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https://github.com/agentscope-ai/ReMe.git
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### 1. Agent Wrapper(统一 Agent 后端抽象) - **`base_agent_wrapper.py`**:`reply()` 返回值从 `tuple[str, Any]` 改为 `dict`(含 `session_id` / `last_message` / `result` / 可选 `structured_output`);`reply_stream()` 改为产出统一的 `StreamChunk`。废弃 `add_tools()`,改为 `add_job_tools(names: list[str])`(按名解析 BaseJob)与 `add_skills()`;新增 `_resolve_job_tools()`、`_merged_kwargs()`、`_chunk()` 辅助方法及 `project_path` / `project_skills_root` 属性。 - **`as_agent_wrapper.py`(AgentScope 后端)**: - 会话持久化重写:`session_path` 落地到 `<vault>/<session_dir>/agentscope/`,`_load_state` 支持 `resume` / `session_id` / `fork_session`,并做 UUID 校验(`_validate_session_id`);`_cleanup_expired_sessions` 按天数清理过期会话。 - 新增内置工具集(`BypassAnalysisBash` + Edit/Glob/Grep/Read/Write),`BypassAnalysisBash` 绕过 AgentScope 自带 Bash 静态分析以让 permission_mode 生效;`_resolve_skills()` 把配置的 skill 暴露给后端,`_load_tool_env()` 注入项目 `.env`。 - `_event_to_chunk()` 把 20+ 种 AgentScope 事件(Reply/Text/Thinking/Data/ToolCall/ToolResult/ModelCall/ExceedMaxIters)归一化为 `StreamChunk`。 - **`cc_agent_wrapper.py`(Claude Code SDK 后端,+551 行)**: - 新增 `_CcFileSessionStore`:基于 vault 的文件型会话存储,实现 append(按 uuid 去重)/ load / list / delete / list_subkeys,并对路径做 `_safe_parts` + `resolve()` 防越界校验。 - `_build_options()`:统一构建 `ClaudeAgentOptions`,处理 skills、disallowed_tools(默认禁 `WebSearch`)、`.env` 注入、Claude Code 的 API 凭据解析(`_claude_code_api_env`,多级 base_url/api_key 回退)、`CLAUDE_CONFIG_DIR` 设置、skill 目录软链接(`_ensure_claude_skill_dir`)。 - `_raw_event_to_chunk()` / `_message_content_to_chunks()`:把 Anthropic 流式事件(message_start/delta/stop、content_block_*)与 SDK 消息块(AssistantMessage/UserMessage/ResultMessage/RateLimitEvent)转换为统一 `StreamChunk`;跟踪 block_id/block_type/tool_call_name 做关联;处理尾部 `"success"` 误报异常的吞掉逻辑。 ### 2. 统一流式协议(StreamChunk / ChunkEnum) - **`stream_chunk.py`**:`StreamChunk` 扩展为承载 AS + CC 双后端完整信息的统一结构,新增 `session_id` / `block_id` / `tool_call_id` / `tool_call_name` / `media_type` / `input_tokens` / `output_tokens` 等字段,纯文本流仍保持轻量。 - **`chunk_enum.py`**:补全生命周期标记 `REPLY_START` / `REPLY_END`,并文档化两套后端事件 → ChunkEnum 的映射。 ### 3. Index 模块重构(变化批次化 + dispatch) - 新增 `_change_batch.py`:`coalesce_changes()` 把同路径多次事件折叠为最终状态(结合 path 存在性判定),`bucket_changes()` 按 watchfiles.Change 分桶。 - 新增 `init_changes.py`(`InitChangesStep`):一次性扫描,对比 file_store / file_catalog 已索引节点计算 added/modified/deleted,写入 `context["changes"]` 后 dispatch。 - 新增 `update_changes.py`:抽象基类 `ChangeApplyStep` 统一 added/modified/deleted 处理与错误收集;`UpdateCatalogStep`(写 file_catalog)、`UpdateIndexStep`(写 file_store,含按后缀解析 chunker)。 - **`watch_changes.py`**:改用 `dispatch_step_specs`(基类提供的 `dispatch_steps()`),每批先 `coalesce_changes` 再 dispatch;默认参数调整(debounce 5000ms / step 1000ms / poll 5000ms)并暴露常量。 - 删除旧步骤:`clear_and_scan` / `foreach_dispatch` / `scan_changes` / `update_catalog`(旧) / `update_index`(旧);`clear_store.py` 取代 clear_and_scan。 ### 4. Evolve / Dream 模块(拆分为多步 pipeline) - 删除旧的单体 `auto_dream.py` / `dream.py` / `dream.yaml`,新增 `dream/` 子包,按 5 个步骤组织: - **`extract.py`**:扫描当日 day-index + daily 笔记,对比 file_catalog 找出 changed/deleted,调用 LLM 全局抽取 `units`(procedure/personal/wiki 三桶)与 `topics`,路径与桶做清洗/路由。 - **`integrate.py`**:逐个 unit 调用 LLM 写入 digest,结构化输出 `IntegrateOutcome`(CREATE/CORROBORATE/REFINE/CORRECT),失败 unit/路径收集回写。 - **`topics.py`**:写 `daily/<date>/interests.yaml`,结合当天已有 + 近 N 天做去重(`normalize_topic`),可走 LLM 或纯规则去重两条路径。 - **`proactive.py`**:读取当日 `interests.yaml`,作为主动推荐话题的入口。 - **`finish.py`**:把变更路径落盘到 dream file_catalog(checkpoint),渲染最终汇总摘要。 - 新增 `schema.py`(`DreamState` 等跨步骤共享状态与结构化输出模型)与 `utils.py`(状态存取、扫描打包、YAML 读写、结构化回复解析等公共函数)。 - `evolve/__init__.py` 导出全部新 step。 ### 5. auto_memory / auto_resource(适配新 Agent API) - **`auto_memory.py`**:会话路径迁移到 `<session_dir>/dialog/<session_id>.jsonl`;改用 `job_tools`;新增 `source_conversation` frontmatter 反向链接(`_session_link`);执行后刷新 day 索引(`refresh_day_index`),并对 session_id 做合法性校验。 - **`auto_resource.py`**:资源改用「同名 daily note」方案(`_compute_note_stem` 取文件 stem);批量处理 `changes: list[dict]`(`_handle_change` 逐项处理,返回逐项结果摘要);agent 会话 id 用稳定的 `uuid5`;同样刷新 day 索引。 ### 6. BaseStep 基类增强 - 新增 `dispatch_steps` / `dispatch_step_specs` 机制:`_resolve_dispatch_step()` 支持字符串或 dict 形式的 step spec,`dispatch_steps()` 复用当前 context 调用下游 step。 - 新增 `config_value()`:按 key 取 app config,缺失时回退 `ApplicationConfig` 默认值。 - 小幅清理:`language` 初始化、`copy()`、`Ref.__init__` 签名精简。 ### 7. Components 改动 - **`file_store/local_file_store.py`**:持久化改用 zstd 压缩(`.jsonl.zst`,通过新 `utils/jsonl_zst.py`);upsert 时先删除旧 chunk 的 keyword 文档;embedding 复用改为 `(text, embedding)` 键控,要求文本一致才复用;新增 `_matches_search_filter()` 对 vector/keyword 搜索做 path/path_prefix/metadata 的统一后过滤。 - **`keyword_index/bm25_index.py`**:索引文件名加入组件名 + tokenizer 指纹(sha256 前 12 位),快照/恢复时校验指纹防配置漂移;空索引 dump 时删除文件,加载失败抛错而非静默。 - **`file_chunker/markdown_file_chunker.py`**:弃用 `python-frontmatter`,改用内置 YAML 解析(非法 YAML 不阻断正文索引),并修正因 frontmatter 占用行号导致的 AST 行号偏移(`line_offset`)。 - **`cron_job.py`**:大幅简化(-187 行),由原来「dispatch 外部 job/step + 多种调度模式」改为「在自身 steps 上跑 cron 表达式」;`Application` 启动顺序随之调整为 base > stream > background > cron。 - 其余小调整:service(base/http/mcp)、file_graph、file_catalog、as_llm、as_embedding、tokenizer、prompt_handler、base_component 的签名/接口微调。 ### 8. Application 生命周期 - `_start()` 启动顺序明确为 components → base → stream → background → cron,启动失败会触发 `_close()` 回滚并 re-raise(不再吞异常)。 - 启动时创建 `session_dir` 目录;新增 `update_component()`(按类型/名就地更新已存在组件,不存在则报错)。 ### 9. File IO / 路径安全 - **`_path.py`**:`resolve_path` 增加 vault 越界防护(`is_relative_to` 校验),禁止 `.` / `..` 路径分量,支持 `allow_empty`。 - **`read.py`**:大文件(超过 `MAX_FILE_READ_BYTES`)走按行读取 `read_file_lines_safe`,避免一次性载入内存。 - **`_file_io.py` / `_daily_index.py` / `_path.py`** 等支持函数补齐(如 `refresh_day_index`、`read_file_lines_safe`)。 - **`env_utils.py`**:新增 `parse_env_file()`,`load_env()` 返回加载到的键值、支持 `override`、对无路径调用做幂等缓存。 ### 10. Config - `ApplicationConfig` 新增 `session_dir`(默认 `reme_session`)。 - `config_parser.py`:环境变量展开后做类型转换(`_convert_value`)、dot-notation 与 key=value 参数校验更严格、配置文件路径支持相对 `_CONFIG_DIR` 查找、根非 dict 报错。 - `default.yaml`:作业编排改用 `init_changes_step` + `dispatch_steps`(index/resource/digest 三个 watch loop 与 reindex);新增 `auto_dream`(4 步)、`proactive` 作业,移除旧 `dream`;file_catalog 增配 `resource` / `digest` / `dream` 实例;LLM 默认值与 Claude Code 凭据配置调整(tool_result_limit 50000、thinking_enable=false 等)。 ### 11. 其它 - 新增 `steps/common/add.py`(`AddStep` 算术 demo)、`channel/__init__.py` 与 common `__init__` 导出整理。 - 新增 4 篇文档:`docs4/auto_dream_logic_and_step_refactor.md`、`docs4/watch_loop_step_refactor_plan.md`、`docs4/todo.md`,以及 `reme_design.md` 更新。 **
252 lines
11 KiB
