Installation
LRS-Agents can be installed via pip or from source.
Requirements
Python 3.9+
pip or conda
Basic Installation
Install the latest stable version from PyPI:
pip install lrs-agents
This installs the core package with minimal dependencies.
Installation with Optional Dependencies
LRS-Agents has several optional dependency groups for different use cases:
All Features
Install everything:
pip install lrs-agents[all]
LangChain Integration
For LangChain tools and agents:
pip install lrs-agents[langchain]
This includes:
langchainlangchain-anthropiclangchain-openailangchain-community
OpenAI Integration
For OpenAI Assistants:
pip install lrs-agents[openai]
Monitoring & Visualization
For dashboards and visualizations:
pip install lrs-agents[monitoring]
This includes:
streamlitplotlymatplotlib
Development
For contributing to LRS-Agents:
pip install lrs-agents[dev]
This includes linting, formatting, and testing tools.
Installation from Source
For the latest development version:
git clone https://github.com/NeuralBlitz/lrs-agents.git
cd lrs-agents
pip install -e .
Development Installation
To contribute to LRS-Agents:
git clone https://github.com/NeuralBlitz/lrs-agents.git
cd lrs-agents
pip install -e ".[dev,test]"
Verify Installation
Check that LRS-Agents is installed correctly:
import lrs
print(lrs.__version__)
# Output: 0.2.0
Quick Test
Run a simple test:
from lrs.core.precision import PrecisionParameters
precision = PrecisionParameters()
print(f"Initial precision: {precision.value}")
precision.update(0.1) # Low error
print(f"After success: {precision.value}")
Configuration
API Keys
LRS-Agents requires API keys for LLM providers. Set them as environment variables:
# Anthropic (Claude)
export ANTHROPIC_API_KEY="sk-ant-api03-..."
# OpenAI (GPT-4)
export OPENAI_API_KEY="sk-..."
Or in Python:
import os
os.environ["ANTHROPIC_API_KEY"] = "sk-ant-api03-..."
Environment Variables
Optional configuration:
# Logging
export LRS_LOG_LEVEL="INFO"
export LRS_LOG_DIR="./logs"
# Database (optional)
export DATABASE_URL="postgresql://user:pass@localhost/lrs"
# Performance
export LRS_MAX_WORKERS="4"
export LRS_CACHE_ENABLED="true"
Docker Installation
Run LRS-Agents in Docker:
docker pull lrsagents/lrs-agents:latest
docker run -e ANTHROPIC_API_KEY=$ANTHROPIC_API_KEY lrsagents/lrs-agents
Or with Docker Compose:
cd docker
docker-compose up -d
This starts:
LRS-Agents API server (port 8000)
Streamlit dashboard (port 8501)
PostgreSQL database (port 5432)
Kubernetes Deployment
Deploy to Kubernetes:
kubectl create namespace lrs-agents
kubectl apply -f k8s/
See the Production Deployment guide for details.
Troubleshooting
Import Errors
If you get import errors:
# Ensure package is installed
pip list | grep lrs-agents
# Reinstall if needed
pip install --force-reinstall lrs-agents
Missing Dependencies
If specific features don’t work:
# Install all optional dependencies
pip install lrs-agents[all]
Version Conflicts
If you have dependency conflicts:
# Create fresh virtual environment
python -m venv venv
source venv/bin/activate # or `venv\Scripts\activate` on Windows
pip install lrs-agents[all]
GPU Support
For GPU-accelerated inference (optional):
# Install PyTorch with CUDA
pip install torch --index-url https://download.pytorch.org/whl/cu118
# Then install LRS-Agents
pip install lrs-agents
Getting Help
If you encounter issues:
Check the GitHub Issues
Join our Hugging Face community
Join our Discord community
Email nuralnexus@icloud.com
Next Steps
Read the Quickstart guide
Understand Core Concepts
Explore ../tutorials/01_quickstart