LlamaIndex Howto

LlamaIndex is a powerful open-source data framework for connecting custom data sources to large language models (LLMs), enabling the creation of intelligent applications augmented by domain-specific knowledge.
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How to Use LlamaIndex

Install LlamaIndex: Install the LlamaIndex package using pip: pip install llama-index
Set up OpenAI API key: Set your OpenAI API key as an environment variable: export OPENAI_API_KEY='your-api-key-here'
Import required modules: Import necessary modules from llama_index: from llama_index import GPTVectorStoreIndex, SimpleDirectoryReader
Load documents: Load your documents using SimpleDirectoryReader: documents = SimpleDirectoryReader('data').load_data()
Create index: Create a vector store index from your documents: index = GPTVectorStoreIndex.from_documents(documents)
Query the index: Create a query engine and ask questions: query_engine = index.as_query_engine() response = query_engine.query('Your question here')
Customize settings (optional): Customize LLM, embedding model, or other settings as needed for your specific use case
Implement advanced features (optional): Explore more advanced features like custom data connectors, different index types, or integrations with other tools and services

LlamaIndex FAQs

LlamaIndex is an open-source data framework for connecting custom data sources to large language models (LLMs). It provides tools for ingesting, indexing, and querying data to build LLM-powered applications augmented with private or domain-specific knowledge.

LlamaIndex Monthly Traffic Trends

LlamaIndex experienced a 2.9% decline in traffic, with 572K visits in November. The lack of recent product updates and the release of Llama 3.2 and Meta's Gemini app powered by Llama 2, which expanded into new markets like education, might have impacted user engagement.

View history traffic

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