FastCode is a token-efficient framework designed for comprehensive code understanding and analysis, targeting developers and researchers working with large codebases. It offers a significant advantage in speed, accuracy, and cost-effectiveness compared to existing solutions, enabling faster and more streamlined code comprehension.

How It Works

FastCode employs a novel three-phase "scouting-first" approach, contrasting with traditional methods that incur high token costs through repeated file loading. It begins by building a semantic map of the codebase using AST-based parsing across multiple languages, a hybrid index combining semantic embeddings with BM25 keyword search, and multi-layer graphs (Call, Dependency, Inheritance) for structural understanding. This is followed by lightning-fast codebase navigation via a two-stage smart search and code skimming techniques that prioritize relevant code units. Finally, cost-efficient context management ensures minimal token expenditure through budget-aware decision-making and resource-optimized learning, prioritizing high-impact, low-cost information.

Quick Start & Requirements

Installation involves cloning the repository, installing dependencies via pip or uv (Python 3.12+ recommended), and configuring API keys in a .env file. The primary command to launch the Web UI is python web_app.py. FastCode supports Linux, macOS, and Windows. Prerequisites include Python 3.12+, Git, and API keys for LLM providers.

Highlighted Details

• Achieves 3-4x faster performance and 44-55% cost reduction compared to competitors like Cursor and Claude Code.
• Delivers the highest accuracy scores across multiple code understanding benchmarks.
• Utilizes up to 10x token savings through smart navigation and context management.
• Supports a wide range of languages including Python, JavaScript/TypeScript, Java, Go, C/C++, Rust, and C#.
• Compatible with local models (e.g., qwen3-coder-30b) and offers multi-repository reasoning capabilities.

Maintenance & Community

The README does not detail specific contributors, sponsorships, or community channels such as Discord or Slack.

Licensing & Compatibility

FastCode is released under the MIT License, which generally permits commercial use and integration into closed-source projects.

Limitations & Caveats

The framework relies on external LLM provider API keys for its core functionality. Performance claims are based on specific benchmarks, and real-world results may vary. While local model support is mentioned, detailed setup for all compatible local models is not elaborated upon in the README.