LLM Skills

Provides large language model (LLM) capabilities to agents.

Robutler supports multiple providers through dedicated skills (e.g., OpenAI, Anthropic) and via LiteLLM proxying. In most cases you can specify model="openai/gpt-4o" and the correct provider skill is created for you.

Features

• Text generation, completion, and chat using supported LLM backends
• Integration with agent tool and skill system

Example: Add LLM Skill to an Agent

from robutler.agents import BaseAgent
from robutler.agents.skills.core.llm.openai.skill import OpenAISkill

agent = BaseAgent(
    name="llm-agent",
    model="openai/gpt-4o",
    skills={
        "llm": OpenAISkill({"model": "gpt-4o-mini"})
    }
)

Example: Use LLM Tool in a Skill

from robutler.agents.skills import Skill, tool

class SummarizeSkill(Skill):
    def __init__(self):
        super().__init__()
        self.llm = self.agent.skills["llm"]

    @tool
    async def summarize(self, text: str) -> str:
        """Summarize a block of text using the LLM"""
        return await self.llm.generate(prompt=f"Summarize: {text}")

Implementation: provider-specific skills, e.g., robutler/agents/skills/core/llm/openai/skill.py.