||
mock_client.call_text = AsyncMock(
|
||||
return_value=("## 审批后方案\n\n方案内容...", _fake_cost(100, 400))
|
||||
)
|
||||
mock_execute.return_value = _tool_result_with_citations()
|
||||
|
||||
# ── First run: collect events until graph pauses on interrupt ──────────
|
||||
interrupted = False
|
||||
async for chunk in graph.astream(_base_state(), config=thread_config):
|
||||
if "__interrupt__" in chunk:
|
||||
interrupted = True
|
||||
break
|
||||
|
||||
assert interrupted, "Graph should have paused at approval step"
|
||||
|
||||
# Verify pending_approval is set in saved state
|
||||
snap = await graph.aget_state(thread_config)
|
||||
assert snap.tasks[0].interrupts, "Expected interrupt tasks in snapshot"
|
||||
|
||||
# ── Resume with approval=True ──────────────────────────────────────────
|
||||
final = await graph.ainvoke(Command(resume=True), config=thread_config)
|
||||
|
||||
assert final["error"] is None
|
||||
assert final["final_output"] is not None
|
||||
assert final["pending_approval"] is None
|
||||
|
||||
|
||||
# ── Test 4: Evidence Insufficient Rejects ────────────────────────────────────
|
||||
|
||||
|
||||
async def test_evidence_insufficient_rejects(
|
||||
graph: Any, thread_config: dict[str, Any]
|
||||
) -> None:
|
||||
"""When no citations are returned, evidence score is insufficient, report skips Claude."""
|
||||
|
||||
ask_tool_input = {
|
||||
"profile_type": "presales",
|
||||
"extracted_fields": [
|
||||
{"field_name": "customer_name", "value": "TestCo", "confidence": 0.8},
|
||||
],
|
||||
"missing_required_fields": [],
|
||||
"task_summary": "无引用证据",
|
||||
}
|
||||
plan_tool_input = {
|
||||
"plan_id": "plan-002",
|
||||
"steps": [
|
||||
{
|
||||
"step_id": "step_01",
|
||||
"tool_name": "enterprise_info_search",
|
||||
"status": "pending",
|
||||
"params": {"company_name": "TestCo"},
|
||||
"output_key": "enterprise_profile",
|
||||
"on_failure": "abort",
|
||||
"approval_required": False,
|
||||
}
|
||||
],
|
||||
"plan_summary": "单步骤无引用计划",
|
||||
}
|
||||
|
||||
# Tool returns no citations
|
||||
empty_result = ToolResult(
|
||||
success=True,
|
||||
data={"summary": "No data found"},
|
||||
citations=[],
|
||||
meta={"mock": True},
|
||||
)
|
||||
|
||||
with (
|
||||
patch("core.llm.claude_client.ClaudeClient") as mock_client_cls,
|
||||
patch("core.tools.executor.ToolExecutor.execute_tool", new_callable=AsyncMock)
|
||||
as mock_execute,
|
||||
):
|
||||
mock_client = mock_client_cls.return_value
|
||||
mock_client.call_with_tools = AsyncMock(
|
||||
side_effect=[
|
||||
(ask_tool_input, _fake_cost()),
|
||||
(plan_tool_input, _fake_cost()),
|
||||
]
|
||||
)
|
||||
mock_execute.return_value = empty_result
|
||||
|
||||
final = await graph.ainvoke(_base_state(), config=thread_config)
|
||||
|
||||
assert final["error"] is None
|
||||
assert final["output_type"] == "insufficient_data"
|
||||
assert final["evidence_level"] == "insufficient"
|
||||
assert final["final_output"] is not None
|
||||
# call_text should NOT have been called
|
||||
assert mock_client.call_text.call_count == 0
|
||||
|
||||
|
||||
# ── Test 5: Tool Whitelist Violation ─────────────────────────────────────────
|
||||
|
||||
|
||||
async def test_tool_whitelist_violation(
|
||||
graph: Any, thread_config: dict[str, Any]
|
||||
) -> None:
|
||||
"""When tool is not in profile whitelist, error.code == 'TOOL_NOT_ALLOWED'."""
|
||||
|
||||
ask_tool_input = {
|
||||
"profile_type": "presales",
|
||||
"extracted_fields": [
|
||||
{"field_name": "customer_name", "value": "BadCo", "confidence": 0.9},
|
||||
],
|
||||
"missing_required_fields": [],
|
||||
"task_summary": "越权工具测试",
|
||||
}
|
||||
# Plan references a tool not in presales allowed_tools
|
||||
plan_with_illegal_tool = [
|
||||
{
|
||||
"step_id": "step_01",
|
||||
"tool_name": "host_isolation", # NOT in presales allowed_tools
|
||||
"status": "pending",
|
||||
"params": {"hosts": ["10.0.0.1"]},
|
||||
"output_key": "isolation_result",
|
||||
"on_failure": "abort",
|
||||
"approval_required": False,
|
||||
}
|
||||
]
|
||||
plan_tool_input = {
|
||||
"plan_id": "plan-evil",
|
||||
"steps": plan_with_illegal_tool,
|
||||
"plan_summary": "包含非法工具",
|
||||
}
|
||||
|
||||
with (
|
||||
patch("core.llm.claude_client.ClaudeClient") as mock_client_cls,
|
||||
patch("core.tools.executor.ToolExecutor.execute_tool", new_callable=AsyncMock)
|
||||
as mock_execute,
|
||||
):
|
||||
mock_client = mock_client_cls.return_value
|
||||
mock_client.call_with_tools = AsyncMock(
|
||||
side_effect=[
|
||||
(ask_tool_input, _fake_cost()),
|
||||
(plan_tool_input, _fake_cost()),
|
||||
]
|
||||
)
|
||||
# Simulate ToolExecutor raising ToolNotAllowedError
|
||||
mock_execute.side_effect = ToolNotAllowedError(
|
||||
tool_name="host_isolation", profile_name="presales"
|
||||
)
|
||||
|
||||
final = await graph.ainvoke(_base_state(), config=thread_config)
|
||||
|
||||
assert final["error"] is not None
|
||||
assert final["error"]["code"] == "TOOL_NOT_ALLOWED"
|
||||
assert "host_isolation" in final["error"]["message"]
|
||||
|
||||
|
||||
# ── Test 6: Audit Logger Completeness ────────────────────────────────────────
|
||||
|
||||
|
||||
async def test_audit_completeness(graph: Any, thread_config: dict[str, Any]) -> None:
|
||||
"""AuditLogger.write_tool_call is invoked once per successfully executed tool."""
