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LlamaIndex 🦙 v0.10.19
LlamaIndex 🦙 v0.10.19

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
    • RAG CLI
  • Chatbots
  • Agents
    • Agents (Putting your RAG Pipeline Together)
      • Build your own OpenAI Agent
      • OpenAI Agent with Query Engine Tools
      • OpenAI Agent Query Planning
      • OpenAI Assistant Agent
      • OpenAI Assistant Advanced Retrieval Cookbook
      • OpenAI agent: specifying a forced function call
      • Single-Turn Multi-Function Calling OpenAI Agents
      • Context-Augmented OpenAI Agent
    • Agentic Strategies (Optimizing your RAG Pipeline)
      • Routers
        • Router Query Engine
        • Retriever Router Query Engine
        • SQL Router Query Engine
        • Router Retriever
      • Query Transformations
        • 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
      • Usage Pattern
      • Module Guides
        • 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
        • Recursive Retriever + Document Agents
        • Multi-Document Agents
        • GPT Builder Demo
        • Single-Turn Multi-Function Calling OpenAI Agents
        • OpenAI Assistant Agent
        • Benchmarking OpenAI Retrieval API (through Assistant Agent)
        • OpenAI Assistant Advanced Retrieval Cookbook
        • ReAct Agent - A Simple Intro with Calculator Tools
        • ReAct Agent with Query Engine (RAG) Tools
        • LLMCompiler Agent Cookbook
        • Building a Custom Agent
        • Building an Agent around a Query Pipeline
        • Step-wise, Controllable Agents
        • Controllable Agents for RAG
        • Controllable Agents for RAG
      • Tools
        • Usage Pattern
        • LlamaHub Tools Guide
      • Lower-Level Agent API
    • Tools
      • Usage Pattern
      • LlamaHub Tools Guide
  • Structured Data Extraction
    • Structured Outputs
      • Pydantic Program
        • LLM Pydantic Program
        • OpenAI Pydantic Program
        • Guidance Pydantic Program
        • Guidance for Sub-Question Query Engine
        • DataFrame Structured Data Extraction
        • Evaporate Demo
      • Query Engines + Pydantic Outputs
        • Query Engine with Pydantic Outputs
        • Pydantic Tree Summarize
        • Download Data
      • Output Parsing Modules
        • Guardrails Output Parsing
        • Langchain Output Parsing
        • Guidance Pydantic Program
        • Guidance for Sub-Question Query Engine
        • OpenAI Pydantic Program
    • Output Parsing Modules
      • Guardrails Output Parsing
      • Langchain Output Parsing
      • Guidance Pydantic Program
      • Guidance for Sub-Question Query Engine
      • OpenAI Pydantic Program
    • Extracting names and locations from descriptions of people
    • Extracting album data from music reviews
    • Extracting information from emails
  • Multi-modal
    • Advanced Multi-Modal Retrieval using GPT4V and Multi-Modal Index/Retriever
    • Multi-modal retrieval with CLIP
    • Image to Image Retrieval
    • Semi-structured Image Retrieval
    • Chroma Multi-Modal Demo with LlamaIndex
    • Multi-Modal on PDF’s with tables.
    • Multi-Modal LLM using Google’s Gemini model for image understanding and build Retrieval Augmented Generation with LlamaIndex
    • Multimodal Ollama Cookbook
    • Multi-Modal GPT4V Pydantic Program
    • Retrieval-Augmented Image Captioning
    • [Beta] Multi-modal ReAct Agent
    • GPT4-V Experiments with General, Specific questions and Chain Of Thought (COT) Prompting Technique.
    • Multi-Modal LLM using Replicate LlaVa, Fuyu 8B, MiniGPT4 models for image reasoning
    • GPT4-V:
    • Evaluating Multi-Modal RAG
    • Multi-Modal LLM using OpenAI GPT-4V model for image reasoning
    • Multi-Modal LLM using Replicate LlaVa, Fuyu 8B, MiniGPT4 models for image reasoning

