📖 Active Page: Tackling Local AI for the Best Active Recall Experiences

Active Page is a privacy-first, local-LLM-powered reading companion designed to solve the "forgetting curve." By leveraging the cutting-edge Gemma 4 E2B model, it transforms passive reading into an interactive learning session through real-time, contextual active recall—running entirely on your machine.

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⚡ Quick Start

1. Prerequisites

2. Initialization

The init.sh script automates the heavy lifting: it manages dependencies via uv, compiles llama.cpp for your specific hardware, and pulls the optimized Gemma 4 E2B weights.

bash init.sh

Note for Silicon/AMD: If using Apple M-Series or AMD GPUs, edit init.sh to enable GGML_METAL=ON or GGML_HIPBLAS=ON respectively for hardware acceleration.

3. Launch

Launch the inference engine and the interactive web interface simultaneously:

bash run.sh

Access the application at: http://localhost:8000

🔧 Troubleshooting

System Crashing / Out of Memory in the init.sh? If your ram or CPU is limited, adjust the pararrel of building the llama.cpp.

• Decrese the -j
• Ensure no other memory-intensive apps are running.

System Crashing / Out of Memory in the run.sh? If your GPU VRAM is limited, adjust the Offload Layers in run.sh:

• Decrease the -ngl (number of GPU layers) value to shift more work to your CPU.
• Ensure no other memory-intensive apps are running.