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llama-hub

archived
run-llama/llama-hub

A library of data loaders for LLMs made by the community

GraphCanon updated 2w · GitHub synced 2w

3.5k stars721 forksLast push 2y Jupyter Notebook MIT

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-hub

Similar 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.

Python runtimePython

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.

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