Mifos Community AI

A comprehensive AI-powered toolkit for the Mifos community, featuring intelligent chatbots, automation tools, translation utilities, and voice-driven banking interfaces. This project aims to provide self-service support, enhance developer productivity, and simplify access to Mifos ecosystem resources through advanced Generative AI technologies.

Overview
Key Components
Quick Start
Project Structure
Technologies Used
Contributing
Links and Resources

Overview

As the Mifos community around its core products (Mifos X, Payment Hub EE, Mobile Applications, and Mifos Gazelle) grows rapidly, this repository provides a suite of AI-powered tools to support implementors, developers, and new users. The tools simplify finding relevant content across multiple sources, automate repetitive tasks, and enable innovative interfaces for banking applications.

Key Components

1. RAG-Based Chatbots

Retrieval-Augmented Generation (RAG) chatbots for querying Mifos codebases using natural language.

Available Bots

Bot	Notebook	Vector Storage	Description
Web App Bot	`Web-App/web-app_bot.ipynb`	`web_app_vector_storage_metadata/`	Query the Mifos Web Application codebase
Mifos Mobile Bot	`Mifos-Mobile/mifos-mobile_bot.ipynb`	`mifos-mobile_vector_storage/`	Explore Mifos Mobile app code and features
Android Client Bot	`Android-Client/android-client_bot.ipynb`	`android-client_vector_storage/`	Navigate the Android Client codebase
Mobile Wallet Bot	`Mobile-Wallet/mobile-wallet_bot.ipynb`	`mobile_wallet_vector_storage/`	Query Mobile Wallet implementation

Note: Mifos Mobile also includes an alternative implementation (mifos-mobile_bot_hf_groq.ipynb) using Groq LLM and Hugging Face embeddings instead of OpenAI.

Deployed Chatbots (No Setup Required!)

Access hosted versions on Hugging Face Spaces:

How It Works

Processes and indexes Mifos codebases, creating vector embeddings using ChromaDB
Uses OpenAI embeddings (text-embedding-3-large) for semantic search
Leverages GPT models to generate human-like responses based on retrieved code snippets
Provides insights on file organization, key components, and project architecture

Local Setup

# Clone the repository
git clone https://github.com/openMF/community-ai.git
cd community-ai

# Install dependencies
pip install -r requirements.txt

# Set up API keys in .env file
echo "OPENAI_API_KEY=your_openai_api_key" > .env
# OR
echo "GEMINI_API_KEY=your_gemini_api_key" >> .env

# Launch Jupyter Notebook
jupyter notebook

# Open any bot notebook (e.g., Web-App/web-app_bot.ipynb)
# Run cells and interact via Gradio interface

2. Community Chatbot Platform

Full-stack chatbot platform with FastAPI backend and Next.js frontend for integrating with Jira, Slack, and GitHub.

📂 Location: community-chatbot/

Features

Jira Agent: Query Jira issues using natural language, generate JQL, and summarize results
Slack Agent: Manage conversations and summarize Slack channel discussions
GitHub Agent: Interact with repositories and ask questions about project code
Modern UI: React-based chat interface with authentication (Firebase)
Agent-Based Workflows: LangChain-powered intelligent automation

Tech Stack

Backend: FastAPI (Python), LangChain, OpenAI
Frontend: Next.js 14, React, Tailwind CSS, shadcn/ui
Authentication: Firebase Auth
Database: Firestore

Quick Start

cd community-chatbot

# Backend setup
python3 -m venv venv
source venv/bin/activate  # On Windows: .\venv\Scripts\activate
pip install -r requirements.txt

# Configure environment variables
# Create a .env file with your API keys
# See how_to_get_keys.md for detailed setup instructions
# Add your API keys for OpenAI, Slack, Jira, GitHub, Firebase

# Start backend (from community-chatbot root)
bash scripts/run_backend.sh
# Or run individual agents:
# python scripts/jira.py
# python scripts/slack.py
# python scripts/github_agent.py

# Frontend setup (new terminal, from community-chatbot root)
pnpm install
pnpm dev

# Access at http://localhost:3000

3. Translation Tools

A. Multilingual Translation Helper

📂 Location: tools/translation-helper/

Gradio-based translation tool powered by Gemini 2.0 Flash.

Features:

Supports 35+ languages (Arabic, Bengali, Chinese, French, German, Hindi, Japanese, Spanish, etc.)
Formal/informal tone switching
Real-time translation with Enter key or button trigger

cd tools/translation-helper
pip install -r requirements.txt
python app.py

B. Android XML Localization Translator

📂 Location: Mifos-Mobile Language Translation/

Translates Android strings.xml files using Groq LLM API.

