📊 llm.report is an open-source logging and analytics platform for OpenAI: Log your ChatGPT API requests, analyze costs, and improve your prompts.
GPL-3.0 License
[!CAUTION] Attention: llm.report is no longer actively maintained. This project was unable to find a sustainable business model, and the founders have moved on to other projects. If you are interested in maintaining or further developing this project, message me on twitter
llm.report is an open-source logging and analytics platform for OpenAI: Log your ChatGPT API requests, analyze costs, and improve your prompts.
Here are some of the features that llm.report provides out-of-the-box:
No-code solution to analyze your OpenAI API costs and token usage.
Log your OpenAI API requests / responses and analyze them to improve your prompts.
Calculate the cost per user for your AI app.
git clone https://github.com/dillionverma/llm.report.git
cd llm.report
yarn
cp .env.example .env
NEXTAUTH_SECRET
using openssl rand -base64 32
and add it to .env
- Requires Docker and Docker Compose to be installed.
- Will start a local Postgres instance with a few test users - the credentials will be logged in the console
yarn dx
Open http://localhost:3000 with your browser!
Here's how you can contribute:
Inspired by Dub and Plausible, both are open-source under the GNU Affero General Public License Version 3 (AGPLv3) or any later version. You can find it here. The reason for this is that we believe in the open-source ethos and want to contribute back to the community.