Python
252 lines
11 KiB
Python
"""Main application entry point."""
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import asyncio
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import heapq
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from concurrent.futures import ThreadPoolExecutor
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from pathlib import Path
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from typing import AsyncGenerator, TypeVar
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from .components import BaseComponent, ApplicationContext
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from .components.job import BackgroundJob, BaseJob, CronJob, StreamJob
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from .components.service import BaseService
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from .enumeration import ComponentEnum
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from .schema import ComponentConfig, Response, StreamChunk
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from .utils import execute_stream_task, print_logo, get_logger
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T = TypeVar("T", bound=BaseComponent)
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_NodeKey = tuple[ComponentEnum, str]
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class Application(BaseComponent):
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"""Wires components from config and runs jobs against them."""
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def __init__(self, **kwargs) -> None:
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self.context = ApplicationContext(**kwargs)
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self._started_components: list[BaseComponent] = []
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self._setup_vault_directories()
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if self.config.enable_logo:
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print_logo(self.config)
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logger = get_logger(log_to_console=self.config.log_to_console, log_to_file=self.config.log_to_file)
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logger.info(f"Initializing {self.config.app_name} Application")
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super().__init__()
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self._init_service()
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self._init_components()
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self._init_jobs()
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@property
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def config(self):
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"""Typed view onto the application config held by the context."""
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return self.context.app_config
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# ----- Wiring (called once during __init__) --------------------------
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def _setup_vault_directories(self) -> None:
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"""Ensure the vault root and configured subdirectories exist on disk."""