Features:

Parses values/strings.xml and generates localized versions
Handles <string> and <string-array> elements
Translation caching to avoid redundant API calls
Safe XML parsing with pretty-printing

cd "Mifos-Mobile Language Translation"
python script.py

C. JSON Translation Utility

📂 Location: WebApp Language Translations/

CLI utility to translate JSON string values using Groq LLM.

Features:

Walks JSON structure and extracts string leaves
Persistent caching per target language
Exponential backoff for API reliability

cd "WebApp Language Translations"
python Script.py

4. Voice-Driven Banking

📂 Location: Voice-Driven_banking-Lam/, voice_driven_banking/

End-to-end voice banking assistant with React frontend and FastAPI backend.

Features

Multilingual Support: English, Hindi, Spanish, French, German, and more
Core Banking Intents:
- Check account balance
- List recent transactions
- Transfer money with OTP verification
Stateful Conversations: Context-aware multi-turn dialogues
Animated UI: Real-time feedback for recording, processing, and speaking states
AI Pipeline:
- STT: Whisper (Hugging Face Transformers)
- NLU/NLG: Google Gemini API (Vertex AI)
- TTS: MMS (Hugging Face Transformers)

Tech Stack

Backend: FastAPI, Google Gemini, Firestore
Frontend: React, Tailwind CSS
Audio Processing: FFmpeg, Whisper, MMS

# Backend setup
cd Voice-Driven_banking-Lam/Backend
python -m venv .venv
source .venv/bin/activate  # On Windows: .\.venv\Scripts\Activate.ps1
pip install -r requirements.txt
# Configure .env file (see Backend README for details)
uvicorn main:app --reload

# Frontend setup (new terminal)
cd Voice-Driven_banking-Lam/Frontend/voicedriven
npm install
npm start

Testing Framework

📂 Location: voice_driven_banking/

Automated testing framework for voice banking interfaces.

cd voice_driven_banking
pip install -r requirements.txt
python voice_banking_test_suite.py

5. Data Extraction & Automation

A. Jira/Confluence Data Scraper

📂 Location: Data Scraping/

Scrapes and extracts data from Mifos Jira/Confluence pages.

cd "Data Scraping"
jupyter notebook DataExtraction.ipynb

B. GitHub Repo Automation

📂 Location: Repo Clone Automation/

Automates cloning and processing of GitHub repositories for RAG applications.

Features:

Selenium-based automated repo download
Converts repository content to text for vector database ingestion

cd "Repo Clone Automation"
python repo_cloner.py
jupyter notebook github_repo_rag.ipynb

6. Slack Bot & Pipeline

📂 Location: Slack_scraper_bot/, slack_pipeline/

Tools for extracting, processing, and querying Slack messages.

Features

Message Extraction: Convert Slack JSON exports to clean text
PII Removal: Automatically redact personal identifiable information
RAG Integration: Query Slack conversations using vector databases
Trustworthy LLM: Confidence scoring for generated responses

Pipeline Components

# Extract messages from Slack JSON
cd Slack_scraper_bot/scripts
python extract.py

# Remove PII
python pii_removal.py

# Create vector database
cd ../../slack_pipeline
python main.py

Demo Bot

cd Slack_scraper_bot/scripts
jupyter notebook demo_bot.ipynb

Quick Start

Prerequisites

Python 3.8+
Node.js 18+ (for Next.js projects)
Jupyter Notebook
API Keys: OpenAI, Gemini, Groq (depending on components used)

Basic Installation

# Clone repository
git clone https://github.com/openMF/community-ai.git
cd community-ai

# Install Python dependencies
pip install -r requirements.txt

# Set up environment variables
# Create a .env file and add your API keys
# OPENAI_API_KEY=your_key_here
# GEMINI_API_KEY=your_key_here
# GROQ_API_KEY=your_key_here

