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llm_service's Introduction

The Steps to Run the LLM service Locally

Running the frontend:

  1. Navigate to the frontend directory: cd frontend
  2. Install node node:18.17.1
  3. Install PNPM: npm install -g [email protected] pnpm:9.1.2
  4. Install Dependencies: pnpm install
  5. start the application in dev mode: pnpm dev
  6. production build: pnpm build
  7. any linter problem pnpm lint:fix or to check pnpm lint

Running the backend

  • run docker containers
  • after making sure that the database and the frontend are running, run the LlmServiceApplication
  • to run the Backend linter mvn spotless:check to fix mvn spotless:check
  • Backend uses cpp plugin to run the modal , C++11 g++ cmake

How to use Docker

  • Run docker compose up -d
  • if something is changed in the front end and you want the latest changes docker compose up -d --no-deps --build build-fe

llm_service's People

Contributors

mgrdich avatar yerish26 avatar rbakkalian avatar atg1996 avatar joseph-alakach avatar aramo2000 avatar

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llm_service's Issues

More documentations on the API

Since the swagger is configured, we need more research to add more documentation on the API, making its functionality part clear.

Conversation skeleton styling fix

The conversation skeleton needs some styling adjustments to enhance its visual presentation and improve user experience. Currently, it lacks consistency and readability in certain areas.

Expected Outcome:
A polished and visually appealing conversation skeleton that provides a seamless experience for users while waiting for content to load.

We need an API that returns all the conversation of particular user

we need to develop an API endpoint that retrieves all conversations associated with a particular user. Through it, the clients will be able to fetch the complete history of conversations for a specified user, for example, viewing past messages and analyzing user engagement.

Expected Outcome:
An API endpoint that retrieves and delivers all conversations related to a specific user, enabling advanced user interaction analytics.

add frontend validation

Users should receive immediate feedback on password strength during input, empowering them to create stronger passwords

error 404/500 pages should have CSS styling.

Adding CSS styling to the 404 and 500 error pages will improve the user experience when encountering these error states. Users will be presented with visually appealing error pages that align with the design of the rest of the application.

show the backend error in the frontend via toasters

By integrating toasters, or notification pop-ups, into our frontend interface, we can dynamically alert users to any errors or validation issues returned from the backend during password validation or other form submissions.

Login registration welcome page design is missing

The login, register, and welcome pages currently lack a skeleton layout, which is essential for providing users with visual feedback while the content is loading. Implementing a skeleton layout for these pages will enhance the user experience by indicating that the page is actively loading and reducing perceived load times.

Dockerise the Java Backend with llama cpp

Due to complex dependencies that llama.cpp uses , normal openjdk image did not work out, we need to use alpine or more basic image and install our dependencies and create new image.

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