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It serves as a helpful Amazon Web Service assistant, capable of answering questions regarding AWS solutions based on an AWS Solutions Architect PDF.\n\n![preview](image/preview.png)\n\n## Getting Started\n\n### Prerequisites\n\nBefore you begin, make sure you have the following installed:\n\n- Python (\u003e=3.10)\n- [Virtualenv](https://virtualenv.pypa.io/en/latest/)\n- [Git](https://git-scm.com/)\n\n### Installation\n\n1. Clone the repository:\n\n   ```bash\n   git clone git@github.com:aibunny/cloudwhiz.git\n   ```\n2. Navigate to the project directory:\n\n   ```bash\n   cd cloudwhiz\n   ```\n3. Create a virtual environment:\n\n   ```bash\n   virtualenv venv\n   ```\n4. Activate the virtual environment:\n\n   - On Windows:\n\n     ```bash\n     .\\venv\\Scripts\\activate\n     ```\n   - On Unix or MacOS:\n\n     ```bash\n     source venv/bin/activate\n     ```\n5. Create a `.env` file in the project root and add your Hugging Face API token:\n\n   ```env\n   HUGGINGFACEHUB_API_TOKEN=hf_your_token_here\n   ```\n6. Install the required dependencies:\n\n   ```bash\n   pip install -r requirements.txt\n   ```\n\n## Running the Application\n\nAfter setting up the environment, you can run the CloudWhiz  using Streamlit. Execute the following command:\n\n```bash\nstreamlit run helper.py\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Faibunny%2Fcloudwhiz","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Faibunny%2Fcloudwhiz","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Faibunny%2Fcloudwhiz/lists"}