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Installation

This guide covers installing SolanaLM for development and production use.

Prerequisites

Before installing SolanaLM, ensure you have the following:

Requirement Version Notes
Python 3.12+ Required for all components
Poetry Latest Recommended for dependency management
RAM 8GB+ 16GB+ recommended for local inference
GPU Optional CUDA-compatible GPU for faster inference
Solana CLI Optional For mainnet/testnet integration

Installation Methods

=== "Poetry (Recommended)"

Poetry provides the best dependency management experience:

```bash
# Clone the repository
git clone https://github.com/solanalm/solanalm.git
cd solanalm

# Install dependencies
poetry install

# Activate the virtual environment
poetry shell

# Verify installation
python scripts/verify_setup.py
```

=== "pip"

For environments where Poetry isn't available:

```bash
# Clone the repository
git clone https://github.com/solanalm/solanalm.git
cd solanalm

# Create and activate virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Verify installation
python scripts/verify_setup.py
```

=== "Docker"

For containerized deployment:

```bash
# Clone the repository
git clone https://github.com/solanalm/solanalm.git
cd solanalm

# Build and run with Docker Compose
docker-compose up -d

# Verify services are running
docker-compose ps
```

Verify Installation

Run the verification script to check your setup:

python scripts/verify_setup.py

Expected output:

✓ Python version: 3.12.0
✓ Poetry installed
✓ Dependencies installed
✓ PyTorch available
✓ CUDA available (optional)
✓ Solana SDK available
✓ Hardware detection working
  - CPU: 8 cores
  - RAM: 16 GB
  - GPU: NVIDIA RTX 3080 (optional)

GPU Support

For GPU-accelerated inference, ensure you have:

  1. NVIDIA GPU with CUDA support
  2. CUDA Toolkit 11.8 or higher
  3. cuDNN library

Install PyTorch with CUDA support:

# For CUDA 11.8
pip install torch --index-url https://download.pytorch.org/whl/cu118

# For CUDA 12.1
pip install torch --index-url https://download.pytorch.org/whl/cu121

Verify GPU availability:

import torch
print(f"CUDA available: {torch.cuda.is_available()}")
print(f"GPU count: {torch.cuda.device_count()}")
if torch.cuda.is_available():
    print(f"GPU name: {torch.cuda.get_device_name(0)}")

Optional Dependencies

External API Support

For proxy nodes that connect to external APIs:

# Install API client libraries
pip install openai anthropic cohere

Set API keys in your environment:

export OPENAI_API_KEY="sk-..."
export ANTHROPIC_API_KEY="sk-ant-..."
export COHERE_API_KEY="..."

Development Tools

For contributing to SolanaLM:

# Install development dependencies
poetry install --with dev

# Or with pip
pip install black flake8 mypy pytest pytest-asyncio

Troubleshooting

Common Issues

??? question "Poetry install fails with dependency conflicts"

Try clearing the cache and reinstalling:

```bash
poetry cache clear pypi --all
poetry lock --no-update
poetry install
```

??? question "PyTorch not detecting GPU"

1. Verify CUDA installation: `nvidia-smi`
2. Check PyTorch CUDA version matches system CUDA
3. Reinstall PyTorch with correct CUDA version

??? question "Import errors after installation"

Ensure you're in the correct virtual environment:

```bash
# With Poetry
poetry shell

# With venv
source venv/bin/activate
```

Getting Help

If you encounter issues:

  1. Check the GitHub Issues
  2. Join our Discord community
  3. Run diagnostics: python scripts/verify_setup.py --verbose

Next Steps