LMAPP

Local LLM CLI – AI everywhere. Easy, simple, and undeniable.
Online or offline. The future is yours to command.

v0.4.0 - Agent Mode. Production Ready. Fully Featured. Free.

See Demo & Features for examples and use cases.

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🚀 Quick Start

Full installation and setup: see QUICKSTART.md. Customize your AI's behavior: see Roles & Workflows Guide.

Everyday commands:

lmapp chat          # Start chatting locally
lmapp chat --agent  # Start in auto-Agent Mode (Copilot-like)
lmapp server start  # Start API server (Web App & VS Code)
lmapp status        # Check backend/model status

🌐 Web Interface (New in v0.4.0)

Access lmapp from your browser without installing the desktop app.

1. Start the server: lmapp server start
2. Open http://localhost:8000 in your browser.
3. Chat, run workflows, and manage settings.

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🎥 Demonstrations

Recommended: Check out our Feature Tour to see lmapp in action!

We offer two ways to explore lmapp:

1. Feature Tour (Read) - A visual walkthrough of features, use cases, and the "first run" experience.
2. Interactive Tour (Run) - A script you can run on your own machine to experience lmapp firsthand.

Explore real-world use cases including:

• 🤖 auto-Agent Mode (Autonomous terminal & file operations)
• 📝 Content Generation (Blogs, Emails, Code)
• 🔍 Document Analysis (Summarization, Q&A)
• 📊 Data Extraction (JSON from text)

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🎯 Features

🤖 auto-Agent Mode (New in v0.4.0)

Turn your terminal into an autonomous coding assistant.

$ lmapp chat --agent
> Create a python script to calculate fibonacci
[AGENT] Creating fib.py...
[AGENT] Running fib.py...

💬 Chat

$ lmapp chat --model mistral
╔════════════════════════════════════════════╗
║        Chat with Mistral (Local)           ║
╚════════════════════════════════════════════╝

You: Explain quantum computing in simple terms

AI: Quantum computers use quantum bits (qubits) instead of regular bits.
While regular bits are 0 or 1, qubits can be both at once (superposition).
This lets them solve certain problems exponentially faster...

You: What are the use cases?

AI: Key use cases include:
  • Drug discovery (molecular simulation)
  • Finance (portfolio optimization)
  • Cryptography (breaking encryption)
  • Machine learning (optimization)

� VS Code Integration

Turn VS Code into an AI-powered IDE with our extension.

1. Start the Server:

   lmapp server start
   

2. Open Dashboard: Go to http://localhost:8000 to see status and chat.
3. Install Extension: Install lmapp-vscode (coming soon to marketplace).
4. Enjoy: Get inline code completions and chat directly in your editor.

�🔍 RAG (Semantic Search)

$ lmapp rag index ~/my_docs
📁 Indexing documents...
✓ Processed: README.md (1,234 tokens)
✓ Processed: GUIDE.pdf (5,678 tokens)
✓ Processed: NOTES.txt (892 tokens)
✓ Index created: 7,804 tokens in 12 documents

$ lmapp rag search "how to optimize python code"
📊 Search Results (3 matches):

1. GUIDE.pdf - Line 45 (score: 0.92)
   "Optimization techniques include: list comprehensions,
    caching, and using built-in functions instead of loops"

2. NOTES.txt - Line 12 (score: 0.88)
   "Profile code with cProfile before optimizing"

3. README.md - Line 89 (score: 0.81)
   "Performance tips for production code"

$ lmapp chat --with-context
You: Summarize the best Python optimization tips from my docs

AI: Based on your documents, here are the key optimization tips:
  1. Use list comprehensions instead of loops
  2. Profile with cProfile before optimizing
  3. Leverage built-in functions (map, filter, etc.)
  4. Implement caching for expensive operations

📦 Batch Processing

$ lmapp batch create inputs.json
Processing 5 queries in batch...
[████████████████████] 100% (5/5)