# Launch Jupyter for chatbots
jupyter notebook

# Or run specific tools (see component sections above)

Project Structure

community-ai/
├── Android-Client/              # Android Client RAG chatbot
│   ├── android-client_bot.ipynb
│   └── android-client_vector_storage/
├── community_chatbot/           # Agent scripts (GitHub, Jira, Slack)
│   └── agent/
├── community-chatbot/           # Full-stack chatbot platform
│   ├── app/                    # Next.js frontend pages
│   ├── components/             # React UI components
│   ├── scripts/                # FastAPI backend agents
│   └── package.json
├── Data Scraping/              # Jira/Confluence data extraction
│   └── DataExtraction.ipynb
├── Mifos-Mobile/               # Mifos Mobile app chatbot
│   ├── mifos-mobile_bot.ipynb
│   ├── mifos-mobile_bot_hf_groq.ipynb  # Alternative using Groq/HF
│   └── mifos-mobile_vector_storage/
├── Mifos-Mobile Language Translation/  # Android XML translator
│   ├── script.py
│   └── Readme.md
├── Mobile-Wallet/              # Mobile Wallet chatbot
│   ├── mobile-wallet_bot.ipynb
│   └── mobile_wallet_vector_storage/
├── Repo Clone Automation/      # GitHub repo automation
│   ├── repo_cloner.py
│   └── github_repo_rag.ipynb
├── Slack_scraper_bot/          # Slack message extraction & bot
│   ├── scripts/
│   └── data/
├── slack_pipeline/             # Slack vector database pipeline
│   ├── main.py
│   └── vectordb.py
├── tools/
│   └── translation-helper/     # Multilingual translation tool
│       └── app.py
├── Voice-Driven_banking-Lam/   # Voice banking assistant
│   ├── Backend/
│   └── Frontend/
├── voice_driven_banking/       # Voice banking test suite
│   └── voice_banking_test_suite.py
├── Web-App/                    # Web App chatbot
│   ├── web-app_bot.ipynb
│   └── web_app_vector_storage_metadata/
├── WebApp Language Translations/  # JSON translation utility
│   └── Script.py
├── CodeCommentingScript.ipynb  # Code preprocessing utility
├── requirements.txt            # Python dependencies
└── README.md

Technologies Used

AI & Machine Learning

LLMs: OpenAI GPT-4, Google Gemini 2.0 Flash, Groq
Embeddings: OpenAI text-embedding-3-large
Frameworks: LangChain, Hugging Face Transformers
Vector Databases: ChromaDB, Pinecone

Backend

Python: FastAPI, Flask
Data Processing: BeautifulSoup, Selenium, pandas

Frontend

React/Next.js 14: Server-side rendering, App Router
UI Libraries: Tailwind CSS, shadcn/ui, Radix UI
State Management: Zustand
Forms: React Hook Form, Zod validation

Database & Storage

Firebase: Firestore, Firebase Auth
Vector Stores: ChromaDB (persistent), Pinecone

Voice & Audio

STT: Whisper (Hugging Face)
TTS: MMS (Hugging Face)
Processing: FFmpeg

Development Tools

Notebooks: Jupyter
UI Prototyping: Gradio
Testing: Jest, Selenium
Package Management: pip, pnpm

Contributing

We welcome contributions from the community! Here's how you can help:

Ways to Contribute

🐛 Report bugs by opening issues
💡 Suggest new features or improvements
📝 Improve documentation
🔧 Submit pull requests with bug fixes or new features
🧪 Test and provide feedback on existing tools

Contribution Workflow

Fork the repository

git clone https://github.com/YOUR_USERNAME/community-ai.git
cd community-ai

Create a feature branch

git checkout -b feature/your-feature-name

Make your changes
- Follow existing code style and conventions
- Add tests if applicable
- Update documentation

Commit your changes

git add .
git commit -m "feat: add your feature description"

Push and create a Pull Request
```
git push origin feature/your-feature-name
```
Then open a PR on GitHub with a clear description of your changes.

Development Guidelines

Use meaningful commit messages (follow Conventional Commits)
Ensure code is well-documented with comments
Test your changes before submitting
Keep PRs focused on a single feature/fix

Links and Resources

Mifos Community

Website: mifos.org
Documentation: docs.mifos.org
Jira: mifosforge.jira.com
Slack: Join our AI Working Group

Related Projects

Deployed Chatbots

License

This project is licensed under the MPL-2.0 License - see the LICENSE file for details.

Support

For questions, issues, or feature requests:

📧 Open an issue on GitHub
💬 Join our Mifos Slack community
📖 Check the documentation

Built with ❤️ by the Mifos Community

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Mifos Community AI

Table of Contents

Overview

Key Components

1. RAG-Based Chatbots

Available Bots

Deployed Chatbots (No Setup Required!)

How It Works

Local Setup

2. Community Chatbot Platform

Features

Tech Stack

Quick Start

3. Translation Tools

A. Multilingual Translation Helper

B. Android XML Localization Translator

C. JSON Translation Utility

4. Voice-Driven Banking

Features

Tech Stack

Testing Framework

5. Data Extraction & Automation

A. Jira/Confluence Data Scraper

B. GitHub Repo Automation

6. Slack Bot & Pipeline

Features

Pipeline Components

Demo Bot

Quick Start

Prerequisites

Basic Installation

Project Structure

Technologies Used

AI & Machine Learning

Backend

Frontend

Database & Storage

Voice & Audio

Development Tools

Contributing

Ways to Contribute

Contribution Workflow

Development Guidelines

Links and Resources

Mifos Community

Related Projects

Deployed Chatbots

License

Support