gade 0.1.0

Gradient-Aware Development Environment - Allocate AI compute dynamically based on code difficulty

GADE - Gradient-Aware Development Environment

Allocate AI compute dynamically based on code difficulty.

GADE measures difficulty across your codebase and focuses 80% of tokens on the 20% hardest regions.

Quick Start

pip install gade

# Analyze a repository
gade analyze ./my-project --top 20

# View heatmap
gade heatmap ./my-project

# Start API server
gade serve --port 8000

Features

• 5 Difficulty Signals: Edit churn, complexity, errors, uncertainty, gradient
• 80/20 Allocation: Smart token distribution by difficulty
• Multi-LLM Support: OpenAI, Anthropic, Google, Ollama, Azure, Bedrock
• Agentic AI Ready: MCP server, OpenAI tools, LangChain integration
• REST API: FastAPI endpoints at /analyze, /score, /regions

Installation

# Core
pip install gade

# With all integrations
pip install gade[all]

# Specific features
pip install gade[llm]        # LLM support
pip install gade[api]        # REST API
pip install gade[mcp]        # Claude Desktop
pip install gade[langchain]  # LangChain tools

Python SDK

from gade import analyze, get_difficulty

result = analyze("./my-project")
for node in result.get_top_k(10):
    print(f"{node.name}: {node.difficulty_score:.2f}")

CLI Commands

Command	Description
gade analyze <path>	Rank code by difficulty
gade heatmap <path>	Terminal visualization
gade refactor <path>	AI-assisted refactoring
gade serve	Start REST API
gade serve-mcp	Start MCP server

Difficulty Tiers

Score	Tier	AI Strategy
< 0.2	compress	Summarize
0.2-0.5	standard	Single-pass
0.5-0.8	deep	Multi-step + tools
≥ 0.8	debate	Multi-pass synthesis

License

MIT