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LocalEyes

Give text based LLMs in Claude Code working eyes using a local Ollama vision model. Screen capture, clipboard reading, and image file analysis — no cloud, no…

// Other[ cli ][ api ][ claude ]#claude#claude-code#computer-vision#llm#local-ai#ollama#open-source#privacy#otherMIT$open-sourceupdated about 23 hours ago
// install
git clone https://github.com/NoPainNullGain/LocalEyes

👁️ LocalEyes

Vision for text-only LLMs in Claude Code. Many flagship models like DeepSeek, CodeLlama, Qwen-Coder, and many other models don't have vision. LocalEyes gives them working eyes via a local Ollama vision model. No cloud, no uploads, no API keys. Private, fast, free.

The problem

DeepSeek is brilliant at reasoning. It's also completely blind. No screenshots, no UIs, no error dialogs — it can't see any of it. The usual fix is uploading your images to GPT-4 or Gemini and asking a second model to describe what's on screen. That breaks the agentic loop. It also means your screenshots are sitting on a cloud provider's server. Neither is ideal.

LocalEyes gives text-only models local vision. Your screen stays on your machine.

Demo

LocalEyes demo

DeepSeek starts blind — then LocalEyes gives it sight. The model describes the app, understands the UI, and can take its own screenshots during agentic work. All local.


Setup (2 minutes)

Prerequisites

ollama pull qwen2.5vl:7b   # one-time, ~4 GB
pip install Pillow

Install

git clone https://github.com/NoPainNullGain/LocalEyes
cd LocalEyes
python install.py

Verify

# Press Win+Shift+S to screenshot something, then:
python ~/.claude/skills/local-eyes/vision.py   # PowerShell / Git Bash
# Or on cmd.exe:
python %USERPROFILE%\.claude\skills\local-eyes\vision.py

Two modes

ModeTriggerCommand
You show the modelYou screenshot something and ask about itpython vision.py
Model looks itselfModel decides it needs visual context during agentic workpython vision.py screen

You show the model

python vision.py                           # describe the clipboard screenshot
python vision.py "What error is shown?"    # focused question

Model looks itself (agentic mode)

python vision.py screen                              # capture full display
python vision.py screen "Transcribe the terminal"    # focused
python vision.py screenshot.png                      # read a saved file

The model will use screen mode on its own during workflows — after builds, during debugging, when implementing UI from mockups. No prompt needed.


Configuration

Edit ~/.claude/skills/local-eyes/config.json:

{
  "ollama_host": "http://localhost:11434",
  "vision_model": "qwen2.5vl:7b",
  "timeout_seconds": 120,
  "temperature": 0.1
}
SettingPurpose
ollama_hostWhere Ollama runs (change for remote GPU servers)
vision_modelModel to use — try qwen3-vl, llama3.2-vision, minicpm-v
timeout_secondsMax wait (increase for large images or slow GPUs)
temperature0.0 = strictly factual, 1.0 = creative descriptions

Override any setting for a single session:

PowerShell: $env:OLLAMA_VISION_MODEL = "qwen3-vl:latest" Bash/Zsh: export OLLAMA_VISION_MODEL="qwen3-vl:latest"

Environment variables override config.json — useful for trying a new model without editing files.


How it works

┌──────────────────────────┐      ┌─────────────────────────┐
│   Claude Code            │      │  Your machine (Ollama)  │
│                          │      │                         │
│  Your model (text)       │──→──→│  qwen2.5vl:7b (vision)  │
│  DeepSeek / text-only    │←──←──│                         │
│                          │ text │  "The screenshot shows  │
│  "I can see that..."     │      │   a terminal with..."   │
└──────────────────────────┘      └─────────────────────────┘
  1. The model runs python vision.py (clipboard, screen, or file)
  2. Script captures the image, base64-encodes it
  3. Sent to Ollama's local API at localhost:11434
  4. Qwen2.5-VL returns a detailed text description
  5. The model reads the description and reasons about it

Nothing leaves your machine.


Platform support

OSScreen captureClipboardStatus
Windows 10/11Fully tested
macOSShould work (untested)
Linux (X11)Should work (untested)
Linux (Wayland)requires scrotYMMV

Troubleshooting

ProblemFix
"Cannot reach Ollama"Run ollama serve in a terminal
"No image on clipboard"Press Win+Shift+S to take a screenshot first
"Model not found"ollama pull qwen2.5vl:7b (~4 GB one-time)
"Pillow is required"pip install Pillow
TimeoutIncrease timeout_seconds in config.json
First request slowModel loads into VRAM on first call (30-60s). Subsequent calls are fast.

Files

LocalEyes/
├── vision.py       # Engine: screen capture, clipboard, Ollama API
├── SKILL.md        # Instructions the model reads to use its eyes
├── config.json     # User settings — edit, don't touch code
├── install.py      # One-command installer
├── LICENSE         # MIT
└── README.md

License

MIT © NoPainNullGain

// compatibility

Platformscli, api
Operating systems
AI compatibilityclaude
LicenseMIT
Pricingopen-source
LanguagePython

// faq

What is LocalEyes?

Give text based LLMs in Claude Code working eyes using a local Ollama vision model. Screen capture, clipboard reading, and image file analysis — no cloud, no uploads, 100% local.. It is open-source on GitHub.

Is LocalEyes free to use?

LocalEyes is open-source under the MIT license, so it is free to use.

What category does LocalEyes belong to?

LocalEyes is listed under other in the Claudeers registry of Claude-compatible tools.

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