GraphCanon updated 1w · GitHub synced 1w
Decision brief
localGPT allows users to chat with local documents using GPT models completely privately without internet access.
Good fit when
- When absolute privacy is required since no data leaves the user's local device.
- For environments where internet connectivity or bandwidth might be limited, as everything runs locally.
Avoid when
- If you need to work across multiple devices seamlessly because localGPT requires installation on each device and does not synchronize state online.
- In scenarios requiring frequent updates or model tuning from a cloud service; localGPT relies solely on locally available models which do not auto-update.
- Requirements:
- Min 4 GB RAM; Requires Docker; Installation is currently tested only on macOS, though instructions for other operating systems are partially provided.
Observed Jul 11, 2026 · Source: enrich:decision_facts
Verify the decision
Maintenance and security
Full trust report- Maintenance
- Active (21d since push)
- As of 1w
- Provenance
- Not a fork · Personal account
- As of 1w
- Security (OSV)
- 44 low (44 low)
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install localGPTHow it fits your stack(1)
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Relationship graph
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Similar tools
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Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
A local tool to enable private chat interactions with documents using GPT models.
Capability facts
- Deploy
- Self-host
Source: dockerfile:docker-compose.yml · Aug 8, 2026
- Docker
- Dockerfile present
Source: dockerfile:docker-compose.yml · Aug 8, 2026
- CLI
- CLI entrypoint
Source: package.json:bin|scripts · Aug 8, 2026
- MCP server
- No MCP server detected
Source: repo_scan · Aug 8, 2026
- Languages
- python, javascript, typescript
Source: github.language+package.json · Aug 8, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Aug 8, 2026)
# Install Node.js dependenciesSource link
Source: README excerpt (regex_v1, Aug 8, 2026)
# Install Python dependenciesSource link
Tags
README
🚀 Quick Start
Note: The installation is currently only tested on macOS.
Option 1: Docker Deployment
---
# Install Ollama locally (required even for Docker)
curl -fsSL https://ollama.ai/install.sh | sh
ollama pull qwen3:0.6b
ollama pull qwen3:8b
---
# Start with Docker (in a new terminal)
./start-docker.sh
---
# Install Python dependencies
pip install -r requirements.txt
---
# Install Node.js dependencies
npm install
---
# Install and start Ollama
curl -fsSL https://ollama.ai/install.sh | sh
ollama pull qwen3:0.6b
ollama pull qwen3:8b
ollama serve
---
### Detailed Installation
#### 1. Install System Dependencies
**Ubuntu/Debian:**
```bash
sudo apt update
sudo apt install python3.8 python3-pip nodejs npm docker.io docker-compose
macOS:
brew install python@3.8 node npm docker docker-compose
Windows:
---
# Install Python 3.8+, Node.js, and Docker Desktop
---
# Install Ollama
curl -fsSL https://ollama.ai/install.sh | sh
---
# Test installation
python -c "from rag_system.main import get_agent; print('✅ Installation successful!')"
---
### 🚀 Quick Start for Contributors
```bash
---
# Install Ollama and models
curl -fsSL https://ollama.ai/install.sh | sh
ollama pull qwen3:0.6b qwen3:8b
---
## 📄 License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details. For models, please check their respective licenses.
---
For agents
This page has a .md twin and JSON over the API.