# kootenpv/neural_complete

A neural network trained to help writing neural network code using autocomplete

Repository: https://github.com/kootenpv/neural_complete
Canonical: https://ross.abutalabs.com/products/neural_complete
Language: Python
License: MIT
License Family: permissive
Last push: 2020-12-23T13:35:35+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3441, "days_push": 2079, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1159, forks 117 (observed 2026-08-28T04:03:48.554928+00:00)

## What it is
Neural Complete is a generative LSTM-based autocomplete system trained on Python Keras source code to help write neural network code. It consists of a Keras-trained backend served with Flask and a thin Angular 2 frontend that displays whole-line code suggestions.

## Use cases
- autocomplete neural network code in python
- train a text generation model on my own source code
- demo of lstm-based code completion
- serve a keras language model with flask
- scrape github for python training data

## When to choose
- you want a small educational example of LSTM text generation for code
- you want to experiment with training autocomplete models on your own corpus
- you need a self-contained demo of keras + flask + angular integration

## When to avoid
- you need production-quality code completion like modern LLM-based assistants
- you want actively maintained software
- you need token-level IDE integration

## Facets
- artifact type: application
- maturity: abandoned
- function: machine-learning, llm-inference, http-server
- domain: machine-learning, deep-learning, developer-tools, web-development
- platform: python, browser
- tags: autocomplete, lstm, keras, code-completion, flask, angular, text-generation, web-server

## Member repositories
- kootenpv/neural_complete (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:48.554928+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:31:54.338564+00:00, confidence not recorded.
  - readme: https://github.com/kootenpv/neural_complete (fetched 2026-08-28T04:03:48.554928+00:00, sha 1fb280a60772)
- Data as of 2026-08-30T08:39:29.467469+00:00.