wbal 0.2.0

Weights & Biases Agent Library - A minimal framework for building LLM agents

WBAL

Weights & Biases Agent Library - A minimal framework for building LLM agents.

Overview

WBAL provides three core primitives:

• Agent - Orchestrates the perceive-invoke-do loop
• Environment - Provides tools and context
• LM - Language model interface

All components inherit from WBALObject (Pydantic BaseModel + observe() method).

Quick Start

import weave
from wbal import Agent, Environment, weaveTool, GPT5MiniTester

weave.init('my-project')

class MyEnv(Environment):
    system_prompt = "You are a helpful assistant."

    @weaveTool
    def greet(self, name: str) -> str:
        """Greet someone by name."""
        return f"Hello, {name}!"

agent = Agent(lm=GPT5MiniTester, env=MyEnv())
result = agent.run("Say hello to Alice")

Installation

From PyPI:

pip install wbal

From source (for local development):

git clone https://github.com/wandb/CodeCurious.git
cd CodeCurious
uv sync

Documentation

Document	Description
USER.md	Usage guide, API reference, examples
DEVELOPER.md	Architecture, contributing, testing
GRIFFIN_AGENT_INSTRUCTIONS.md	Detailed framework guide

API

from wbal import (
    # Core
    Agent, Environment, StatefulEnvironment, LM,

    # Models
    GPT5Large, GPT5MiniTester,

    # Decorators
    weaveTool, tool,

    # Mixins
    ExitableAgent,

    # Helpers
    tool_timeout, format_openai_tool_response,
)

Examples

See examples/ for complete implementations.

Structure

wbal/
├── wbal/
│   ├── agent.py        # Agent class
│   ├── environment.py  # Environment, StatefulEnvironment
│   ├── lm.py           # LM, GPT5Large, GPT5MiniTester
│   ├── helper.py       # Tool decorators and utilities
│   └── mixins.py       # ExitableAgent
├── tests/
└── examples/