This service implements use cases related to expense classification by utilizing Language Learning Models (LLMs). It showcases how to classify, generate code, and provide recommendations using several orchestrators (working with LLM) such as Guidance, Semantic Kernel, Prompt Flow, Llama Index, and Langchain. are used to categorize expenses, recommend savings, and generate SQL to visualize.
Before you begin, ensure you have the following software installed and provisioned:
To initialize the project, you'll need to create a .env file at the root of the project. This file should contain all of the environment variables required by the project. Use the .env.example file as a template.
To run the project locally, execute the following command:
docker-compose upThis project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.
When you submit a pull request, a CLA bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.
This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact [email protected] with any additional questions or comments.