|
||||
|
||||
ask_tool_input = {
|
||||
"profile_type": "presales",
|
||||
"extracted_fields": [
|
||||
{"field_name": "customer_name", "value": "AuditCo", "confidence": 0.9},
|
||||
],
|
||||
"missing_required_fields": [],
|
||||
"task_summary": "审计完整性测试",
|
||||
}
|
||||
plan_tool_input = {
|
||||
"plan_id": "plan-audit",
|
||||
"steps": [
|
||||
{
|
||||
"step_id": "step_01",
|
||||
"tool_name": "enterprise_info_search",
|
||||
"status": "pending",
|
||||
"params": {"company_name": "AuditCo"},
|
||||
"output_key": "enterprise_profile",
|
||||
"on_failure": "abort",
|
||||
"approval_required": False,
|
||||
}
|
||||
],
|
||||
"plan_summary": "单工具审计测试",
|
||||
}
|
||||
|
||||
with (
|
||||
patch("core.llm.claude_client.ClaudeClient") as mock_client_cls,
|
||||
patch("core.tools.executor.ToolExecutor.execute_tool", new_callable=AsyncMock)
|
||||
as mock_execute,
|
||||
patch("core.audit.logger.AuditLogger.write_tool_call", new_callable=AsyncMock)
|
||||
as mock_write_tool_call,
|
||||
):
|
||||
mock_client = mock_client_cls.return_value
|
||||
mock_client.call_with_tools = AsyncMock(
|
||||
side_effect=[
|
||||
(ask_tool_input, _fake_cost()),
|
||||
(plan_tool_input, _fake_cost()),
|
||||
]
|
||||
)
|
||||
mock_client.call_text = AsyncMock(
|
||||
return_value=("## 报告\n内容...", _fake_cost(100, 300))
|
||||
)
|
||||
mock_execute.return_value = _tool_result_with_citations()
|
||||
|
||||
await graph.ainvoke(_base_state(), config=thread_config)
|
||||
|
||||
# AuditLogger.write_tool_call called once (one tool step)
|
||||
assert mock_write_tool_call.call_count == 1
|
||||
call_kwargs = mock_write_tool_call.call_args.kwargs
|
||||
assert call_kwargs["tool_name"] == "enterprise_info_search"
|
||||
assert call_kwargs["trace_id"] is not None
|
||||
|
||||
|
||||
# ── Test 7: Mock Tool Audit Flag ──────────────────────────────────────────────
|
||||
|
||||
|
||||
async def test_mock_tool_audit_flag(graph: Any, thread_config: dict[str, Any]) -> None:
|
||||
"""When a tool returns meta.mock=True, the audit log receives mock_flag=True."""
|
||||
|
||||
ask_tool_input = {
|
||||
"profile_type": "presales",
|
||||
"extracted_fields": [
|
||||
{"field_name": "customer_name", "value": "MockCo", "confidence": 0.85},
|
||||
],
|
||||
"missing_required_fields": [],
|
||||
"task_summary": "Mock标志测试",
|
||||
}
|
||||
plan_tool_input = {
|
||||
"plan_id": "plan-mock",
|
||||
"steps": [
|
||||
{
|
||||
"step_id": "step_01",
|
||||
"tool_name": "enterprise_info_search",
|
||||
"status": "pending",
|
||||
"params": {"company_name": "MockCo"},
|
||||
"output_key": "enterprise_profile",
|
||||
"on_failure": "abort",
|
||||
"approval_required": False,
|
||||
}
|
||||
],
|
||||
"plan_summary": "Mock工具测试",
|
||||
}
|
||||
mock_tool_result = ToolResult(
|
||||
success=True,
|
||||
data={"summary": "Mock data returned"},
|
||||
citations=[
|
||||
Citation(
|
||||
id="cit_mock",
|
||||
source="mock_db",
|
||||
relevance=Decimal("0.90"),
|
||||
verified=True,
|
||||
)
|
||||
],
|
||||
meta={"mock": True, "reason": "external_api_unavailable"},
|
||||
)
|
||||
|
||||
# Capture what AuditLogger.write_tool_call receives
|
||||
captured_calls: list[dict[str, Any]] = []
|
||||
|
||||
async def capture_write_tool_call(**kwargs: Any) -> None:
|
||||
captured_calls.append(kwargs)
|
||||
|
||||
with (
|
||||
patch("core.llm.claude_client.ClaudeClient") as mock_client_cls,
|
||||
patch("core.tools.executor.ToolExecutor.execute_tool", new_callable=AsyncMock)
|
||||
as mock_execute,
|
||||
patch(
|
||||
"core.audit.logger.AuditLogger.write_tool_call",
|
||||
side_effect=capture_write_tool_call,
|
||||
),
|
||||
):
|
||||
mock_client = mock_client_cls.return_value
|
||||
mock_client.call_with_tools = AsyncMock(
|
||||
side_effect=[
|
||||
(ask_tool_input, _fake_cost()),
|
||||
(plan_tool_input, _fake_cost()),
|
||||
]
|
||||
)
|
||||
mock_client.call_text = AsyncMock(
|
||||
return_value=("## 报告\n...", _fake_cost())
|
||||
)
|
||||
mock_execute.return_value = mock_tool_result
|
||||
|
||||
await graph.ainvoke(_base_state(), config=thread_config)
|
||||
|
||||
assert len(captured_calls) == 1
|
||||
# The ToolResult passed to write_tool_call should have meta.mock=True
|
||||
result_arg = captured_calls[0]["result"]
|
||||
assert result_arg.meta.get("mock") is True
|
||||
@@ -12,7 +12,9 @@ import pytest
|
||||
# Set required environment variables before importing app
|
||||
os.environ.setdefault("DATABASE_URL", "postgresql+asyncpg://test:test@localhost/test")
|
||||
os.environ.setdefault("JWT_SECRET_KEY", "test-secret-key-32-characters-long!!")
|
||||
os.environ.setdefault("AUDIT_KEYRING_JSON", '{"key1": "AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA="}')
|
||||
os.environ.setdefault(
|
||||
"AUDIT_KEYRING_JSON", '{"key1": "AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA="}'
|
||||
)
|
||||
os.environ.setdefault("AUDIT_ACTIVE_KEY_ID", "key1")
|
||||
|
||||
from fastapi import FastAPI
|
||||
@@ -125,9 +127,9 @@ def test_chat_requires_auth_returns_401(client_with_mocks):
|
||||
def test_chat_with_valid_token_returns_stream(client_with_mocks):
|
||||
"""Test chat endpoint with valid token returns stream."""
