Enterprise-grade ChatGPT API integration with conversation management, caching, and monitoring built with .NET 8

Features • Quick Start • API Docs • Deployment

IntelliBot API is a production-ready .NET 8 Web API for integrating OpenAI's ChatGPT into your applications. It provides advanced features like conversation memory, Redis caching, rate limiting, and real-time streaming for building intelligent chatbot applications and AI-powered solutions.

🔥 Perfect for: Chat applications, AI assistants, customer support bots, and enterprise AI solutions

• Multi-Model Support: GPT-3.5 Turbo, GPT-4, GPT-4 Turbo, GPT-4o
• Conversation Management: Persistent chat history with context awareness
• Streaming Responses: Real-time token streaming for better UX
• Smart Caching: Redis-powered response caching to reduce API costs

• Rate Limiting: Configurable request throttling per user/IP
• Resilience Patterns: Polly retry policies and circuit breakers
• Structured Logging: Serilog with JSON formatting for observability
• API Documentation: Auto-generated Swagger/OpenAPI with examples
• Validation: FluentValidation for robust request validation

• Usage Statistics: Token tracking and cost estimation
• Performance Metrics: Response times and error rate monitoring
• Health Checks: Comprehensive service health monitoring

IntelliBotAPI/ ├── 🎯 IntelliBot.API/ # Controllers, DTOs, Configuration ├── 🧠 IntelliBot.Application/ # Services, Validators, Business Logic ├── 💾 IntelliBot.Infrastructure/ # Repositories, External APIs, Caching ├── 📦 IntelliBot.Core/ # Entities, Interfaces, Enums └── 🔧 IntelliBot.Shared/ # Utilities, Extensions, Constants 

• .NET 8 SDK
• PostgreSQL 14+
• Redis 6+
• OpenAI API Key

1. Clone and setup

git clone https://github.com/yourusername/IntelliBotAPI.git cd IntelliBotAPI/src/IntelliBot.API

2. Configure environment Update appsettings.Development.json:

{ "OpenAI": { "ApiKey": "your-openai-api-key", "DefaultModel": "gpt-3.5-turbo" }, "ConnectionStrings": { "DefaultConnection": "Host=localhost;Database=IntelliBot;Username=postgres;Password=yourpassword", "Redis": "localhost:6379" } }

3. Run database migrations

dotnet ef database update

4. Run the application

dotnet run

• API: https://localhost:7131
• Swagger UI: https://localhost:7131/swagger
• Health Check: https://localhost:7131/health

curl -X POST "https://localhost:7131/api/chat/message" \ -H "Content-Type: application/json" \ -d '{  "message": "Explain quantum computing in simple terms",  "model": 1,  "temperature": 0.7  }'

docker-compose up -d

Configure in appsettings.json:

{ "RateLimiting": { "RequestsPerMinute": 10, "RequestsPerHour": 100, "RequestsPerDay": 1000 } }

dotnet build

dotnet test

• EditorConfig for consistent code style
• XML Documentation for public APIs
• Async/Await pattern throughout

{ "Timestamp": "2025-10-18T12:00:00Z", "Level": "Information", "Message": "Chat request processed", "Properties": { "ProcessingTimeMs": 1250, "TokensUsed": 150, "Model": "gpt-3.5-turbo", "ConversationId": "conv-123" } }

• Overall health: GET /health
• Database health: GET /health/ready
• External services: GET /health/live

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

See our Contributing Guide for details.

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

• 📚 Documentation
• 🐛 Issue Tracker
• 💬 Discussions

• OpenAI for the ChatGPT API
• .NET Team for the excellent framework
• All contributors and users of this project