@deepseek-ai/dsh-qwen-mm
Qwen-MM-Plugins integration bundle for DeepSeek Harness: bundled multimodal skills, MCP server rows, and an image attachment bridge for text-only model routes
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Qwen-MM-Plugins integration bundle for DeepSeek Harness: bundled multimodal skills, MCP server rows, and an image attachment bridge for text-only model routes
Give DeepSeek Harness agents the ability to read images directly: a model-facing read_image tool that answers questions about an image through any OpenAI-compatible vision endpoint.
Multi-provider AI balance widget for the dsh web sidebar: a live, auto-refreshing balance pill plus a detail popover listing DeepSeek and any added providers (MiMo etc.). Keys are stored per-machine in ~/.dsh/ai-balances.json and resolved from the local credential seam, never hardcoded.
GLM 视觉模型插件:注册 glm-vision 供应商路由(glm-4.6v 系列,image+text 输入声明)并提供 glm_vision 工具,让 DeepSeek 等文本主模型直接调用智谱视觉模型看图。
Eyes for text-only DeepSeek: view_image tool (any OpenAI-compatible VLM, local Ollama or cloud) + chat image-attachment bridge that rewrites pasted/dropped images into view_image path markers
Vision sidecar for text-only coding agents.
DSH 视觉原语工具:参考 DeepSeek《Thinking with Visual Primitives》论文,将图片路由到外部视觉模型并返回带视觉基元的文本分析。纯文本循环,对话模型无需原生视觉能力即可'看见'图片。
Persistent vision plugin for DeepSeek Harness: registers the vision_analyze tool backed by a configurable multimodal model, with a settings-page UI. Zero dependencies.
Vision-augmented DeepSeek adapter plugin for DeepSeek Harness: a vision-capable model describes image input, then a text-only DeepSeek model reasons over the description
Open Eyes for DeepSeek Harness: delegate images to a configurable multimodal model through OpenAI Responses, Chat Completions, or Anthropic Messages.
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
Native interactive visual-reasoning plugin for DeepSeek Harness: precise pixel grounding (SOM grid, zoom, annotate, measure, diff, color, OCR) + MiMo V2.5 multimodal backend, with zero external MCP servers.
Vision + Android UI automation plugin for DeepSeek Harness: gpt-5.6-luna screenshot understanding and real-tap mobile app testing via adb
Plug-and-play image reading for text-only models: admits pasted images, projects them as [Image #N], and provides a first-class read_image tool backed by a configurable vision model, with a 读图 settings page (设置 → 读图) bridged over typert Remote.
为 DeepSeek Harness 提供外部视觉模型能力:纯文本主模型通过 describe_image 工具调用外部视觉模型看图,拿到纯文字描述(多模态补全)。静态 Cordis 插件,随 DSH 启动自动加载。
Adds opt-in image-capable sibling routes for text-only providers and converts image blocks into budgeted, locally enhanced OCR, color-statistics, pixel-scan, and metadata evidence before delegation.
Multi-provider media generation, visual understanding, prompt optimization, and an integrated Iris workbench for DeepSeek Harness.
DSH multimodal input plugin: route file attachments (images, video, audio, text) through per-preset model chains and feed the results to the session model as prompt tokens. Adds a Multimodal settings page.
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。
DeepSeek Harness plugin: multimodal tools (image/audio/video/document understanding, transcription, image generation) via Gemini API or the local Antigravity CLI.
dsh auto-vision bridge: paste an image into a text-only model's composer and a configured multimodal model transcribes it as text, automatically.
DSH host plugin: automatically sends images in user messages to a vision model (default mimo-v2.5 on opencode-go) and feeds the returned text description to the main text model (e.g. deepseek-v4-pro), without touching the visible chat transcript.
Vision for text-only DeepSeek Harness agents: delegate image reading to a one-shot subagent on a configurable vision route (MiniMax / Kimi / any OpenAI-compatible provider), keeping image bytes and the vision model's context out of the main session.
MindsEye: model-driven vision tools, structured evidence, and exact cache for DeepSeek Harness