|
||||
# Mock get_current_user dependency
|
||||
|
||||
from api.contracts import UserContext
|
||||
from api.middleware.auth import get_current_user
|
||||
from fastapi import FastAPI
|
||||
|
||||
# Get the test app from the client
|
||||
test_app: FastAPI = client_with_mocks.app # type: ignore[attr-defined]
|
||||
@@ -163,9 +165,9 @@ def test_chat_with_valid_token_returns_stream(client_with_mocks):
|
||||
def test_approve_requires_approve_permission_returns_403(client_with_mocks):
|
||||
"""Test approve endpoint requires approve:write permission."""
|
||||
# Mock get_current_user with user role (no approve:write)
|
||||
|
||||
from api.contracts import UserContext
|
||||
from api.middleware.auth import get_current_user
|
||||
from fastapi import FastAPI
|
||||
|
||||
test_app: FastAPI = client_with_mocks.app # type: ignore[attr-defined]
|
||||
|
||||
@@ -194,9 +196,9 @@ def test_approve_requires_approve_permission_returns_403(client_with_mocks):
|
||||
def test_approve_with_operator_role_succeeds(client_with_mocks):
|
||||
"""Test approve endpoint succeeds with operator role."""
|
||||
# Mock get_current_user with operator role (has approve:write)
|
||||
|
||||
from api.contracts import UserContext
|
||||
from api.middleware.auth import get_current_user
|
||||
from fastapi import FastAPI
|
||||
|
||||
test_app: FastAPI = client_with_mocks.app # type: ignore[attr-defined]
|
||||
|
||||
@@ -239,9 +241,9 @@ def test_trace_requires_auth_returns_401(client_with_mocks):
|
||||
def test_trace_with_valid_token_returns_data(client_with_mocks):
|
||||
"""Test trace endpoint with valid token returns data."""
|
||||
# Mock get_current_user
|
||||
|
||||
from api.contracts import UserContext
|
||||
from api.middleware.auth import get_current_user
|
||||
from fastapi import FastAPI
|
||||
|
||||
test_app: FastAPI = client_with_mocks.app # type: ignore[attr-defined]
|
||||
|
||||
@@ -275,9 +277,10 @@ def test_trace_with_valid_token_returns_data(client_with_mocks):
|
||||
|
||||
def test_auth_with_valid_jwt_token():
|
||||
"""Test auth middleware with valid JWT token."""
|
||||
from api.middleware.auth import get_current_user
|
||||
from fastapi.security import HTTPAuthorizationCredentials
|
||||
|
||||
from api.middleware.auth import get_current_user
|
||||
|
||||
with patch("jose.jwt.decode") as mock_decode:
|
||||
mock_decode.return_value = {
|
||||
"sub": "user-123",
|
||||
@@ -302,11 +305,12 @@ def test_auth_with_valid_jwt_token():
|
||||
|
||||
def test_auth_with_expired_token_raises_401():
|
||||
"""Test auth middleware with expired token raises 401."""
|
||||
from api.middleware.auth import get_current_user
|
||||
from fastapi import HTTPException
|
||||
from fastapi.security import HTTPAuthorizationCredentials
|
||||
from jose import jwt
|
||||
|
||||
from api.middleware.auth import get_current_user
|
||||
|
||||
with patch("jose.jwt.decode") as mock_decode:
|
||||
mock_decode.side_effect = jwt.ExpiredSignatureError("Token expired")
|
||||
|
||||
@@ -325,11 +329,12 @@ def test_auth_with_expired_token_raises_401():
|
||||
|
||||
def test_auth_with_invalid_token_raises_401():
|
||||
"""Test auth middleware with invalid token raises 401."""
|
||||
from api.middleware.auth import get_current_user
|
||||
from fastapi import HTTPException
|
||||
from fastapi.security import HTTPAuthorizationCredentials
|
||||
from jose import JWTError
|
||||
|
||||
from api.middleware.auth import get_current_user
|
||||
|
||||
with patch("jose.jwt.decode") as mock_decode:
|
||||
mock_decode.side_effect = JWTError("Invalid token")
|
||||
|
||||
@@ -354,10 +359,11 @@ def test_auth_with_invalid_token_raises_401():
|
||||
@pytest.mark.asyncio
|
||||
async def test_rate_limit_middleware_allows_within_limit():
|
||||
"""Test rate limit middleware allows requests within limit."""
|
||||
from api.middleware.rate_limit import RateLimitMiddleware
|
||||
from fastapi import FastAPI, Request
|
||||
from redis.asyncio import Redis
|
||||
|
||||
from api.middleware.rate_limit import RateLimitMiddleware
|
||||
|
||||
app_test = FastAPI()
|
||||
redis_mock = AsyncMock(spec=Redis)
|
||||
redis_mock.incr = AsyncMock(return_value=1)
|
||||
@@ -382,10 +388,11 @@ async def test_rate_limit_middleware_allows_within_limit():
|
||||
@pytest.mark.asyncio
|
||||
async def test_rate_limit_middleware_blocks_over_limit():
|
||||
"""Test rate limit middleware blocks requests over limit."""
|
||||
from api.middleware.rate_limit import RateLimitMiddleware
|
||||
from fastapi import FastAPI, HTTPException, Request
|
||||
from redis.asyncio import Redis
|
||||
|
||||
from api.middleware.rate_limit import RateLimitMiddleware
|
||||
|
||||
app_test = FastAPI()
|
||||
redis_mock = AsyncMock(spec=Redis)
|
||||
redis_mock.incr = AsyncMock(return_value=100) # Over limit
|
||||
|
||||
@@ -4,7 +4,7 @@ Unit tests for core.audit module.
|
||||
|
||||
import base64
|
||||
import os
|
||||
from unittest.mock import AsyncMock, MagicMock, patch
|
||||
from unittest.mock import MagicMock, patch
|
||||
|
||||
import pytest
|
||||
|
||||
@@ -12,7 +12,6 @@ from core.audit.encryptor import DecryptionError, EncryptionError, Encryptor
|
||||
from core.audit.logger import AuditLogger
|
||||
from core.audit.sanitizer import Sanitizer
|
||||
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════
|
||||
# Sanitizer Tests
|
||||
# ═══════════════════════════════════════════════════════════════
|
||||
@@ -316,7 +315,9 @@ async def test_audit_logger_write_node_complete(mock_db_session, mock_settings_w
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_audit_logger_with_otel_tracer(mock_db_session, mock_tool_result, mock_settings_with_keyring):
|
||||
async def test_audit_logger_with_otel_tracer(
|
||||
mock_db_session, mock_tool_result, mock_settings_with_keyring
|
||||
):
|
||||
"""Test that OTel tracer path is executed."""
