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Project Setup Instructions

Prerequisites

Ensure that you have the following installed on your system:

  • WSL (Windows Subsystem for Linux)
  • Ubuntu
  • VS Code
  • Podman

Steps

  1. Restart your system and open the terminal.

    wsl -l -v
  2. Open Ubuntu.

    # It will open your VS code on your Ubuntu WSL
    code
  3. Make a directory in the VS Code Terminal.

    mkdir <your-repo-name>
    cd <your-repo-name>
  4. Initialize Git in VS Code Terminal.

    git init
    git config --global user.name "iitm-rollno"
    git config --global user.email "iitm-email"
    git remote add <your-repo-name> <your-repo-link.git>
    git pull <your-repo-name> main
  5. Authenticate yourself using VS Code to allow authentication for the repo.

  6. Go to your repo. On the left extreme of VS Code, there’s a node-type shape; open that and figure out where you have created the repo using the open folder.

  7. Open Ubuntu Terminal (not VS Code terminal).

    cd <your-repo-name>
    ls  # to list all the files and ensure you are in the GitHub repo
  8. Do your first commit. Make a new file app.py in VS Code.

Build the Docker Image

Make sure you have Podman installed. Run the following command to build the Docker image:

podman build -t user-name/repo-name .

Run the Docker Container

  • Run the container with the following command:
podman run -e AIPROXY_TOKEN=$env:AIPROXY_TOKEN -p 8000:8000 user-name/repo-name

Access the API

  • You can access the API at http://localhost:8000/. Use the following endpoints:

  • Home Endpoint: GET /

    • Returns a simple message to check if the server is running.
  • Run Task Endpoint: POST /run?task=<task_description>

    • Execute a specific task by providing a task description.
  • Read File Endpoint: GET /read?path=<file_path>

    • Read the contents of a specified file.

Example Commands

  • To run a specific task, use:
curl -X POST "http://localhost:8000/run?task=Format+/data/format.md+using+prettier"
  • To read a file, use:
curl "http://localhost:8000/read?path=/data/format.md"

Contribution Guidelines

  1. Fork the repository.
  2. Create a new branch for your feature or bug fix.
  3. Make your changes and commit them.
  4. Push your changes to your forked repository.
  5. Create a pull request to the main repository.

License

  • This project is licensed under the MIT License. See the LICENSE file for details.

About

Intelligent automation agent utilizing a LLM and RAG to automate routine operational tasks in a CI pipeline, enhancing efficiency in log processing, data extraction, and report generation.

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