Code graph CLI for semantic search and agent context

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"WHAT ARE THE ACTIVITIES OF A SYSTEM?
 I HAVE NOT THE SLIGHTEST IDEA.
 THE PATH APPEARS"

⚠️ WARNING: This project is in early development and is not yet stable. APIs and functionality may change significantly between versions.

Ummon is a code analysis tool that builds knowledge graphs from codebases to enhance understanding, improve AI assistance, and enable sophisticated querying. It creates connections between code entities (functions, classes, modules) and domain concepts, making it easier to reason about complex software systems and identify relevant code for specific tasks.

Named after the AI Ummon from Dan Simmons' Hyperion Cantos, this project provides deep insights into codebases that help both humans and AI assistants better understand software systems.

Core Features

1. Knowledge Graph Construction

   • Indexes code to create a semantic representation
   • Maps relationships between code entities (calls, imports, dependencies)
   • Works with multiple languages (Rust, Python, JavaScript, Java)
   • Supports both incremental updates and full rebuilds
   • Tracks file modifications to minimize reprocessing
   • See Knowledge Graph Documentation for more details

2. Advanced Querying System

   • Query your codebase using a powerful structured query language or natural language
   • Two main query types:
     • Select queries: select [entity_type] where [conditions]
     • Traversal queries: [source_type] [relationship] [target_type] where [conditions]
   • Natural language translation for user-friendly interaction
   • Rich filtering capabilities with attribute conditions and logical operators
   • Multiple output formats (text, JSON, CSV, tree)
   • Examples: "select functions where name like 'auth%'", "show me all authentication functions"
   • See Query System Documentation for more details

3. Relevance Agent

   • Suggests code files relevant to a proposed change or query
   • Uses semantic analysis to extract technical keywords from natural language descriptions
   • Identifies related entities in the knowledge graph using entity relationships
   • Scores files by relevance using both proximity and graph centrality metrics
   • Enables context-aware assistance with a ranked list of most relevant files
   • Example: For "Fix authentication bug", it identifies auth-related files
   • See Relevance Agent Documentation for more details

4. Domain Model Extraction

   • Uses LLMs to identify business entities and concepts
   • Maps domain concepts to implementation details
   • Creates a bridge between technical and business understanding
   • See Domain Extraction Documentation for more details

Installation and Setup

cargo install ummon

Usage

# Index a codebase (performs incremental update by default)
ummon index /path/to/codebase

# Perform a full rebuild of the knowledge graph
ummon index /path/to/codebase --full

# Index with domain model extraction enabled
ummon index /path/to/codebase --enable-domain-extraction

# Specify a custom domain directory for extraction
ummon index /path/to/codebase --enable-domain-extraction --domain-dir models/

# Query using natural language
ummon query "show all authentication functions"

# Query using structured query language
ummon query "select functions where name like 'auth%'" --no-llm

# Find relationships between entities (traversal query)
ummon query "functions calling functions where name like 'validate%'" --no-llm

# Query with different output formats
ummon query "select functions" --format json
ummon query "select functions" --format csv
ummon query "select functions" --format tree

# Filter query results by type
ummon query "find api" --type-filter function

# Filter by file path pattern
ummon query "show all entities" --path src/auth

# Limit the number of results
ummon query "select functions" --limit 10

# Skip LLM processing for structured queries
ummon query "select functions where file_path like 'src/auth/%'" --no-llm

# Generate AI-assisted recommendations
ummon assist "implement a user registration function"

# Get relevant file suggestions for a proposed change
ummon assist --suggest-files "fix authentication token validation"

Configuration

Ummon uses environment variables only for sensitive information:

• OPENROUTER_API_KEY: API key for LLM services (required for queries and domain extraction)

All other configuration is handled through command-line flags.

Architecture

Ummon is built with a modular architecture:

• Language-specific parsers for code analysis
• Graph-based storage for entities and relationships
• SQLite database with metadata tracking for efficient updates
• Intelligent update mechanisms for incremental indexing
• LLM integration for semantic understanding
• Relevance agent for context-aware assistance
• Command-line interface for user interaction

Language Support

Ummon supports parsing and analysis of multiple programming languages:

• Rust: Class/structs, traits, implementations, functions, modules
• Python: Classes, functions, decorators, imports
• JavaScript: Classes, functions, arrow functions, imports
• Java: Classes, interfaces, methods, constructors, fields

The Java parser supports parsing of:

• Class and interface definitions with modifiers
• Constructor declarations
• Method declarations with parameter types
• Field declarations with types
• Package declarations and imports (including wildcard and static imports)
• Documentation comments extraction
• Method calls and relationships

Knowledge Graph Updates

Ummon provides two approaches to updating the knowledge graph:

Incremental Updates (Default)

When run without the --full flag, Ummon will perform an incremental update:

• Tracks the timestamp of the last indexing operation
• Detects files modified since the last index using file modification times
• Removes only the entities and relationships associated with modified files
• Reindexes only the modified files, preserving the rest of the graph
• Significantly faster for large codebases with small changes

Full Rebuilds

When run with the --full flag, Ummon will perform a complete rebuild:

• Purges all entities and relationships from the database
• Reindexes the entire codebase from scratch
• Useful after major changes or when the graph might be in an inconsistent state

Documentation

For more detailed documentation, see:

• Getting Started: Installation and quick start guides
• Feature Documentation: Detailed documentation for each feature
• CLI Reference: Complete command-line reference
• Configuration: Configuration options and best practices

Development

Build & Test Commands

# Build the project
cargo build

# Run the project
cargo run

# Run with specific command
cargo run -- index .              # Incremental index of current directory
cargo run -- index . --full       # Full rebuild of the knowledge graph
cargo run -- query "show funcs"   # Query the knowledge graph

# Run tests
cargo test
cargo test -- --nocapture  # Show test output
cargo test <test_name>     # Run specific test

# Format code
cargo fmt

Test Resources

• test/java/: Java test files for parser testing
  • Test.java: Simple Java class for basic parsing
  • ComplexExample.java: Advanced Java features (generics, annotations, etc.)
• test/javascript/: JavaScript test files for testing

License

APACHE License