mimo

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mimo takes real conversational turns and fine-tunes a local language model on Apple Silicon (Metal/MPS) to replicate the authentic speaking style, vocabulary, and rhythm of individual speakers.

It integrates with the local fleet:

paranco lifts chat exports and archives out of macOS protected folders into ordinary directories.
whatsapp parser directly ingests WhatsApp chat exports (.txt and .zip) for iOS and Android, stripping invisible Unicode markers and formatting multi-line turns.
LoRA on Metal (MPS) trains low-rank adapter weights on Apple Silicon M4 without sending a single byte off the machine.
Ollama Adapter compiles and registers calibrated persona models (e.g. eugenio-clone) for zero-latency inference in the terminal and native app.
Online web sessions are switched off. The page at nerln.github.io/mimo/ no longer collects or sends messages, and nothing goes to the local training corpus from the web.

git clone https://github.com/nerln/mimo
cd mimo
./build.sh                                     # builds Mimo.app
python3 engine/whatsapp_parser.py chat.zip     # imports a WhatsApp export
python3 engine/extract_turns.py                # extracts turns from WhatsApp and Paranco inbox
python3 engine/train_lora.py --speaker Eugenio # trains LoRA on Apple Silicon MPS
python3 engine/ollama_adapter.py --speaker Eugenio --test

The macOS App

A native SwiftUI application (Mimo.app) built with SwiftPM and ad-hoc code signing:

Storage & Paranco: routes inspection, file lift monitoring, and speaker word count statistics.
WhatsApp Import: native NSOpenPanel file picker supporting .txt and compressed .zip exports.
Local Fine-Tuning: speaker selection, base model picker (qwen3:4b-instruct-2507-q4_K_M, olivera:q4), epoch controls, and real-time loss tracking.
Clone Chat: instant conversational interface with the local persona model.
Online Sessions: switched off. Room codes, invite links and dataset synchronization from the web no longer work.