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matterloop-observability

MatterLoop 的事件是业务事实,不是日志字符串。matterloop-observability 把 Core LoopEvent 接到日志、指标、树形 Trace 和评分,同时把日志后端与 OpenTelemetry 的进程级配置留给宿主应用。

pip install matterloop-observability
# 需要 OpenTelemetry 导出时(含 SDK 与 OTLP/HTTP Exporter)
pip install "matterloop-observability[otel]"

一次合理的装配

import logging

from matterloop_observability import (
    CompositeEventPublisher,
    HandlerEventPublisher,
    MetricsHandler,
    PublisherFailureMode,
    Redactor,
    StructuredLoggingHandler,
)

redactor = Redactor(extra_fields=("tenant_secret", "session_credential"))
metrics = MetricsHandler()

events = CompositeEventPublisher(
    publishers=(
        HandlerEventPublisher(
            StructuredLoggingHandler(
                logger=logging.getLogger("app.matterloop.audit"),
                redactor=redactor,
            )
        ),
        HandlerEventPublisher(metrics),
    ),
    failure_mode=PublisherFailureMode.RAISE,
)

将 events 注入 AgentLoop(events=...)。处理器按顺序执行;同步处理器不创建后台队列,也不接管 Logger 或其关闭流程。唯一的例外是下文用于 Trace 导出的 BatchingPipeline:它持有后台守护线程, 由调用方在应用退出前 shutdown()。

失败策略要显式选择

CompositeEventPublisher(publishers, failure_mode) 支持两种策略:

  • LOG_AND_CONTINUE 是默认值,适合可丢失的遥测。单个发布器失败会记录异常,并继续发布后续事件。
  • RAISE 在第一个失败处停止,适合审计不可缺失的场景。代价是可观测性故障可能中断业务闭环。

如果要求“状态提交与审计记录同时成功”,顺序调用几个 Publisher 并不能提供事务保证。应使用 Outbox、持久化事件表或消息系统完成原子交接。

日志里有什么

StructuredLoggingHandler(logger, redactor) 输出单行 JSON,包含事件类型、run_id、Loop 状态、 发生时间、事件说明和请求 metadata。默认 Logger 名称是 matterloop.events;日志格式、轮转、 保留期和访问控制仍由应用配置。

Redactor(extra_fields) 会递归检查映射键,默认识别 token、authorization、cookie、 api_key、password 和 secret,也能命中 access_token 之类的前后缀名称。它不会扫描自由文本: 提示词、模型输出、URL 查询参数和异常堆栈里的秘密仍可能泄漏。不要把凭据放进 goal、detail 或任意字符串 metadata。

指标与 Trace

  • MetricsHandler 保存当前进程内的事件计数,适合测试和轻量诊断。
  • OpenTelemetryMetricsHandler 写入 matterloop.loop.events,只附带事件类型和 Loop 状态。
  • TracingHandler 已废弃:它为每个事件创建孤立的短 Span,无法还原父子关系,请改用下文的 TraceBuilder,它会在后续版本移除。

OpenTelemetryMetricsHandler 与 TracingHandler 只使用 API,宿主必须先配置 SDK、Exporter、采样 和资源属性,构造时缺少依赖会立即抛出 RuntimeError。OtelExporter 例外:它自带 SDK 与 OTLP/HTTP Exporter(由 [otel] extra 提供),缺少依赖时构造抛出 ImportError。

树形 Trace 与评分

TraceBuilder(pipeline) 实现 Core EventPublisher 协议,把生命周期事件流重建为树形跨度结构: 根跨度覆盖整个运行,执行、验证、迭代快照和整体完成度验收各成跨度;验证跨度关闭时会把 VerificationResult.score(0–100)归一提取为 Score。已关闭的跨度和评分进入 BatchingPipeline(exporter, flush_at, flush_interval),由后台守护线程聚批后交给 SpanExporter。

from matterloop_observability import (
    BatchingPipeline,
    CompositeEventPublisher,
    JsonlExporter,
    PublisherFailureMode,
    TraceBuilder,
)

pipeline = BatchingPipeline(
    JsonlExporter("traces.jsonl"),
    flush_at=50,
    flush_interval=5.0,
)
trace_builder = TraceBuilder(pipeline)
events = CompositeEventPublisher(
    publishers=(audit_publisher, trace_builder),
    failure_mode=PublisherFailureMode.RAISE,
)
# 应用退出前:pipeline.shutdown()

JsonlExporter(path) 每行追加一个带 type 字段的 JSON 记录,零额外依赖。OtelExporter(endpoint) 按原父子关系和起止时间把跨度重建到 OTLP/HTTP 后端,评分导出为同一 trace 下名为 score:<name> 的瞬时子跨度。实际 OTel trace/span ID 由 SDK 生成,MatterLoop 的 run_id、span_id 和父标识分别 保存在 matterloop.trace_id、matterloop.span_id、matterloop.parent_span_id 属性中。流水线队列有界 (默认 10000),满时丢新并告警;OTel 需等待根跨度到达以建立公开 API 的父子 context,单运行暂存同样 默认最多 10000 条,超过后丢新并告警。导出失败重试一次后丢弃,任何异常都不会抛回 Loop 主流程。

