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Generative AI is revolutionizing industries by autonomously creating text, images, audio, and video. Libraries like LangChain, LlamaIndex, Hugging Face Transformers, LoRA, and OpenAI API offer frameworks for diverse applications such as chatbots, content generation, education, and healthcare. These tools address needs like knowledge management, Retrieval-Augmented Generation (RAG), and cost-effective embedding, with specific strengths in optimized indexing, parameter efficiency, and scalability. This review highlights their development, advantages, and trade-offs in accuracy, cost, speed, and resource utilization, emphasizing suitability for specific tasks. Insights from various studies underline the libraries’ ability to balance performance and resource constraints effectively. Additionally, the future scope of generative AI includes growth in multimodal capabilities, real-time learning, and ethical AI practices, paving the way for more robust and responsible AI implementations.

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Comparative Study of LLM Libraries: LangChain, LlamaIndex, OpenAI API, Hugging Face, and LoRA

  • 会议论文

  • 发表日期：

    2026年

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  • Shreya Bansal,
  • Ishika,
  • Muskan,
  • Greeshma Arya

摘要

Generative AI is revolutionizing industries by autonomously creating text, images, audio, and video. Libraries like LangChain, LlamaIndex, Hugging Face Transformers, LoRA, and OpenAI API offer frameworks for diverse applications such as chatbots, content generation, education, and healthcare. These tools address needs like knowledge management, Retrieval-Augmented Generation (RAG), and cost-effective embedding, with specific strengths in optimized indexing, parameter efficiency, and scalability. This review highlights their development, advantages, and trade-offs in accuracy, cost, speed, and resource utilization, emphasizing suitability for specific tasks. Insights from various studies underline the libraries’ ability to balance performance and resource constraints effectively. Additionally, the future scope of generative AI includes growth in multimodal capabilities, real-time learning, and ethical AI practices, paving the way for more robust and responsible AI implementations.