Telco-RAG is a specialized Retrieval-Augmented Generation (RAG) framework designed to tackle the unique challenges presented by the telecommunications industry, particularly when working with complex and rapidly evolving 3GPP documents.

• Bornea, A.-L., Ayed, F., De Domenico, A., Piovesan, N., & Maatouk, A. (2024). Telco-RAG: Navigating the Challenges of Retrieval-Augmented Language Models for Telecommunications. arXiv preprint arXiv:2404.15939. DOI | Read the paper

• Custom RAG Pipeline: Tailored specifically to handle the intricacies of telecommunications standards.
• Enhanced Query Processing: Utilizes a dual-stage query enhancement and retrieval process to improve the accuracy and relevance of generated responses.
• Hyperparameter Optimization: Carefully tuned to deliver the best performance by optimizing chunk sizes, context length, and embedding models.
• NN Router: A neural network-based router that improves the efficiency and accuracy of document retrieval, significantly reducing RAM usage.
• Open-Source: Freely available for the community to use, adapt, and improve upon.

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To get started with Telco-RAG, you'll need to clone the repository and set up the environment:

git clone https://github.com/netop-team/telco-rag.git
cd <repository-directory>

Prerequisites Python 3.8+ Uvicorn Other dependencies listed in requirements.txt

Installation Install the necessary Python packages:

cd .\Telco-RAG_api\
pip install -r requirements.txt

Running the API To launch the API server, use the following command:

uvicorn main:app --reload

License This project is licensed under the MIT License - see the LICENSE file for details.