Preface¶

The DeepSeek Harness (DSH) ecosystem emphasizes “everything is a plugin.” When developers need to monitor community sentiment or observe public opinion trends in a specific community, they usually have to write their own crawlers and visualization scripts. DeepSeekHarness-community-index aims to use a plugin-based approach to directly display sentiment metrics for the r/DeepSeek community within the DSH environment.

This plugin is maintained by RiRi9909 and is licensed under the MIT License. It registers a panel named “Sentiment Cockpit,” providing developers with a real-time, visual sentiment monitoring entry point.

Core Features¶

This plugin primarily provides the following capabilities:

• Sentiment Cockpit Panel: Registers a “Sentiment Cockpit” section in the DSH settings panel, displaying the DSI Optimism Index (0–100) and Anger Index for the r/DeepSeek community in real time.
• Desktop Widget (macOS): Supports native macOS borderless floating windows, with two states: Mini and Full. It starts in a mini capsule style by default, and can be expanded into a dashboard by clicking.
• Data Refresh and Fault Tolerance: The data pipeline automatically refreshes every 60 minutes by default. If the pipeline fails or the cache is corrupted, it automatically falls back to a built-in snapshot file to ensure that the panel does not display as blank.
• Build-Free Authorization: Implemented in pure JavaScript and contains no build scripts. Installing from Git does not require the allowBuilds authorization.

Installation and Enablement¶

Installation from a Git repository is recommended. Run the following command in a terminal to add the plugin:

dsh plugin --profile web add github:RiRi9909/DeepSeekHarness-community-index

After installation, restart DeepSeek Harness. The “Sentiment Cockpit” section can then be found in the settings menu.

Usage¶

1. View the Panel: Open Settings → Sentiment Cockpit. The panel automatically fetches the latest data and displays the current DSI Index, Anger Index, and last update time.
2. Manual Refresh: Click the “Refresh” button on the panel to immediately rerun the data pipeline (the refresh takes about 1–20 minutes).
3. View a Snapshot: Click the “Open in new tab” button to open a standalone HTML snapshot file in the browser.
4. Configure Refresh Frequency: In the sentiment-cockpit settings namespace, you can adjust intervalMinutes (default 60 minutes, range 10–1440 minutes).

Configuration¶

The desktop widget configuration is located under the sentiment-cockpit settings namespace:

• desktopEnabled: Whether to automatically open the desktop widget when DSH starts (default false).
• desktopMode: The window layering mode. "desktop" indicates that the window is fixed to the desktop layer and can be covered by regular windows; "floating" indicates that it is always on top.
• desktopScale: The window scaling ratio (0.7–1.6).
• desktopX / desktopY: The window coordinates. If set to a negative number (default -1), it will automatically be placed in the bottom-right corner of the screen.

The configuration takes effect after DSH is restarted. The widget position and state are automatically restored after a restart, but each startup still defaults to the Mini state.

Dependencies and Maintenance¶

The plugin depends on the DSH shared runtime environment:

• Host Dependencies: @deepseek-ai/cordis, @deepseek-ai/dsh-settings, @deepseek-ai/dsh-typert-protocol, schemastery.
• Client Dependencies: react, dsh-client-runtime, dsh-client-connection, dsh-client-locale, dsh-client-ui-slots.

The data pipeline only depends on the system Python3 and its standard library, with no additional third-party packages required. If you need to manually update the data snapshot, you can run the following command:

python3 lib/pipeline/run_pipeline.py --out ~/.dsh/storages/dsh-sentiment-cockpit

Notes¶

• Permission Security: The plugin runs with the permissions of the current DSH process. It is recommended to inspect the source code and license before installation.
• System Dependencies: The desktop widget depends on precompiled binary files in the assets/desktop directory, or local swiftc compilation. On non-arm64 Mac architectures, you may need to compile main.swift yourself.
• Data Source: The data is sourced from the Arctic Shift mirror API.

Conclusion¶

DeepSeekHarness-community-index provides developers with a lightweight solution for monitoring r/DeepSeek community sentiment without leaving the DSH interface. Its weighted model based on DSI metrics and fallback mechanism to local snapshots help ensure data observability and stability.

GitHub Repository