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This project is a feedback generation from human interaction to OpenAI response. Data generated from this application can be used for reinforcement learning for OpenAI.

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hbarve1/openai-response-optimisation

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OpenAI Response Optimisation

This project is a feedback generation from human interaction to OpenAI response. Data generated from this application can be used for reinforcement learning for OpenAI.

This workspace has been generated by Nx, a Smart, fast and extensible build system.

Development server

Prerequisite

  • Docker - v20
  • Node.js - >=v16
  • npm - >=v8
  • replicate .env.sample and rename to .env, put all required value in it

Docker setup

  • Docker is used for local development database setup
  • run following command in root folder
  • docker compose --env-file .env -f ./docker/docker-compose.yml up

Installation

  • npm install
  • npm run prisma -- db push - to push prisma schema to database
  • npm run dev:api - to run backend api server
  • npm run dev:app - to run frontend nextjs server
  • npx prisma studio - to run prisma GUI linked with database

Understand this workspace

Run nx graph to see a diagram of the dependencies of the projects.

Remote caching

Run npx nx connect-to-nx-cloud to enable remote caching and make CI faster.

Further help

Visit the Nx Documentation to learn more.

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This project is a feedback generation from human interaction to OpenAI response. Data generated from this application can be used for reinforcement learning for OpenAI.

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