Job created: batch_20250211_143022
Estimated time: 45 seconds

$ lmapp batch results batch_20250211_143022 --json
{
  "job_id": "batch_20250211_143022",
  "status": "completed",
  "results": [
    {"input": "Explain AI", "output": "AI is..."},
    {"input": "What is ML?", "output": "Machine learning..."},
    ...
  ],
  "completed_at": "2025-02-11T14:30:47Z"
}

🔌 Plugins

$ lmapp plugin list
Available Plugins:
  ✓ translator     - Real-time translation (8 languages)
  ✓ summarizer     - Extract key points from long text
  ✓ code-reviewer  - Analyze code and suggest improvements
  ✓ sql-generator  - Write SQL queries from descriptions
  ✓ regex-helper   - Build and test regex patterns
  ✓ json-validator - Validate and format JSON
  ✓ git-helper     - Explain git commands and operations
  ✓ api-tester     - Test REST APIs interactively

$ lmapp plugin install translator
Installing translator plugin...
✓ Downloaded (245 KB)
✓ Installed successfully
Ready to use: lmapp translate --help

$ lmapp translate --text "Hello World" --to spanish
Translation (Spanish):
"¡Hola Mundo!"

⚙️ Configuration

$ lmapp config show
Current Configuration:
  Model: mistral (7B)
  Temperature: 0.7
  Max Tokens: 2048
  Context Size: 4096
  System Prompt: You are a helpful AI assistant

$ lmapp config set temperature 0.3
✓ Configuration updated

$ lmapp config --set-prompt
Enter your custom system prompt:
> You are a Python expert. Help with code, explain concepts clearly.
✓ System prompt saved

$ lmapp status
Status Report:
  ✓ Backend: Ollama (running)
  ✓ Model: mistral (7.4B)
  ✓ Memory: 6.2 GB / 16 GB
  ✓ Performance: 45 tokens/sec

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💡 Who Is This For?

Perfect Fit

• Developers - Code explanations, debugging, documentation, CLI workflows
• Students & Researchers - Study partner, research assistance, offline-first
• SysAdmins - Command lookups, automation scripts, system analysis
• Professionals - Writing, analysis, research, note-taking
• Privacy-Conscious Users - Want AI without cloud dependencies
• Gamers - Quick tips, cheat codes, game help without searching websites
• Travelers - Offline knowledge access (camping, flights, road trips, deployment)
• Anyone who values control over convenience

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🌟 Real-World Examples

Example 1: No Internet? No Problem!

Scenario: Camping, road trip, flight, deployment - anywhere without internet
Question: "Why does the sky look blue?"

$ lmapp chat
> AI: Hello, how may I help you?
> You: Why does the sky look blue?

> AI: Short answer: the sky is blue because air molecules scatter 
     sunlight more strongly at short (blue) wavelengths than at long 
     (red) wavelengths — a process called Rayleigh scattering.

     A bit more detail:
     • Sunlight contains all visible colors
     • Rayleigh scattering scales as 1/λ^4
     • Blue light (~450 nm) scattered many times more than red (~650 nm)
     • At sunrise/sunset, blue light scattered out → sky looks red/orange
     • Clouds look white (Mie scattering of larger water droplets)
     
     Extra neat fact: scattered sky light is partially polarized!

> AI: Is there anything else I can help you with?

Key Point: Full scientific answers WITHOUT internet

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Example 2: Gaming Power User

Scenario: Playing GTA San Andreas, need cheat codes and tips

$ lmapp chat
> You: I'm playing GTA San Andreas, show me cheat codes and top 20 tips

> AI: Nice! Which platform? (PC, PS2/3/4/5, Xbox)
> You: PC

> AI: Here are PC cheat codes (type during gameplay):
     HESOYAM - Health, Armor, $250,000
     AEZAKMI - Never Wanted
     BAGUVIX - Infinite Health
     FULLCLIP - Infinite Ammo
     [20+ more codes...]

     Top 20 Tips & Tricks:
     1. Save often — use multiple save slots
     2. Complete side jobs for cash/stat boosts (Ambulance, Firefighter)
     3. Grind stats: stamina, muscle, driving/flying skill
     4. Learn weapon ranges, aim for headshots
     5. Keep Armor on you at all times
     [15+ more detailed tips...]