Understanding

  • Building an LLM application
  • Using LLMs
    • Privacy and Security
  • Loading Data (Ingestion)
    • LlamaHub
    • Documents / Nodes
      • Defining and Customizing Documents
        • Metadata Extraction Usage Pattern
          • Extracting Metadata for Better Document Indexing and Understanding
          • Automated Metadata Extraction for Better Retrieval + Synthesis
          • Entity Metadata Extraction
          • Metadata Extraction and Augmentation w/ Marvin
          • Pydantic Extractor
      • Defining and Customizing Nodes
      • Transformations
    • Node Parser Usage Pattern
      • Node Parser Modules
    • Ingestion Pipeline
      • Transformations
      • Advanced Ingestion Pipeline
      • Async Ingestion Pipeline + Metadata Extraction
      • Ingestion Pipeline + Document Management
      • Redis Ingestion Pipeline
      • Building a Live RAG Pipeline over Google Drive Files
      • Parallelizing Ingestion Pipeline
  • Indexing
  • Storing
  • Querying
  • Putting It All Together
    • Q&A patterns
      • A Guide to Extracting Terms and Definitions
      • Knowledge Graphs
      • Structured Data
      • A Guide to LlamaIndex + Structured Data
      • Airbyte SQL Index Guide
    • Full-Stack Web Application
      • 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
      • Build your own OpenAI Agent
      • OpenAI Agent with Query Engine Tools
      • OpenAI Agent Query Planning
      • OpenAI Assistant Agent
      • OpenAI Assistant Advanced Retrieval Cookbook
      • OpenAI agent: specifying a forced function call
      • Single-Turn Multi-Function Calling OpenAI Agents
      • Context-Augmented OpenAI Agent
    • Full-Stack Projects
      • create-llama Blog
      • create-llama Repo
      • create-llama Additional Templates
      • SEC Insights App
      • SEC Insights Repo
      • Chat LlamaIndex App
      • Chat LlamaIndex Repo
      • RAGs Repo
      • RAG CLI
  • Tracing and Debugging
  • Evaluating
    • Cost Analysis
      • Usage Pattern

Optimizing

  • Basic Strategies
    • Accessing/Customizing Prompts within Higher-Level Modules
    • Advanced Prompt Techniques (Variable Mappings, Functions)
    • Advanced Prompt Techniques (Variable Mappings, Functions)
    • Prompt Engineering for RAG
    • BM25 Retriever
    • Reciprocal Rerank Fusion Retriever
    • Weaviate Vector Store - Hybrid Search
    • Pinecone Vector Store - Hybrid Search
    • Vector Store Index usage examples
    • Defining and Customizing Documents
      • Metadata Extraction Usage Pattern
        • Extracting Metadata for Better Document Indexing and Understanding
        • Automated Metadata Extraction for Better Retrieval + Synthesis
        • Entity Metadata Extraction
        • Metadata Extraction and Augmentation w/ Marvin
        • Pydantic Extractor
    • Defining and Customizing Nodes
    • Metadata Extraction Usage Pattern
      • Extracting Metadata for Better Document Indexing and Understanding
      • Automated Metadata Extraction for Better Retrieval + Synthesis
      • Entity Metadata Extraction
      • Metadata Extraction and Augmentation w/ Marvin
      • Pydantic Extractor
    • Multi-Tenancy RAG with LlamaIndex
  • Advanced Retrieval Strategies
    • Query Transform Cookbook
    • Query Transformations
      • HyDE Query Transform
      • Multi-Step Query Engine
    • Composable Objects
    • DeepMemory (Activeloop)
    • Weaviate Vector Store - Hybrid Search
    • Pinecone Vector Store - Hybrid Search
  • Agentic strategies
    • Routers
      • Router Query Engine
      • Retriever Router Query Engine
      • SQL Router Query Engine
      • Router Retriever
    • Query Transformations
      • 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
    • End-to-End Evaluation
      • QuestionGeneration
      • BatchEvalRunner - Running Multiple Evaluations
      • Correctness Evaluator
      • Faithfulness Evaluator
      • Guideline Evaluator
      • Pairwise Evaluator
      • Relevancy Evaluator
      • Embedding Similarity Evaluator
    • Component Wise Evaluation
      • BEIR Out of Domain Benchmark
      • HotpotQADistractor Demo
    • Evaluating
      • Usage Pattern (Response Evaluation)
      • Usage Pattern (Retrieval)
      • Modules
        • Faithfulness Evaluator
        • Relevancy Evaluator
        • Answer Relevancy and Context Relevancy Evaluations
        • 🚀 RAG/LLM Evaluators - DeepEval
        • Guideline Evaluator
        • Correctness Evaluator
        • Embedding Similarity Evaluator
        • QuestionGeneration
        • BatchEvalRunner - Running Multiple Evaluations
        • Evaluating Multi-Modal RAG
        • Retrieval Evaluation
      • Evaluating With LabelledRagDataset’s
        • Benchmarking RAG Pipelines With A LabelledRagDatatset
        • Downloading a LlamaDataset from LlamaHub
      • Contributing A LabelledRagDataset
        • LlamaDataset Submission Template Notebook
    • Component Wise Evaluation
      • BEIR Out of Domain Benchmark
      • HotpotQADistractor Demo
    • End-to-End Evaluation
      • QuestionGeneration
      • BatchEvalRunner - Running Multiple Evaluations
      • Correctness Evaluator
      • Faithfulness Evaluator
      • Guideline Evaluator
      • Pairwise Evaluator
      • Relevancy Evaluator
      • Embedding Similarity Evaluator
  • Fine-tuning
    • Fine-tuning an Adapter
    • Embedding Fine-tuning Guide
    • Router Fine-tuning
    • Embedding Fine-tuning Repo
    • Embedding Fine-tuning Blog
    • GPT-3.5 Fine-tuning Notebook (Colab)
    • GPT-3.5 Fine-tuning Notebook (Notebook link)
    • Fine-tuning a gpt-3.5 ReAct Agent on Better Chain of Thought
    • [WIP] Function Calling Fine-tuning
    • GPT-3.5 Fine-tuning Notebook (Colab)
    • GPT-3.5 Fine-tuning Notebook (in Repo)
    • OpenAI Function Calling Fine-tuning
    • Llama2 Structured Output Fine-tuning
    • Llama 2 Text-to-SQL Fine-tuning (w/ Gradient.AI)
    • Llama 2 Text-to-SQL Fine-tuning (w/ Modal, Repo)
    • Llama 2 Text-to-SQL Fine-tuning (w/ Modal, Notebook)
    • Knowledge Distillation For Fine-Tuning A GPT-3.5 Judge (Correctness)
    • Knowledge Distillation For Fine-Tuning A GPT-3.5 Judge (Pairwise)
    • Cross-Encoder Finetuning
    • Finetuning Llama 2 for Text-to-SQL
    • Finetuning GPT-3.5 to Distill GPT-4
    • Cohere Custom Reranker
  • Building Performant RAG Applications for Production
    • Recursive Retriever + Query Engine Demo
    • Document Summary Index
    • Metadata Replacement + Node Sentence Window
    • Auto-Retrieval from a Vector Database
    • Document Summary Index
    • Recursive Retriever + Document Agents
    • Comparing Methods for Structured Retrieval (Auto-Retrieval vs. Recursive Retrieval)
    • Sub Question Query Engine
    • Joint QA Summary Query Engine
    • Recursive Retriever + Document Agents
    • Router Query Engine
    • OpenAI Agent + Query Engine Experimental Cookbook
    • OpenAI Agent Query Planning
    • Embedding Fine-tuning Guide
  • Writing Custom Modules
  • Building RAG from Scratch (Lower-Level)
    • Building Data Ingestion from Scratch
    • Building Retrieval from Scratch
    • Building RAG from Scratch (Open-source only!)
    • Building a (Very Simple) Vector Store from Scratch
    • Building Response Synthesis from Scratch
    • Building Evaluation from Scratch
    • Building Hybrid Search from Scratch
    • Building a Router from Scratch
    • Building an Advanced Fusion Retriever from Scratch
    • Query Pipeline for Advanced Text-to-SQL
    • Query Pipeline over Pandas DataFrames

