NEUROFANG

UNLEASH THE POWER OF LOCAL LLMs

Enhance AI understanding of large codebases with our cutting-edge RAG and optimized parsing framework. Run powerful AI tools locally with minimal VRAM requirements.

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CORE FEATURES

NEUROFANG enhances AI LLM's ability to interact with large codebases through a suite of powerful tools.

Custom Parser

Lightweight regex-based parser that accurately extracts function and class definitions without external dependencies.

Indexing

Breaks code into chunks and stores them in a vector database for efficient retrieval and analysis.

Semantic Search

Enables natural language queries using semantic embeddings to find relevant code segments.

AI-Powered Linting

Identifies readability, efficiency, and bug-related issues in code with AI assistance.

Chain-of-Thought Analysis

Provides multi-step reasoning for complex tasks like debugging or optimization.

Smart Refactoring

Suggests AI-Powered improvements to enhance code quality and maintainability.

USE CASES

From code analysis to game development, NEUROFANG's versatile architecture enables a wide range of applications.

Enhanced Code Understanding

  • Codebase Indexing

    Break down large codebases into manageable chunks for efficient analysis.

  • Semantic Search

    Find relevant code segments using natural language queries.

  • Chain-of-Thought Analysis

    Multi-step reasoning for complex debugging and optimization tasks.

# Example: Chain-of-Thought Analysis
Step 1 - Understanding:
Analyzing the inefficient_loop function...
Step 2 - Dependency Analysis:
Identifying relationships between components...
Step 3 - Final Recommendation:
sum_of_numbers = sum(range(0, n+1))