SpanRecord 是不可变跨度记录:trace_id(即产生跨度的 run_id)、span_id、parent_span_id、 name、observation_type、started_at、ended_at、attributes、level 和 status_message。 Score 是不可变评分:name、value(NUMERIC 归一到 0–1)、data_type、source、run_id、 step_id、comment、evidence 和 timestamp。score_from_verification 完成验证结论到 NUMERIC 评分的映射;score_from_review 接受具备 score/summary/evidence 属性的鸭子类型审查结论, 不要求安装 agents 组件。

生产环境:与数据库共用一条实时 OTel Trace

如果应用还要为 SQLAlchemy、HTTP 客户端或消息队列做 OTel 自动埋点,最佳实践是由应用只创建一个 TracerProvider:先把它设置为全局 Provider,再把同一实例传给 OtelExporter。production preset 识别到 OtelExporter 后,会在 Loop 执行时实时创建 matterloop.run、Planner/Executor/Verifier 和 generation Span;自动 instrumentation 产生的数据库/HTTP Span 会继承当前阶段,成为同一 Trace 的子节点。 阻塞或暂停前,实时发布器会把当前 matterloop.run 的标准 W3C traceparent/tracestate 写入同一次 checkpoint CAS。恢复时从这个上下文创建新的真实子 Span:人工等待不计入执行时长,跨进程恢复仍在同一条 Trace 中,并且后端能找到已导出的真实父节点。checkpoint 只保存 traceparent/tracestate,不会持久化 W3C baggage,避免业务元数据被带入存储。run_id 只作为业务关联标识和查询属性,不决定 OTel Trace ID。

pip install "matterloop-observability[otel]" opentelemetry-instrumentation-sqlalchemy
import os

from opentelemetry import trace
from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
from opentelemetry.instrumentation.sqlalchemy import SQLAlchemyInstrumentor
from opentelemetry.sdk.resources import Resource
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import BatchSpanProcessor

from matterloop_observability import OtelExporter
from matterloop_presets import build_production_runtime

provider = TracerProvider(Resource.create({"service.name": "my-agent-service"}))
provider.add_span_processor(
    BatchSpanProcessor(OTLPSpanExporter(endpoint=os.environ["OTEL_EXPORTER_OTLP_TRACES_ENDPOINT"]))
)
# 一个进程只能设置一次;必须在初始化框架和自动 instrumentation 前完成。
trace.set_tracer_provider(provider)
SQLAlchemyInstrumentor().instrument(engine=engine)

runtime = build_production_runtime(
    model=model_client,
    config=production_config,
    queue_backend=queue_backend,
    run_repository=run_repository,
    checkpoint_store=checkpoint_store,
    audit_publisher=audit_publisher,
    trace_exporter=OtelExporter(tracer_provider=provider),
)

应用关闭时先 await runtime.aclose(),再由应用对它拥有的 Provider 执行 provider.force_flush() 和 provider.shutdown()。不要把 OtelExporter(endpoint=...) 自行创建的内部 Provider 用于数据库自动埋点: 它没有注册成全局 Provider,数据库 Span 会落到另一条 Trace(或被默认 no-op Provider 丢弃);production preset 会为这种配置记录警告,内部 Provider 的关闭也仍由调用方管理。

模型调用跨度

from matterloop_observability import wrap_model_client

client = wrap_model_client(model_client, trace_builder)

TracedModelClient(client, trace_builder, pipeline) 可包装任意 ModelClient:请求 metadata 含 run_id 时记录一个 generation 跨度,内容包含脱敏后的输入消息、采样参数、输出文本和六项 Token 用量,父跨度由 trace_builder 按 run_id/step_id 解析,解析不到时挂到运行根跨度;metadata 缺少 run_id 时直接透传,观测永远不会阻断调用。模型异常会记录 ERROR 跨度并原样继续抛出。 agents 组件的 Planner、Worker、Verifier 和 Reviewer 已在请求 metadata 中写入 run_id、step_id 和 agent,包装注册进 ModelRegistry 的客户端即可自动获得模型跨度;production preset 可通过 trace_exporter 参数一键完成这套装配。传入普通 SpanExporter 时使用离线 TracedModelClient;传入 共享 Provider 的 OtelExporter 时使用实时 OpenTelemetryModelClient,generation 会嵌套在对应阶段下。 见 matterloop-presets。

扩展方式

同步或异步 callable 可用 HandlerEventPublisher(handler) 接入。跨度与评分的批量、重试和背压已由 BatchingPipeline 提供;需要自定义事件去向时,直接实现 Core EventPublisher.publish(event), 在实现内部管理有界队列和关闭流程。

本包当前面向 Core LoopEvent。TeamLoop 事件的数据结构不同,需要单独适配,不能把团队事件发布器 直接塞给这些处理器。生产拓扑和关闭顺序见企业集成指南。

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