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# Copilot Agent - Python Implementation
## Project Overview
This directory contains the Python implementation developed with Copilot AI assistance for the MerchantsOfHope.org platform.
## Core Requirements
- Multi-tenant architecture with isolated business lines
- OIDC and social media login
- Job seeker functionality (browse positions, submit resumes, complete application process)
- Job provider functionality (manage positions and applications)
- USA law compliance
- English-only support
- Critical accessibility compliance (US Government contracts)
- Regulatory compliance (PCI, GDPR, SOC, FedRAMP)
## Technical Implementation
- Containerized with Docker
- Docker Compose for service dependencies
- Deployable to Kubernetes clusters
- Port: 26000
- Test Driven Development (TDD)
- High test coverage with all tests passing
- Follow language-specific best practices for security, QA, SRE/devops

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testnew/python/gemini/.gitignore vendored Normal file
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# Python
__pycache__/
*.pyc
*.pyo
*.pyd
.Python
env/
venv/
# Docker
docker-compose.override.yml
# IDE
.idea/
.vscode/

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# Use an official Python runtime as a parent image
FROM python:3.8-slim
# Set the working directory in the container
WORKDIR /app
# Copy the current directory contents into the container at /app
COPY . /app
# Install any needed packages specified in requirements.txt
RUN pip install --no-cache-dir -r requirements.txt
# Make port 16000 available to the world outside this container
EXPOSE 16000
# Define environment variable
ENV NAME World
# Run app.py when the container launches
CMD ["python", "app/main.py"]

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# Gemini Agent - Python Implementation
## Project Overview
This directory contains the Python implementation developed with Gemini AI assistance for the MerchantsOfHope.org platform.
## Core Requirements
- Multi-tenant architecture with isolated business lines
- OIDC and social media login
- Job seeker functionality (browse positions, submit resumes, complete application process)
- Job provider functionality (manage positions and applications)
- USA law compliance
- English-only support
- Critical accessibility compliance (US Government contracts)
- Regulatory compliance (PCI, GDPR, SOC, FedRAMP)
## Technical Implementation
- Containerized with Docker
- Docker Compose for service dependencies
- Deployable to Kubernetes clusters
- Port: 16000
- Test Driven Development (TDD)
- High test coverage with all tests passing
- Follow language-specific best practices for security, QA, SRE/devops

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from flask import Flask, jsonify
app = Flask(__name__)
@app.route('/')
def index():
return jsonify({"message": "Hello World"})
@app.route('/health')
def health():
return jsonify({"status": "UP"})
if __name__ == '__main__':
app.run(host='0.0.0.0', port=16000)

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version: '3.8'
services:
web:
build: .
ports:
- "16000:16000"

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Flask
pytest

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import pytest
from app.main import app
@pytest.fixture
def client():
app.config['TESTING'] = True
with app.test_client() as client:
yield client
def test_health_check(client):
"""Test the health check endpoint."""
rv = client.get('/health')
assert rv.status_code == 200
assert rv.get_json() == {'status': 'UP'}

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# Qwen Agent - Python Implementation
## Project Overview
This directory contains the Python implementation developed with Qwen AI assistance for the MerchantsOfHope.org platform.
## Core Requirements
- Multi-tenant architecture with isolated business lines
- OIDC and social media login
- Job seeker functionality (browse positions, submit resumes, complete application process)
- Job provider functionality (manage positions and applications)
- USA law compliance
- English-only support
- Critical accessibility compliance (US Government contracts)
- Regulatory compliance (PCI, GDPR, SOC, FedRAMP)
## Technical Implementation
- Containerized with Docker
- Docker Compose for service dependencies
- Deployable to Kubernetes clusters
- Port: 21000
- Test Driven Development (TDD)
- High test coverage with all tests passing
- Follow language-specific best practices for security, QA, SRE/devops