synalinks CLAUDE.md

CLAUDE.md

This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.

Project Overview

Synalinks is a neuro-symbolic Language Model (LM) framework inspired by Keras. It provides a declarative API for building, training, and deploying LM-based applications including RAGs, autonomous agents, and self-evolving reasoning systems.

Development Commands

# Install dependencies
./shell/install.sh

# Run tests with coverage
./shell/test.sh

# Run a single test file
uv run pytest synalinks/src/path/to/test_file.py -v

# Run a specific test
uv run pytest synalinks/src/path/to/test_file.py::test_function_name -v

# Lint check
./shell/lint.sh

# Format code
./shell/format.sh

# Build documentation
./shell/doc.sh

Architecture

Core Abstractions

The framework follows a Keras-like pattern with these core abstractions:

• Module (synalinks/src/modules/module.py): Base class for all composable units, similar to Keras Layers. Modules have:

  • __init__(): Define attributes and create variables
  • build(): Create state that depends on input shapes
  • call(): The forward pass logic (async)
  • get_config()/from_config(): Serialization support

• Program (synalinks/src/programs/program.py): Groups modules into trainable/deployable objects (like Keras Models). Inherits from both Trainer and Module. Supports:

  • Functional API: Chain module calls from Input to outputs
  • Subclassing: Override call() method
  • Sequential: Stack of single-input/single-output modules

• DataModel: Pydantic-based structured data with JSON schema support. All module I/O uses DataModels.

Key Components

• Generator (synalinks/src/modules/core/generator.py): Core module for LM inference with structured outputs
• FunctionCallingAgent (synalinks/src/modules/agents/function_calling_agent.py): Autonomous agent with parallel tool calling
• ChainOfThought (synalinks/src/modules/ttc/chain_of_thought.py): Generator with thinking field for step-by-step reasoning