|
||||
mock_tracer = MagicMock()
|
||||
logger = AuditLogger(db_session_factory=mock_db_session, otel_tracer=mock_tracer)
|
||||
@@ -418,7 +419,9 @@ async def test_audit_logger_exception_handling(mock_db_session, mock_settings_wi
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_audit_logger_encrypted_payload_exception(mock_db_session, mock_settings_with_keyring):
|
||||
async def test_audit_logger_encrypted_payload_exception(
|
||||
mock_db_session, mock_settings_with_keyring
|
||||
):
|
||||
"""Test exception handling in encrypted payload writing."""
|
||||
logger = AuditLogger(db_session_factory=mock_db_session)
|
||||
|
||||
|
||||
@@ -7,15 +7,14 @@ from unittest.mock import AsyncMock, MagicMock, patch
|
||||
|
||||
import pytest
|
||||
import respx
|
||||
from anthropic import APIStatusError, APITimeoutError, RateLimitError
|
||||
from httpx import Request, Response
|
||||
from anthropic import APIStatusError, RateLimitError
|
||||
from httpx import Response
|
||||
|
||||
from core.llm.claude_client import (
|
||||
ClaudeClient,
|
||||
CostCalculation,
|
||||
LLMRateLimitError,
|
||||
LLMServerError,
|
||||
LLMTimeoutError,
|
||||
)
|
||||
|
||||
|
||||
@@ -134,7 +133,7 @@ async def test_call_with_tools_returns_tool_input_dict(mock_settings):
|
||||
},
|
||||
}
|
||||
|
||||
route = respx.post("https://api.anthropic.com/v1/messages").mock(
|
||||
respx.post("https://api.anthropic.com/v1/messages").mock(
|
||||
return_value=Response(200, json=mock_response)
|
||||
)
|
||||
|
||||
@@ -144,7 +143,9 @@ async def test_call_with_tools_returns_tool_input_dict(mock_settings):
|
||||
with patch.object(client.client.messages, "create", new_callable=AsyncMock) as mock_create:
|
||||
# Create mock response object
|
||||
mock_msg = MagicMock()
|
||||
mock_msg.content = [MagicMock(type="tool_use", input={"field1": "value1", "field2": 42})]
|
||||
mock_msg.content = [
|
||||
MagicMock(type="tool_use", input={"field1": "value1", "field2": 42})
|
||||
]
|
||||
mock_msg.usage = MagicMock(
|
||||
input_tokens=100,
|
||||
output_tokens=50,
|
||||
|
||||
@@ -2,9 +2,8 @@
|
||||
Unit tests for core.engine.graph.
|
||||
"""
|
||||
|
||||
import pytest
|
||||
|
||||
from core.engine.graph import build_agent_graph, create_agent_graph_for_tests
|
||||
from core.engine.graph import create_agent_graph_for_tests
|
||||
from core.engine.state import AgentState
|
||||
|
||||
|
||||
@@ -16,7 +15,7 @@ def test_graph_compiles_without_error():
|
||||
|
||||
def test_graph_clarification_routes_to_end():
|
||||
"""Test that clarification_needed routes to END."""
|
||||
graph = create_agent_graph_for_tests()
|
||||
create_agent_graph_for_tests()
|
||||
|
||||
# Create state that needs clarification
|
||||
state = AgentState(
|
||||
@@ -37,7 +36,7 @@ def test_graph_clarification_routes_to_end():
|
||||
|
||||
def test_graph_error_in_plan_routes_to_end():
|
||||
"""Test that error in plan node routes to END."""
|
||||
graph = create_agent_graph_for_tests()
|
||||
create_agent_graph_for_tests()
|
||||
|
||||
# Create state with error
|
||||
state = AgentState(
|
||||
|
||||
@@ -5,7 +5,6 @@ Note: These tests focus on the implemented functionality.
|
||||
Full integration tests will be added once all dependencies are implemented.
|
||||
"""
|
||||
|
||||
from decimal import Decimal
|
||||
|
||||
import pytest
|
||||
|
||||
|
||||
@@ -3,9 +3,6 @@ Unit tests for core.engine.state.AgentState.
|
||||
"""
|
||||
|
||||
import json
|
||||
from decimal import Decimal
|
||||
|
||||
import pytest
|
||||
|
||||
from core.engine.state import AgentState
|
||||
|
||||
|
||||
@@ -6,7 +6,7 @@ from unittest.mock import MagicMock, patch
|
||||
|
||||
import pytest
|
||||
|
||||
from core.router.model_router import ModelConfig, ModelRouter
|
||||
from core.router.model_router import ModelRouter
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
|
||||
@@ -0,0 +1,276 @@
|
||||
"""
|
||||
Unit tests for the Profile schema, loader, and registry.
|
||||
|
||||
Tests cover:
|
||||
- Valid YAML profiles load without errors
|
||||
- Schema validator catches tool-reference violations
|
||||
- Evidence threshold ordering invariant
|
||||
- Registry singleton, cache, and reload behaviour
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import pytest
|
||||
from pydantic import ValidationError
|
||||
|
||||
from core.profile.loader import ProfileValidationError, load_profile
|
||||
from core.profile.registry import ProfileRegistry
|
||||
from core.profile.schema import (
|
||||
EvidenceThresholds,
|
||||
Profile,
|
||||
)
|
||||
|
||||
# ── Fixtures ────────────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
@pytest.fixture(autouse=True)
|
||||
def clear_registry():
|
||||
"""Ensure registry cache is clean before/after each test."""
|
||||
ProfileRegistry.instance().clear()
|
||||
yield
|
||||
ProfileRegistry.instance().clear()
|
||||
|
||||
|
||||
def _minimal_profile(**overrides) -> dict:
|
||||
"""Return a minimal valid Profile dict, with optional field overrides."""
