cfdaily
c89863a288
Step 1: 基础设施 - prompt_composer.py: PromptContext 新增 action_type + action_steps 字段 - spawner.py: handler 路径提取 action_type/action_steps 传入 PromptContext - db.py: comments CHECK 约束加入 action_report Step 2: ToolchainHandler 强化 - ToolchainContextSection: 加 steps 渲染 + action_hint（按 action_type） - ToolchainApiSection: 改为 action_report 提交指引 + Gitea 协作指引 - ToolchainConstraintsSection: 5 条强约束 + Red Flags 防self-rationalization - verify_completion: action_report → output → comment 三层 fallback - review_merged 始终通过（纯通知） - infrastructure_failure 始终通过（防递归） - 修复 LENGTH(content) → LENGTH(body) bug - on_failure 三分路: 业务→Gitea PR comment / 系统→Gitea Issue / 基础设施→toolchain task Step 3: toolchain_routes 改造 - 新增 _toolchain_db_path() + _send_toolchain_task() - 所有 8 个 handler 改为 _send_toolchain_task - _send_mail 保留但不再被 toolchain handler 调用 - _send_deploy_failure_mail → _send_deploy_failure_task Step 4: 测试 - 29 个单元测试全部通过 - 全量 456 passed, 3 skipped, 0 failures
130 lines
4.2 KiB
Python
130 lines
4.2 KiB
Python
"""
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prompt_composer.py — PromptSection Protocol + PromptContext + PromptComposer
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拼装器：有序管理 prompt 段落，按优先级排序后合并为最终 prompt。
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"""
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import logging
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from dataclasses import dataclass, field
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from typing import Dict, List, Optional, Protocol, runtime_checkable
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logger = logging.getLogger("moziplus-v2.prompt_composer")
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# ---------------------------------------------------------------------------
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# Section 优先级范围约定
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# ---------------------------------------------------------------------------
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PRIORITY_CONTEXT = 10 # 任务上下文
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PRIORITY_PRIOR = 20 # 前序信息
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PRIORITY_ROLE = 30 # 角色规范
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PRIORITY_API = 40 # API 操作指令
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PRIORITY_CONSTRAINTS = 50 # 硬约束
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PRIORITY_EXTENSION = 60 # 扩展段
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# ---------------------------------------------------------------------------
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# PromptSection Protocol
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# ---------------------------------------------------------------------------
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@runtime_checkable
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class PromptSection(Protocol):
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"""一个 prompt 段"""
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name: str # 段名（去重用，同名覆盖）
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priority: int # 排序优先级（小数字=靠前）
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def render(self, context: "PromptContext") -> str:
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"""渲染此段的文本内容。返回空字符串表示不注入。"""
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...
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def should_include(self, context: "PromptContext") -> bool:
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"""是否注入此段（默认 True，条件段可覆盖）。"""
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...
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# ---------------------------------------------------------------------------
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# PromptContext 数据对象
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# ---------------------------------------------------------------------------
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@dataclass
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class PromptContext:
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"""Prompt 渲染的统一上下文"""
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task_id: str
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title: str
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description: str
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must_haves: str
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project_id: str
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agent_id: str
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task: Optional[Dict] = None
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role: str = "executor"
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spawn_type: str = "executor"
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# mail 专用
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from_agent: str = ""
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mail_type: str = "" # inform / request
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# toolchain 专用
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event_type: str = "" # ci_failure / review_request / ...
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event_data: Dict = field(default_factory=dict)
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action_type: str = "" # 动作分类（review_result / ci_failure / ...）
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action_steps: list = field(default_factory=list) # 结构化编号步骤列表
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# 前序产出
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depends_on_outputs: Optional[List] = None
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# ---------------------------------------------------------------------------
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# PromptComposer 拼装器
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# ---------------------------------------------------------------------------
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class PromptComposer:
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"""有序拼装 prompt sections"""
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SEPARATOR = "\n\n---\n\n"
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TOKEN_BUDGET_WARN = 800 # token 预算警告阈值
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CHARS_PER_TOKEN = 3.5 # 估算比率
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def __init__(self) -> None:
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self._sections: List[PromptSection] = []
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def add(self, section: PromptSection) -> None:
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"""添加一个 section（同名覆盖）"""
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self._sections = [s for s in self._sections if s.name != section.name]
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self._sections.append(section)
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def add_many(self, sections: List[PromptSection]) -> None:
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"""批量添加"""
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for s in sections:
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self.add(s)
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def compose(self, context: PromptContext) -> str:
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"""拼装最终 prompt
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1. 过滤 should_include=False 的段
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2. 按 priority 排序
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3. 逐段 render
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4. 过滤空段
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5. 用分隔符连接
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6. Token 预算警告（不截断）
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"""
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active = [s for s in self._sections if s.should_include(context)]
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active.sort(key=lambda s: s.priority)
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parts = [s.render(context) for s in active]
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parts = [p for p in parts if p.strip()]
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result = self.SEPARATOR.join(parts)
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# Token 估算
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tokens = max(1, int(len(result) / self.CHARS_PER_TOKEN))
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logger.debug(
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"Composed prompt from %d sections, %d tokens",
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len(parts), tokens,
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)
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if tokens > self.TOKEN_BUDGET_WARN:
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logger.warning(
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"Prompt exceeds %d token budget: %d tokens (task_id=%s)",
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self.TOKEN_BUDGET_WARN, tokens, context.task_id,
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)
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return result
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