Local GPT-SoVITS text-to-speech for DSH: reads replies aloud, switches voices from the right sidebar, and trains a new voice from a dropped audio sample. First run downloads an 11.4 GB engine and need

China-ready voice input for the composer. Requires a local Python bridge (pip install dashscope websockets, run bridge/voice-bridge.py) — the plugin alone does not work. Browser mic streams 16 kHz PCM

Cloudflare Workers AI media tools for dsh - text-to-image, text-to-speech and speech-to-text. Per-model price badges, a native settings card, reuse of an existing Cloudflare account, and output files

Give your text-only model eyes - chat image attachments are auto-described via a vision model (default prompt), with iterative re-parsing through model-generated prompts when details are missing; syst

by Renji004

Local eyes for text-only models: eyes_render draws text/shapes/Mermaid onto a canvas in the Web GUI, eyes_paste captures pasted images, eyes_ocr reads text via the built-in Windows OCR (offline), and

Local art pipeline for DSH: drives the locally installed SD WebUI and ComfyUI backends through ten image_* tools and an Art Studio sidebar panel with an embedded ComfyUI canvas, post-processes with th

A conversational voice frontend Agent for dsh: speak naturally over ByteDance Duplex, delegate requests to background tasks, and hear their asynchronous results reported by voice.

by shisuiqingqian

DeepSeek Harness Plugin: Reads local videos or web links, returning a timestamped word-by-word transcript along with keyframe images for the model to review frame by frame.

Transcribe local audio and video files offline with a composer panel, a CLI, and an agent skill, powered by SenseVoice int8.

Model-facing image_describe (image recognition) tool over the DashScope OpenAI-compatible API (qwen3.7-flash), plus a paste bridge: on text-only sessions, pasted images auto-convert to file paths at send time and re

by flashyiyi

Voice announcements when a conversation ends (session title, round, outcome) plus live sentence-by-sentence reading of replies, via built-in edge-tts with zero third-party dependencies.

Two-tier image reading for text-only models: fast local OCR (RapidOCR, offline) first, vision-model fallback (modlens).

Pixel-level screenshot diff for visual regression. Two local PNGs in; a machine-readable first line (`PIXEL_CHANGED=true|false`, greppable as an assertion), then the difference ratio, per-region bound

Vision bridge for text-only DeepSeek routes that analyzes attached and local images through configurable OpenAI Responses, Chat Completions, or Anthropic Messages endpoints while leaving image-capable

by davidekingsss

Agent screen capture on macOS and Windows: one tool captures the screen and returns the image itself, so the model sees it without a second call. On Windows a whole burst runs in one engine call; on m

Vision understanding + image generation/editing for DeepSeek Harness (read images with Qwen/OpenAI/Anthropic/Gemini, generate and edit with Qwen-Image). A rework of liustack/modlens (MIT). Remove @liu