|
||||
base = {
|
||||
"name": "Test Profile",
|
||||
"version": "0.1.0",
|
||||
"description": "Unit test profile",
|
||||
"profile_type": "test",
|
||||
"allowed_tools": ["tool_a", "tool_b"],
|
||||
"workflow_steps": [
|
||||
{
|
||||
"id": "step_01",
|
||||
"tool": "tool_a",
|
||||
"output_key": "result",
|
||||
}
|
||||
],
|
||||
"approval_rules": [
|
||||
{
|
||||
"risk_level": "high",
|
||||
"require_approval": True,
|
||||
"approver_role": "admin",
|
||||
}
|
||||
],
|
||||
"evidence_thresholds": {
|
||||
"output_normal": 0.85,
|
||||
"output_with_warning": 0.60,
|
||||
"reject": 0.60,
|
||||
},
|
||||
"model_routing": {
|
||||
"default": "local",
|
||||
"complex_reasoning": "claude-sonnet-4-6-20260217",
|
||||
},
|
||||
"permissions": {
|
||||
"allowed_roles": ["admin"],
|
||||
"data_scope_required": [],
|
||||
},
|
||||
}
|
||||
base.update(overrides)
|
||||
return base
|
||||
|
||||
|
||||
# ── Presales Profile ─────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
def test_presales_profile_loads_without_error():
|
||||
"""Presales profile.yaml loads and validates successfully."""
|
||||
profile = load_profile("presales")
|
||||
assert profile.profile_type == "presales"
|
||||
assert profile.version == "1.0.0"
|
||||
assert profile.name == "企业预售方案生成"
|
||||
|
||||
|
||||
def test_presales_all_tools_in_allowed_list():
|
||||
"""All workflow step tools in presales profile appear in allowed_tools."""
|
||||
profile = load_profile("presales")
|
||||
for step in profile.workflow_steps:
|
||||
assert step.tool in profile.allowed_tools, (
|
||||
f"Step '{step.id}' tool '{step.tool}' not in allowed_tools"
|
||||
)
|
||||
|
||||
|
||||
def test_presales_workflow_steps_tool_references_valid():
|
||||
"""Presales workflow has at least 3 steps with the expected output keys."""
|
||||
profile = load_profile("presales")
|
||||
assert len(profile.workflow_steps) >= 3
|
||||
output_keys = {s.output_key for s in profile.workflow_steps}
|
||||
assert "enterprise_profile" in output_keys
|
||||
assert "matched_cases" in output_keys
|
||||
assert "final_document" in output_keys
|
||||
|
||||
|
||||
def test_presales_required_sections_present():
|
||||
"""Presales profile defines the required output sections."""
|
||||
profile = load_profile("presales")
|
||||
assert "执行摘要" in profile.required_sections
|
||||
assert "方案设计" in profile.required_sections
|
||||
|
||||
|
||||
def test_presales_input_fields_include_customer_name():
|
||||
"""Presales input_fields contain a required 'customer_name' field."""
|
||||
profile = load_profile("presales")
|
||||
names = {f["name"] for f in profile.input_fields}
|
||||
assert "customer_name" in names
|
||||
customer = next(f for f in profile.input_fields if f["name"] == "customer_name")
|
||||
assert customer.get("required") is True
|
||||
|
||||
|
||||
# ── Security Analysis Profile ────────────────────────────────────────────────
|
||||
|
||||
|
||||
def test_security_profile_loads_without_error():
|
||||
"""Security analysis profile.yaml loads and validates successfully."""
|
||||
profile = load_profile("security_analysis")
|
||||
assert profile.profile_type == "security_analysis"
|
||||
|
||||
|
||||
def test_security_profile_has_high_risk_approval():
|
||||
"""Security profile includes approval rule for high-risk operations."""
|
||||
profile = load_profile("security_analysis")
|
||||
high_risk_steps = [s for s in profile.workflow_steps if s.approval_required]
|
||||
assert len(high_risk_steps) >= 1, "Expected at least one approval-required step"
|
||||
# host_isolation step must require approval
|
||||
isolation_step = next(
|
||||
(s for s in profile.workflow_steps if "isolation" in s.tool), None
|
||||
)
|
||||
assert isolation_step is not None, "Expected a host_isolation workflow step"
|
||||
assert isolation_step.approval_required is True
|
||||
|
||||
|
||||
def test_security_profile_relaxed_evidence_thresholds():
|
||||
"""Security profile uses relaxed output_with_warning threshold (≤ 0.60)."""
|
||||
profile = load_profile("security_analysis")
|
||||
assert profile.evidence_thresholds.output_with_warning <= 0.60
|
||||
|
||||
|
||||
# ── Knowledge QA Profile ──────────────────────────────────────────────────────
|
||||
|
||||
|
||||
def test_knowledge_qa_profile_loads_without_error():
|
||||
"""Knowledge QA profile.yaml loads and validates successfully."""
|
||||
profile = load_profile("knowledge_qa")
|
||||
assert profile.profile_type == "knowledge_qa"
|
||||
|
||||
|
||||
def test_knowledge_qa_only_uses_rag_retriever():
|
||||
"""Knowledge QA profile only allows rag_case_retriever tool."""
|
||||
profile = load_profile("knowledge_qa")
|
||||
assert profile.allowed_tools == ["rag_case_retriever"]
|
||||
|
||||
|
||||
def test_knowledge_qa_strict_reject_threshold():
|
||||
"""Knowledge QA has no warning zone: reject == output_with_warning."""
|
||||
profile = load_profile("knowledge_qa")
|
||||
thresholds = profile.evidence_thresholds
|
||||
assert thresholds.reject == thresholds.output_with_warning, (
|
||||
"Knowledge QA should have no warning zone (reject == output_with_warning)"
|
||||
)
|
||||
assert thresholds.output_normal >= 0.90, (
|
||||
"Knowledge QA requires high evidence quality (output_normal >= 0.90)"
|
||||
)
|
||||
|
||||
|
||||
# ── Schema Validator: Tool References ────────────────────────────────────────
|
||||
|
||||
|
||||
def test_profile_validator_rejects_unknown_tool_in_steps():
|
||||
"""Profile creation raises ValidationError when a step tool is not in allowed_tools."""
|
||||
data = _minimal_profile(
|
||||
workflow_steps=[
|
||||
{
|
||||
"id": "step_01",
|
||||
"tool": "unauthorized_tool", # not in allowed_tools
|
||||
"output_key": "result",
|
||||
}
|
||||
]
|
||||
)
|
||||
with pytest.raises(ValidationError, match="not in allowed_tools"):
|
||||
Profile.model_validate(data)
|
||||
|
||||
|
||||
def test_profile_validator_accepts_valid_tool_references():
|
||||
"""Profile creation succeeds when all step tools are in allowed_tools."""
