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Prompt engineering toolkit with version control and analytics for better LLM outputs.

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Multimodal Prompt Studio is a platform to craft, test, and analyze prompts.

One interface. Multiple modalities.

The tool helps prompt engineers, AI developers, researchers working with large language models. It enables organizations to maintain consistent prompt engineering practices.

Features

  • Multimodal Editor – Combine text, image, and audio prompts in a single workspace
  • A/B Testing – Compare multiple versions and track performance
  • Prompt Versioning – Full history, branching, and rollback support
  • Analytics – Token usage, latency, and output quality insights
  • Template Library – Reusable prompt patterns for fast iteration
  • Document Manager – Inject your own context (RAG-ready)

demo

Architecture

The application follows a modern microservices architecture:

Component Technology Purpose
Frontend React with TypeScript, Redux Responsive UI for prompt creation and testing
Backend Python FastAPI Efficient API services and LLM integration
Database PostgreSQL Secure storage for prompts and analytics
Deployment Docker Consistent environments across systems

Prerequisites

  • Docker and Docker Compose
  • Node.js 16+ (for local frontend development)
  • Python 3.9+ (for local backend development)

Installation

# Clone repository
git clone https://github.com/KazKozDev/prompt-studio.git
cd prompt-studio

# Configure environment
cp .env.example .env

# Start development containers
docker-compose -f docker/docker-compose.dev.yml up -d

# Initialize database
docker-compose -f docker/docker-compose.dev.yml exec backend python init_db.py

Access Points

API Integration

Access comprehensive API documentation at http://localhost:8000/api/docs after startup.

Key endpoints:

  • /api/prompts - Create and manage prompts
  • /api/tests - Run tests and retrieve results
  • /api/analytics - Access performance metrics

License

Apache License 2.0 - see the LICENSE file for details.

Copyright 2025 Multimodal Prompt Studio

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.

If you like this project, please give it a star ⭐

For questions, feedback, or support, reach out to:

Artem KK | Issue Tracker