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Merge pull request #4987 from mrveiss/Dev_new_gui
Merging Dev_new_gui → main. All conflicts resolved (31 files), user_management router gap fixed. Verified no functionality lost from #4571 direct-to-main commit.
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.github/dependabot.yml

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- dependency-name: "vite"
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update-types: ["version-update:semver-major"]
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- package-ecosystem: "npm"
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directory: "/autobot-slm-frontend"
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target-branch: "Dev_new_gui"
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schedule:
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interval: "weekly"
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day: "monday"
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open-pull-requests-limit: 3
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labels:
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- "dependencies"
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- "frontend"
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- package-ecosystem: "github-actions"
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directory: "/"
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target-branch: "Dev_new_gui"

.github/workflows/ci.yml

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cd autobot-frontend
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npm run lint
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- name: Check i18n keys
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run: |
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cd autobot-frontend
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npm run check:i18n
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- name: Run frontend type checking
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run: |
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cd autobot-frontend

.github/workflows/frontend-test.yml

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working-directory: autobot-frontend
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run: npm run lint
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- name: Check i18n keys
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working-directory: autobot-frontend
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run: npm run check:i18n
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- name: Run unit tests
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working-directory: autobot-frontend
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run: npm run test:unit

.idx/dev.nix

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.mcp/package-lock.json

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CLAUDE.md

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Before spawning agents or starting worktree work:
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1. **Verify branch isolation:** `git branch --show-current` in main session. Should be `Dev_new_gui`. If on a feature branch, STOP — you'll break parallel worktrees.
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2. **Create worktrees correctly:** Each issue gets `.worktrees/issue-XXXX/` with dedicated branch. NO shared branches between worktrees.
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3. **Check git status:** `git status` — main session must be clean (no uncommitted changes).
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4. **Verify issue isn't resolved:** Check if issue is already closed or if `Dev_new_gui` already has the fix.
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5. **Confirm approach:** For architectural decisions, state in 1-2 sentences and wait for confirmation.
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2. **Verify Bash is approved:** Main session must have Bash permission approved — sub-agents inherit from parent. If Bash requires a prompt, approve it once before spawning any agents.
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3. **Create worktrees correctly:** Each issue gets `.worktrees/issue-XXXX/` with dedicated branch. NO shared branches between worktrees.
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4. **Check git status:** `git status` — main session must be clean (no uncommitted changes).
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5. **Verify issue isn't resolved:** Check if issue is already closed or if `Dev_new_gui` already has the fix via `git log origin/Dev_new_gui --oneline --grep="#XXXX"`.
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6. **Confirm approach:** For architectural decisions, state in 1-2 sentences and wait for confirmation.
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**Critical:** If you accidentally switched to a feature branch during parallel work, immediately switch back to `Dev_new_gui`. You may have broken active worktrees.
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---
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## Branch Safety (MANDATORY)
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**Never run these operations without explicit user confirmation:**
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- `git reset --hard` — discards uncommitted work permanently
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- `git push --force` / `git push -f` — rewrites remote history
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- `git branch -D` / deleting remote branches — permanent unless reflog exists
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- `git clean -fd` / mass file deletion — unrecoverable
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- `git cherry-pick` across divergent histories — high conflict risk
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- Any operation touching `main` or `master` directly
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**Before any bulk git operation:**
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1. Run `git status` and `git diff --stat` — confirm exactly what will be affected
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2. State the operation and its scope in one sentence to the user before executing
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3. For branch deletions: verify the branch content is merged (`git branch -r --merged origin/Dev_new_gui`) before deleting
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4. For file deletions: `grep -r` to confirm nothing references the files first
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**If something goes wrong:** Stop immediately. Do not attempt recovery with more destructive commands. Report current state to user and wait for instructions.
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**Why:** In past sessions, Claude staged 5,371 files for deletion in a worktree, nearly reset `main` during a cherry-pick with 30+ conflicts, and committed fixes to wrong branches. These incidents required manual recovery.
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---
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## Branching Discipline (Issue #4113)
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**PROTECTED BRANCHES:** Direct commits are blocked by pre-commit hook.
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## Batch Execution Default
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When the user says "implement all X-labeled issues", "fix all Y bugs", or "run `/team-implement` on Z" — **launch immediately without asking for scope clarification.** The pattern is well-established.
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Default behavior:
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- Batch size: 3 agents max per round (API rate limit)
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- All issues get their own worktree: `.worktrees/issue-XXXX/`
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- Main session stays on `Dev_new_gui` — never switches
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- Agents commit locally; main session pushes and creates PRs
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- After each batch: review, merge, file discovery issues, then next batch
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**Do NOT ask:** "Which issues should I include?", "Should I do them in parallel?", "How many at a time?" — just run the pre-flight checklist and start.
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**Only stop to ask** if: a specific issue has unresolved dependencies, an architectural decision is needed, or the pre-flight checklist finds a problem (dirty branch, unresolved PRs, etc.).
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---
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## Parallel Agents Strategy
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When spawning multiple agents for batch work with `/team-implement`:
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## Sub-Agent Permission Enforcement (NEW)
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## Sub-Agent Permission Enforcement (CRITICAL)
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Sub-agents without Bash permissions cannot complete git operations and will stall mid-batch, forcing manual intervention. This is the #1 cause of batch failures.
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**When spawning agents for parallel work:**
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**Required tools for every implementation agent:** `Bash, Read, Edit, Write, Grep, Glob`
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1. **Verify permissions upfront:** Ensure agents have Bash, Read, Edit, Grep tool access
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2. **Document in agent prompt:** "If you lose Bash permissions, STOP and report — don't retry"
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3. **Monitor for permission failures:** After each batch, check for "Permission denied" errors
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4. **Main session as fallback:** If agent fails on git push, main session handles it (main session has full credentials)
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**Every agent prompt MUST include this line:**
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> "You have Bash, Read, Edit, Write, Grep, and Glob permissions. If you lose Bash permissions at any point, STOP immediately and report — do not retry or work around it."
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**Key principle:** Agents commit locally only. Main session (with SSH/credentials) always handles pushes.
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**Pre-launch check:** Before spawning any agent batch, confirm the main session has Bash approved. Sub-agents inherit from the parent session — if Bash requires approval in the main session, it will also require approval in each sub-agent, blocking all parallel work.
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**Main session as fallback:** Agents commit locally only — they do NOT push. Main session handles all git push and `gh pr create` operations (SSH credentials always available in main session).
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**On permission failure:** Do not retry the same agent. Report to user with: which agent failed, at which step, and what was left incomplete. Main session then completes the git operation manually.
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- ✅ Criterion 3 — evidence here"
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```
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### Discovery Issues (File During Every Task)
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While implementing, if you notice **any** bug, inconsistency, dead code, missing test, hardcoded value, or tech debt that is NOT part of the current issue — file a GitHub issue for it immediately. Do not fix it inline, do not add a TODO comment, do not ignore it.
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```bash
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gh issue create --title "discovery(<area>): <what you found>" --body "..." --label "tech-debt"
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```
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**Before closing any issue**, confirm: did I file a GitHub issue for every gap I noticed during implementation? If not, file them now. This is mandatory — not optional.
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**Why:** Gaps noticed inline and not filed are permanently lost. Discovery issues filed during implementation are the primary source of the issue backlog and prevent regressions from accumulating silently.
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### If ANY Criterion Not Met
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- **DO NOT close the issue** — leave it OPEN

