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[![Lint CI Status](https://github.com/sortedcord/alemno-payments/actions/workflows/lint.yml/badge.svg)](https://github.com/sortedcord/alemno-payments/actions/workflows/lint.yml)
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An asynchronous transactional data cleaning, validation, and LLM powered categorization pipeline.
## 🚀 Features
- Reads multi format dates and handles missing transaction IDs by auto generating unique fallbacks, and parses messy amounts with currency signs and commas cleanly.
- Offloads validation, spend conversion, and analysis to a Celery background worker backed by Redis.
- Integrates with the Google GenAI SDK (`gemini-3.5-flash`) using structured output schemas to categorize transaction records into database-defined custom categories.
- Uses Redis caching with a 24-hour TTL to store live exchange rates, falling back to a hardcoded rate of `93.0` if offline.
- Statistical Anomaly Detection:
- Flags transactions exceeding 3 times the account's median spend as statistical outliers.
- Flags domestic transactions in USD currency.
- Flags high value transactions and transactions with fraud indicative keywords.
## 🐳 Self Hosting & Deployment
We publish production-ready images to **GitHub Container Registry (GHCR)**. You can pull them directly or run them via Docker Compose.
### Option A: Docker Compose (Using Pre-built Images)
Create a `docker-compose.yml` file to self-host the entire stack:
```yaml
version: "3.8"
services:
db:
image: postgres:16-alpine
container_name: alemno_db
ports:
- "5432:5432"
environment:
POSTGRES_USER: postgres
POSTGRES_PASSWORD: postgres
POSTGRES_DB: alemno_payments
volumes:
- postgres_data:/var/lib/postgresql/data
healthcheck:
test: ["CMD-SHELL", "pg_isready -U postgres -d alemno_payments"]
interval: 5s
timeout: 5s
retries: 5
redis:
image: redis:7-alpine
container_name: alemno_redis
ports:
- "6379:6379"
web:
image: ghcr.io/sortedcord/alemno-payments/web:latest
container_name: alemno_web
ports:
- "3000:3000"
environment:
- POSTGRES_HOST=db
- POSTGRES_PORT=5432
- POSTGRES_USER=postgres
- POSTGRES_PASSWORD=postgres
- POSTGRES_DB=alemno_payments
- REDIS_HOST=redis
- REDIS_PORT=6379
- REDIS_DB=0
- GEMINI_API_KEY=your-gemini-api-key
depends_on:
db:
condition: service_healthy
redis:
condition: service_started
worker:
image: ghcr.io/sortedcord/alemno-payments/worker:latest
container_name: alemno_worker
environment:
- POSTGRES_HOST=db
- POSTGRES_PORT=5432
- POSTGRES_USER=postgres
- POSTGRES_PASSWORD=postgres
- POSTGRES_DB=alemno_payments
- REDIS_HOST=redis
- REDIS_PORT=6379
- REDIS_DB=0
- GEMINI_API_KEY=your-gemini-api-key
depends_on:
db:
condition: service_healthy
redis:
condition: service_started
volumes:
postgres_data:
```
Launch the stack:
```bash
docker compose up -d
```
### Option B: Direct Pull (Manual Run)
You can pull and run individual containers manually from GHCR:
1. **Pull the images**:
```bash
docker pull ghcr.io/sortedcord/alemno-payments/web:latest
docker pull ghcr.io/sortedcord/alemno-payments/worker:latest
```
2. **Run Web (FastAPI API Server)**:
```bash
docker run -d \
--name alemno_web \
-p 3000:3000 \
-e POSTGRES_HOST=your-db-host \
-e REDIS_HOST=your-redis-host \
-e GEMINI_API_KEY=your-gemini-api-key \
ghcr.io/sortedcord/alemno-payments/web:latest
```
3. **Run Worker (Celery Processing Worker)**:
```bash
docker run -d \
--name alemno_worker \
-e POSTGRES_HOST=your-db-host \
-e REDIS_HOST=your-redis-host \
-e GEMINI_API_KEY=your-gemini-api-key \
ghcr.io/sortedcord/alemno-payments/worker:latest celery -A app.worker.celery_app worker --loglevel=info
```