> AI: Need anything else? Specific mission help?

Key Point: Skip endless website searches, get comprehensive game help instantly

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📖 Basic Usage

# Start chat
lmapp chat

# Use specific model
lmapp chat --model mistral

# Check status
lmapp status

# View configuration
lmapp config show

Supported Backends: Ollama, llamafile (auto-detected). Extensible architecture supports custom backends.

See QUICKSTART.md for complete usage guide.

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✅ Quality & Features

• 🧪 587 tests (100% coverage)
• 🔒 100% private (no cloud, no tracking)
• ⚡ Fast & lightweight (<200ms startup)
• 🔌 8 production plugins
• 🔍 RAG system (semantic search)
• 📦 Batch processing
• 💾 Session persistence
• 🌐 Web UI (optional)

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🔐 Privacy & Security

• 100% Local - Everything runs on your device
• No Cloud - No internet after setup
• No Telemetry - Zero tracking
• Open Source - MIT licensed
• Your Data - You own it all

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🗺️ Roadmap

v0.3.0 (Current) - Production ready
v0.4.0+ - Mobile/desktop apps, team features, enterprise tier

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🤝 Contributing

Help wanted! See Contributing Guide for code contributions, bug reports, or feature ideas.

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All contributions welcome: bug fixes, features, documentation, tests, and ideas.

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💬 Support

• Found a bug? Open an Issue
• Questions? See Troubleshooting Guide
• Discussions? Use GitHub Discussions

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⚙️ Troubleshooting

Issue	Solution
command not found	Add ~/.local/bin to $PATH or use pipx install lmapp
ModuleNotFoundError	Reinstall: pip install --upgrade lmapp
Debian/Ubuntu issues	Use pipx install lmapp instead of pip

See Troubleshooting Guide for more.

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❓ FAQ

Q: How do I install?
pip install lmapp

Q: How do I update?
pip install --upgrade lmapp

Q: Can I use commercially?
Yes! MIT License allows it. See LICENSE.

Q: Does it collect data?
No. 100% local, no telemetry.

More questions? See Troubleshooting Guide.

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📚 Documentation

• Security Policy
• License
• Changelog

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📄 License

MIT License - See LICENSE file

This means:

• ✅ Use commercially
• ✅ Modify and distribute
• ✅ Include in closed-source projects
• ✅ Just include the license

Third-Party Licenses

• Ollama: MIT License
• llamafile: Apache 2.0 License
• Pydantic: MIT License
• Pytest: MIT License
• AI Models: Various (see model documentation)

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🙏 Built With

• Ollama - LLM management platform
• llamafile - Portable LLM runtime
• Pydantic - Data validation
• Pytest - Testing framework
• Meta, Mistral, and other amazing AI model creators

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⭐ Show Your Support

If lmapp helps you, please:

• ⭐ Star this repository
• 🐛 Report bugs and suggest features
• 📢 Share with friends and colleagues
• 🤝 Contribute improvements
• 📝 Share your use cases

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📞 Get Started Now

pip install lmapp
lmapp chat

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📖 Documentation Map

Document	Purpose
QUICKSTART.md	5-minute setup guide ⭐ Start here
docs/installation.md	Installation methods for all platforms
docs/CONFIGURATION.md	Configuration, environment, and settings
docs/development.md	Developer workflow and tips
TROUBLESHOOTING.md	Solutions for common issues
SECURITY.md	Security policy and vulnerability reporting
CHANGELOG.md	Release history
CONTRIBUTING.md	Contribution guidelines
CODE_OF_CONDUCT.md	Community standards
LICENSE	License terms
DEMO.md	Live examples and feature tour
API_REFERENCE.md	Lightweight CLI + HTTP API reference

Additional references:

• docs/ERROR_DATABASE.md - Known errors and fixes

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Welcome to the future of local AI. 🚀 This is the way...