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dsh-token-stats

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Token usage & cost statistics plugin for DeepSeek Harness — per model / date / session, cost estimation (USD/CNY), CSV/JSON export | DeepSeek Harness Token 用量统计插件:按模型/日期/会话统计用量与费用,支持 CSV/JSON 导出

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READMESource: main@b53474c3

dsh-token-stats

Token usage & cost statistics plugin for DeepSeek Harness (DSH).

Tracks token consumption per model, per date, and per session with cost estimation in USD / CNY, served as a native page under Settings → 📊 Token Stats. Installed as an external DSH plugin, it loads automatically at DSH startup — no manual activation needed.

中文说明

Features

  • 📊 Native settings page (dark/light aware, follows DSH theme tokens, i18n zh/en)
  • 📈 Daily / weekly / monthly trends with an SVG line chart (zero dependencies)
  • 💰 Cost estimation (USD & CNY) from a built-in pricing table for DeepSeek, GPT, Claude, Gemini, Qwen…
  • 🔁 History backfill: scans all persisted session logs at startup, so stats survive restarts
  • ⚡ Fast: batched session-title reads with an in-memory cache (TTL 5 min), single-pass summaries, memoized pricing
  • 📤 CSV / JSON export, filterable by model and session

Screenshot

Token Stats dashboard

Installation

The plugin is installed as an external DSH profile dependency.

  1. Clone / copy this repository to a local folder, e.g. D:\dev\dsh-token-stats

  2. In your DSH profile manifest (~/.dsh/profiles/web/package.json):

    {
      "dependencies": {
        "dsh-token-stats": "file:D:/dev/dsh-token-stats"
      },
      "dsh": {
        "profile": {
          "bundles": ["@deepseek-ai/dsh-base", "@deepseek-ai/dsh-web-app", "dsh-token-stats"]
        }
      }
    }
    
  3. cd ~/.dsh/profiles/web && pnpm install

  4. Restart DSH web. Open Settings → 📊 Token Stats.

cordis.patch.yml declares the bundle-layer mount point so the plugin auto-loads at startup.

How it works

  • Authoritative data = DSH persisted session logs: assistant/message events carry real usage (input / output / cache-read / cache-write / reasoning tokens), request/header events carry provider/model.
  • A one-shot backfill at startup (sessionQuery) rebuilds the in-memory aggregation index from all history (bounded concurrency).
  • llm/stream usage chunks are captured for live (display-only) in-flight totals.
  • When an adapter reports no usage, tokenMeter.estimateMessage is used and the record is flagged estimated.

HTTP API (/token-stats/api)

op description
summary today / week / month / total aggregates
query time series (day/week/month) + per-model / per-session aggregates; filters: model, sessionId, from, to
models built-in pricing table (USD per 1M tokens) + USD→CNY rate
sessions session list (id + title)
export CSV / JSON dump (format=csv|json, optional model / sessionId)

Development

node --check index.js      # server half
node --check client.js     # browser half
node test-plugin.js        # standalone mock tests: correctness + performance benchmarks
.\sync-deploy.ps1          # re-sync sources into the DSH profile (then restart DSH web)

Performance

Measured on the author's machine (14 sessions / ~10k records):

endpoint before after
sessions ~1700 ms (N serial readTitle calls) ~12 ms (one batched readTitleSnapshots + cache)
summary ~110 ms (4× full-array filters) <1 ms (single pass)
query ~10 ms ~18 ms at 10k records (memoized cost)

License

MIT © 2026 quansheng

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