|
||||
data = _minimal_profile()
|
||||
profile = Profile.model_validate(data)
|
||||
assert profile.workflow_steps[0].tool == "tool_a"
|
||||
|
||||
|
||||
# ── Evidence Thresholds: Logical Ordering ────────────────────────────────────
|
||||
|
||||
|
||||
def test_profile_evidence_thresholds_logical_ordering():
|
||||
"""All three profiles satisfy output_normal >= output_with_warning >= reject."""
|
||||
for profile_type in ("presales", "security_analysis", "knowledge_qa"):
|
||||
profile = load_profile(profile_type)
|
||||
t = profile.evidence_thresholds
|
||||
assert t.output_normal >= t.output_with_warning, (
|
||||
f"[{profile_type}] output_normal ({t.output_normal}) "
|
||||
f"must be >= output_with_warning ({t.output_with_warning})"
|
||||
)
|
||||
assert t.output_with_warning >= t.reject, (
|
||||
f"[{profile_type}] output_with_warning ({t.output_with_warning}) "
|
||||
f"must be >= reject ({t.reject})"
|
||||
)
|
||||
|
||||
|
||||
def test_evidence_thresholds_rejects_illogical_ordering():
|
||||
"""EvidenceThresholds model_validator rejects output_with_warning > output_normal."""
|
||||
with pytest.raises(ValidationError, match="ordering violated"):
|
||||
EvidenceThresholds(output_normal=0.50, output_with_warning=0.80, reject=0.40)
|
||||
|
||||
|
||||
# ── Registry ─────────────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
def test_registry_get_returns_profile():
|
||||
"""Registry.get loads and returns a Profile instance."""
|
||||
registry = ProfileRegistry.instance()
|
||||
profile = registry.get("presales")
|
||||
assert isinstance(profile, Profile)
|
||||
assert profile.profile_type == "presales"
|
||||
|
||||
|
||||
def test_registry_get_caches_profile():
|
||||
"""Registry.get returns the same object on repeated calls (cache hit)."""
|
||||
registry = ProfileRegistry.instance()
|
||||
p1 = registry.get("presales")
|
||||
p2 = registry.get("presales")
|
||||
assert p1 is p2
|
||||
|
||||
|
||||
def test_registry_reload_returns_fresh_profile():
|
||||
"""Registry.reload evicts cache and returns a freshly loaded Profile."""
|
||||
registry = ProfileRegistry.instance()
|
||||
p1 = registry.get("presales")
|
||||
p2 = registry.reload("presales")
|
||||
# Content must be equal (same YAML) but not the same object after reload
|
||||
assert p1.profile_type == p2.profile_type
|
||||
assert p1.version == p2.version
|
||||
|
||||
|
||||
def test_registry_validate_all_succeeds():
|
||||
"""validate_all loads all profiles without raising."""
|
||||
registry = ProfileRegistry.instance()
|
||||
results = registry.validate_all()
|
||||
assert "presales" in results
|
||||
assert "security_analysis" in results
|
||||
assert "knowledge_qa" in results
|
||||
assert all(isinstance(v, Profile) for v in results.values())
|
||||
|
||||
|
||||
def test_registry_raises_on_unknown_profile():
|
||||
"""Registry.get raises ProfileValidationError for a non-existent profile."""
|
||||
registry = ProfileRegistry.instance()
|
||||
with pytest.raises(ProfileValidationError, match="not found"):
|
||||
registry.get("nonexistent_profile_xyz")
|
||||
|
||||
|
||||
# ── Loader Edge Cases ─────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
def test_loader_raises_for_missing_file():
|
||||
"""load_profile raises ProfileValidationError for missing profile type."""
|
||||
with pytest.raises(ProfileValidationError, match="not found"):
|
||||
load_profile("does_not_exist")
|
||||
@@ -2,9 +2,10 @@
|
||||
Unit tests for core.llm.prompt_builder.
|
||||
"""
|
||||
|
||||
import pytest
|
||||
|
||||
from core.llm.prompt_builder import (
|
||||
_SYSTEM_BASE,
|
||||
build_act_step_message,
|
||||
build_ask_user_message,
|
||||
build_plan_message,
|
||||
build_report_message,
|
||||
@@ -99,3 +100,64 @@ def test_build_report_message():
|
||||
assert "doc1" in message
|
||||
assert "doc2" in message
|
||||
assert "Template hint" in message
|
||||
|
||||
|
||||
# ── P10 Verification Tests ──────────────────────────────────────────────────
|
||||
|
||||
|
||||
def test_system_base_contains_governance_rules():
|
||||
"""L0 system prompt must contain all governance rule keywords."""
|
||||
for keyword in ["工具白名单", "高风险写操作", "敏感信息", "引用强制", "幻觉自检"]:
|
||||
assert keyword in _SYSTEM_BASE, f"系统 Prompt 缺少关键治理规则: {keyword}"
|
||||
|
||||
|
||||
def test_build_ask_message_contains_required_fields():
|
||||
"""L1-A ask message must list fields with [必填]/[可选] markers and call extract_user_params."""
|
||||
schema = {
|
||||
"input_fields": [
|
||||
{"name": "customer_name", "description": "客户名称", "required": True},
|
||||
{"name": "industry", "description": "行业", "required": False},
|
||||
]
|
||||
}
|
||||
msg = build_ask_user_message("帮我做预售方案", schema)
|
||||
assert "customer_name" in msg
|
||||
assert "[必填]" in msg
|
||||
assert "[可选]" in msg
|
||||
assert "extract_user_params" in msg
|
||||
|
||||
|
||||
def test_build_act_message_approval_instructions():
|
||||
"""L1-C act message must contain approval_request block and '等待审批' instruction."""
|
||||
step = {
|
||||
"step_id": "s1",
|
||||
"tool_name": "risky_tool",
|
||||
"risk_level": "high",
|
||||
"approval_required": True,
|
||||
}
|
||||
msg = build_act_step_message(step, {}, "")
|
||||
assert "<approval_request>" in msg
|
||||
assert "等待审批" in msg
|
||||
|
||||
|
||||
def test_build_report_message_insufficient_evidence():
|
||||
"""L1-E report for 'insufficient' evidence must include data_insufficient block."""
|
||||
msg = build_report_message("insufficient", {}, [], "")
|
||||
assert "<data_insufficient>" in msg
|
||||
assert "缺少" in msg
|
||||
|
||||
|
||||
def test_build_report_message_limited_evidence_has_warning():
|
||||
"""L1-E report for 'limited' evidence must include ⚠️ and a data-limitation section."""
