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A simple "Be My Eyes" web app with a llama.cpp/llava backend
| Date | Stars |
|---|---|
| 2026-07-24 | 495 |
| 2026-07-25 | 495 |
| 2026-07-28 | 495 |
| 2026-07-30 | 495 |
| 2026-08-06 | 495 |
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# LLaVaVision  A simple "Be My Eyes" web app with a llama.cpp/llava backend created in about an hour using ChatGPT, Copilot, and some minor help from me, [@lxe](https://twitter.com/lxe). It describes what it sees using [SkunkworksAI BakLLaVA-1](https://huggingface.co/SkunkworksAI/BakLLaVA-1) model via [llama.cpp](https://github.com/ggerganov/llama.cpp) and narrates the text using [Web Speech API](https://developer.mozilla.org/en-US/docs/Web/API/Web_Speech_API). Inspired by [Fuzzy-Search/realtime-bakllava](https://github.com/Fuzzy-Search/realtime-bakllava). ## Getting Started You will need a machine with about ~5 GB of RAM/VRAM for the q4_k version. ### Set up the llama.cpp server (Optional) Install the CUDA toolkit: ```shell sudo apt install nvidia-cuda-toolkit ``` Build llama.cpp (build instructions for various platforms at [llama.cpp build](https://github.com/ggerganov/llama.cpp#build)): ```shell git clone https://github.com/ggerganov/llama.cpp cd llama.cpp mkdir build cd build cmake .. -DLLAMA_CUBLAS=ON # Remove the flag if CUDA is unavailable cmake --build . --config Release ``` Download the models from [ggml_bakllava-1](https://huggingface.co/mys/ggml_bakllava-1/tree/main): ```shell wget https://huggingface.co/mys/ggml_bakllava-1/resolve/main/mmproj-model-f16.gguf wget https://huggingface.co/mys/ggml_bakllava-1/resolve/main/ggml-model-q4_k.gguf # Choose another quant if preferred ``` Start the server (server options detailed [here](https://github.com/ggerganov/llama.cpp/blob/master/examples/server/README.md)): ```shell ./bin/server -m ggml-model-q4_k.gguf --mmproj mmproj-model-f16.gguf -ngl 35 -ts 100,0 # For GPU-only, single GPU # ./bin/server -m ggml-model-q4_k.gguf --mmproj mmproj-model-f16.gguf # For CPU ``` ### Launch LLaVaVision Clone and set up the environment: ```shell git clone https://github.com/lxe/llavavision cd llavavision python3 -m venv venv . ./venv/bin/activate pip install -r requirements.txt ``` Create dummy certificates and start the server. HTTPS is required for mobile video functionality: ```shell openssl req -newkey rsa:4096 -x509 -sha256 -days 365 -nodes -out cert.pem -keyout key.pem flask run --host=0.0.0.0 --key key.pem --cert cert.pem --debug ``` Access https://your-machine-ip:5000 from your mobile device. Optionally, start a local tunnel with ngrok or localtunnel: ```shell npx localtunnel --local-https --allow-invalid-cert --port 5000 ``` ## Acknowledgements and Inspiration - [Fuzzy-Search/realtime-bakllava](https://github.com/Fuzzy-Search/realtime-bakllava) - [Multimodal LLama.cpp](https://github.com/ggerganov/llama.cpp/issues/3332) - [llava-vl.github.io](https://llava-vl.github.io/) - [SkunkworksAI/BakLLaVA-1](https://huggingface.co/SkunkworksAI/BakLLaVA-1)
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Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:82987e3e3279dfaa, topic:llm, topic:llama
matched fp:82987e3e3279dfaa, topic:llamacpp
matched fp:82987e3e3279dfaa, topic:computer-vision
matched fp:82987e3e3279dfaa, topic:multimodal, readme:multimodal