Why a Local RAG Chatbot for Trading Research
Most "AI trading assistant" products are black boxes: your notes, strategy docs, and market notes get shipped to a third-party API, billed per token, and stored who-knows-where. For a retail NIFTY trader or a quant researcher, that is the worst of all worlds — you pay continuously, you leak your edge, and you cannot audit what the model actually read.
This guide shows how to build a Retrieval-Augmented Generation (RAG) chatbot that runs 100% locally on an Android phone using Termux + Ollama. It ingests your own research (PDFs, markdown notes, option-chain exports) and answers questions grounded only in that data. No OpenAI key. No Anthropic key. No monthly bill. No data leaving the device.
OBSERVED: Running ollama run llama3.2 on a mid-range phone inside Termux is slow but usable for document Q&A (3–8 tokens/sec). On a laptop it is smooth.
SOURCE: Local testing on Termux 0.118, Ollama 0.3.x, Android 14.