|
||||
msg = build_report_message("limited", {}, [], "")
|
||||
assert "⚠️" in msg
|
||||
assert "数据局限性" in msg
|
||||
|
||||
|
||||
def test_system_messages_has_cache_control_or_degrades_gracefully():
|
||||
"""build_system_messages must return valid message dicts; cache_control is optional."""
|
||||
msgs = build_system_messages()
|
||||
assert isinstance(msgs, list)
|
||||
assert len(msgs) >= 1
|
||||
# cache_control optional (SDK version differences), but structure must be valid
|
||||
for m in msgs:
|
||||
assert "type" in m and "text" in m
|
||||
|
||||
@@ -0,0 +1,214 @@
|
||||
"""
|
||||
Unit tests for core/verify/scorer.py.
|
||||
|
||||
Covers:
|
||||
- EvidenceScorer score formula and level determination
|
||||
- Edge cases: no citations, no required_fields, bad relevance values
|
||||
- VerifiedCitation construction and model_dump
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from decimal import Decimal
|
||||
|
||||
import pytest
|
||||
|
||||
from core.verify.scorer import EvidenceScorer, ScorerResult, VerifiedCitation
|
||||
|
||||
# ── Fixtures ──────────────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def scorer() -> EvidenceScorer:
|
||||
return EvidenceScorer()
|
||||
|
||||
|
||||
def _citation(relevance: float, source: str = "db", id: str = "c1") -> dict:
|
||||
return {"id": id, "source": source, "relevance": relevance, "content_preview": "preview"}
|
||||
|
||||
|
||||
# ── VerifiedCitation ──────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
def test_verified_citation_model_dump():
|
||||
vc = VerifiedCitation(
|
||||
id="cit_1",
|
||||
source="enterprise_db",
|
||||
relevance=Decimal("0.93"),
|
||||
content_preview="企业信息摘要",
|
||||
section="overview",
|
||||
verified=True,
|
||||
)
|
||||
d = vc.model_dump()
|
||||
assert d["id"] == "cit_1"
|
||||
assert d["source"] == "enterprise_db"
|
||||
assert d["relevance"] == "0.93"
|
||||
assert d["content_preview"] == "企业信息摘要"
|
||||
assert d["section"] == "overview"
|
||||
assert d["verified"] is True
|
||||
|
||||
|
||||
def test_verified_citation_defaults():
|
||||
vc = VerifiedCitation(id="x", source="y", relevance=Decimal("0.5"))
|
||||
assert vc.content_preview == ""
|
||||
assert vc.section == ""
|
||||
assert vc.verified is True
|
||||
|
||||
|
||||
# ── EvidenceScorer: sufficient ────────────────────────────────────────────────
|
||||
|
||||
|
||||
def test_scorer_sufficient_level(scorer: EvidenceScorer):
|
||||
"""High-relevance citations + all required fields → sufficient."""
|
||||
citations = [_citation(0.95), _citation(0.90, id="c2")]
|
||||
step_outputs = {"enterprise_profile": {"customer_name": "ABC", "industry": "制造"}}
|
||||
required_fields = ["customer_name", "industry"]
|
||||
historical_accuracy = Decimal("0.85")
|
||||
|
||||
result = scorer.score(citations, step_outputs, required_fields, historical_accuracy)
|
||||
|
||||
assert result.level == "sufficient"
|
||||
assert result.score >= Decimal("0.80")
|
||||
assert len(result.verified_citations) == 2
|
||||
|
||||
|
||||
# ── EvidenceScorer: limited ───────────────────────────────────────────────────
|
||||
|
||||
|
||||
def test_scorer_limited_level(scorer: EvidenceScorer):
|
||||
"""Medium relevance + partial fields → limited range."""
|
||||
citations = [_citation(0.60)]
|
||||
step_outputs = {"result": {"customer_name": "XYZ"}}
|
||||
required_fields = ["customer_name", "industry"] # industry missing
|
||||
historical_accuracy = Decimal("0.60")
|
||||
|
||||
result = scorer.score(citations, step_outputs, required_fields, historical_accuracy)
|
||||
|
||||
assert result.level in ("limited", "insufficient")
|
||||
assert Decimal("0") <= result.score <= Decimal("1")
|
||||
|
||||
|
||||
# ── EvidenceScorer: insufficient ─────────────────────────────────────────────
|
||||
|
||||
|
||||
def test_scorer_insufficient_no_citations(scorer: EvidenceScorer):
|
||||
"""Zero citations → retrieval_score=0 → likely insufficient."""
|
||||
result = scorer.score(
|
||||
citations=[],
|
||||
step_outputs={"result": {}},
|
||||
required_fields=["field_a", "field_b"],
|
||||
historical_accuracy=Decimal("0.50"),
|
||||
)
|
||||
assert result.level == "insufficient"
|
||||
assert result.score < Decimal("0.55")
|
||||
assert result.verified_citations == []
|
||||
|
||||
|
||||
def test_scorer_insufficient_low_relevance(scorer: EvidenceScorer):
|
||||
"""Very low relevance citations → insufficient."""
|
||||
citations = [_citation(0.10), _citation(0.05, id="c2")]
|
||||
result = scorer.score(
|
||||
citations=citations,
|
||||
step_outputs={},
|
||||
required_fields=["missing_field"],
|
||||
historical_accuracy=Decimal("0.30"),
|
||||
)
|
||||
assert result.level == "insufficient"
|
||||
|
||||
|
||||
# ── EvidenceScorer: edge cases ────────────────────────────────────────────────
|
||||
|
||||
|
||||
def test_scorer_no_required_fields(scorer: EvidenceScorer):
|
||||
"""Empty required_fields → completeness_score=1."""
|
||||
citations = [_citation(0.85)]
|
||||
result = scorer.score(
|
||||
citations=citations,
|
||||
step_outputs={},
|
||||
required_fields=[],
|
||||
historical_accuracy=Decimal("0.80"),
|
||||
)
|
||||
# completeness=1, retrieval~0.85, history=0.8 → score = 0.4*0.85 + 0.3*1 + 0.3*0.8 = 0.82
|
||||
assert result.level == "sufficient"
|
||||
|
||||
|
||||
def test_scorer_string_relevance_value(scorer: EvidenceScorer):
|
||||
"""String numeric relevance value is accepted by the scorer."""
|
||||
citations = [{"id": "c1", "source": "db", "relevance": "0.75"}]
|
||||
result = scorer.score(
|
||||
citations=citations,
|
||||
step_outputs={},
|
||||
required_fields=[],
|
||||
historical_accuracy=Decimal("0.90"),
|
||||
)
|
||||
# relevance=0.75; completeness=1; history=0.9 → score ≥ 0.55
|
||||
assert result.level in ("limited", "sufficient")
|
||||
|
||||
|
||||
def test_scorer_missing_relevance_key(scorer: EvidenceScorer):
|
||||
"""Citation without relevance key → defaults to 0."""
