Welcome to LLMSurf! This comprehensive guide will walk you through the complete setup process, from installation to your first automation workflow. By the end of this tutorial, you'll have a fully functional AI assistant running on your Mac.

Prerequisites

Before we begin, ensure you have:

  • A Mac running macOS 12.0 or later
  • At least 8GB of RAM (16GB recommended)
  • At least 10GB of free disk space
  • An internet connection for initial setup
  • Administrative privileges on your Mac

Step 1: Install Ollama

1 Download Ollama

Ollama is the backbone that allows LLMSurf to run local language models efficiently.

# Download Ollama from the official website # Visit: https://ollama.ai/download # Or use Homebrew (if installed): brew install ollama

Alternative: Download the latest Ollama.app directly from the official website and drag it to your Applications folder.

2 Start Ollama Service

Launch Ollama to begin the service:

# Start Ollama service ollama serve # Or launch Ollama.app from Applications folder

You should see output indicating that Ollama is running on http://localhost:11434.

Step 2: Install LLMSurf

1 Download LLMSurf

Download the latest version of LLMSurf from the official releases:

# Visit the releases page open https://github.com/yyaadet/llmsurf/releases # Download the latest .dmg file # Example: LLMSurf-v1.0.0.dmg

2 Install the Application

Follow the standard macOS installation process:

  1. Double-click the downloaded .dmg file
  2. Drag LLMSurf.app to your Applications folder
  3. Eject the disk image
  4. Launch LLMSurf from Applications
Important: If you encounter a security warning, follow the steps in the troubleshooting section below.

3 Grant Permissions

LLMSurf may request certain permissions on first launch:

  • Accessibility: Required for system automation features
  • Screen Recording: Needed for visual analysis capabilities
  • File Access: Required for knowledge base operations

Click "Allow" for each permission request to ensure full functionality.

Step 3: Initial Configuration

1 Welcome Screen

Upon first launch, you'll see the LLMSurf welcome screen:

  • Review the welcome message and click "Get Started"
  • Choose your preferred language
  • Select your primary use case (Research, Development, Business, etc.)

2 Model Selection

Choose the appropriate language model for your needs:

  • For General Use: Llama 2 7B or Mistral 7B
  • For Coding: CodeLlama or Deepseek Coder
  • For Research: Mixtral or Qwen models
  • For Speed: Gemma 2B or Phi models
# LLMSurf will automatically pull your selected model # Example commands that run in the background: ollama pull llama2:7b ollama pull nomic-embed-text

Step 4: Create Your First Knowledge Base

1 Access Knowledge Management

Navigate to the Knowledge section in LLMSurf:

  • Click on "Knowledge" in the main menu
  • Select "Create New Knowledge Base"
  • Choose a descriptive name for your knowledge base

2 Import Documents

Add your documents to the knowledge base:

  • Supported Formats: PDF, DOCX, TXT, MD, PPTX, XLSX
  • Drag & Drop: Simply drag files into the LLMSurf window
  • Folder Import: Import entire directories at once
  • Web Import: Add URLs for web content

3 Processing

LLMSurf will automatically process your documents:

  • Text extraction and chunking
  • Embedding generation for semantic search
  • Index creation for fast retrieval
  • Quality scoring and validation

Step 5: Your First Automation

1 Start a Conversation

Open LLMSurf and begin a new conversation:

  • Type a question or describe a task
  • Use natural language - no special syntax required
  • Mention your knowledge base if relevant

2 Try Basic Queries

Test with some simple requests:

  • "Summarize the key findings from my research papers"
  • "Analyze the competitive landscape in fintech"
  • "Generate a report on market trends"
  • "Help me debug this Python code"

3 Advanced Features

Once comfortable, try advanced capabilities:

  • Multi-platform Search: "Search Twitter and Reddit for recent discussions about AI"
  • R Code Generation: "Create a statistical analysis of my sales data"
  • Task Automation: "Set up a workflow to monitor competitor prices daily"
  • Document Analysis: "Extract key insights from these 50 research papers"

Troubleshooting Common Issues

macOS Security Warnings

If you encounter security warnings when launching LLMSurf:

# Open Terminal and run these commands: # 1. Disable Gatekeeper temporarily sudo spctl --master-disable # 2. Remove quarantine attributes cd /Applications sudo xattr -rd com.apple.quarantine LLMSurf.app # 3. Re-enable Gatekeeper (recommended) sudo spctl --master-enable

Model Download Issues

If models fail to download:

  • Check your internet connection
  • Verify Ollama is running (ollama serve)
  • Try a different model size
  • Check available disk space

Performance Issues

If LLMSurf runs slowly:

  • Ensure you're using an appropriate model size
  • Close other memory-intensive applications
  • Consider upgrading your RAM if using large models
  • Restart both Ollama and LLMSurf

Best Practices

Knowledge Base Organization

  • Create separate knowledge bases for different projects or domains
  • Use descriptive names and tags for easy identification
  • Regularly update your knowledge bases with new information
  • Export important knowledge bases for backup

Model Selection

  • Start with smaller models (7B parameters) for faster responses
  • Use larger models (13B+ parameters) for complex analysis tasks
  • Consider your hardware limitations when choosing model sizes
  • Test different models for your specific use cases

Workflow Optimization

  • Create templates for frequently used query types
  • Use the conversation history to build complex multi-step tasks
  • Leverage R integration for statistical analysis and data visualization
  • Combine multiple capabilities for comprehensive workflows

Next Steps

Now that you have LLMSurf set up, explore these advanced features:

  • Custom Model Training: Fine-tune models on your specific domain
  • API Integration: Connect LLMSurf to your existing tools and workflows
  • Team Collaboration: Share knowledge bases and workflows with team members
  • Advanced Automation: Create complex multi-step automation workflows

Getting Help

  • Documentation: Visit the official documentation site
  • Community: Join the LLMSurf Discord community
  • GitHub Issues: Report bugs or request features
  • Email Support: Contact support@yyaadet.com

Conclusion

Congratulations! You now have a fully functional AI assistant running on your Mac. LLMSurf combines the power of local language models with intelligent automation to transform how you work with information.

Remember: The more you use LLMSurf, the better it becomes at understanding your needs and providing relevant assistance. Start with simple queries and gradually explore more complex use cases as you become comfortable with the system.

Welcome to the future of AI-assisted productivity!