llm-cockpit
A local-first, multi-user web interface for Ollama: a dashboard for what's loaded and how it's behaving, plus a Claude-shaped chat / code UI you can pip install and have running in five minutes.
The cockpit assumes you already have Ollama running. It does not install, manage, or supervise Ollama — it talks to it.
Status
v1.0.0 — public PyPI release. The core local cockpit is implemented,
published through PyPI trusted publishing, and smoke-tested on Neuroforge.
See docs/process/SPRINT_STATE.md and
docs/specs/functional/UC-11-pypi-publish.md.
What it does
- Dashboard with placement board. Kanban-style zones —
GPU 0,GPU 1, …,Cross GPU,On Demand. Admin drag-drops model cards to shape what's warm where; non-admin sees the board read-only. Each card is intentionally compact: 30-day calls, cold-load time, single-GPU and tensor/multi-GPU tokens/s, single-GPU and tensor/multi-GPU context, and a temperature-backed heat signal. "Load model" searches the Ollama registry and downloads without leaving the page. GPU panel is optional (nvidia-smi). - Chat. Pick any chat-tagged model from your Ollama install and have a streaming conversation. Per-user history, per-conversation system prompt, code-block highlighting.
- Code. Same shell as Chat, filtered to code-tagged models, with a coder-default system prompt and diff rendering.
- Admin (user management). Add / delete users, set roles on a
chat < code < adminladder, reset passwords. Force first-login password change for any seeded or admin-created account. - Admin (Ollama configuration). Sortable model-management table with tag, placement, keep-alive, performance metrics, per-model test/delete, and sequential "Test all models" progress/ETA. The page also contains the tagging-heuristic editor, code-mode default system prompt, per-model metrics drill-down, and full audit log.
- LAN access. Installer asks whether to bind to
127.0.0.1only or0.0.0.0, so phones / tablets / other laptops on the same LAN can use the cockpit without a reverse proxy. HTTPS is out of scope for v0.1; for off-LAN access use a VPN (Tailscale / WireGuard) or a TLS terminator.
Quick start
# 1. Have Ollama running (https://ollama.com/download)
ollama serve # or: systemctl --user start ollama
# 2. Install the cockpit from PyPI
pipx install llm-cockpit
# 3. Bootstrap (probes Ollama, creates admin / ollama, sets must_change_password)
cockpit-admin init
# 4. Run
cockpit-admin serve
# 5. Open http://localhost:8080 → log in as admin / ollama → change password → use.
Other planned shapes:
cockpit-admin systemd-installon Linux once UC-08 Slice E is re-verified.
Roles (ADR-004)
Each user has one role on a ladder. Higher roles include lower-rung capabilities.
| Role | What it can do |
|---|---|
chat |
Log in, chat with chat-tagged models, see own conversations, change own password. |
code |
Above + code with code-tagged models, see own code conversations. |
admin |
Above + manage users, configure Ollama (tags, pull/delete, defaults), see system-wide metrics + audit log. |
Bootstrap seeds one user: admin / ollama with a forced password change on first login.
Repo layout
src/cockpit/ Python package (planned shape per ADR-002 v1.1)
├── cli.py cockpit-admin entry point
├── main.py FastAPI app
├── routers/ auth, dashboard, chat, code, admin_users, admin_ollama
├── services/ users, model_tags, metrics, audit, settings
├── ports/ LLMChat, Telemetry (hexagonal)
├── adapters/ ollama_chat, telemetry, fake_chat, fake_telemetry
├── models.py / schemas.py
├── migrations/ alembic
├── frontend_dist/ built Next.js static export, bundled at wheel-build time
└── default_config/ model_tag_heuristics.yaml, code_default_system_prompt.md
docs/ mirror of the vault subset (synced at sprint review)
├── PROCESS.md, SPRINT_STATE.md
├── decisions/ ADR-001..004
├── design-principles/ DP-INDEX (inherits from AgenticBlox)
├── specs/{user,functional,test}/ UC-01..UC-12
├── architecture/COMPONENTS.md
└── STATUS.md
scripts/sync-docs-from-vault.sh
Documentation
| Where | What |
|---|---|
docs/PROCESS.md |
Spec-First + 1-week-sprint discipline. |
docs/architecture/COMPONENTS.md |
Component map + the two ports (LLMChat, Telemetry). |
docs/decisions/ |
ADRs. ADR-001 process; ADR-002 stack; ADR-003 public framing; ADR-004 role ladder. |
docs/design-principles/DP-INDEX.md |
Which AgenticBlox DPs we adopt, defer, or skip. |
docs/specs/ |
One folder per spec type (user / functional / test). |
Process
Vault is the source of truth (DP-024); docs/ is the mirror, updated at sprint review by scripts/sync-docs-from-vault.sh.
Status flow Draft → Review → Accepted → In Progress → Done → User Accepted. Implementation only starts on a Functional Spec at status Accepted. Review→Accepted and Done→User Accepted always require explicit owner approval.
Branches: feature/US-NN-short-title → develop → main. Commit prefix: [US-NN] short description.
License
MIT. See LICENSE.
Project home
This repo is the implementation. The design source-of-truth is the project hub in the Obsidian vault at 020 Projects/LLM-Cockpit/.
Metadata
Release files for llm-cockpit 1.0.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| llm_cockpit-1.0.2.tar.gz | 847.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| llm_cockpit-1.0.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 1.7 MB
Release files / llm_cockpit-1.0.2.tar.gz
| Download URL | llm_cockpit-1.0.2.tar.gz |
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