Module Guides

  • Models
    • Using LLMs
      • Using LLMs as standalone modules
      • Customizing LLMs within LlamaIndex Abstractions
      • Available LLM integrations
        • AI21
        • Anthropic
        • Anyscale
        • Bedrock
        • Connect to Bedrock with Access Keys
        • Clarifai LLM
        • Cohere
        • DashScope LLMS
        • Multi-Modal LLM using DashScope qwen-vl model for image reasoning
        • EverlyAI
        • Fireworks
        • Friendli
        • Gradient Base Model
        • Gradient Model Adapter
        • Groq
        • HuggingFace LLM - Camel-5b
        • HuggingFace LLM - StableLM
        • Local Llama2 + VectorStoreIndex
        • Konko
        • LangChain LLM
        • LiteLLM
        • Llama API
        • LlamaCPP
        • LocalAI
        • Maritalk
        • MistralAI
        • MistralAI Cookbook
        • Monster API <> LLamaIndex
        • MyMagic AI LLM
        • Neutrino AI
        • Nvidia TensorRT-LLM
        • Nvidia Triton
        • Ollama - Llama 2 7B
        • OpenAI
        • Azure OpenAI
        • OpenLLM
        • OpenRouter
        • PaLM
        • Perplexity
        • Portkey
        • Predibase
        • Replicate - Llama 2 13B
        • Replicate - Vicuna 13B
        • Llama2 + VectorStoreIndex
        • RunGPT
        • Setup
        • Interacting with LLM deployed in Amazon SageMaker Endpoint with LlamaIndex
        • Together AI LLM
        • Vertex AI
        • Basic auth example for service account
        • Streaming Usage
        • Chat Usage
        • Async Chat
        • Streaming Chat
        • Gemini Models
        • Install Vllm
        • Orca-7b Completion Example
        • LLama-2-7b Completion Example
        • mistral chat 7b Completion Example
        • Api Response
        • Xorbits Inference
        • ModelScope LLMS
      • Embeddings
        • Azure OpenAI
        • Embeddings with Clarifai
        • CohereAI Embeddings
        • Custom Embeddings
        • Elasticsearch Embeddings
        • Qdrant FastEmbed Embeddings
        • Google PaLM Embeddings
        • Gradient Embeddings
        • Anyscale Embeddings
        • Local Embeddings with HuggingFace
        • Jina Embeddings
        • LangChain Embeddings
        • LLMRails Embeddings
        • MistralAI Embeddings
        • OpenAI Embeddings
        • Interacting with Embeddings deployed in Amazon SageMaker Endpoint with LlamaIndex
        • Text Embedding Inference
        • Together AI Embeddings
        • Voyage Embeddings
        • Nomic Embedding
        • Fireworks Embeddings
      • Prompts
        • Usage Pattern
        • Completion prompts
        • Chat prompts
        • Accessing/Customizing Prompts within Higher-Level Modules
        • Advanced Prompt Techniques (Variable Mappings, Functions)
        • Prompt Engineering for RAG
        • “Optimization by Prompting” for RAG
        • EmotionPrompt in RAG
      • Using local models
      • Run Llama2 locally
    • Embeddings
      • Azure OpenAI
      • Embeddings with Clarifai
      • CohereAI Embeddings
      • Custom Embeddings
      • Elasticsearch Embeddings
      • Qdrant FastEmbed Embeddings
      • Google PaLM Embeddings
      • Gradient Embeddings
      • Anyscale Embeddings
      • Local Embeddings with HuggingFace
      • Jina Embeddings
      • LangChain Embeddings
      • LLMRails Embeddings
      • MistralAI Embeddings
      • OpenAI Embeddings
      • Interacting with Embeddings deployed in Amazon SageMaker Endpoint with LlamaIndex
      • Text Embedding Inference
      • Together AI Embeddings
      • Voyage Embeddings
      • Nomic Embedding
      • Fireworks Embeddings
    • [Beta] Multi-modal models
      • Multi-Modal LLM using OpenAI GPT-4V model for image reasoning
      • Multi-Modal LLM using Google’s Gemini model for image understanding and build Retrieval Augmented Generation with LlamaIndex
      • Multi-Modal LLM using Replicate LlaVa, Fuyu 8B, MiniGPT4 models for image reasoning
      • Multi-Modal GPT4V Pydantic Program
      • GPT4-V Experiments with General, Specific questions and Chain Of Thought (COT) Prompting Technique.
      • Retrieval-Augmented Image Captioning
      • Multi-Modal LLM using Anthropic model for image reasoning
      • Advanced Multi-Modal Retrieval using GPT4V and Multi-Modal Index/Retriever
      • Multi-Modal on PDF’s with tables.
