@liangdacheng/dsh-vision-bridge
DSH-native vision bridge for text-only models with native image attachments, multi-image evidence batching, and session-scoped validated Evidence caching.
277 results
DSH-native vision bridge for text-only models with native image attachments, multi-image evidence batching, and session-scoped validated Evidence caching.
Gives a text-only LLM vision capability
Multimodal plugin for DeepSeek Harness: understand images and generate images through configurable OpenAI-compatible or DashScope endpoints.
Popper: a falsification-driven correction loop for agent sessions — claim commitment, gate falsification, and mutually exclusive hypothesis revision, with an append-only evidence ledger
DSH agent tools: slice a large image into labeled tiles (size or columns x rows) with an overview and a visual workbench; read_tiles selects only what the vision model needs — by region, explicit ids, the user's workbench selection, or a named target a vision model grounds on the overview.
DeepSeek Harness (DSH) native plugin: the describe_image tool, a vision bridge (image -> mimo-v2.5 -> text description) over the ctx.fs / ctx.credentials seams
Adaptive image routing for DeepSeek Harness: pass images directly to native multimodal models and transcribe them only for text-only models.
OmniVision for DeepSeek Harness: an OmniParser-powered GUI agent plugin — screen capture, element recognition, click/type automation and a browser vision dock with recognition history, diffing and summary
Bridges images into text for DeepSeek Harness: when the session's selected model cannot see images, a configured vision model describes them and the descriptions enter the durable session history as folded context rows — your message stays untouched.
Transparent image preprocessing route for DeepSeek Harness
mm-vision (通感编码器) for DeepSeek Harness — give any text-only LLM the ability to see images via structured spatial text encoding. Registers the mm_vision tool.
DSH 静默视觉增强:主模型照常选择,图片自动交给固定视觉模型后以隐藏上下文返回主模型。
DeepSeek Harness 原生插件:让纯文本模型(如 DeepSeek)经 agent/pre-step 劫持 + resolveModelInfo 包装自动识别上传图片(qwen-vl),使纯文本对话也能“看见”图片。
DSH 视觉插件(Edge 豆包桥接):通用识图 + 数学建模图专项(几何图形/流程图/图表/表格/公式)+ 不确定项澄清闭环。零成本,免 API Key。
DSH plugin: auto-detect and configure model capabilities (reasoningEfforts + input modalities) for llm-pi-ai. Successor to dsh-reasoning-efforts.
Image routing for text-only models in DeepSeek Harness: a global analyze_image tool (Kimi vision) plus automatic rewriting of pasted images into attachment references when the active model cannot see images.
为 dsh-tool-vision 桥接导出的图片提供对话内联预览:用户粘贴的图片在气泡中显示缩略图,不改变桥接文本与模型行为
Remote SSH workspace and closed-loop deployment Agent for DeepSeek Harness: SSH Files, terminal, remote editing, zero-to-one Bootstrap, Runbooks, automation, Vision/OCR and safe recovery.
DSH plugin: a persistent, per-session Python interpreter provisioned with Biomni's biomedical tool library, plus a Settings section that reports what the interpreter can actually do.
DSH vision bridge (DSH >= 0.1.2-rc.1): when the selected chat model is text-only, attached images are described by a local Ollama VL model (qwen3-vl:8b) with keep_alive VRAM cooling. Install-time patch of dsh-api-session-controller prompt admission + runtime status companion.
DeepSeek Harness plugin: auto-route image-bearing requests to deepseek-v4-flash-vision-exp, then fall back to the original model.
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。
DSH plugin: auto-tiles oversized chat images into labelled grid pieces (row/col metadata, overlap-aware, multi-image group isolation) so the DeepSeek vision model keeps fine detail instead of the ~800px downsample.
Model pricing and capability board for DeepSeek Harness: compare per-1M-token prices, find the cheapest route, and see coding/agentic/vision tags for every LLM you can connect — in the DSH settings UI.