AutoRAG

Pipeline Optimizer

Automates the process of finding and optimizing an effective pipeline for Retrieval-Augmented Generation (RAG) models.

AutoRAG: An Open-Source Framework for Retrieval-Augmented Generation (RAG) Evaluation & Optimization with AutoML-Style Automation

GitHub

3k stars
23 watching
228 forks
Language: Python
last commit: almost 2 years ago
Linked from 1 awesome list

analysisautomlbenchmarkingdocument-parserembeddingsevaluationllmllm-evaluationllm-opsopen-sourceopsoptimizationpipelinepythonqaragrag-evaluationretrieval-augmented-generation

Backlinks from these awesome lists:

Related projects:

RepositoryDescriptionStars
automl/auto-pytorchAn automatic deep learning framework that jointly optimizes network architecture and training hyperparameters.2,385
whyhow-ai/rule-based-retrievalA Python package that enables the creation and management of Retrieval Augmented Generation applications with filtering capabilities.229
microsoft/flamlAutomates machine learning workflows and optimizes model performance using large language models and efficient algorithms3,968
udellgroup/oboeAutomated machine learning system for selecting promising models or pipelines for new datasets82
datacanvasio/hypergbmAutomated machine learning tool for tabular data pipelines343
pku-dair/mindwareAn efficient AutoML system that automates the machine learning lifecycle53
infiniflow/ragflowAn RAG (Retrieval-Augmented Generation) engine based on deep document understanding to provide truthful question-answering capabilities.25,479
autogluon/autogluonAutomates machine learning tasks to train accurate models in just a few lines of code8,167
explodinggradients/ragasA toolkit for evaluating and optimizing Large Language Model applications with objective metrics, test data generation, and seamless integrations.7,598
pathwaycom/llm-appProvides pre-built AI application templates to integrate Large Language Models (LLMs) with various data sources for scalable RAG and enterprise search.7,426
automaapp/automaAn extension for automating browser tasks by creating a workflow of connected blocks.12,581
western-oc2-lab/automl-implementation-for-static-and-dynamic-data-analyticsAutomated Machine Learning implementation for static and dynamic data analytics with a focus on IoT anomaly detection624
mljar/mljar-supervisedAutomated Machine Learning library for Python that streamlines data preparation, model selection, and hyperparameter tuning for tabular data.3,081
llmware-ai/llmwareA framework for building enterprise LLM-based applications using small, specialized models8,303
truefoundry/cognitaA modular framework for building production-ready AI applications with integrated data management and model deployment capabilities3,401