      • Multi-Modal Retrieval using GPT text embedding and CLIP image embedding for Wikipedia Articles
      • Image to Image Retrieval using CLIP embedding and image correlation reasoning using GPT4V
      • Chroma Multi-Modal Demo with LlamaIndex
      • Evaluating Multi-Modal RAG
  • Prompts
    • Usage Pattern
    • Completion prompts
    • Chat prompts
    • Accessing/Customizing Prompts within Higher-Level Modules
    • Advanced Prompt Techniques (Variable Mappings, Functions)
    • Prompt Engineering for RAG
    • “Optimization by Prompting” for RAG
    • EmotionPrompt in RAG
  • Loading Data
    • Data Connectors (LlamaHub)
      • Usage Pattern
      • Module Guides
        • Simple Directory Reader
        • Psychic Reader
        • DeepLake Reader
        • Qdrant Reader
        • Discord Reader
        • MongoDB Reader
        • Chroma Reader
        • MyScale Reader
        • Faiss Reader
        • Obsidian Reader
        • Slack Reader
        • Web Page Reader
        • Pinecone Reader
        • Pathway Reader
        • Mbox Reader
        • MilvusReader
        • Notion Reader
        • Github Repo Reader
        • Google Docs Reader
        • Database Reader
        • Twitter Reader
        • Weaviate Reader
        • Make Reader
        • Deplot Reader Demo
    • Documents / Nodes
      • Defining and Customizing Documents
        • Metadata Extraction Usage Pattern
          • Extracting Metadata for Better Document Indexing and Understanding
          • Automated Metadata Extraction for Better Retrieval + Synthesis
          • Entity Metadata Extraction
          • Metadata Extraction and Augmentation w/ Marvin
          • Pydantic Extractor
      • Defining and Customizing Nodes
      • Transformations
    • Node Parser Usage Pattern
      • Node Parser Modules
    • Ingestion Pipeline
      • Transformations
      • Advanced Ingestion Pipeline
      • Async Ingestion Pipeline + Metadata Extraction
      • Ingestion Pipeline + Document Management
      • Redis Ingestion Pipeline
      • Building a Live RAG Pipeline over Google Drive Files
      • Parallelizing Ingestion Pipeline
  • Indexing
    • LlamaCloudIndex + LlamaCloudRetriever
    • Using VectorStoreIndex
      • Metadata Extraction
        • Extracting Metadata for Better Document Indexing and Understanding
        • Automated Metadata Extraction for Better Retrieval + Synthesis
        • Entity Metadata Extraction
        • Metadata Extraction and Augmentation w/ Marvin
        • Pydantic Extractor
      • Document Management
      • Vector Store Index usage examples
      • Composable Objects
    • How Each Index Works
    • Module Guides
      • VectorStoreIndex
        • Metadata Extraction
          • Extracting Metadata for Better Document Indexing and Understanding
          • Automated Metadata Extraction for Better Retrieval + Synthesis
          • Entity Metadata Extraction
          • Metadata Extraction and Augmentation w/ Marvin
          • Pydantic Extractor
        • Document Management
        • Vector Store Index usage examples
        • Composable Objects
      • Summary Index
      • Tree Index
      • Keyword Table Index
      • Knowledge Graph Index
      • Knowledge Graph Query Engine
      • Knowledge Graph RAG Query Engine
      • REBEL + Knowledge Graph Index
      • REBEL + Wikipedia Filtering
      • SQL Index
      • SQL Query Engine with LlamaIndex + DuckDB
      • Document Summary Index
      • The ObjectIndex Class
  • Storing
    • Customizing Storage
    • Persisting & Loading Data
    • Vector Stores
      • Astra DB
      • Simple Vector Store - Async Index Creation
      • Azure AI Search
      • Azure CosmosDB MongoDB Vector Store
      • Baidu VectorDB
      • Cassandra Vector Store
      • Chroma
      • DashVector Vector Store
      • Deep Lake Vector Store Quickstart
      • DocArray Hnsw Vector Store
      • DocArray InMemory Vector Store
      • DuckDB
      • Epsilla Vector Store
      • Jaguar Vector Store
      • LanceDB Vector Store
      • Lantern Vector Store
      • Metal Vector Store
      • Milvus Vector Store
      • MyScale Vector Store
      • Elasticsearch Vector Store
      • Faiss Vector Store
      • MongoDB Atlas
      • Neo4j vector store
      • Opensearch Vector Store
      • Pinecone Vector Store
      • Pinecone Vector Store - Hybrid Search
      • pgvecto.rs
      • Postgres Vector Store
      • Redis Vector Store
