dsh-usage-dashboard
Run the following command in DeepSeek Harness:
dsh plugin install gongshiyun/dsh-usage-dashboard
Paste the following prompt into your AI chat to install this plugin:
Run dsh plugin install gongshiyun/dsh-usage-dashboard in your terminal to install; the source code is available at https://github.com/gongshiyun/dsh-usage-dashboard .
About this plugin
Managing a DeepSeek API account often means juggling scattered balance endpoints and raw token logs with no clear sense of what a conversation is really costing or how many turns the balance can still cover. dsh-usage-dashboard brings all of this into a single, at-a-glance dashboard so spending becomes visible, predictable, and easy to plan around.
Under the hood it fetches account balances from the official DeepSeek API and extracts per-conversation token usage from session logs, converting everything into monetary amounts using a built-in pricing history that supports multiple models, peak-and-valley time windows, and multiple effective dates. The dashboard covers three layers: a real-time estimate pinned below the composer (current session cost, remaining balance, estimated turns left, refreshed every 4 seconds); a global conversation table in the settings panel (token and cost breakdown per session, newest first); and per-model aggregates showing average cost, total spend, and how many conversations the balance can still cover. When DeepSeek adjusts pricing, you simply append a new era and older sessions are automatically reconciled at the price in effect at the time.
The plugin is built for developers, tech leads, and teams that call the DeepSeek API at high frequency. Whether tracking a personal token budget or allocating costs across a multi-model project, you get a clear usage picture right inside DSH Desktop or Web without leaving your workspace.
Use Cases
- Check balance and estimated remaining turns before a conversation to avoid mid-session out-of-funds errors
- Review per-session token and cost breakdown in the settings panel for monthly expense reconciliation
- Aggregate spend across models to allocate call quotas sensibly in multi-model projects
Best For
- Independent developers who call the DeepSeek API frequently
- Tech leads responsible for cost allocation across multi-model projects
- AI application teams that need unified management of balance, usage, and spend in one panel
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