dsh-qwen-multimodal
DSH bundle: Qwen multimodal bridge — vision (qwen3-vl), speech-to-text (qwen3-asr), text-to-image (qwen-image), via the deepseek-vision skill scripts
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DSH bundle: Qwen multimodal bridge — vision (qwen3-vl), speech-to-text (qwen3-asr), text-to-image (qwen-image), via the deepseek-vision skill scripts
DSH plugin that drives a local macOS camera gesture mouse helper.
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
Vision bundle + plugin for DeepSeek Harness: the describe_image tool reads local images and asks any configured multimodal route, with zero core changes
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
DeepSeek Harness plugin: Codex image generation/edit/vision tools backed by the local codex-image-bridge skill.
Document and image analysis tools for agent harnesses, powered by a local OpenAI Codex CLI.
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。
DSH 插件:通过硅基流动(SiliconFlow)视觉大模型识别/分析图片,支持本地文件路径、http(s) 图片 URL 与 base64 data URL。含持久化的粘贴识别面板(web 端)。
Zero-config local vision and realtime audio routing for DeepSeek Harness
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).
Bridges the four z.ai GLM Coding Plan MCP servers into DeepSeek Harness via the in-box @deepseek-ai/dsh-mcp-client: vision (GLM-4.6V stdio via npx @z_ai/mcp-server), web reader, web search prime, and zread repo MCP (streamable-http at open.bigmodel.cn)
Bridge Apple's on-device Vision framework (macOS) into DeepSeek Harness: OCR, image classification, face detection, and document layout as local dsh tools. No network, no API key, no daemon.
让 dsh 用独立的 OpenAI 兼容视觉模型读图:主对话历史只保留纯文本描述,图片字节不进上下文,纯文本模型也能读图。
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。
Image translation for non-multimodal models via GLM-4V-Flash: intercepts images, generates descriptions, injects as text.
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).
Vision DSH bundle: give the agent screen/window vision — see tool captures via the bundled Python cvision and returns the image natively
ModLens-style vision bridge for DeepSeek Harness: deepseek-v4-pro as the brain, deepseek-v4-flash-vision-exp as the eyes.