README.md

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# AutoBot: Self-Hosted AI Automation Platform
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<div align="center">
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> **Self-Hosted Infrastructure Automation with Conversational AI**
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>
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> AutoBot is a **self-hosted AI platform** that brings conversational AI to distributed Linux administration, fleet management, and infrastructure automation — all from a beautiful, modern interface. Own your data. Control your infrastructure. No vendor lock-in.
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# Your data. Your AI.
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**AutoBot is the self-hosted AI platform that belongs to you — not to us.**
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Feed it your docs, your codebase, your business knowledge.
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Plug in any brain you want — Ollama, OpenAI, Claude, Gemini, or any LLM.
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Your data stays on your machine. Your AI stays yours.
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[Get Started](#quick-start-3-steps) · [Documentation](docs/) · [Community](https://github.com/mrveiss/AutoBot-AI/discussions) · [Sponsor](https://github.com/sponsors/mrveiss)
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[![Docker Smoke Test](https://github.com/mrveiss/AutoBot-AI/actions/workflows/docker-smoke-test.yml/badge.svg)](https://github.com/mrveiss/AutoBot-AI/actions/workflows/docker-smoke-test.yml)
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[![codecov](https://codecov.io/gh/mrveiss/AutoBot-AI/branch/main/graph/badge.svg)](https://codecov.io/gh/mrveiss/AutoBot-AI)
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[![GitHub Sponsors](https://img.shields.io/github/sponsors/mrveiss?label=Sponsor&logo=GitHub&style=flat-square)](https://github.com/sponsors/mrveiss)
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</div>
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---
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> WordPress gave everyone a website. AutoBot gives everyone an AI.
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> Self-hosted. Open source. Yours to extend.
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**AutoBot is not a SaaS subscription. It's infrastructure you own.**
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Deploy it once with Docker Compose. Feed your knowledge base — drag in docs, paste URLs, upload files.
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Connect whatever LLM you trust. Run it forever, on your terms.
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| What you get | What stays yours |
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|---|---|
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| Chat interface | Your prompts |
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| RAG knowledge base | Your documents |
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| Fleet management | Your infrastructure |
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| Plugin ecosystem | Your data |
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## Quick Start (3 Steps)
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### 1. Clone the Repository

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