LLM Engineer Toolkit: A Curated Collection of 120+ LLM Libraries 154

What is LLM Engineer Toolkit?

LLM Engineer Toolkit is a carefully curated library of LLM tools that categorizes more than 120 LLM-related libraries in detail by function and use, covering the tools needed for the entire LLM development workflow—from training and fine-tuning, application development, inference serving, to safety and evaluation.

LLM Engineer Toolkit Tool Categories

1. LLM Training and Fine-Tuning

• unsloth: Quickly fine-tunes LLMs and reduces memory usage.

• PEFT: A parameter-efficient fine-tuning library.

• TRL: Trains Transformer language models via reinforcement learning.

• DeepSpeed: A distributed training and inference optimization library.

2. LLM Application Development

• LangChain: Develops applications based on LLMs.

• Llama Index: Provides a data framework for LLM applications.

• Haystack: An end-to-end LLM framework that supports integration with Transformer models and vector search.

3. LLM Inference

• vLLM: A high-throughput, memory-efficient inference engine.

• LightLLM: A lightweight, scalable inference framework.

• TensorRT-LLM: An Nvidia framework for optimizing LLM inference.

4. LLM Serving

• Langcorn: Automatically deploys LangChain applications as FastAPI services.

• LitServe: A fast serving engine that supports batching, streaming, and automatic GPU scaling.

5. LLM Data Extraction

• Crawl4AI: An open-source, LLM-friendly web crawler.

• Docling: A document parsing tool.

• PyMuPDF4LLM: A tool for extracting content from PDFs.

6. LLM Data Generation

• DataDreamer: A synthetic data generation library.

• fabricator: A flexible synthetic data generation framework.

7. LLM Safety and Monitoring

• LLM Guard: A security tool for LLM interactions.

• Weights & Biases: Tracks LLM performance.

• Helicone: An open-source LLM observability platform.

8. LLM Evaluation

• Ragas: An evaluation tool for LLM applications.

• LangTest: Provides a variety of test types to evaluate the accuracy, bias, and robustness of LLMs.

9. LLM Embedding Models

• Sentence-Transformers: State-of-the-art text embedding models.

• Text Embedding Inference: A high-performance embedding model inference tool.

10. Others

• LLM Transparency Tool: Analyzes the internal mechanisms of Transformer models.

• mergekit: A tool for merging pre-trained LLMs.

llm-engineer-toolkit libraryGitHub Repository:https://github.com/KalyanKS-NLP/llm-engineer-toolkit