Timmy Time — Mission Control

A local-first dashboard for your sovereign AI agents. Talk to Timmy, watch his status, verify Ollama is running — all from a browser, no cloud required.

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Prerequisites

You need three things on your Mac before anything else:

Python 3.11+

python3 --version   # should be 3.11 or higher

If not: brew install python@3.11

Ollama (runs the local LLM)

brew install ollama

Or download from https://ollama.com

Git — already on every Mac.

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Quickstart (copy-paste friendly)

1. Clone the branch

git clone -b claude/run-tests-IYl0F https://github.com/Alexspayne/Timmy-time-dashboard.git
cd Timmy-time-dashboard

2. Create a virtual environment and install

python3 -m venv .venv
source .venv/bin/activate
pip install -e ".[dev]"

3. Pull the model (one-time, ~2 GB download)

Open a new terminal tab and run:

ollama serve

Back in your first tab:

ollama pull llama3.2

4. Start the dashboard

uvicorn dashboard.app:app --reload

Open your browser to http://localhost:8000

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Access from your phone

The dashboard is mobile-optimized. To open it on your phone:

Step 1 — bind to your local network (instead of just localhost):

uvicorn dashboard.app:app --host 0.0.0.0 --port 8000 --reload

Step 2 — find your Mac's IP address:

ipconfig getifaddr en0

This prints something like 192.168.1.42. If you're on ethernet instead of Wi-Fi, try en1.

Step 3 — open on your phone:

Make sure your phone is on the same Wi-Fi network as your Mac, then open:

http://192.168.1.42:8000

(replace with your actual IP)

On mobile the layout switches to a single column — status panels become a horizontal scroll strip at the top, chat fills the rest of the screen. The input field is sized to prevent iOS from zooming in when you tap it.

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What you'll see

The dashboard has two panels on the left and a chat window on the right:

• AGENTS — Timmy's metadata (model, type, version)
• SYSTEM HEALTH — live Ollama status, auto-refreshes every 30 seconds
• TIMMY INTERFACE — type a message, hit SEND, get a response from the local LLM

If Ollama isn't running when you send a message, the chat will show a "Timmy is offline" error instead of crashing.

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Run the tests

No Ollama needed — all external calls are mocked.

pytest

Expected output:

27 passed in 0.67s

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Optional: CLI

With your venv active:

timmy chat "What is sovereignty?"
timmy think "Bitcoin and self-custody"
timmy status

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Big Brain — AirLLM backend (Apple Silicon / large RAM)

Run 70B or 405B models locally with no GPU required, using AirLLM's layer-by-layer loading strategy. On M-series Macs the MLX backend is selected automatically for maximum throughput. Everything stays local. No cloud. No telemetry. Sats are sovereignty, boss.

One-line install

pip install ".[bigbrain]"
# Apple Silicon only — adds the MLX-accelerated backend:
pip install "airllm[mlx]"

Run with the big brain

# Explicit flag — works anywhere airllm is installed:
timmy chat "Explain self-custody" --backend airllm --model-size 70b

# Or set it once in .env and forget about it:
echo "TIMMY_MODEL_BACKEND=auto" >> .env
echo "AIRLLM_MODEL_SIZE=70b"   >> .env
timmy chat "What is sovereignty?"

--backend auto (or TIMMY_MODEL_BACKEND=auto) selects AirLLM automatically on Apple Silicon when the package is installed, and falls back to Ollama everywhere else — so the same .env works on any machine.

Model sizes

Flag	Parameters	Approx. RAM needed
8b	8 billion	~16 GB
70b	70 billion	~140 GB
405b	405 billion	~810 GB

Models are downloaded from HuggingFace on first run and cached locally. You need a HuggingFace account and huggingface-cli login for gated models (Llama 3.1 requires accepting Meta's license at hf.co/meta-llama).

Architecture with AirLLM

timmy chat --backend airllm
    │
    ▼
TimmyAirLLMAgent          (src/timmy/backends.py)
    │
    ├─ Apple Silicon? ──► AirLLMMLX  (MLX tensors, Metal GPU)
    └─ Everything else ──► AutoModel  (PyTorch, CPU/CUDA)
         │
         └─ Layers loaded on-demand from ~/.cache/huggingface/

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Architecture

graph TD
    Phone["📱 Phone / Browser"]
    Browser["💻 Browser"]

    Phone  -->|HTTP + HTMX| FastAPI
    Browser -->|HTTP + HTMX| FastAPI

    subgraph "Local Machine"
        FastAPI["FastAPI\n(dashboard.app)"]
        Jinja["Jinja2 Templates\n+ static CSS"]
        Timmy["Timmy Agent\n(Agno wrapper)"]
        Ollama["Ollama\n:11434"]
        SQLite[("SQLite\ntimmy.db")]

        FastAPI -->|renders| Jinja
        FastAPI -->|/agents/timmy/chat| Timmy
        FastAPI -->|/health/status ping| Ollama
        Timmy   -->|LLM call| Ollama
        Timmy   -->|conversation memory| SQLite
    end

All traffic stays on your local network. No cloud, no telemetry.

Configuration

Override defaults without touching code — create a .env file (see .env.example):

cp .env.example .env
# then edit .env

Variable	Default	Purpose
OLLAMA_URL	http://localhost:11434	Ollama host (useful if Ollama runs on another machine)
OLLAMA_MODEL	llama3.2	LLM model served by Ollama
DEBUG	false	Set true to enable /docs and /redoc

Project layout

src/
  config.py       # pydantic-settings (reads .env)
  timmy/          # Timmy agent — wraps Agno (soul = prompt, body = Agno)
  dashboard/      # FastAPI app + routes + Jinja2 templates
static/           # CSS (dark mission-control theme)
tests/            # pytest suite (27 tests, no Ollama required)
.env.example      # environment variable reference
pyproject.toml    # dependencies and build config

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Troubleshooting

ollama: command not found — Ollama isn't installed or isn't on your PATH. Install via Homebrew or the .dmg from ollama.com.

connection refused in the chat — Ollama isn't running. Open a terminal and run ollama serve, then try again.

ModuleNotFoundError: No module named 'dashboard' — You're not in the venv or forgot pip install -e .. Run source .venv/bin/activate then pip install -e ".[dev]".

Health panel shows DOWN — Ollama isn't running. The chat still works for testing but will return the offline error message.

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Roadmap

Version	Name	Milestone
1.0.0	Genesis	Agno + Ollama + SQLite + Dashboard
2.0.0	Exodus	MCP tools + multi-agent
3.0.0	Revelation	Bitcoin Lightning treasury + single .app