dsh-koboldcpp-hands
KoboldCpp for DeepSeek Harness - a tool plugin that lets the harness online model hand repetitive text and vision (OCR) labor to a local KoboldCpp (llama.cpp) server.
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KoboldCpp for DeepSeek Harness - a tool plugin that lets the harness online model hand repetitive text and vision (OCR) labor to a local KoboldCpp (llama.cpp) server.
Vision recognition plugin for DeepSeek Harness: paste images into the composer, recognize them via GLM-4V on the host side, and inject the result into the conversation.
飞书与 DeepSeek Harness 双向集成:总结推送、回复路由、绑定 UI 与二维码 provisioning。 / Bidirectional Feishu integration for DeepSeek Harness: summary delivery, reply routing, binding UI, and QR provisioning.
The see tool for the DeepSeek Harness: offline OCR with positions (macOS Vision) + ASCII layout art (PIL) + vision-model semantic description (mimo-v2.5 via the opencode-go gateway). Works with any model, including text-only ones.
DSH bundle: Qwen multimodal bridge — vision (qwen3-vl), speech-to-text (qwen3-asr), text-to-image (qwen-image), via the deepseek-vision skill scripts
Model-facing ocr_image tool that runs local RapidOCR (via a Python subprocess) and returns image text as plain text, so text-only DeepSeek models can read images
Paste images into DeepSeek Harness chat and have them read by a free local backend (macOS Vision / Tesseract) before the text-only DeepSeek model answers
Lightweight DSH upload bridge: images and common documents become workspace paths so a text-only DeepSeek model can read them with Qwen-MM-Plugins vision tools.
DSH plugin: keep text-only models (deepseek-v4-flash / deepseek-v4-pro) as the session default, and automatically route requests that carry image content to a configured vision-capable model (deepseek-v4-flash-vision-exp) 鈥?no manual model switching (periscope).
格物审视面插件:gewu_prep(HTML 逐页截图 + subagent_vision 简报契约生成,宿主直起 Chrome)+ gewu_locate(真值核验:文字定位到页码/行号)。让无视觉能力的主脑经 subagent_vision 完成视觉检验。
A canvas the agent draws on and then sees: eyes_render draws text/shapes in the Web GUI, stores the PNG locally, and hands the result back to the model. Windows-only: eyes_ocr reads text via the built-in Windows OCR engine (Windows.Media.Ocr).
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。
常驻视觉服务:直连视觉模型(默认 opencode-go/minimax-m3,回退 zai-coding-cn/glm-4.6v)。describe_image / subagent_vision 工具 + 粘贴图片自动转译(llm/stream 钩子)+ 输入框视觉状态小胶囊与详情页(活动日志:指令/思考过程/输出)。零子代理、零 agent 上下文开销,按会话记忆窗支持视觉追问与验收。
DeepSeek Harness 原生视觉 Bundle:粘贴或拖入图片,通过托管的 deepseek-vision-mcp 调用 OpenAI 兼容视觉模型。
替换侧边栏左上角的品牌名与构建徽标文案(默认 DSH Local Build + commit hash),经 WebUI 插件配置页卡片实时配置。 | Replace the sidebar's top-left brand name and build-revision badge text (defaults to DSH Local Build + commit hash) via a live settings card in the Plugin Config page.
Infrastructure plugin for dsh: provisions the kimi-webbridge daemon (auto-install with SHA-256 verification, auto-start) and registers the kimi-webbridge skill that documents the full 25-action browser protocol. Registers a thin kimi_webbridge tool (status health check only).
ModLens-style vision bridge for DeepSeek Harness: deepseek-v4-pro as the brain, deepseek-v4-flash-vision-exp as the eyes.
dsh-std Community v0.15 ModelProvider: DeepSeek-V4-Pro with images captioned by V4-Flash-Vision-Exp. Requires @dsh-std/adapter-dsh on DeepSeek Harness.
DSH profile plugin: converts read_image PNG/WebP attachments to opaque sRGB JPEG so LM Studio's openai-completions endpoint accepts them
Automatic per-task model hot-switching for DeepSeek Harness (dsh): image-aware tasks route to the vision model automatically, every other task keeps your default model. Zero extra tokens, no context disturbance.
DeepSeek Harness web plugin: a Model Capabilities settings page for declaring model input modalities, context window, output cap and image budgets without hand-editing settings.yaml.
DSH 模型视觉开关:设置页「模型视觉」行,为 llm-pi-ai 自定义路由下手写声明的模型切换 input 视觉模态(settings.mutate 官方通道,热生效)。
DeepSeek Harness plugin: analyse images out of band with a vision model — pasted images are digested into text before admission and a describe_image tool covers image paths, all without ever changing the session's model.
DeepSeek Harness plugin: transcodes images to a base64-safe format (PNG) before a vision request, fixing gateways like LM Studio that reject non-PNG/JPEG/GIF data URLs with "'url' field must be a base64 encoded image."