@goodandready/dsh-vision-bridge
Flagship multimodal vision hub for DeepSeek Harness: ~40 tools, PDF drag-and-drop, LaTeX formulas, complex tables, QR codes, UI flow diagrams, and multi-model consensus.
24 results
Flagship multimodal vision hub for DeepSeek Harness: ~40 tools, PDF drag-and-drop, LaTeX formulas, complex tables, QR codes, UI flow diagrams, and multi-model consensus.
A DeepSeek-style paperclip attach button in the DSH web composer; uploads files to the DSH host (model-aware: native image blocks for multimodal models, file paths for text-only models).
MiniMax multimodal bridge for DeepSeek Harness (DSH). One mmx_bridge tool covers describe/image/video/speech/music/cover/search/quota; optional web_search/read_image takeover; built-in client enhancement renders inline players/previews plus a settings-page management card in the Web GUI.
Automatic Web image-to-text bridge plus vision and OCR tools for DeepSeek Harness
Global model request headers plus image input, reasoning, and DeepSeek system-role compatibility for custom providers
DeepSeek Harness native plugin: vision capabilities for text-only LLMs (describe, OCR, VQA, layout analysis, clipboard)
DeepSeek vision bridge for the dsh web GUI: route image attachments to a vision model (pi-ai / llama.cpp Qwen3-VL) and continue the conversation with the text description on a text-only LLM (DeepSeek)
dsh 插件:给文本模型补一双眼睛 + 给多模态模型补一对观察 UI 渲染的眼睛 —— 设置弹窗选视觉模型 + meow_vision 工具 + meow_preview 组件截图工具
Explicit model input-modality selection for the DeepSeek Harness Web UI
DeepSeek Harness LLM adapter plugin for locally deployed Qwen models behind a vLLM OpenAI-compatible endpoint: per-model multimodal switch, fully configurable reasoning efforts, and a web settings page (client plugin) for editing the deployment from the frontend
Vision + Android UI automation plugin for DeepSeek Harness: gpt-5.6-luna screenshot understanding and real-tap mobile app testing via adb
DSH 插件:可接入识图模型 API(本地大模型识图工具 + 设置界面)。配置 OpenAI 兼容的识图接口(LM Studio / vLLM / Ollama 等),接口留空即不启用识图模型。
dsh auto-vision bridge: paste an image into a text-only model's composer and a configured multimodal model transcribes it as text, automatically.
MindsEye: model-driven vision tools, structured evidence, and exact cache for DeepSeek Harness
Persistent vision plugin for DeepSeek Harness: registers the vision_analyze tool backed by a configurable multimodal model, with a settings-page UI. Zero dependencies.
Per-model vision (image input) toggle for DeepSeek Harness (dsh): list every configured model and flip a switch to enable/disable image support without hand-editing settings.yaml. 为 DeepSeek Harness 提供按模型的「支持图片」开关:无需手改 settings.yaml。
Model-facing describe_image + extract_text tools for the DeepSeek Harness web GUI: gives a text-only model reliable image understanding and OCR through an OpenAI-compatible vision endpoint, with critical-inspection prompts, auto-preprocessing, retries, and a persistent answer cache.
DSH 文件适配插件(面向 DSH 0.1.2-alpha.1):拖拽/粘贴/点击上传/@ 文件引用加入本地文件,以「文件:<路径>」引用随消息发出;主模型按需调用 dshomnifile 工具解析——文本多编码直读、Office/PDF 等文档由 anydoc 提文本、文档内嵌图片与扫描/图文混排 PDF 页由进程内 pdfjs 渲染 + 配置的多模态模型识别(内容哈希缓存 + 并发排队)并组装为 Markdown;聊天内文件卡片可预览图片、本地打开源文件;识别走官方 ctx.llm.stream。
DSH 图片插件,三个工具覆盖三种场景:ask_user_choice 图片/图文混合选择卡(Web GUI 渲染,可放大查看)+ show_images 回复内嵌图片(图文混排)+ save_received_images 盲模型收图存为工作区文件;聊天栏所有图片点击放大,支持滚轮缩放与拖拽平移。来源支持本地路径 / http(s) URL / base64 data URI。零 token 本地渲染,纯插件实现不改核心包。
DeepSeek Harness plugin: PDF→Word (.docx) conversion with layout fidelity (fonts/tables/images/borders), OCR scan mode, and optional multimodal LLM verification. Registers the pdf_to_word model tool.
DSH 插件:提供文本 / 图像 / 视频 / 语音 / 音乐 五个生成工具,模型从 llm-pi-ai 自动发现,含 Settings UI (llm-multimodal namespace)。
Give DeepSeek Harness agents eyes: local image analysis via vision models — um_analyze_img tool + model-capability recognition + hot-switch settings UI
Voice for DeepSeek Harness backed by Xiaomi MiMo: browser-native 🎤/🔊 UI (MiMo TTS read-aloud) + voice_transcribe/voice_speak calling MiMo ASR/TTS directly, with a configurable voice map and in-conversation speech strips. Fork of zhuiyueya/dsh-voice (MIT).
A headless-first macOS Computer Use driver for DeepSeek Harness with AX-first observations, window-bound multimodal evidence, host-owned approval, and evidence-backed action receipts