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efoniction/ai-mental-health

★ 14HTMLAudience · developerComplexity · 3/5Setup · moderate

TLDR

A web app for mental health support that lets users log moods, track emotional patterns over time, and chat with an AI, while giving clinicians a dashboard with automated risk-flagging.

Mindmap

mindmap
  root((ai-mental-health))
    User Features
      Daily mood logging
      Emotional trend charts
      Coping suggestions
      Crisis helpline links
    Clinician Dashboard
      Patient mood charts
      Risk flagging
      Audit logs
    Tech Stack
      Python Flask
      SQLite
      Google Gemini Pro
      Chart.js
    Audience
      Mental health support
      Research projects
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Things people build with this

USE CASE 1

Build a self-hosted mood-tracking app where users log emotions daily and see trend charts over weeks.

USE CASE 2

Create a mental health research prototype with an admin dashboard that flags high-risk language in user conversations.

USE CASE 3

Add an AI chatbot companion to a wellness platform using Google Gemini Pro as the conversational engine.

Tech stack

PythonFlaskSQLiteHTMLJavaScriptGoogle Gemini ProChart.js

Getting it running

Difficulty · moderate Time to first run · 30min

Requires a free Google Gemini API key stored in a local config file before starting the server.

No license information was mentioned in the explanation.

In plain English

This repository contains a web application for mental health support, designed to be available at any hour and to provide a private, personalized experience through an AI chatbot. The chatbot is powered by Google Gemini Pro, which is a large language model that handles the conversational side of the platform. For regular users, the app lets you log your mood daily, view charts of your emotional patterns over time, and receive suggestions for coping techniques based on those trends. There is also a quick link to crisis helplines from around the world if someone needs urgent support. Account access is private, with each user having a unique login. The platform also has a separate interface for mental health professionals and administrators. This side shows patient mood charts, behavioral trends, and a system that watches for language suggesting suicidal intent or high-risk states, flagging those cases automatically. Administrators can manage user accounts, review system statistics, and access an audit log that tracks who accessed what data. The technical foundation is a Python web server using the Flask framework, with a local SQLite database for storing records. The front end is built with plain HTML, CSS, and JavaScript, styled with a modern glass-like visual design. Charts are drawn using a library called Chart.js. The README notes the project was developed for research and educational purposes to explore how AI tools can improve access to mental health support. Setup requires a free Google Gemini API key, which you store in a local configuration file before starting the server.

Copy-paste prompts

Prompt 1
Help me set up the ai-mental-health app locally. Walk me through getting a Google Gemini API key, putting it in the config file, and running the Flask server.
Prompt 2
I want to extend ai-mental-health so users can also log sleep quality alongside mood. Show me which database model to update and where to add the chart.
Prompt 3
Explain how the risk-flagging system in ai-mental-health detects suicidal intent and how I could tune the sensitivity of those alerts.
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