TtTRz/dsh-langfuse

Langfuse LLM 可观测性,适用于 DeepSeek Harness —— 每个代理会话对应一棵 OpenTelemetry 跟踪树,包含反馈分数和子代理谱系。

项目介绍Project Overview

dsh-langfuse 是 DeepSeek Harness 的 Langfuse 可观测插件,把每个 agent 会话导出为 OpenTelemetry 追踪树:轮次成 trace、模型步成 generation、工具调用成 span,并带 token、TTFT、反馈分与子代理血缘。适合需要会话追踪、用量统计或反馈分析时启用。默认 DISABLED,需配密钥;投递为至多一次,子代理跨重启血缘不保证。

dsh-langfuse is a Langfuse observability plugin for DeepSeek Harness. It exports each agent session as an OpenTelemetry trace tree: turns become traces, model steps become generations, and tool calls become spans, with token usage, TTFT, feedback scores, and same-process subagent lineage. Use it for session tracing, usage monitoring, or feedback analysis. It is DISABLED by default and requires keys; delivery is at-most-once, and cross-restart subagent lineage is not guaranteed.

或使用命令行安装(适合开发者)Or use CLI install (for developers)

命令行安装CLI Install

dsh plugin --profile web add dsh-langfuse

TtTRz/dsh-langfuse 加入你的 DSH 配置(web profile)即可启用。

READMEREADME

dsh-langfuse

Langfuse LLM observability for DeepSeek Harness — one OpenTelemetry trace tree per agent session, with feedback scores and subagent lineage.

npm version license node downloads

Send every agent session to Langfuse as an OpenTelemetry trace tree — turn → trace, model step → generation, tool call → tool span — with GenAI semantic-convention attributes, token usage, time-to-first-token, and error statuses.

✨ Features

  • 🧵 Full session tracing — every turn, generation, and tool call lands in Langfuse with model, provider, usage (incl. cache-read & reasoning tokens), and TTFT.
  • 🚚 Content-Length transport — spans are delivered as a single write with an explicit Content-Length header, never chunked. Some Langfuse deployments sit behind gateways that mangle chunked POST bodies (400 Failed to parse OTel JSON Trace); this transport sidesteps that class of bugs entirely.
  • 👍 Feedback scores/feedback records become TEXT scores on the session's latest turn trace.
  • 🔗 Subagent lineage — child-session turn traces link to the parent session's trace (same-process).
  • 🎚️ Three sharing modesFULL (live), FEEDBACK_ONLY (export only when the user records feedback), DISABLED (default; nothing leaves the process).
  • 🔒 Opt-in inputs — generation input (system prompt / tools / prompt) is exported only when includeGenerationInput is on.
  • 🛡️ Fail-loud config — bad URLs, missing keys, and invalid bounds throw at plugin load, before any transport exists.

🚀 Quick Start

dsh plugin --profile web add dsh-langfuse

export LANGFUSE_PUBLIC_KEY=pk-lf-...
export LANGFUSE_SECRET_KEY=sk-lf-...
# optional: self-hosted or non-EU region
export LANGFUSE_HOST=https://langfuse.example.com

dsh web   # restart the running instance, then take a turn

With a key present the backend runs in FULL mode; without one it is DISABLED. LANGFUSE_TELEMETRY_MODE=FEEDBACK_ONLY narrows sharing to feedback-gated release, and LANGFUSE_INCLUDE_GENERATION_INPUT=1 exports generation inputs.

The bundled patch disables the base profile's session-telemetry-otel row (the telemetry seam accepts exactly one backend per context) and mounts this one. dsh --profile web --dump-config shows the composed result without booting.

As an explicit cordis.yml row

- id: session-telemetry-langfuse
  name: dsh-langfuse
  config:
    mode: FULL                 # FULL | FEEDBACK_ONLY | DISABLED (default)
    exporter:
      url: https://cloud.langfuse.com/api/public/otel/v1/traces
    auth:
      publicKey: !!js process.env.LANGFUSE_PUBLIC_KEY
      secretKey: !!js process.env.LANGFUSE_SECRET_KEY
    processor: {}              # optional; passed verbatim to BatchSpanProcessor
    includeGenerationInput: false

⚙️ Configuration

Field Default Meaning
mode DISABLED FULL exports every session live; FEEDBACK_ONLY exports the canonical session log only when feedback is recorded; DISABLED constructs nothing.
exporter.url Full OTLP traces endpoint (…/api/public/otel/v1/traces). Required unless DISABLED.
exporter.timeoutMillis 10000 Per-request timeout.
auth.publicKey / auth.secretKey Langfuse project key pair (Basic auth). Required unless DISABLED.
processor {} Passed verbatim to BatchSpanProcessor (scheduledDelayMillis, maxQueueSize, …). Retries (bounded backoff, 6 attempts) live in the exporter.
includeGenerationInput false Export langfuse.observation.input (system prompt / tool schemas / model / user prompt).
maxAttributeChars 16384 Per-attribute payload ceiling; longer payloads are truncated with a …[truncated] marker (the canonical log keeps the full bytes).
shutdownTimeoutMillis 3000 Deadline on the SDK's shutdown drain.
feedbackScoreName user-feedback Langfuse score name for /feedback pushes.

🧭 What appears in Langfuse

dsh session event Langfuse concept
turn/start / turn/end trace (turn N; error end reasons → ERROR status)
step/start + request/header + assistant/message generation (step T.S) — model, provider, output, gen_ai.usage.* tokens
first assistant/chunk of a step langfuse.observation.completion_start_time (TTFT)
tool/call + tool/result tool span (arguments → input, result → output, isError → ERROR)
user/message trace input
feedback/record TEXT score on the session's latest turn trace
subagent session turns trace links to the parent session's trace
agent-error ops record exception event + ERROR status
every other event type (todo, plan, compaction, …) span event on the open turn

Correlation attributes use this package's own vocabulary (dsh.turn_idx, dsh.step_idx, dsh.event_seq, …) so multiple telemetry backends can share one Langfuse project without attribute collisions.

🏗️ How it works

  • A telemetry-seam backend. The harness logs everything model-visible to the canonical session log; this plugin implements SessionTelemetryBackend (@deepseek-ai/dsh-session-telemetry), so it captures every event — including ones it has never heard of — with the seam's consent semantics and redaction waterfall for free.
  • OTel SDK + custom exporter. Spans are built with BasicTracerProvider + BatchSpanProcessor, serialized with @opentelemetry/otlp-transformer, and delivered by a custom SpanExporter with Content-Length and bounded retries.
  • A folding timeline. SessionTimeline replays the flat record stream into span trees keyed by (session.id, turn, step). Span boundaries always use the record's own timestamp — live capture and canonical-log replay produce identical trees.
  • At-most-once delivery (inherited from the seam): the loss window is the crash window; receivers correlate on langfuse.session.id + dsh.turn_idx + dsh.event_seq.

🧪 Development

npm run check   # biome + typecheck + vitest (unit & seam integration) + build

30 tests cover config validation, the folding timeline, the transport (Content-Length, no Transfer-Encoding, retry/backoff), score pushes, and a full seam integration that drives a real SessionTelemetryCoordinator and asserts the wire payload.

⚠️ Limitations

  • One backend per context (the seam throws on duplicates — the bundled patch disables the official OTLP-logs row).
  • Subagent lineage is same-process best-effort (a resumed parent's trace id is unknown across restarts).
  • No durable delivery (at-most-once).
  • Score pushes are fire-and-forget (failures only log).

📄 License

MIT

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