GraphCanon updated 2w · GitHub synced 2w
Decision brief
community-driven data loaders for LlamaIndex/LangChain
Good fit when
- Community-specific features require engagement with community
- Integrates seamlessly with LlamaIndex or LangChain
Avoid when
- Limited support if the community lacks activity
- Not suitable without familiarity with Poetry for dependency management
Observed Jul 12, 2026 · Source: enrich:decision_facts
Verify the decision
Maintenance and security
Full trust report- Maintenance
- Archived (889d since push)
- As of 2w
- Provenance
- Not a fork · Organization account
- As of 2w
- Security (OSV)
- 121 low (121 low)
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Backing
Company context for LlamaIndex. Display-only - separate from trust and ranking.
- Company
- LlamaIndex·GitHub org profile·1mo
- Funding
- $19,000,000 (2024-02)·GraphCanon curated seed (public press)·1mo
- Commercial model
- Open core·GraphCanon curated seed·1mo
Install
git clone https://github.com/run-llama/llama-hubSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
Provides a collection of data loaders to be used with LlamaIndex and/or LangChain.
Capability facts
- Languages
- jupyter notebook, python
Source: github.language+pyproject.toml · Aug 8, 2026
Categories
Graph entities
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Aug 8, 2026)
Create a new Python virtual environment. The command below creates an environment in `.venv`,Source link
Tags
README
Installation
pip install llama-hub
download and install dependencies
LlavaCompletionPack = download_llama_pack( "LlavaCompletionPack", "./llava_pack" )
---
# download and install dependencies for benchmark dataset
rag_dataset, documents = download_llama_dataset(
"PaulGrahamEssayDataset", "./data"
)
---
### Step 0: Setup virtual environment, install Poetry and dependencies
Create a new Python virtual environment. The command below creates an environment in `.venv`,
and activates it:
```bash
python -m venv .venv
source .venv/bin/activate
if you are in windows, use the following to activate your virtual environment:
.venv\scripts\activate
Install poetry:
pip install poetry
Install the required dependencies (this will also install llama_index):
poetry install
This will create an editable install of llama-hub in your venv.
For agents
This page has a .md twin and JSON over the API.