https://github.com/better-call-jason/docker-llaravellama
Docker container image of LlaraveLlama for easy deployment of your private AI Chat Suite
https://github.com/better-call-jason/docker-llaravellama
Last synced: about 1 year ago
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Docker container image of LlaraveLlama for easy deployment of your private AI Chat Suite
- Host: GitHub
- URL: https://github.com/better-call-jason/docker-llaravellama
- Owner: Better-Call-Jason
- License: mit
- Created: 2024-12-13T18:49:10.000Z (over 1 year ago)
- Default Branch: master
- Last Pushed: 2025-01-09T14:35:04.000Z (over 1 year ago)
- Last Synced: 2025-04-02T16:13:34.210Z (over 1 year ago)
- Language: Shell
- Size: 5.27 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Docker-LlaraveLlama: Private AI Chat Suite -- Docker Version
[](https://github.com/Better-Call-Jason/LlaraveLlama/issues)
Welcome to LlaraveLlama - the most user-friendly private AI chat suite that brings enterprise-grade AI to your local machine in under 3 minutes. By seamlessly combining Laravel's reliability with Ollama's AI capabilities, we've created a zero-configuration solution that gives you instant access to powerful AI models, complete with a polished interface and 20+ pre-configured AI assistants. Whether you're a privacy enthusiast, developer, or someone who wants their own private GPT-like experience without the technical hassle, LlaraveLlama delivers everything you need with just a single command.
Experience the power of LlaraveLlama in action through our live demo, running efficiently on a minimal shared cloud setup with just 4GB RAM and 2 CPU cores at: [Live Demo](http://demo.llaravellama.com)
## Table of Contents
- [Preview](#-preview)
- [Features](#-features)
- [System Requirements](#-system-requirements)
- [Installation Guide](#-installation-guide)
- [1. Clone the Repository](#1-clone-the-repository)
- [2. Prerequisites Setup](#2-prerequisites-setup)
- [A. Docker Installation](#a-docker-installation)
- [B. NVIDIA Setup](#b-nvidia-setup-gpu-version-only)
- [3. Choose Your Installation Method](#3-choose-your-installation-method)
- [A. CPU Version](#a-cpu-version-default)
- [B. GPU Version](#b-gpu-version)
- [C. Build From Source](#c-build-from-source)
- [Components](#-components)
- [Configuration](#-configuration)
- [To Add More Ollama Models](#to-add-more-ollama-models)
- [Accessing the Application](#-accessing-the-application)
- [Contributing](#-contributing)
- [License](#-license)
- [Related Projects](#-related-projects)
## 📸 Preview
LlaraveLlama in action - showcasing features, themes and debug mode
## ✨ Features
- **Easy Deployment**: Get up and running in minutes with just a few commands
- **Consistent Environment**: Same experience across all platforms
- **Isolated Resources**: Run multiple instances without conflicts
- **Simple Updates**: Pull the latest images for instant updates
- **Zero Configuration**: No need to install PHP, Node.js, or any other dependencies
## 🛠 System Requirements
- Any platform that can run Docker
- Minimum 8GB RAM recommended
- 10GB free disk space
- Docker Engine 20.10 or newer
- Docker Compose v2.0 or newer
Tested Platforms:
- Ubuntu 22.04/24.04 LTS
- macOS
- Windows with WSL2
## 🚀 Installation Guide
### 1. Clone the Repository
First, clone the repository to get access to all necessary files and utilities:
```bash
git clone https://github.com/Better-Call-Jason/Docker-LlaraveLlama.git
```
```bash
cd Docker-LlaraveLlama
```
### 2. Prerequisites Setup
Use our utility scripts to set up your environment:
#### A. Docker Installation
If you don't have Docker installed:
```bash
chmod +x utilities/docker_setup.sh
```
```bash
./utilities/docker_setup.sh
```
#### B. NVIDIA Setup (GPU Version Only)
1. If you plan to use GPU acceleration:
```bash
chmod +x utilities/nvidia_setup.sh
```
```bash
./utilities/nvidia_setup.sh
```
2. After running the nvidia_setup.sh script, you'll need to reboot your system, the script will prompt you just run :
```bash
sudo reboot
```
Once rebooted :
```bash
cd Docker-LlaraveLlama
```
3. Check the nvidia configuration:
```bash
nvidia-smi
```
4. To continually see operation of GPU in the background :
```bash
watch -n 1 nvidia-smi
```
### 3. Choose Your Installation Method
#### A. CPU Version (Default)
Best for most users and general deployment:
```bash
