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It integrates real-time access tools like search, retrieval, summarization, and argumentation into AI models via a Python library.\n\nTo read the research paper detailing RTRA, click [here](https://eternityai.tech).\n\n## Installation\n\nInstall Rtrafactor into your project using pip:\n\n```bash\npip install rtrafactor\n```\n\n## Package Validation\n\nEnsure the authenticity of the installed package:\n\n```bash\npip show rtrafactor\n```\n\n## Usage\n\nRtrafactor is available as a L2LM (Language-to-Language Model) architecture, currently integrated with HuggingFace's Inference API. Follow these steps to use Rtrafactor:\n\n1. **Import RTRAConnector**: \n\n   ```python\n   from rtrafactor import RTRAConnector\n   ```\n\n2. **Instantiate RTRAConnector**: \n\n   ```python\n   connector = RTRAConnector(huggingface_model, huggingface_api_token)\n   ```\n\n3. **Query for Answers**: \n\n   ```python\n   query = \"Your question here?\"\n   one_shot_answer = connector.compare_answers(query)\n   print(one_shot_answer)\n   ```\n\n## Examples\n\nHere are some example queries you can try with Rtrafactor:\n\n1. **Why is Delhi's CM in jail?**\n2. **Who is Dr. Kuldip Singh Patel?**\n3. **Who is Udit Akhouri?**\n\n## Limitations \u0026 Future Scope\n\nWhile RTRA enhances model capabilities, there are still limitations to address:\n\n- **Hallucination \u0026 Citation**: Addressing false information and improving citation accuracy.\n- **Latency**: Reducing response time and optimizing underlying architecture.\n\n## Breakthrough\n\nRTRA architecture challenges the conventional approach of relying on vast computational resources by democratizing access to the internet's information. It enables developers, including solo developers and small teams, to build efficient models without requiring extensive computational resources.\n\n## Acknowledgements\n\nThis project was developed by Udit Raj, Sanya Gupta, and other fellow researchers at the Indian Institute of Technology, Patna, as part of ongoing research in AI and natural language processing.\n\n---\n\nFor detailed usage examples and code, visit [Rtrafactor on Google Colab](https://colab.research.google.com/drive/1nzJou9tONTF6AOKqJTZc8--rIwI38JuR?usp=sharing).\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fuditakhourii%2Frtrafactor","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fuditakhourii%2Frtrafactor","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fuditakhourii%2Frtrafactor/lists"}