llama-hub
A library of data loaders for LLMs made by the community -- to be used with LlamaIndex and/or LangChain
Star Growth
Overview
LlamaHub was a community-driven library of data loaders, readers, tools, and packs designed to connect large language models to various knowledge sources. Created by Jesse Zhang and later donated to LlamaIndex, it served as a centralized repository for integrations with LlamaIndex and LangChain. The library enabled easy data ingestion from sources like Google Docs, SQL databases, Notion, Slack, Gmail, and Google Calendar, allowing developers to build customized data agents. However, the repository has been archived and is now read-only. With the launch of LlamaIndex v0.10, all integrations have been migrated to the core llama-index Python repository. While LlamaHub accumulated 3,475 GitHub stars and provided a valuable service to the LLM community, users should now access these integrations directly through the main LlamaIndex repository. The llamahub.ai website continues to exist as a browsable directory pointing to integrations available in the updated location.
Deep Analysis
vs custom data connectors: community-driven modular approach with 100+ pre-built loaders for LlamaIndex/LangChain — eliminated the need to write custom data ingestion code for common sources
⚡ Capabilities
- • Community-driven data loader library for LLM applications
- • 100+ connectors: Google Docs, SQL, Notion, Slack, Gmail, and more
- • Data readers, tools, and llama-packs for RAG pipelines
- • Direct integration with LlamaIndex and LangChain
- • llamaindex-cli tool for direct loader downloads
🔗 Integrations
✓ Best For
- ✓ Building RAG systems with diverse data sources
- ✓ Multi-source data ingestion for LLM applications
- ✓ Quick prototyping of data-to-LLM pipelines
✗ Not Ideal For
- ✗ Standalone LLM platform (middleware only)
- ✗ New projects (use llama-index core instead)
- ✗ Non-Python ecosystems
Languages
Deployment
⚠ Known Limitations
- ⚠ Repository is archived and read-only
- ⚠ Integrations migrated to core llama-index repository
- ⚠ Active development occurs elsewhere
- ⚠ No standalone maintenance
Pros
- + Extensive community-contributed collection of data loaders and integrations for popular LLM frameworks
- + Simplified data ingestion with ready-to-use connectors for major platforms like Google Workspace, Notion, and Slack
- + Well-documented examples and Jupyter notebooks demonstrating real-world data agent implementations
Cons
- - Repository is archived and read-only, with no new development or maintenance
- - All functionality has been migrated to the main llama-index repository, making this version obsolete
- - Installation may be deprecated as the PyPI package redirects users to the updated implementation
Use Cases
- • Legacy projects that need to maintain compatibility with older LlamaIndex versions
- • Learning from historical examples of data loader implementations and patterns
- • Understanding the evolution of LlamaIndex's integration ecosystem before consulting current documentation