Open Source LLM Performance Tracker
An open source Next app template to monitor your AI apps
Listed in categories:
Artificial IntelligenceOpen SourceAnalytics
Description
LLM Performance Tracker is a template for creating a dashboard and cost calculator specifically designed for tracking the performance and costs associated with large language models (LLMs). Built with Next.js and Tinybird, it allows users to monitor various metrics related to LLM usage, including costs, requests, tokens, and duration, categorized by model, provider, organization, project, environment, and user.
How to use Open Source LLM Performance Tracker?
To use the LLM Performance Tracker, fork the GitHub repository, customize it according to your needs, and set up the necessary environment variables. Start the Tinybird service locally, configure the Next.js application, and run it to access the dashboard in your browser.
Core features of Open Source LLM Performance Tracker:
1️⃣
Track LLM costs, requests, tokens, and duration by various dimensions
2️⃣
Multitenant user-facing dashboard
3️⃣
AI cost calculator
4️⃣
Vector search integration
5️⃣
Ask AI feature integration
Why could be used Open Source LLM Performance Tracker?
| # | Use case | Status | |
|---|---|---|---|
| # 1 | Organizations can monitor their LLM usage and costs effectively | ✅ | |
| # 2 | Developers can customize the dashboard to fit their specific analytics needs | ✅ | |
| # 3 | Data scientists can analyze performance metrics across different models and environments | ✅ | |
Who developed Open Source LLM Performance Tracker?
Tinybird is a company focused on providing tools for real-time data analytics and performance tracking, enabling developers and organizations to build efficient data-driven applications.