Integrating Open Source Models with LlamaIndex

LlamaIndex is a data framework for LLM applications. Learn how to use open source models with LlamaIndex.

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Installation

bash
pip install llama-index llama-index-llms-huggingface

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Basic Setup

python
from llama_index.core import VectorStoreIndex, SimpleDirectoryReader, Settings
from llama_index.llms.huggingface import HuggingFaceLLM
Settings.llm = HuggingFaceLLM(model_name="meta-llama/Llama-2-7b-chat-hf")
documents = SimpleDirectoryReader("data").load_data()
index = VectorStoreIndex.from_documents(documents)
query_engine = index.as_query_engine()
response = query_engine.query("What is the main topic?")

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Advanced Features

Hierarchical indexing for large documents

Custom retrievers and query engines

Multi-document agents

Persistent storage with vector databases