ai-logmaster 1.0.1

Smart error analysis tool with AI-powered solutions

AI LogMaster

Smart error analysis tool with AI-powered solutions

Wrap any command and get instant, intelligent debugging help powered by AI and documentation retrieval.

Features

• 🤖 AI-Powered Analysis - Uses LangChain and LLMs for intelligent error diagnosis
• 📚 Smart Documentation Retrieval - Automatically fetches relevant docs when needed
• 💰 API Quota Optimization - Intelligent agent minimizes API calls (70-80% reduction)
• ⚡ Zero Setup - Just wrap your command and go
• 🔧 Multi-Provider Support - Works with OpenAI, Anthropic, Google, NVIDIA, and more
• 🎯 Pattern-Based Caching - Common errors use cached solutions (no API calls)

Installation

pip install ai-logmaster

Quick Start

1. Initialize Configuration

logmaster init

This creates ~/.ai-logmaster/config.yaml. Edit it to set your API key:

ai:
  provider: "nvidia"
  api_key: "your-api-key-here"

Or use environment variable:

export NVIDIA_API_KEY="your-api-key"

2. Run Your Command

logmaster run "python your_script.py"

That's it! The tool will:

1. ✅ Execute your command
2. ✅ Capture output in real-time
3. ✅ Detect errors automatically
4. ✅ Analyze with AI
5. ✅ Show solutions with documentation references

Example Output

[TRIAGE] Executing: python broken.py
============================================================
[ERROR]  TypeError: unsupported operand type(s) for /: 'int' and 'str'
============================================================

[TRIAGE] ⚠️  Error detected! Analyzing...

[AGENT] Classifying error type...
[AGENT] Error type: type, Needs docs: True
[AGENT] Fetching documentation from web...
[AGENT] ✓ Fetched 989 chars of documentation
[AGENT] Analyzing with AI...
[AGENT] ✓ Analysis complete (API calls: 1)

╔══════════════════════════════════════════════════════════╗
║ 🔍 DIAGNOSIS                                             ║
╠══════════════════════════════════════════════════════════╣
║ Type: TypeError                                          ║
║ Confidence: 90%                                          ║
║ Method: AI + Docs                                        ║
╠══════════════════════════════════════════════════════════╣
║ 📋 ROOT CAUSE                                            ║
╠══════════════════════════════════════════════════════════╣
║ Division operation between integer and string           ║
╠══════════════════════════════════════════════════════════╣
║ 💡 RECOMMENDED FIXES                                     ║
╠══════════════════════════════════════════════════════════╣
║ 1. Ensure divisor is numeric type                       ║
║ 2. Convert string to int/float if needed                ║
║ 3. Validate inputs before operations                    ║
╠══════════════════════════════════════════════════════════╣
║ 📚 DOCUMENTATION SOURCES                                 ║
╠══════════════════════════════════════════════════════════╣
║ • https://docs.python.org/3/library/exceptions.html     ║
╚══════════════════════════════════════════════════════════╝

Configuration

AI Providers

Edit ~/.ai-logmaster/config.yaml:

NVIDIA (Default - Free Tier Available)

ai:
  provider: "nvidia"
  model: "mistralai/mistral-small-3.1-24b-instruct-2503"
  api_key: "${NVIDIA_API_KEY}"
  base_url: "https://integrate.api.nvidia.com/v1"

OpenAI

ai:
  provider: "openai"
  model: "gpt-4"
  api_key: "${OPENAI_API_KEY}"

Anthropic

ai:
  provider: "anthropic"
  model: "claude-3-opus-20240229"
  api_key: "${ANTHROPIC_API_KEY}"

Google

ai:
  provider: "google"
  model: "gemini-pro"
  api_key: "${GOOGLE_API_KEY}"

Agent Optimization

Control when AI is used to minimize API costs:

agent:
  use_cached_solutions: true  # Use cached solutions for common errors
  fetch_documentation: true   # Fetch docs from web
  
  # These errors use cached solutions (0 API calls)
  cached_error_types:
    - connection
    - import
    - memory
    - timeout
    - permission
  
  # These errors use AI + docs (1 API call each)
  complex_error_types:
    - syntax
    - type
    - value
    - unknown

Quota Management

quota:
  enabled: true
  daily_limit: 100      # Maximum API calls per day
  warn_threshold: 0.8   # Warn at 80%

How It Works

Smart Agent Flow

Error Detected
    ↓
Classify Error (Pattern Matching - FREE)
    ↓
    ├─→ Common Error? → Use Cached Solution (0 API calls)
    │
    └─→ Complex/Unknown? → Fetch Docs (FREE) → AI Analysis (1 API call)

API Call Optimization

Without Agent: Every error = 1 API call

With Agent:

• Connection errors: 0 API calls ✅
• Import errors: 0 API calls ✅
• Memory errors: 0 API calls ✅
• Timeout errors: 0 API calls ✅
• Permission errors: 0 API calls ✅
• Syntax errors: 1 API call 💰
• Type errors: 1 API call 💰
• Unknown errors: 1 API call 💰

Result: 70-80% reduction in API calls!

Usage Examples

Python Script

logmaster run "python app.py"

Node.js Application

logmaster run "node server.js"

Shell Script

logmaster run "bash deploy.sh"

Complex Command

logmaster run "npm run build && npm start"

With Custom Buffer Size

logmaster run "python script.py" --buffer 200

Advanced Features

RAG Support (Optional)

Install with RAG capabilities for enhanced documentation retrieval:

pip install ai-logmaster[rag]

Enable in config:

rag:
  enabled: true
  vector_store: "faiss"
  chunk_size: 1000
  top_k: 3

Development

Install from Source

git clone https://github.com/Divodude/ai-logmaster.git
cd ai-logmaster
pip install -e .

Run Tests

python run_agent_tests.py

Requirements

• Python 3.8+
• API key for your chosen AI provider (NVIDIA, OpenAI, Anthropic, or Google)

License

MIT License - see LICENSE file for details.

Contributing

Contributions welcome! Please open an issue or PR.

Support

• 📧 Email: [e-mail]
• 🐛 Issues: https://github.com/Divodude/ai-logmaster/issues
• 📖 Docs: https://github.com/Divodude/ai-logmaster

☕ Buy Me a Coffee

If you find AI LogMaster helpful and want to support its development, consider buying me a coffee! Your support helps keep this project alive and continuously improving.

Scan to send ₹100 via UPI

Every contribution, no matter how small, is greatly appreciated! 🙏

Acknowledgments

Built with:

• LangChain - LLM framework
• LangGraph - Agent orchestration
• DuckDuckGo Search - Documentation retrieval

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Made with ❤️ by Divyansh