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cfg = self.config
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vault_path = Path(cfg.vault_dir).absolute()
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vault_path.mkdir(parents=True, exist_ok=True)
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for subdir in [cfg.metadata_dir, cfg.session_dir, cfg.resource_dir, cfg.daily_dir, cfg.digest_dir]:
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if subdir:
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(vault_path / subdir).mkdir(parents=True, exist_ok=True)
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def _init_service(self) -> None:
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"""Instantiate the single service backend declared in config.service."""
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self.context.service = self._instantiate(
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ComponentEnum.SERVICE,
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self.config.service,
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label="Service",
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expected_type=BaseService,
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)
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def _init_components(self) -> None:
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"""Instantiate every component declared under config.components."""
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for ctype, group in self.config.components.items():
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self.context.components[ctype] = {}
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for name, cfg in group.items():
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self.context.components[ctype][name] = self._instantiate(
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ctype,
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cfg,
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label=f"Component '{name}'",
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expected_type=BaseComponent,
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name=name,
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)
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def _init_jobs(self) -> None:
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"""Instantiate every job declared under config.jobs."""
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for name, cfg in self.config.jobs.items():
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self.context.jobs[name] = self._instantiate(
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ComponentEnum.JOB,
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cfg,
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label=f"Job '{name}'",
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expected_type=BaseJob,
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name=name,
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)
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def _instantiate(
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self,
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ctype: ComponentEnum,
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cfg: ComponentConfig,
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*,
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label: str,
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expected_type: type[T],
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name: str | None = None,
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) -> T:
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"""Resolve cfg.backend through the registry and construct the instance.
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`label` is the human-readable identifier used only in error messages.
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`expected_type` narrows the return type and guards against a backend
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registered under the wrong ComponentEnum.
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`name` is forwarded to the constructor for named components/jobs;
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leave it None for the service, which is keyed solely by type.
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"""
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# Lazy import: the registry self-populates as component modules load.
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from .components import R
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if not cfg.backend:
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raise ValueError(f"{label} is missing the required 'backend' field")
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backend_cls = R.get(ctype, cfg.backend)
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if backend_cls is None:
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raise ValueError(f"Unregistered backend '{cfg.backend}' for {label}")
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params = cfg.model_dump()
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params["app_context"] = self.context
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if name is not None:
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params.setdefault("name", name)
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instance = backend_cls(**params)
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if not isinstance(instance, expected_type):
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got, want = type(instance).__name__, expected_type.__name__
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raise TypeError(f"{label} backend '{cfg.backend}' produced {got}, expected {want} subclass")
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return instance
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# ----- Dependency ordering ------------------------------------------
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def _topological_order(self) -> list[BaseComponent]:
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"""Return components in dependency order via Kahn's algorithm; raise on missing dep or cycle."""
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nodes: dict[_NodeKey, BaseComponent] = {
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(ctype, name): comp for ctype, group in self.context.components.items() for name, comp in group.items()
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}
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in_degree, dependents = self._build_dependency_graph(nodes)
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ready = [k for k, d in in_degree.items() if d == 0]
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heapq.heapify(ready)
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ordered: list[BaseComponent] = []
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while ready:
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key = heapq.heappop(ready)
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ordered.append(nodes[key])
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for downstream in dependents[key]:
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in_degree[downstream] -= 1
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if in_degree[downstream] == 0:
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heapq.heappush(ready, downstream)
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if len(ordered) != len(nodes):
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unresolved = [f"{k[0].value}:{k[1]}" for k, d in in_degree.items() if d > 0]
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raise ValueError(f"Circular dependency detected among: {unresolved}")
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return ordered
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@staticmethod
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def _build_dependency_graph(
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nodes: dict[_NodeKey, BaseComponent],
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) -> tuple[dict[_NodeKey, int], dict[_NodeKey, list[_NodeKey]]]:
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"""Compute in-degree and adjacency lists; raise if a required dep is missing."""
