Sample ChatGpt AWS CLI bot

Dockerfile

# Use an official Python runtime as a parent image
FROM python:3.10-slim

# Set the working directory in the container
WORKDIR /app

# Copy the requirements file to the container
COPY requirements.txt .

# Install the dependencies
RUN pip install --no-cache-dir -r requirements.txt


RUN apt-get update && \
    apt-get install -y \
        unzip \
        curl \
    && apt-get clean \
    && curl "https://awscli.amazonaws.com/awscli-exe-linux-x86_64.zip" -o "awscliv2.zip" \
    && unzip awscliv2.zip \
    && ./aws/install \
    && rm -rf \
        awscliv2.zip \
    && apt-get -y purge curl \
    && apt-get -y purge unzip
    
# Copy the current directory contents into the container at /app
COPY . .

# Expose port 8000 to the outside world
EXPOSE 8000

# Run the FastAPI application using Uvicorn
CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]

main.py

import subprocess
from typing import List
from fastapi import FastAPI, HTTPException
from pydantic import BaseModel, validator
from fastapi import Header, Depends
from typing import Optional


app = FastAPI()


API_TOKEN = "secure_api_token"

# Pydantic model for the input
class AWSCommand(BaseModel):
    command: str
    args: List[str]


def verify_token(token: Optional[str] = Header(None, alias="x-api-key")):
    if token is None or token != API_TOKEN:
        raise HTTPException(status_code=401, detail="Unauthorized")
    return token


@app.post("/run-aws-cli")
def run_aws_cli(command_data: AWSCommand, token: str = Depends(verify_token)):
    try:
        # Construct the AWS CLI command
        cli_command = [command_data.command] + command_data.args

        # Execute the command and capture output
        result = subprocess.run(cli_command, stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True)

        if result.returncode != 0:
            raise HTTPException(status_code=500, detail=f"Error: {result.stderr}")

        return {"output": result.stdout}

    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))


if __name__ == "__main__":
    import uvicorn
    uvicorn.run(app, host="0.0.0.0", port=8000)

requirements.txt

fastapi
uvicorn
pydantic
boto3