      • Qdrant Vector Store
      • Qdrant Hybrid Search
      • Rockset Vector Store
      • Simple Vector Store
      • Supabase Vector Store
      • Tair Vector Store
      • Tencent Cloud VectorDB
      • Timescale Vector Store (PostgreSQL)
      • Weaviate Vector Store
      • Weaviate Vector Store - Hybrid Search
      • Zep Vector Store
    • Document Stores
    • Index Stores
    • Key-Value Stores
    • Using Graph Stores
      • Neo4j Graph Store
      • Nebula Graph Store
      • Knowledge Graph Query Engine
      • Kuzu Graph Store
      • FalkorDB Graph Store
    • Chat Stores
  • Querying
    • Query Pipeline
      • Usage Pattern
      • Module Usage
      • Module Guides
        • An Introduction to LlamaIndex Query Pipelines
        • Query Pipeline with Async/Parallel Execution
        • Query Pipeline over Pandas DataFrames
        • Query Pipeline for Advanced Text-to-SQL
        • Building an Agent around a Query Pipeline
    • Query Engine
      • Usage Pattern
        • Response Modes
        • Streaming
      • Module Guides
        • Custom Query Engine
        • Retriever Query Engine
        • Text-to-SQL Guide (Query Engine + Retriever)
        • JSON Query Engine
        • Pandas Query Engine
        • JSONalyze Query Engine
        • Knowledge Graph Query Engine
        • Knowledge Graph RAG Query Engine
        • Structured Hierarchical Retrieval
        • Router Query Engine
        • Retriever Router Query Engine
        • Joint QA Summary Query Engine
        • Sub Question Query Engine
        • Multi-Step Query Engine
        • SQL Router Query Engine
        • SQL Auto Vector Query Engine
        • SQL Join Query Engine
        • [Beta] Text-to-SQL with PGVector
        • SQL Query Engine with LlamaIndex + DuckDB
        • Retry Query Engine
        • CitationQueryEngine
        • Recursive Retriever + Query Engine Demo
        • Joint Tabular/Semantic QA over Tesla 10K
        • Recursive Retriever + Document Agents
        • Ensemble Query Engine Guide
        • Sub Question Query Engine
        • Recursive Retriever + Document Agents
        • Multi-Document Agents
        • Multi-Document Agents (V1)
        • FLARE Query Engine
      • Supporting Modules
        • Query Transformations
          • HyDE Query Transform
          • Multi-Step Query Engine
    • Chat Engine
      • Usage Pattern
      • Module Guides
        • ReAct Chat Engine
        • OpenAI Chat Engine
        • Condense Question Chat Engine
        • Context Chat Engine
        • Context Plus Condense Chat Engine
        • Simple Chat Engine
    • Agents
      • Usage Pattern
      • Module Guides
        • 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
        • Recursive Retriever + Document Agents
        • Multi-Document Agents
        • GPT Builder Demo
        • Single-Turn Multi-Function Calling OpenAI Agents
        • OpenAI Assistant Agent
        • Benchmarking OpenAI Retrieval API (through Assistant Agent)
        • OpenAI Assistant Advanced Retrieval Cookbook
        • ReAct Agent - A Simple Intro with Calculator Tools
        • ReAct Agent with Query Engine (RAG) Tools
        • LLMCompiler Agent Cookbook
        • Building a Custom Agent
        • Building an Agent around a Query Pipeline
        • Step-wise, Controllable Agents
        • Controllable Agents for RAG
        • Controllable Agents for RAG
      • Tools
        • Usage Pattern
        • LlamaHub Tools Guide
      • Lower-Level Agent API
    • Retriever
      • Retriever Modes
      • Retriever Modules
        • Define Custom Retriever
        • BM25 Hybrid Retriever
        • Simple Fusion Retriever
        • Reciprocal Rerank Fusion Retriever
        • Relative Score Fusion and Distribution-Based Score Fusion
        • Auto Merging Retriever
        • Metadata Replacement + Node Sentence Window
        • Composable Objects
        • A Simple to Advanced Guide with Auto-Retrieval (with Pinecone + Arize Phoenix)
        • Auto-Retrieval (with Lantern)
        • Auto-Retrieval (with Chroma)
        • Auto-Retrieval (with BagelDB)
        • Structured Hierarchical Retrieval
        • Auto-Retrieval from a Vectara Index
        • Knowledge Graph RAG Retriever
        • Recursive Retriever + Query Engine Demo
        • Recursive Retriever + Node References
        • Recursive Retriever + Node References + Braintrust
        • Router Retriever