docker compose up -d
```
#### B. GPU Version
For users with NVIDIA GPUs who want accelerated inference:
```bash
docker compose -f docker-compose.gpu.yml up -d
```
#### C. Build From Source
For users who want to customize their installation:
For CPU users:
```bash
docker compose -f docker-compose.build.yml build
```
```bash
docker compose -f docker-compose.build.yml up -d
```
For GPU users:
```bash
docker compose -f docker-compose.build.gpu.yml build
```
```bash
docker compose -f docker-compose.build.gpu.yml up -d
```
## 📦 Components
### Docker Images
- `meowsaytounge/llaravellama:latest`: Main application
- `meowsaytounge/llaravellama-ollama:latest`: Ollama service with pre-configured models
### Pre-installed Models
The Ollama container comes with:
- llama3.2:3b
- gemma2:2b
- qwen2.5:3b
## 🔧 Configuration
### Environment Variables
Configure in your docker-compose.yml:
```yaml
environment:
- OLLAMA_HOST=ollama
- OLLAMA_BASE_URL=http://ollama:11434
# Add any additional Laravel environment variables here
```
### To Add More Ollama Models
1. While the docker container is running, enter the project directory :
```bash
cd Docker-LlaraveLlama
```
2. Enter the Ollama docker container, with this command :
```bash
docker exec -it docker-llaravellama-ollama-1 bash
```
3. Run the Ollama command :
```bash
ollama
```
You should see output like this :
```bash
root@f03132f2eeaf:/# ollama
Usage:
ollama [flags]
ollama [command]
Available Commands:
serve Start ollama
create Create a model from a Modelfile
show Show information for a model
run Run a model
stop Stop a running model
pull Pull a model from a registry
push Push a model to a registry
list List models
ps List running models
cp Copy a model
rm Remove a model
help Help about any command
Flags:
-h, --help help for ollama
-v, --version Show version information
Use "ollama [command] --help" for more information about a command.
```
4. Utilize the Ollama Pull command to pull models from Ollama for example:
```bash
ollama pull codestral
```
```bash
ollama pull codellama:13b
```
The install output will look like this :
```bash
root@f03132f2eeaf:/# ollama pull codestral
pulling manifest
pulling 22a849aafe3d... 100% ▕██████████████████████████████████████████████████████████████████▏ 12 GB
pulling 51707752a87c... 100% ▕██████████████████████████████████████████████████████████████████▏ 480 B
pulling 5b68668f65de... 100% ▕██████████████████████████████████████████████████████████████████▏ 11 KB
pulling 5dea4f4d0fff... 100% ▕██████████████████████████████████████████████████████████████████▏ 63 B
pulling 2be2362e38c7... 100% ▕██████████████████████████████████████████████████████████████████▏ 486 B
verifying sha256 digest
writing manifest
success
root@f03132f2eeaf:/# ollama pull codellama:13b
pulling manifest
pulling e73cc17c7181... 100% ▕██████████████████████████████████████████████████████████████████▏ 7.4 GB
pulling 8c17c2ebb0ea... 100% ▕██████████████████████████████████████████████████████████████████▏ 7.0 KB
pulling 590d74a5569b... 100% ▕██████████████████████████████████████████████████████████████████▏ 4.8 KB
pulling 2e0493f67d0c... 100% ▕██████████████████████████████████████████████████████████████████▏ 59 B
pulling 7f6a57943a88... 100% ▕██████████████████████████████████████████████████████████████████▏ 120 B
pulling 35e261fb2c73... 100% ▕██████████████████████████████████████████████████████████████████▏ 530 B
verifying sha256 digest
writing manifest
success
```
5. Exit the container or close the terminal. Now you can use these new models in your private LlaraveLlama instance, just refresh your browser page and the new models will appear in the list of available models.
### Debugging
Enable debug mode by setting `APP_DEBUG=true` in your docker-compose.yml. The debug panel is fully responsive and works on mobile devices.
## 📱 Accessing the Application
- Local access: `http://localhost`
- Network access: `http://your_computer_ip_address`
- Mobile access: Ensure your device is on the same network or exposed to the internet : `http://host_ip`
## 🤝 Contributing
Contributions are welcome! Feel free to submit issues and pull requests.
## 📜 License
LlaraveLlama is open-source software licensed under the [MIT license](LICENSE).
## 🔗 Related Projects
- [LlaraveLlama](https://github.com/Better-Call-Jason/LlaraveLlama) - The original non-Docker version