llm.report - Open-Source Tools for Cost Analysis and Prompt Improvement

Project Introduction: llm.report

llm.report is an open-source logging and analytics platform designed to enhance the interaction with OpenAI's ChatGPT by logging API requests, analyzing related costs, and improving prompt efficiency. Despite its innovative approach, llm.report is currently not being actively maintained, as the founders have transitioned to other endeavors. However, it remains a valuable tool for those interested in diving into OpenAI analytics.

Key Features

OpenAI API Analytics

llm.report provides a straightforward, no-code solution for analyzing OpenAI API costs and token usage. This feature helps users keep track of and optimize their spending on API calls, providing insights into usage patterns without complex configurations.

Logs

Users can log requests and responses from the OpenAI API, allowing for a detailed analysis to enhance prompt effectiveness. This feature aids in refining prompt strategies by understanding the dynamics of successful interactions.

User Analytics

This tool calculates the cost incurred per user for applications leveraging AI, providing a clear view of user-specific expenses. This feature is particularly useful for developers looking to gauge the financial impact of their AI-enabled applications.

Installation

Self-Hosted Installation

Clone the Repository

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

Navigate to the Directory
```
cd llm.report
```
Install Dependencies
```
yarn
```
Set Up Environment Variables
```
cp .env.example .env
```
Generate a secure secret using openssl rand -base64 32 for NEXTAUTH_SECRET and add it to the .env file.
Quick Start
- Requires Docker and Docker Compose.
- Initiates a local Postgres instance with test user credentials logged in the console.
```
yarn dx
```
The application can then be accessed at http://localhost:3000 in a web browser.

Tech Stack

llm.report utilizes a variety of modern technologies and tools to ensure a robust and scalable solution:

Next.js: Framework for building the application.
Typescript: For type safety and better code documentation.
Tailwind CSS: For designing responsive and adaptive interfaces.
Shadcn & Magic UI: For user interface components.
Postgres: Leveraged as the database system.
NextAuth.js: Handles authentication processes.
Stripe: Manages payment transactions.
Resend: Used for sending emails.

Contributing

Community involvement is welcomed in the form of issues for bugs or feature improvements, and pull requests to enhance the project. Contributors can explore opportunities to extend the platform's capabilities or improve existing functionalities.

Licensing and Credits

llm.report is inspired by other open-source projects like Dub and Plausible, adhering to the GNU Affero General Public License Version 3 or later. The project acknowledges various organizations and tools like OpenAI, shadcn-ui, and vercel for their contributions to its development.

Despite its inactive maintenance, llm.report remains a comprehensive analytics tool for OpenAI users, inviting interested developers to extend and adapt its features for future use.