Baretools AI

The un-framework for AI Agents — just the plumbing, no supply-chain baggage.

Status: Alpha. Python 3.10-3.13. Zero runtime dependencies. CI runs ruff, pytest, and package builds on every push and pull request to main.

Get Started · Why Baretools? · Concepts · Provider Integrations · API Reference · Changelog

pip install baretools-ai installs one package and zero runtime dependencies. No Pydantic required. No httpx. No hidden transitive packages that drift, get compromised, or bloat your Docker image.

What Baretools Does

Baretools handles the mechanical plumbing between your Python functions and LLM tool calls:

Function → schema: converts your typed Python function into the exact JSON shape each provider expects
Response → calls: parses raw provider responses into normalised ToolCall dicts
Calls → results: executes your functions, capturing errors without crashing
Results → messages: formats outputs back into the provider-native message shape

Everything else — prompts, context, retries, state, orchestration — stays in your code.

Quick Start

from baretools import tool, ToolRegistry, parse_tool_calls, format_tool_results

@tool
def get_weather(location: str) -> str:
    """Get current weather for a location."""
    return f"Sunny, 72°F in {location}"

tools = ToolRegistry()
tools.register(get_weather)

# Same pattern for OpenAI, Anthropic, or Gemini — only provider= changes
schemas    = tools.get_schemas("openai")
tool_calls = parse_tool_calls(llm_response, provider="openai")
results    = tools.execute(tool_calls)
messages   = format_tool_results(results, provider="openai")

Install

pip install baretools-ai

Optional Pydantic support (only needed if your tools accept BaseModel parameters):

pip install "baretools-ai[pydantic]"

Supported Providers

Provider	Schema format	`parse_tool_calls`	`format_tool_results`
OpenAI	`{"type":"function","function":{...}}`	✓	✓
Anthropic	`{"name":...,"input_schema":{...}}`	✓	✓
Gemini	`{"functionDeclarations":[...]}`	✓	✓

View source on GitHub

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