Framework Integrations

Use Kalibr with CrewAI, LangChain, and OpenAI Agents SDK.

Overview

Kalibr integrates with popular agent frameworks via router.as_langchain(), which returns a LangChain-compatible LLM that uses Kalibr for routing.

CrewAI

Install

pip install kalibr crewai openai anthropic

Code (Python only)

from kalibr import Router
from crewai import Agent, Task, Crew

# Create Kalibr router
router = Router(
    goal="research_task",
    paths=["gpt-4o-mini", "claude-sonnet-4-20250514"]
)

# Get LangChain-compatible LLM
llm = router.as_langchain()

# Use with CrewAI
researcher = Agent(
    role="Researcher",
    goal="Find accurate information",
    backstory="You are a research assistant.",
    llm=llm,  # Kalibr handles model selection
    verbose=True
)

task = Task(
    description="Research the history of Python programming language.",
    expected_output="A summary of Python's history.",
    agent=researcher
)

crew = Crew(agents=[researcher], tasks=[task])
result = crew.kickoff()

# Report outcome to Kalibr
router.report(success=len(str(result)) > 100)

Note: CrewAI requires Python 3.10+.

LangChain

Install

pip install kalibr langchain langchain-openai langchain-anthropic

Code (Python only)

from kalibr import Router
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.output_parsers import StrOutputParser

router = Router(
    goal="summarize_text",
    paths=["gpt-4o-mini", "claude-sonnet-4-20250514"]
)

llm = router.as_langchain()

prompt = ChatPromptTemplate.from_template("Summarize this: {text}")
chain = prompt | llm | StrOutputParser()

result = chain.invoke({"text": "Long article text here..."})

router.report(success=len(result) > 50)

OpenAI Agents SDK

Install

pip install kalibr openai-agents

Code (Python only)

from kalibr import Router

router = Router(
    goal="agent_task",
    paths=["gpt-4o", "gpt-4o-mini"]
)

# Get routing decision
from kalibr import get_policy

policy = get_policy(goal="agent_task")  # goal is required
model = policy["recommended_model"]

# Use with OpenAI Agents SDK
from openai_agents import Agent

agent = Agent(model=model)
result = agent.run("Your task here")

router.report(success=result.success)

When to Use as_langchain() vs get_policy()

Next

• API Reference - Full Router API
• Production Guide - Error handling, monitoring