|
||||
citations = [{"id": "c1", "source": "db"}]
|
||||
result = scorer.score(
|
||||
citations=citations,
|
||||
step_outputs={},
|
||||
required_fields=[],
|
||||
historical_accuracy=Decimal("0.85"),
|
||||
)
|
||||
assert isinstance(result, ScorerResult)
|
||||
|
||||
|
||||
def test_scorer_score_clamped_to_one(scorer: EvidenceScorer):
|
||||
"""Score is clamped to [0, 1] even for unusual inputs."""
|
||||
citations = [_citation(1.0), _citation(1.0, id="c2")]
|
||||
result = scorer.score(
|
||||
citations=citations,
|
||||
step_outputs={"k": {"a": 1, "b": 2}},
|
||||
required_fields=["a", "b"],
|
||||
historical_accuracy=Decimal("1.0"),
|
||||
)
|
||||
assert result.score <= Decimal("1")
|
||||
assert result.score >= Decimal("0")
|
||||
|
||||
|
||||
def test_scorer_step_outputs_with_non_dict_values(scorer: EvidenceScorer):
|
||||
"""Non-dict step output values are safely ignored in completeness check."""
|
||||
citations = [_citation(0.85)]
|
||||
step_outputs = {
|
||||
"step1": {"field_a": "value"},
|
||||
"step2": "plain_string", # not a dict, should be ignored
|
||||
"step3": None, # not a dict
|
||||
}
|
||||
result = scorer.score(
|
||||
citations=citations,
|
||||
step_outputs=step_outputs,
|
||||
required_fields=["field_a"],
|
||||
historical_accuracy=Decimal("0.80"),
|
||||
)
|
||||
assert isinstance(result, ScorerResult)
|
||||
|
||||
|
||||
def test_scorer_result_verified_citations_built_correctly(scorer: EvidenceScorer):
|
||||
"""Verified citations carry through with correct attributes."""
|
||||
citations = [
|
||||
{
|
||||
"id": "cite_001",
|
||||
"source": "case_library",
|
||||
"relevance": 0.88,
|
||||
"content_preview": "案例摘要",
|
||||
"section": "intro",
|
||||
}
|
||||
]
|
||||
result = scorer.score(
|
||||
citations=citations,
|
||||
step_outputs={},
|
||||
required_fields=[],
|
||||
historical_accuracy=Decimal("0.80"),
|
||||
)
|
||||
assert len(result.verified_citations) == 1
|
||||
vc = result.verified_citations[0]
|
||||
assert vc.id == "cite_001"
|
||||
assert vc.source == "case_library"
|
||||
assert vc.relevance == Decimal("0.88")
|
||||
assert vc.content_preview == "案例摘要"
|
||||
assert vc.section == "intro"
|
||||
assert vc.verified is True
|
||||
@@ -8,8 +8,6 @@ from typing import Any
|
||||
import pytest
|
||||
from pydantic import BaseModel
|
||||
|
||||
from core.tools.doc_generator import WordDocGeneratorTool
|
||||
from core.tools.enterprise_info import EnterpriseInfoInput, EnterpriseInfoSearchTool
|
||||
from core.tools.base import (
|
||||
BaseTool,
|
||||
RiskLevel,
|
||||
@@ -19,8 +17,10 @@ from core.tools.base import (
|
||||
ToolNotFoundError,
|
||||
ToolResult,
|
||||
)
|
||||
from core.tools.rag_retriever import RagCaseRetrieverTool
|
||||
from core.tools.doc_generator import WordDocGeneratorTool
|
||||
from core.tools.enterprise_info import EnterpriseInfoSearchTool
|
||||
from core.tools.executor import ToolExecutor
|
||||
from core.tools.rag_retriever import RagCaseRetrieverTool
|
||||
from core.tools.registry import ToolRegistry, get_registry
|
||||
|
||||
|
||||
|
||||
@@ -59,6 +59,7 @@ dev = [
|
||||
{ name = "pytest-asyncio" },
|
||||
{ name = "pytest-cov" },
|
||||
{ name = "pytest-mock" },
|
||||
{ name = "pytest-timeout" },
|
||||
{ name = "respx" },
|
||||
{ name = "ruff" },
|
||||
{ name = "testcontainers" },
|
||||
@@ -109,6 +110,7 @@ dev = [
|
||||
{ name = "pytest-asyncio", specifier = ">=0.24.0" },
|
||||
{ name = "pytest-cov", specifier = ">=5.0.0" },
|
||||
{ name = "pytest-mock", specifier = ">=3.14.0" },
|
||||
{ name = "pytest-timeout", specifier = ">=2.3.0" },
|
||||
{ name = "respx", specifier = ">=0.21.0" },
|
||||
{ name = "ruff", specifier = ">=0.6.0" },
|
||||
{ name = "testcontainers", extras = ["postgresql"], specifier = ">=4.8.0" },
|
||||
@@ -2402,6 +2404,18 @@ wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/5a/cc/06253936f4a7fa2e0f48dfe6d851d9c56df896a9ab09ac019d70b760619c/pytest_mock-3.15.1-py3-none-any.whl", hash = "sha256:0a25e2eb88fe5168d535041d09a4529a188176ae608a6d249ee65abc0949630d", size = 10095, upload-time = "2025-09-16T16:37:25.734Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "pytest-timeout"
|
||||
version = "2.4.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "pytest" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/ac/82/4c9ecabab13363e72d880f2fb504c5f750433b2b6f16e99f4ec21ada284c/pytest_timeout-2.4.0.tar.gz", hash = "sha256:7e68e90b01f9eff71332b25001f85c75495fc4e3a836701876183c4bcfd0540a", size = 17973, upload-time = "2025-05-05T19:44:34.99Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/fa/b6/3127540ecdf1464a00e5a01ee60a1b09175f6913f0644ac748494d9c4b21/pytest_timeout-2.4.0-py3-none-any.whl", hash = "sha256:c42667e5cdadb151aeb5b26d114aff6bdf5a907f176a007a30b940d3d865b5c2", size = 14382, upload-time = "2025-05-05T19:44:33.502Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "python-dateutil"
|
||||
version = "2.9.0.post0"
|
||||
|
||||
Reference in New Issue
Block a user