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Intelligent versioning system for LLM prompts with Git integration

Project description

Prompt Versioner Logo

A comprehensive Python library for managing and versioning LLM prompts, with built-in A/B testing, metric tracking, and performance monitoring capabilities.

License: MIT PyPI - Version Python 3.11+ Downloads GitHub Repo stars

✨ Features🚀 Quick Start📖 Documentation🎯 Examples


🎯 Why Prompt Versioner?

Prompt Versioner provides enterprise-grade prompt management with:

  • 🔄 Version Control: Full versioning of prompts
  • 📊 Performance Tracking: Metrics and regression detection
  • 🧪 A/B Testing: Built-in statistical framework
  • ⚡ Real-time Monitoring: Alerts and dashboards
  • 👥 Team Collaboration: Annotations and reviews
  • 🎨 Modern UI: Responsive web dashboard

✨ Features

🔧 Core Functionality

  • Automatic MAJOR/MINOR/PATCH versioning
  • Metrics tracking: tokens, latency, quality, cost
  • Multi-model performance comparison
  • Export & share prompt history
  • Optional Git integration

🧪 Advanced Testing & Monitoring

  • A/B Testing framework
  • Model performance benchmarking
  • Automated regression detection
  • Live metrics dashboards
  • Custom alert thresholds

👥 Collaboration & Management

  • Team annotations and feedback
  • Version comparison & visual diff
  • Search & filtering by metadata, performance, and tags

🎨 Modern Web Interface

  • Interactive dashboard with responsive layout
  • Dark/Light themes
  • Tab navigation for Prompts, Testing, Comparison, Alerts
  • Real-time updates

Dashboard Overview


📦 Installation

Prerequisites

  • Python 3.11+
  • Poetry (recommended) or pip
  • Git (optional)

Using PyPI

pip install prompt-versioner

🚀 Quick Start

from prompt_versioner import PromptVersioner, VersionBump

pv = PromptVersioner(project_name="my-first-project", enable_git=False)
pv.save_version(
    name="assistant-prompt",
    system_prompt="You are a helpful assistant.",
    user_prompt="Please answer the following question: {question}",
    bump_type=VersionBump.MAJOR
)

print("✅ Created first prompt version 1.0.0!")

🎨 Web Dashboard

Core Features

📋 Prompts Management

  • Version history with visual diff
  • Semantic search
  • Bulk operations
  • Live preview

Prompts Management

📊 Metrics & Analytics

  • Token usage, latency, cost analysis
  • Quality score tracking
  • Multi-model performance comparison with automatic "best model" detection

Metrics Dashboard

Model Comparison: Test the same prompt across different models (GPT-4, Claude, Gemini, etc.) and see aggregated metrics with automatic identification of the fastest, cheapest, and highest-quality model.

🧪 A/B Testing

  • Split testing
  • Real-time results

AB Testing Interface

🔍 Version Comparison

  • Side-by-side visual diff
  • Metadata & performance delta
  • Smart annotations

Version Comparison

⚠️ Smart Alerts

  • Automatic detection of regressions
  • Cost and error monitoring
  • Custom metrics & thresholds

Alerts System


💻 CLI Interface

# Initialization & Setup
pv init                              # Initialize prompt versioner

# Prompt Operations
pv list                              # List all tracked prompts
pv versions <prompt>                 # List versions of a prompt
pv show <prompt> <version>           # Show version details

# Model Pricing & Cost Estimation
pv models                            # List all models with pricing
pv models --sort-by input            # Sort by input price
pv models --filter gpt               # Filter specific models
pv estimate-cost <model> <in> <out>  # Estimate cost for usage
pv compare-costs <in> <out>          # Compare costs across models

# Version Comparison
pv diff <prompt> <v1> <v2>           # Show diff between versions
pv compare <prompt> <v1> <v2>        # Compare with metrics

# Management
pv delete <prompt> <version>         # Delete a version
pv rollback <prompt> <version>       # Rollback to version
pv clear-db                          # Clear database

# Dashboard
pv dashboard --port 5000             # Launch web dashboard

📖 Examples

Examples in examples/ are fully functional:

File Description
basic_usage.py Getting started
version_management.py Advanced version control
metrics_tracking.py Metrics logging
multi_models.py Multi-model comparison
ab_testing.py Statistical testing
performance_monitoring.py Automated monitoring
summarization_example.py Real-world summarization
run_dashboard.py Launch dashboard
clear_db.py Reset database

🌟 Contributing

See CONTRIBUTING.md for contribution guidelines.


📄 License

MIT License - LICENSE


📞 Support


Build by Sveva Pepe, NLP Engineer
⭐ Star this project if it helps you build better AI applications!

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