Launch and watch Guaardvark's Swarm Orchestrator: parallel coding agents, each in its own git worktree, working a markdown plan and merging back deterministically. Use when the user wants several agents on one codebase at once, says "swarm this", or asks about a running swarm, worktrees, or merge status.
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
Read setup first; needs the swarm plugin (POST /api/plugins/swarm/start).
B=${GUAARDVARK_URL:-http://localhost:5000}. Status is also the MCP tool swarm_status.
A markdown file in the target repo. Each ## heading is one task. Structured fields are optional;
the parser infers file scope from paths in the prose when they are absent:
# Plan: split the settings page
## Extract the GPU panel
- files: frontend/src/pages/SettingsPage.jsx, frontend/src/components/settings/GpuPanel.jsx
- backend: claude
Move the GPU section into its own component with the same props.
## Add a test for the panel
- files: frontend/src/__tests__/GpuPanel.test.jsx
- depends_on: Extract the GPU panel
backend / assign to picks the agent backend (Claude Code, or a local Cline/OpenClaw agent on
Ollama in Flight Mode). Tasks that touch the same files should depend on each other; the parser
warns about conflicts.
curl -s -X POST $B/api/swarm/launch -H 'Content-Type: application/json' -d '{
"plan_path": "/abs/path/repo/docs/plan.md", "repo_path": "/abs/path/repo",
"max_agents": 4, "auto_merge": false, "flight_mode": false, "dry_run": false,
"acknowledge_dirty_tree": false
}'
acknowledge_dirty_tree: true; tell the user what is
uncommitted first.self_code: true targets Guaardvark's own checkout and is only allowed on the configured root.dry_run: true parses the plan and reports tasks and conflicts without starting agents.| call | |
|---|---|
GET $B/api/swarm/status and GET $B/api/swarm/status/<swarm_id> | tasks, states, worktrees |
GET $B/api/swarm/<swarm_id>/logs/<task_id>?lines=100 | one agent's log |
GET $B/api/swarm/<swarm_id>/diff/<task_id> | its diff before merge |
POST $B/api/swarm/<swarm_id>/bus/broadcast | message every agent |
POST $B/api/swarm/merge {"swarm_id": "...", "repo_path": "..."} | merge finished branches in dependency order |
POST $B/api/swarm/cancel | stop |
POST $B/api/swarm/cleanup {"swarm_id": "...", "delete_branches": false} | remove worktrees |
GET $B/api/swarm/templates | saved plan templates |
merge unless the user asked for auto_merge.max_agents at or below the machine's capacity; each Claude agent is a separate session and
each local agent competes for the GPU with generation jobs.还没有评价。欢迎分享你的使用感受。
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Build consistent characters, environments and props in Guaardvark's Cast Library and train LoRAs for them locally (reference photos → vision bible → sample plan → approved samples → training). Use when the user wants the same face or object across images, videos, a music video, or a Film Crew production, or asks to "train a LoRA".
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Code intelligence over repositories Guaardvark has indexed: semantic code search, exact-text search, file listing, PageRank repository map, import dependency graph, reading one class or function, analysis and generated rewrites, plus the System Mapper and self-improvement status. Use when the user asks where something is implemented, how modules depend on each other, or wants an architecture map of an indexed repo.
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Run Guaardvark's five-role Film Crew locally: screenwriter, casting (Cast Library LoRAs), cinematographer storyboards, keyframe renders, editor. Turns a logline or screenplay into a finished short video with human gates at casting and storyboard. Use when the user says "film this", "make a short film", "storyboard this script", or "start the film crew".
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Generate or edit images on the user's own GPU through Guaardvark: single images, instruction edits, background cut-outs, inpaint and outpaint, consistent characters from the Cast Library, and batch runs of many prompts. Use when the user asks to create, draw, render, visualize, edit, or batch-generate images locally.
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Answer from the user's own indexed documents with Guaardvark's local RAG, browse and read indexed files section by section, remember facts across sessions, and process or fetch new material. Use when the user asks what their documents say, wants a source-cited answer from their files, says "remember this", or asks to index a PDF, DOCX, spreadsheet, image or URL.
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Add any Hugging Face image or video model, checkpoint or LoRA to Guaardvark from a URL, list what is installed, and download registry models on request. Use when the user pastes a huggingface.co link or a .safetensors URL, asks "can it run <model>", or wants a new LoRA or checkpoint available in the Studio.
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