        • Ensemble Retrieval Guide
        • Google Generative Language Semantic Retriever
        • Structured Hierarchical Retrieval
        • Google Generative Language Semantic Retriever
        • Vectara Managed Index
        • Managed Index with Zilliz Cloud Pipelines
        • VideoDB Retriever
        • Chunk + Document Hybrid Retrieval with Long-Context Embeddings (Together.ai)
        • You.com Retriever
        • Text-to-SQL Guide (Query Engine + Retriever)
        • DeepMemory (Activeloop)
        • Pathway Retriever
    • Response Synthesizer
      • Response Synthesis Modules
        • Refine
        • Refine with Structured Answer Filtering
        • Tree Summarize
        • Pydantic Tree Summarize
    • Routers
      • Router Query Engine
      • Retriever Router Query Engine
      • SQL Router Query Engine
      • Router Retriever
    • Node Postprocessor
      • Node Postprocessor Modules
        • Sentence Embedding Optimizer
        • Cohere Rerank
        • LLM Reranker Demonstration (2021 Lyft 10-k)
        • LLM Reranker Demonstration (Great Gatsby)
        • Recency Filtering
        • Time-Weighted Rerank
        • PII Masking
        • Forward/Backward Augmentation
        • Metadata Replacement + Node Sentence Window
        • LongContextReorder
        • RankGPT Reranker Demonstration (Van Gogh Wiki)
        • Colbert Rerank
        • Jina Rerank
        • mixedbread Rerank Cookbook
    • Structured Outputs
      • Pydantic Program
        • LLM Pydantic Program
        • OpenAI Pydantic Program
        • Guidance Pydantic Program
        • Guidance for Sub-Question Query Engine
        • DataFrame Structured Data Extraction
        • Evaporate Demo
      • Query Engines + Pydantic Outputs
        • Query Engine with Pydantic Outputs
        • Pydantic Tree Summarize
        • Download Data
      • Output Parsing Modules
        • Guardrails Output Parsing
        • Langchain Output Parsing
        • Guidance Pydantic Program
        • Guidance for Sub-Question Query Engine
        • OpenAI Pydantic Program
  • Agents
    • Usage Pattern
    • Module Guides
      • 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
      • Recursive Retriever + Document Agents
      • Multi-Document Agents
      • GPT Builder Demo
      • Single-Turn Multi-Function Calling OpenAI Agents
      • OpenAI Assistant Agent
      • Benchmarking OpenAI Retrieval API (through Assistant Agent)
      • OpenAI Assistant Advanced Retrieval Cookbook
      • ReAct Agent - A Simple Intro with Calculator Tools
      • ReAct Agent with Query Engine (RAG) Tools
      • LLMCompiler Agent Cookbook
      • Building a Custom Agent
      • Building an Agent around a Query Pipeline
      • Step-wise, Controllable Agents
      • Controllable Agents for RAG
      • Controllable Agents for RAG
    • Tools
      • Usage Pattern
      • LlamaHub Tools Guide
    • Lower-Level Agent API
  • Observability
    • Langfuse Callback Handler
    • Wandb Callback Handler
    • Observability with OpenLLMetry
    • Arize Phoenix Tracing Tutorial
    • OpenInference Callback Handler + Arize Phoenix
    • Evaluating Search and Retrieval with Arize Phoenix
    • Evaluating and Tracking with TruLens
    • Quickstart Guide with LlamaIndex + TruLens
    • Colab
    • HoneyHive LlamaIndex Tracer
    • PromptLayer Handler
    • Callbacks
      • Langfuse Callback Handler
      • Token Counting Handler
      • Llama Debug Handler
      • Wandb Callback Handler
      • Aim Callback
      • OpenInference Callback Handler + Arize Phoenix
      • Token Counting - Migration Guide
  • Evaluating
    • Usage Pattern (Response Evaluation)
    • Usage Pattern (Retrieval)
    • Modules
      • Faithfulness Evaluator
      • Relevancy Evaluator
      • Answer Relevancy and Context Relevancy Evaluations
      • 🚀 RAG/LLM Evaluators - DeepEval
      • Guideline Evaluator
      • Correctness Evaluator
      • Embedding Similarity Evaluator
      • QuestionGeneration
      • BatchEvalRunner - Running Multiple Evaluations
      • Evaluating Multi-Modal RAG
      • Retrieval Evaluation
    • Evaluating With LabelledRagDataset’s
      • Benchmarking RAG Pipelines With A LabelledRagDatatset
      • Downloading a LlamaDataset from LlamaHub
    • Contributing A LabelledRagDataset
      • LlamaDataset Submission Template Notebook
  • Supporting Modules
    • Configuring Settings

