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Helper modules for AI Engineering RAG Bootcamp reference implementations

Project description

aieng-rag-utils

aieng-rag-utils is a Python library providing utility functions and tools to streamline Retrieval-Augmented Generation (RAG) workflows. It is designed to help AI engineers build, evaluate, and deploy RAG-based applications efficiently.

Features

  • Document loaders, chunkers and pretty-print
  • Web Search
  • Vector store integrations
  • Query and retrieval helpers
  • Evaluation and benchmarking tools

Installation

pip3 install aieng-rag-utils

Sample Usage

from aieng.rag.utils import get_device_name
from aieng.rag.utils.search import DocumentReader
from aieng.rag.utils.pubmed import RAGLLM

device = get_device_name()

doc_reader = DocumentReader(directory_path="./source_documents")
docs, chunks = doc_reader.load()

llm = RAGLLM(
    llm_type="openai",
    llm_name="gpt-4o",
    api_base=OPENAI_BASE_URL,
    api_key=OPENAI_API_KEY,
).load_model(**rag_cfg) # RAG Configuration

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