From d4751b90615b6bb8ef6dc5717ba9bf477cf1c8bd Mon Sep 17 00:00:00 2001 From: John Patrick Teruel Date: Fri, 24 Apr 2026 22:03:36 +0800 Subject: [PATCH] Update documentation - consumer now in Docker MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - README: 3 steps → 2 steps (no manual consumer startup needed) - DEMO: Updated quick start to use 'docker compose logs -f consumer' - Updated references from 'Consumer Terminal' to 'consumer logs' - Clarified that entire system runs via 'docker compose up -d' Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --- DEMO.md | 54 ++++++++++++++++++++---------------------------------- README.md | 13 ++++++------- 2 files changed, 26 insertions(+), 41 deletions(-) diff --git a/DEMO.md b/DEMO.md index 2760025..70e6b7c 100644 --- a/DEMO.md +++ b/DEMO.md @@ -1,19 +1,19 @@ # PayGuard Fraud Detection - Complete Demo Guide -## Quick Start (5 minutes) +## Quick Start (2 minutes) ```bash -# Terminal 1: Start all services +# Terminal 1: Start all services (including consumer) docker compose up -d --build -# Terminal 2: Start fraud detection consumer -cd consumer && python3 pipeline.py +# Terminal 2: Watch consumer logs (real-time fraud detection) +docker compose logs -f consumer # Terminal 3: Open in browser http://localhost:3000 ``` -Then submit transactions and watch fraud detection work! +Then submit transactions and watch fraud detection work in real-time! --- @@ -30,7 +30,7 @@ Transaction → Features → ML Layer 1 → ML Layer 2 → Decision → Risk Ass 1. **Frontend** (http://localhost:3000) - User submits transactions 2. **API** (http://localhost:8000) - Validates, publishes to Kafka 3. **Kafka** - Message broker queues transactions -4. **Consumer** - Picks up messages and runs ML pipeline +4. **Consumer** (Docker container) - Picks up messages and runs ML pipeline 5. **ML Models** - Score fraud risk (0.0-1.0 scale) 6. **Redis** - Stores final results @@ -52,20 +52,15 @@ Transaction → Features → ML Layer 1 → ML Layer 2 → Decision → Risk Ass docker compose ps ``` -Verify all 5 are "Up": +Verify all 6 are "Up": ``` -zookeeper - Running -kafka - Healthy -redis - Healthy -api - Healthy with CORS -frontend - Healthy -``` - -### Consumer Dependencies - -```bash -# Make sure Python packages are installed -python3 -m pip install --break-system-packages kafka-python redis requests pybreaker +NAME STATUS PORTS +payguard-zookeeper Up 2181 +payguard-kafka Healthy 9092 +payguard-redis Healthy 6379 +payguard-api Healthy with CORS 8000 +payguard-frontend Healthy 3000 +payguard-consumer Up (internal) ``` --- @@ -79,22 +74,13 @@ docker compose ps ``` **Expected output:** -``` -NAME STATUS PORTS -payguard-zookeeper Up 2181 -payguard-kafka Healthy 9092 -payguard-redis Healthy 6379 -payguard-api Healthy with CORS 8000 -payguard-frontend Healthy 3000 -``` +All 6 services should show "Up" status. -### Step 2: Start Consumer Pipeline (1 minute) +### Step 2: Watch Consumer Logs (1 minute) ```bash # Terminal 2 -cd /Users/pat/Projects/PAT/payguard-poc -cd consumer -python3 pipeline.py +docker compose logs -f consumer ``` **Expected output:** @@ -126,7 +112,7 @@ You'll see the PayGuard transaction form. ### Step 5: Submit Test Transactions (6 minutes) -Submit these 4 scenarios in order. After each one, watch the Consumer Terminal for output. +Submit these 4 scenarios in order. After each one, watch the Consumer logs for output. --- @@ -151,7 +137,7 @@ Description: Morning coffee purchase } ``` -**Watch Consumer Terminal:** +**Watch consumer logs (from Terminal 2):** ``` [INFO] [TRANSACTION INTAKE] Processing transaction: txn_abc123 [INFO] Amount: $75.50 | Merchant: Starbucks Coffee @@ -188,7 +174,7 @@ Description: Laptop purchase } ``` -**Watch Consumer Terminal:** +**Watch consumer logs (from Terminal 2):** ``` [INFO] [TRANSACTION INTAKE] Processing transaction: txn_def456 [INFO] Amount: $5000.00 | Merchant: Electronics Store diff --git a/README.md b/README.md index 698db2f..56a7b80 100644 --- a/README.md +++ b/README.md @@ -1,19 +1,18 @@ # 🚀 PayGuard Fraud Detection System - Quick Start -## Get Started in 3 Steps (5 minutes) +## Get Started in 2 Steps (2 minutes) ```bash -# 1️⃣ Start all Docker services +# 1️⃣ Start all Docker services (including fraud detection consumer) docker compose up -d --build -# 2️⃣ Start the fraud detection consumer -cd consumer && python3 pipeline.py - -# 3️⃣ Open the frontend +# 2️⃣ Open the frontend # Visit http://localhost:3000 in your browser ``` -**That's it!** Now submit transactions and watch fraud detection work in real-time. +**That's it!** The entire system runs in Docker. Submit transactions and watch fraud detection work in real-time. + +Monitor consumer logs with: `docker compose logs -f consumer` ---