API Reference

  • API Reference
    • Agents
    • Callbacks
    • Composability
    • Evaluation
    • Example Notebooks
    • Indices
      • Summary Index
      • Table Index
      • Tree Index
      • Vector Store Index
      • Structured Store Index
      • Knowledge Graph Index
      • Empty Index
    • LLMs
    • BaseEmbedding
    • Memory
    • Node Postprocessors
    • Node
      • BaseComponent
      • BaseNode
      • Document
      • ImageDocument
      • ImageNode
      • IndexNode
      • MetadataMode
      • Node
      • NodeRelationship
      • NodeWithScore
      • ObjectType
      • QueryBundle
      • RelatedNodeInfo
      • TextNode
      • TransformComponent
    • Playground
    • Prompt Templates
    • Querying an Index
      • Retrievers
        • Empty Index Retriever
        • Knowledge Graph Retriever
        • List Retriever
        • Keyword Table Retrievers
        • Tree Retrievers
        • Vector Store Retrievers
        • Transform Retriever
      • Response Synthesizer
      • Query Engines
        • Graph Query Engine
        • Multistep Query Engine
        • Retriever Query Engine
        • Transform Query Engine
        • Router Query Engine
        • Retriever Router Query Engine
        • Sub Question Query Engine
        • SQL Join Query Engine
        • Flare Query Engine
        • Citation Query Engine
        • Knowledge Graph Query Engine
        • SQL Query Engine
        • Pandas Query Engine
      • Chat Engines
        • Simple Chat Engine
        • Condense Question Chat Engine
        • Condense Plus Context Chat Engine
      • Query Bundle
      • Query Transform
    • Data Connectors
      • BasePydanticReader
      • BaseReader
      • ReaderConfig
    • Response
    • Service Context
      • Embeddings
      • OpenAIEmbedding
      • HuggingFaceEmbedding
      • OptimumEmbedding
      • InstructorEmbedding
      • LangchainEmbedding
      • GoogleUnivSentEncoderEmbedding
      • Node Parser
        • get_leaf_nodes
        • get_root_nodes
        • get_child_nodes
        • get_deeper_nodes
        • TokenTextSplitter
        • SentenceSplitter
        • CodeSplitter
        • SimpleFileNodeParser
        • HTMLNodeParser
        • MarkdownNodeParser
        • JSONNodeParser
        • SentenceWindowNodeParser
        • SemanticSplitterNodeParser
        • NodeParser
        • HierarchicalNodeParser
        • TextSplitter
        • MarkdownElementNodeParser
        • MetadataAwareTextSplitter
        • LangchainNodeParser
        • UnstructuredElementNodeParser
        • SimpleNodeParser
      • PromptHelper
      • LLMs
    • Storage Context
      • Document Store
      • Index Store
      • Vector Store
        • VectorStoreQuery
        • VectorStoreQueryResult
        • MetadataFilters
        • MetadataFilter
        • MetadataInfo
        • ExactMatchFilter
        • FilterCondition
        • FilterOperator
        • SimpleVectorStore
        • VectorStoreInfo
      • KV Storage
      • Loading Indices
    • Structured Index Configuration

