Gradient-Aware Development Environment - Allocate AI compute dynamically based on code difficulty
Project description
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 (works on all systems)
python -m gade analyze ./my-project --top 20
# View heatmap
python -m gade heatmap ./my-project
Windows Users: If
gadecommand doesn't work, usepython -m gadeinstead. This is the recommended universal approach.
Cloud API
Use the hosted API — no setup required:
curl -X POST "https://web-production-8b5ca.up.railway.app/analyze" \
-H "Content-Type: application/json" \
-d '{"repo_path": "./my-project", "top_k": 10}'
📖 API Docs: web-production-8b5ca.up.railway.app/docs
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: Hosted cloud API or self-host
Installation
pip install gade
Python SDK
from gade import analyze
result = analyze("./my-project")
for node in result.get_top_k(10):
print(f"{node.node_name}: {node.difficulty_score:.2f}")
CLI Commands
| Command | Description |
|---|---|
python -m gade analyze <path> |
Rank code by difficulty |
python -m gade heatmap <path> |
Terminal visualization |
python -m gade refactor <path> |
AI-assisted refactoring |
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
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