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in_degree: dict[_NodeKey, int] = dict.fromkeys(nodes, 0)
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dependents: dict[_NodeKey, list[_NodeKey]] = {k: [] for k in nodes}
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for key, comp in nodes.items():
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for dep in comp.dependencies:
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dep_key = (dep.ctype, dep.name)
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if dep_key in nodes:
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dependents[dep_key].append(key)
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in_degree[key] += 1
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elif not dep.optional:
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raise ValueError(
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f"Component {key[0].value}:{key[1]} depends on unregistered {dep.ctype.value}:{dep.name}",
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)
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return in_degree, dependents
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# ----- Lifecycle -----------------------------------------------------
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async def _start(self) -> None:
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"""Start components, then jobs as base > stream > background > cron."""
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pool_size = self.config.thread_pool_max_workers
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if pool_size > 0:
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self.context.thread_pool = ThreadPoolExecutor(max_workers=pool_size)
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self.logger.info(f"Thread pool created with max_workers={pool_size}")
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try:
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components = self._topological_order()
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jobs = list(self.context.jobs.values())
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base_jobs = [j for j in jobs if not isinstance(j, (StreamJob, BackgroundJob))]
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stream_jobs = [j for j in jobs if isinstance(j, StreamJob)]
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background_jobs = [j for j in jobs if isinstance(j, BackgroundJob) and not isinstance(j, CronJob)]
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cron_jobs = [j for j in jobs if isinstance(j, CronJob)]
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for c in components + base_jobs + stream_jobs + background_jobs + cron_jobs:
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await self._start_one(c)
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except Exception:
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await self._close()
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raise
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async def _start_one(self, c: BaseComponent) -> None:
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"""Start one component and record it for ordered shutdown."""
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try:
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if isinstance(c, BackgroundJob):
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self.logger.info(f"Starting background job: {c.name}")
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await c.start()
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self._started_components.append(c)
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except Exception as e:
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self.logger.exception(f"Failed to start {c.component_type.value}:{c.name}: {e}")
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raise
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async def _close(self) -> None:
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"""Close in reverse start order so every peer outlives its dependents."""
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for c in reversed(self._started_components):
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try:
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await c.close()
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except Exception as e:
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self.logger.exception(f"Failed to close {c.component_type.value}:{c.name}: {e}")
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self._started_components.clear()
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if self.context.thread_pool is not None:
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self.context.thread_pool.shutdown(wait=True)
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self.context.thread_pool = None
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# ----- Job execution -------------------------------------------------
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async def run_job(self, name: str, /, **kwargs) -> Response:
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"""Execute a registered job by name and return its final Response."""
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if name not in self.context.jobs:
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raise KeyError(f"Job '{name}' not found")
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return await self.context.jobs[name](**kwargs)
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async def update_component(self, component_enum: ComponentEnum | str, name: str, /, **kwargs) -> BaseComponent:
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"""Update an existing component by type/name; never creates missing components."""
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component_enum = ComponentEnum(component_enum)
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group = self.context.components.get(component_enum)
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if not group or name not in group:
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raise KeyError(f"Component '{name}' not found in {component_enum.value}")
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component = group[name]
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for key, value in kwargs.items():
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if not hasattr(component, key):
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raise AttributeError(f"Component {component_enum.value}:{name} has no attribute '{key}'")
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setattr(component, key, value)
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return component
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async def run_stream_job(self, name: str, /, **kwargs) -> AsyncGenerator[StreamChunk, None]:
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"""Execute a streaming job, yielding chunks as they are produced."""
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if name not in self.context.jobs:
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raise KeyError(f"Job '{name}' not found")
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stream_queue: asyncio.Queue = asyncio.Queue()
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task = asyncio.create_task(self.context.jobs[name](stream_queue=stream_queue, **kwargs))
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async for chunk in execute_stream_task(
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stream_queue=stream_queue,
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task=task,
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task_name=name,
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output_format="chunk",
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):
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assert isinstance(chunk, StreamChunk)
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yield chunk
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def run_app(self):
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"""Serve the application through the configured service backend."""
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assert isinstance(self.context.service, BaseService)
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self.context.service.run_app(app=self)
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