Community

  • Integrations
    • Llama Packs 🦙📦
      • Llama Packs Example
      • Llama Pack - Resume Screener 📄
      • Ollama Llama Pack Example
    • Observability
      • Langfuse Callback Handler
      • Wandb Callback Handler
      • Observability with OpenLLMetry
      • Arize Phoenix Tracing Tutorial
      • OpenInference Callback Handler + Arize Phoenix
      • Evaluating Search and Retrieval with Arize Phoenix
      • Evaluating and Tracking with TruLens
      • Quickstart Guide with LlamaIndex + TruLens
      • Colab
      • HoneyHive LlamaIndex Tracer
      • PromptLayer Handler
      • Callbacks
        • Langfuse Callback Handler
        • Token Counting Handler
        • Llama Debug Handler
        • Wandb Callback Handler
        • Aim Callback
        • OpenInference Callback Handler + Arize Phoenix
        • Token Counting - Migration Guide
    • Perform Evaluations on LlamaIndex with UpTrain
    • How to go about it?
    • 1. Using the UpTrain Callback Handler Open In Colab
    • 1. RAG Query Engine Evaluation
    • 2. Sub-Question Query Engine Evaluation
    • 3. Re-ranking
    • 3b. Re-ranking (With different number of nodes)
    • UpTrain’s Managed Service Dashboard and Insights
    • 2. Using EvalLlamaIndex Open In Colab
    • Alternative 1: Evaluate using UpTrain’s Open-Source Software (OSS)
    • Alternative 2: Evaluate using UpTrain’s Managed Service and Dashboards
    • Unit Testing LLMs/RAG With DeepEval
    • Tracing with Graphsignal
    • Evaluating and Tracking with TruLens
    • Guidance
    • LM Format Enforcer
    • Guardrails
    • OpenAI Function Calling
    • Using Vector Stores
      • Astra DB
      • Simple Vector Store - Async Index Creation
      • Azure AI Search
      • Azure CosmosDB MongoDB Vector Store
      • Cassandra Vector Store
      • Chroma
      • DashVector Vector Store
      • Deep Lake Vector Store Quickstart
      • DocArray Hnsw Vector Store
      • DocArray InMemory Vector Store
      • Epsilla Vector Store
      • LanceDB Vector Store
      • Lantern Vector Store
      • Metal Vector Store
      • Milvus Vector Store
      • MyScale Vector Store
      • Elasticsearch Vector Store
      • Faiss Vector Store
      • MongoDB Atlas
      • Neo4j vector store
      • Opensearch Vector Store
      • Pinecone Vector Store
      • Pinecone Vector Store - Hybrid Search
      • pgvecto.rs
      • Postgres Vector Store
      • Redis Vector Store
      • Qdrant Vector Store
      • Qdrant Hybrid Search
      • Rockset Vector Store
      • Simple Vector Store
      • Supabase Vector Store
      • Tair Vector Store
      • Tencent Cloud VectorDB
      • Timescale Vector Store (PostgreSQL)
      • Upstash Vector Store
      • Weaviate Vector Store
      • Weaviate Vector Store - Hybrid Search
      • Zep Vector Store
    • Using Graph Stores
      • Neo4j Graph Store
      • Nebula Graph Store
      • Knowledge Graph Query Engine
      • Kuzu Graph Store
      • FalkorDB Graph Store
    • Using Managed Indices
      • Google Generative Language Semantic Retriever
      • Vectara Managed Index
      • Auto-Retrieval from a Vectara Index
      • Managed Index with Zilliz Cloud Pipelines
    • Using with Langchain 🦜🔗
    • Streamlit
    • Chainlit
    • LlamaIndex + Ray
    • ChatGPT Plugin Integrations
    • Poe
    • Airbyte
    • Fleet Context Embeddings - Building a Hybrid Search Engine for the Llamaindex Library
  • Frequently Asked Questions (FAQ)
    • Large Language Models
    • Embeddings
    • Vector Database
    • Query Engines
    • Chat Engines
    • Documents and Nodes
  • Full-Stack Projects
    • create-llama Blog
    • create-llama Repo
    • create-llama Additional Templates
    • SEC Insights App
    • SEC Insights Repo
    • Chat LlamaIndex App
    • Chat LlamaIndex Repo
    • RAGs Repo
    • RAG CLI

Contributing

  • Contributing to LlamaIndex
  • Documentation Guide

Changes

  • ChangeLog
  • Deprecated Terms
Back to top

Query Engines#

Below we show some general query engine classes.

General Query Engines

  • Graph Query Engine
  • Multistep Query Engine
  • Retriever Query Engine
  • Transform Query Engine
  • Router Query Engine
  • Retriever Router Query Engine
  • Sub Question Query Engine
  • SQL Join Query Engine
  • Flare Query Engine
  • Citation Query Engine
  • Knowledge Graph Query Engine

We also show query engine classes specific to our structured indices.

Structured Indices Query Engines

  • SQL Query Engine
  • Pandas Query Engine
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Graph Query Engine
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Response Synthesizer
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