coreouto
A minimal, extensible agent library for Python.
Built on five philosophies: minimalism, extensibility, explicitness, fragmentation, conciseness.
The whole library reduces to one idea: an agent is called with a message, runs an internal loop, and returns its response when the provider's end-of-turn signal classifies as END — the text of that turn becomes the final answer. The exact field and value depend on the provider: Anthropic's stop_reason (end_turn, max_tokens, stop_sequence, refusal), OpenAI Chat Completions' finish_reason (stop, length, content_filter), OpenAI Responses' status (failed, cancelled, incomplete:content_filter), Google Gemini's finishReason (MAX_TOKENS, SAFETY, ...). To output text without ending the loop (e.g. share progress before calling more tools), the model calls the continue_loop tool. Everything else — providers, tools, presets, hooks, multi-agent — is an opt-in extension.
import os
import coreouto as co
from coreouto.providers.openai import OpenAIProvider
@co.register_tool("search")
def search(query: str) -> str:
"""Search the web for `query`."""
return f"<results for {query}>"
co.register_provider("minimax", OpenAIProvider(
api_key=os.environ["MINIMAX_API_KEY"],
base_url="https://api.minimax.io/v1",
))
preset = co.register_agent_preset(
"researcher", model="MiniMax-M3", provider="minimax",
system_prompt="You are a research assistant.",
tools=["search"],
)
response = co.Agent(preset.to_config()).call_sync("Find me recent news about fusion energy.")
print(response.content)
Install
pip install coreouto
# with providers
pip install coreouto[openai]
pip install coreouto[anthropic]
pip install coreouto[google]
pip install coreouto[all]
Documentation
See docs/ for the full documentation set:
- Philosophy — the five principles
- Quickstart
- Agent
- Providers
- Tools
- Presets
- Hooks
- Multi-agent
- System prompts — the default prompt and how to write your own
License
Apache 2.0 — see LICENSE.
1 maintainer
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