Minimal CPU-only Ollama Docker Image

🦙 chat-o-llama: A lightweight, modern web interface for AI conversations with support for both Ollama and llama.cpp backends. Features persistent conversation management, real-time backend switching, intelligent context compression, and a clean responsive UI.

A high-performance Python library for extracting structured content from PDF documents with layout-aware text extraction. pdf_to_json preserves document structure including headings (H1-H6) and body text, outputting clean JSON format.

An LLM-based content moderator. Firefox extension to block webpages unrelated to work, based on page title and URL. Local LLMs with Ollama and Langchain to ensure your browsing history never leaves your device, for complete privacy. Google Gemini also supported.

A high-performance C/C++ inference server for Qwen3-ASR , optimized for CPU-only real-time streaming speech recognition.

CPU-only RAG stack: PDFs→Docling→Ollama→pgvector. Windows/macOS/Linux. Docker Compose. Graph-aware code search + scanned PDF OCR.

LISA: Train 32B-120B language models on limited RAM (8GB). Layer-by-layer processing + LoRA adapters = 97% memory reduction.

Cloud transcription stores your audio. Local alternatives need a GPU. Whiscribe runs on CPU, in your browser, with one Python script.

Image Classification with On-Device Inference, built with Flutter, AI model runs on mobile cpu

Face locking system built on ArcFace (ONNX) and 5-point alignment that recognizes a selected identity, locks onto it, tracks facial actions, and records behavior over time.

Public distributed LLM across any platform

A new one shot face swap approach for image and video domains - version tailored to work on CPU

Pre-built Llama-CPP Wheel for HF Spaces (Python 3.13)

Hybrid RAG on CPU-only SQLite: FTS5 + embeddings + RRF fusion. 235 knowledge sources.

Semantic plagiarism & content originality detector using sentence-transformer embeddings + FAISS. Catches paraphrasing, not just copy-paste. 3 severity levels, originality scoring, HTML/JSON/terminal reports. 100% local, no API keys, CPU-only.

Probabilistic Signed Distance Fusion with View Planning on CPU

One-line TTS for Python. Real speech on any CPU. No GPU, no cloud, no API keys.

Real-time sign language detection & translation using MediaPipe, LSTM, and Gemini 2.5 Flash — with WebSocket streaming, TTS audio output, and a Next.js frontend. CPU-only, low-spec friendly.

CPU-optimized RAG pipeline reducing latency 2.7× (247ms → 92ms). Implements caching, filtering, quantization for production. Complete with FastAPI, Docker, benchmarks, investor materials. The engineering showcase that sells itself.