Track, Analyze, and Improve: Using llm.report for OpenAI Logging & Analytics

Are you looking for better insights into your OpenAI usage? Tired of guessing how much your AI apps are costing you? llm.report is an open-source logging and analytics platform designed specifically for OpenAI, giving you the power to track, analyze, and optimize your language model applications.

What is llm.report and Why Should You Care?

llm.report offers a suite of features to help you understand and improve your OpenAI-powered applications. It goes beyond simple API calls, providing valuable insights into cost analysis, token usage, and user behavior. With OpenAI logging and analytics, you gain a clearer picture of how your models are performing and where you can optimize for better efficiency and cost-effectiveness.

Key Benefits of Using llm.report:

• Cost Analysis: Track your OpenAI API expenses with precision.
• Token Usage: Monitor token consumption to identify areas for prompt optimization to leverage the power of GPT-4 analytics.
• Prompt Improvement: Analyze request/response logs to refine your prompts for better results.
• User Analytics: Understand how individual users are interacting with your AI applications, helping you tailor the experience and manage costs.

Features That Make llm.report Stand Out

llm.report isn't just another analytics tool, it is designed to specifically address the challenges of working with Large Language Models. Let's delve into the features that make it a powerful asset for your OpenAI projects:

Gain Insights with OpenAI API Analytics

Understand your OpenAI API costs and token usage in a no-code environment. Visualize your data and quickly identify trends and anomalies. This feature helps you stay on budget and optimize your OpenAI usage with ease.

Log and Analyze Your OpenAI API Requests

llm.report allows you to comprehensively log your OpenAI API requests and responses. By analyzing these logs, you can fine-tune your prompts, identify errors, and significantly improve the performance of your language models.

User-Level Cost Tracking

Calculate the cost associated with each user of your AI application. This is crucial for understanding the economics of your product and making informed decisions about pricing tiers and resource allocation.

Getting Started with llm.report: Self-Hosted Installation Made Easy

Setting up llm.report is straightforward, offering you full control over your data. Here's a breakdown of the self-hosted installation process:

1. Clone the Repository:

   git clone https://github.com/dillionverma/llm.report.git
   

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2. Navigate to the Directory:

   cd llm.report
   

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3. Install Dependencies:

   yarn
   

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4. Configure Environment Variables:

   cp .env.example .env
   

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   Generate a NEXTAUTH_SECRET using openssl rand -base64 32 and add it to your .env file.

5. Quickstart with Docker:

   Ensure you have Docker and Docker Compose installed. Then, run:

   yarn dx
   

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   This will initiate a local PostgreSQL instance pre-loaded with test user credentials, which will be displayed in your console.

Finally, open http://localhost:3000 in your browser to access your llm.report dashboard.

Tech Stack: Built for Performance and Scalability

llm.report is built upon a robust and modern tech stack, ensuring performance, scalability, and ease of maintenance:

• Framework: Next.js
• Language: Typescript
• CSS: Tailwind
• UI Components: Shadcn & Magic UI
• Database: Postgres
• Authentication: NextAuth.js
• Payments: Stripe
• Emails: Resend

Contributing to the Future of OpenAI Analytics

llm.report is an open-source project, and contributions are highly encouraged! Here are a few ways you can get involved:

• Report Bugs: Open an issue if you encounter a bug.
• Submit Pull Requests: Contribute new features, improvements, or bug fixes by submitting a pull request.

Open Source and Inspired by the Best

Inspired by projects like Dub and Plausible, llm.report is open-source under the GNU Affero General Public License Version 3 (AGPLv3). This commitment to open-source ensures community-driven development and transparency.

Level Up Your OpenAI Game with Data

Don't fly blind with your OpenAI projects. Implement llm.report to gain actionable insights, optimize your prompts, control your costs, and deliver better experiences to your users. Start leveraging the power of LLM analytics today.