dsh-plugin-custom-provider-enhancer
DeepSeek Harness plugin that enhances custom provider setup by auto-discovering models and auto-populating contextWindow, maxTokens, vision, and reasoning capabilities from models.dev
149 results
DeepSeek Harness plugin that enhances custom provider setup by auto-discovering models and auto-populating contextWindow, maxTokens, vision, and reasoning capabilities from models.dev
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.
Transparent image preprocessing route for DeepSeek Harness
Vision toolkit for DeepSeek Harness -- glance, ground, detect, crop CLI tools for text-only agents to understand images
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.
DeepSeek Harness plugin: direct multimodal image transfer declarations + per-session image clearing, reasoning-effort auto-fill, and progressive Figma MCP bridging (design-to-code + AI-driven design).
Extensible animated theme library for DeepSeek Harness
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 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 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.
DSH plugin: prompt the agent to dispatch image recognition to an opencode-go mimo-v2.5 subagent
通过三方多模态 API 为纯文本 LLM 提供图像理解与文档理解能力(OCR、表格、公式、 版面解析、PDF/扫描件→Markdown、截图/照片/图表问答)。使用场景:用户粘贴或给出 图片/PDF 路径时解读内容、从文档提取文字与表格、对截图提问、发票/论文/票据解析。 触发词:图片理解、OCR、文档解析、截图内容、PDF 提取、表格识别、公式识别、票据识别、 扫描件、image、vision。实现为 Python 标准库 CLI(urllib/json/base64),零三方依赖。
DeepSeek Harness 视觉桥:自动发现你已配置的多模态模型,给纯文本主模型装上 vision 工具,识别结果以纯文本返回。零配置,一条命令安装。
On-demand vision for text-only LLMs in DeepSeek Harness: keep pasted/attached images in the backend, and let the model call view_image to look at them anytime via any OpenAI-compatible vision endpoint — as if the model were natively multimodal.
锑元素
Lightweight, route-preserving vision link for DSH: a configured vision model sees while the selected text model stays in control.
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。
Model-facing analyze_image tool for the DeepSeek Harness: multi-modal image understanding via any OpenAI- or Anthropic-compatible vision API, with 8 analysis modes, local path / http(s) URL / data URL input, and a Web UI hint that guides image-incapable models to the reliable local-path route.
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.
88API Image Studio for DSH: six Image2, Image 2.5, and Nano Banana models for text-to-image, multi-reference editing, 2K/4K output, and sequential batches.
DeepSeek Harness Web plugin: per-model input-modality selector on the Models settings page for third-party (pi-ai) providers
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.
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.