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LlamaIndex 🦙 0.9.48

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LlamaIndex 🦙 0.9.48

Getting Started

Installation and Setup
How to read these docs
Starter Tutorial
High-Level Concepts
Customization Tutorial
Discover LlamaIndex Video Series

Use Cases

Q&A
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- RAG CLI
Chatbots
Agents
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- Agents (Putting your RAG Pipeline Together)
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- Agentic Strategies (Optimizing your RAG Pipeline)
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  - Routers
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  - Query Transformations
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    - HyDE Query Transform
    - Multi-Step Query Engine
  - Sub Question Query Engine (Intro)
  - Build your own OpenAI Agent
  - OpenAI Agent with Query Engine Tools
  - Retrieval-Augmented OpenAI Agent
  - OpenAI Agent + Query Engine Experimental Cookbook
  - OpenAI Agent Query Planning
  - Context-Augmented OpenAI Agent
- Agents
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- Tools
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  - Usage Pattern
  - LlamaHub Tools Guide
Structured Data Extraction
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- Structured Outputs
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  - Pydantic Program
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  - Query Engines + Pydantic Outputs
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  - Output Parsing Modules
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- Output Parsing Modules
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- Extracting names and locations from descriptions of people
- Extracting album data from music reviews
- Extracting information from emails
Multi-modal
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Understanding

Building an LLM application
Using LLMs
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- Privacy and Security
Loading Data (Ingestion)
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- LlamaHub
- Documents / Nodes
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  - Defining and Customizing Documents
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    - Metadata Extraction Usage Pattern
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  - Defining and Customizing Nodes
  - Transformations
- Node Parser Usage Pattern
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  - Node Parser Modules
- Ingestion Pipeline
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Indexing
Storing
Querying
Putting It All Together
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- Q&A patterns
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- Full-Stack Web Application
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  - A Guide to Building a Full-Stack Web App with LLamaIndex
  - A Guide to Building a Full-Stack LlamaIndex Web App with Delphic
- How to Build a Chatbot
- Agents
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- Full-Stack Projects
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Tracing and Debugging
Evaluating
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- Cost Analysis
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  - Usage Pattern

Optimizing

Basic Strategies
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Advanced Retrieval Strategies
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- Query Transform Cookbook
- Query Transformations
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  - HyDE Query Transform
  - Multi-Step Query Engine
- Composable Objects
- DeepMemory (Activeloop)
- Weaviate Vector Store - Hybrid Search
- Pinecone Vector Store - Hybrid Search
Agentic strategies
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- Routers
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- Query Transformations
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  - HyDE Query Transform
  - Multi-Step Query Engine
- Sub Question Query Engine (Intro)
- Build your own OpenAI Agent
- OpenAI Agent with Query Engine Tools
- Retrieval-Augmented OpenAI Agent
- OpenAI Agent + Query Engine Experimental Cookbook
- OpenAI Agent Query Planning
- Context-Augmented OpenAI Agent
Evaluation
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- End-to-End Evaluation
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- Component Wise Evaluation
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  - BEIR Out of Domain Benchmark
  - HotpotQADistractor Demo
- Evaluating
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  - Usage Pattern (Response Evaluation)
  - Usage Pattern (Retrieval)
  - Modules
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  - Evaluating With LabelledRagDataset’s
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    - Benchmarking RAG Pipelines With A LabelledRagDatatset
    - Downloading a LlamaDataset from LlamaHub
  - Contributing A LabelledRagDataset
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    - LlamaDataset Submission Template Notebook
- Component Wise Evaluation
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  - BEIR Out of Domain Benchmark
  - HotpotQADistractor Demo
- End-to-End Evaluation
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Fine-tuning
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Building Performant RAG Applications for Production
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Writing Custom Modules
Building RAG from Scratch (Lower-Level)
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Module Guides

Models
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Prompts
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Loading Data
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- Data Connectors (LlamaHub)
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  - Usage Pattern
  - Module Guides
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- Documents / Nodes
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  - Defining and Customizing Documents
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    - Metadata Extraction Usage Pattern
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  - Defining and Customizing Nodes
  - Transformations
- Node Parser Usage Pattern
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  - Node Parser Modules
- Ingestion Pipeline
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Indexing
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- Using VectorStoreIndex
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- How Each Index Works
- Module Guides
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- Composability
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Storing
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Querying
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- Query Pipeline
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  - Usage Pattern
  - Module Usage
  - Module Guides
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- Query Engine
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  - Usage Pattern
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    - Response Modes
    - Streaming
  - Module Guides
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  - Supporting Modules
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    - Query Transformations
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      - HyDE Query Transform
      - Multi-Step Query Engine
- Chat Engine
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  - Usage Pattern
  - Module Guides
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- Agents
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- Retriever
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  - Retriever Modes
  - Retriever Modules
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- Response Synthesizer
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  - Response Synthesis Modules
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- Routers
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- Node Postprocessor
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  - Node Postprocessor Modules
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- Structured Outputs
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  - Pydantic Program
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  - Query Engines + Pydantic Outputs
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  - Output Parsing Modules
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Agents
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Observability
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Evaluating
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- Usage Pattern (Response Evaluation)
- Usage Pattern (Retrieval)
- Modules
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- Evaluating With LabelledRagDataset’s
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  - Benchmarking RAG Pipelines With A LabelledRagDatatset
  - Downloading a LlamaDataset from LlamaHub
- Contributing A LabelledRagDataset
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  - LlamaDataset Submission Template Notebook
Supporting Modules
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- ServiceContext

API Reference

API Reference
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- Agents
- Callbacks
- Composability
- Evaluation
- Example Notebooks
- Finetuning
- Indices
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- LLM Predictors
- LLMs
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- Memory
- Multi-Modal LLMs, Vector Stores, Embeddings, Retriever, and Query Engine
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  - OpenAI
  - Replicate
- Node Postprocessor
- Node
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- Playground
- Prompt Templates
- Querying an Index
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  - Retrievers
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  - Response Synthesizer
  - Query Engines
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  - Chat Engines
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  - Query Bundle
  - Query Transform
- Data Connectors
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- Response
- Service Context
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  - Embeddings
  - OpenAIEmbedding
  - HuggingFaceEmbedding
  - OptimumEmbedding
  - InstructorEmbedding
  - LangchainEmbedding
  - GoogleUnivSentEncoderEmbedding
  - Node Parser
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  - PromptHelper
  - LLMs
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- Embeddings
- OpenAIEmbedding
- HuggingFaceEmbedding
- OptimumEmbedding
- InstructorEmbedding
- LangchainEmbedding
- GoogleUnivSentEncoderEmbedding
- Storage Context
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- Structured Index Configuration

Community

Integrations
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Frequently Asked Questions (FAQ)
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Full-Stack Projects
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Contributing

Contributing to LlamaIndex
Documentation Guide

Changes

ChangeLog
Deprecated Terms

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get_root_nodes#

llama_index.node_parser.get_root_nodes(nodes: List[BaseNode]) → List[BaseNode]#: Get root nodes.

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get_root_nodes
- get_root_nodes()