⚡ Smart Prompt Studio

A production-minded backend for managing, rendering, validating, and executing reusable AI prompts.

🧠 Prompt Management • 🛡️ Guardrails • 🤖 AI Execution • 📋 Evaluation • 📦 Docker • 🔄 CI

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🚀 What is Smart Prompt Studio?

Smart Prompt Studio is a FastAPI-based backend built around one simple idea:

Treat prompts like backend-managed application assets, not random strings buried inside code.

Instead of scattering prompts throughout an application, this service provides a central layer for:

• 📝 Creating prompts
• 🔢 Managing prompt versions
• 🧩 Rendering variables
• 🛡️ Validating prompts before execution
• 🤖 Sending prompts to an AI provider
• 📊 Tracking execution behavior
• 🧪 Testing failure paths
• 📋 Evaluating prompt behavior
• 🪵 Logging requests and services
• 🐳 Running inside Docker
• 🔄 Validating changes through GitHub Actions

The project is intentionally small.

The engineering lessons are not.

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✨ Core Features

📝 Prompt Management

Create reusable prompts through the API.

POST /prompts

Prompts contain structured messages instead of one giant string.

This keeps prompt construction explicit and maintainable.

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🎯 Project Goal

The goal is to build a clean foundation for AI-powered backend systems.

Smart Prompt Studio focuses on the engineering layer surrounding an LLM:

Client
  │
  ▼
FastAPI API
  │
  ▼
Prompt Service
  │
  ├── Versioning
  ├── Variable Rendering
  └── Validation
  │
  ▼
Guardrail Service
  │
  ▼
AI Service
  │
  ▼
AI Provider
  │
  ▼
Response

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🏗️ Architecture

The project follows a service-oriented FastAPI structure.

Smart-Prompt-Studio/
│
├── app/
│   ├── config.py
│   ├── logging_config.py
│   ├── main.py
│   ├── schemas.py
│   │
│   ├── exceptions/
│   │   ├── custom_exceptions.py
│   │   └── handlers.py
│   │
│   ├── middleware/
│   │   ├── __init__.py
│   │   └── request_logging.py
│   │
│   └── services/
│       ├── ai_service.py
│       ├── guardrail_service.py
│       └── prompt_service.py
│
├── tests/
│   ├── test_ai_service_errors.py
│   ├── test_ai_service_logging.py
│   └── test_prompt_evalutation.py
│
├── .github/
│   └── workflows/
│       └── ci.yml
│
├── .dockerignore
├── .env.example
├── .gitignore
├── Dockerfile
└── requirements.txt

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🧰 Tech Stack

Technology                                  Purpose
-🐍 Python                               Application language
-⚡ FastAPI                              API framework
-📦 Pydantic                             Data validation
-🤖 OpenAI-compatible SDK                AI communication
-🧪 Pytest                               Automated testing
-🐳 Docker                               Containerization
-🔄 GitHub Actions                       CI
-🪵 Python Logging                       Observability
-🌿 Git                                  Version control

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📌 Current Status

┌──────────────────────────────┐
│ Smart Prompt Studio          │
├──────────────────────────────┤
│ Prompt Management       ✅   │
│ Versioning              ✅   │
│ Variable Rendering      ✅   │
│ Guardrails              ✅   │
│ AI Integration          ✅   │
│ Error Handling          ✅   │
│ Logging                 ✅   │
│ Automated Tests         ✅   │
│ Docker                  ✅   │
│ GitHub Actions CI       ✅   │
└──────────────────────────────┘

Local test suite:

10 passed

CI:

✅ Passed

Docker:

✅ Verified

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⚡ Final Snapshot

Smart Prompt Studio is a compact AI backend focused on one principle:

Build the engineering around the model, not just the model call.

It combines:

⚡ FastAPI
🧠 Prompt Management
🛡️ Guardrails
🤖 AI Execution
🪵 Logging
🧪 Testing
🐳 Docker
🔄 CI
🌿 Git

Small enough to understand.

Structured enough to extend.

Practical enough to build upon.

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🗿 Built With Python

Made as part of a hands-on journey toward production-grade AI Backend Engineering.

Code → Test → Containerize → Automate → Ship

Smart Prompt Studio

The prompt is only the beginning.