aidbg 0.1.2

Local-first CLI AI debugger for Python projects

AI Debugger - aidbg

aidbg is a local-first, CLI-based AI debugging tool for Python projects.

It wraps program execution, detects runtime failures, collects minimal diagnostic context, and returns a structured debugging explanation using an LLM — without running background processes or monitoring your system.

aidbg activates only when your program crashes, analyzes the error, prints a concise fix, and exits immediately.

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✨ Why aidbg?

Modern developers often copy-paste tracebacks into AI chat tools to debug errors.

aidbg removes that friction.

Instead of:

python app.py
# copy error
# open browser
# paste into AI

You do:

aidbg run app.py

And get:

• Root Cause
• Fix
• Short Explanation

All inside your terminal.

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🔍 Key Features

• CLI-based execution wrapper

• Event-driven (no background daemon)

• Zero idle CPU usage

• Minimal context collection

• Token-controlled LLM responses

• Guardrails against unsafe or hacky fixes

• Multi-provider support:

  • Groq
  • OpenAI
  • Ollama (local)

• Global and project-level configuration

• Fully open-source core

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🧠 How It Works

Execution Flow:

aidbg run app.py
  → executes script
  → detects crash (non-zero exit)
  → extracts traceback
  → collects minimal context
  → sends structured prompt to LLM
  → prints debugging result
  → exits

aidbg never:

• Runs continuously
• Monitors your system
• Sends your full repository
• Collects environment variables
• Reads .env files
• Uploads datasets

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📦 Installation

pip install aidbg

Or from source:

pip install -e .

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⚙️ Configuration

Initialize configuration:

aidbg init

Project-specific config:

aidbg init --local

Config priority:

1. Project config (.aidbg/config.json)

2. Global config (~/.aidbg/config.json)

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🛠 Usage

aidbg run app.py

Example output:

Root Cause:
Division by zero.

Fix:
Validate the divisor before performing the division.

Explanation:
Python raises ZeroDivisionError when the divisor is zero.

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🔐 Privacy Model

aidbg follows a minimal context principle.

Collected:

• Relevant traceback frames
• Failing file + line number
• Code snippet around failure
• Shallow project structure (depth ≤ 2)
• Python version
• OS
• requirements.txt (if present)

Never collected:

• Full repository
• Secrets
• Environment variables
• Binary files
• Historical logs

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🧩 Project Structure

aidbg/
│
├─ cli.py
│   Entry point for CLI commands.
│
├─ runner.py
│   Executes target Python script via subprocess.
│
├─ trigger.py
│   Crash detection and LLM orchestration logic.
│
├─ init.py
│   Interactive configuration (global / project).
│
├─ config.py
│   Configuration loading and priority resolution.
│
├─ prompt.py
│   LLM system and user prompt construction.
│
├─ logic/
│   ├─ complexity.py
│   │   Error classification (simple vs complex).
│   └─ token_budget.py
│       Fixed token budget logic.
│
├─ context/
│   ├─ collector.py
│   │   Traceback parsing and file extraction.
│   ├─ project_tree.py
│   │   Shallow project structure extraction.
│   ├─ environment.py
│   │   Python version and OS detection.
│   └─ dependencies.py
│       Lightweight dependency parsing.
│
├─ llm/
│   ├─ base.py
│   ├─ groq.py
│   ├─ openai.py
│   └─ ollama.py
│
└─ tests/
    Basic unit tests for stability.

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🧪 Testing

pytest

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📈 Roadmap

Phase 1 (Current):

• CLI tool
• Multi-provider support
• Token-controlled responses
• Guarded fix suggestions

Phase 2 (Planned):

• Specialized lightweight debugging model
• Optional hosted API
• Possible commercial extension
• The core CLI tool will remain open-source.

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📄 License

MIT License.

The open-source CLI tool is released under MIT. Future hosted APIs or proprietary debugging models may be released under separate commercial terms.

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🤝 Contributing

Pull requests welcome. Please keep contributions minimal, testable, and consistent with the local-first philosophy.