Integración · Conexión en 60 segundos · Sin margen
LangChain + OrcaRouter
LangChain's ChatOpenAI class takes a base_url parameter. Pointing it at OrcaRouter gives every chain, agent, and retriever automatic failover and zero-markup pricing without touching the rest of your graph.
Conexión
Listo en cinco pasos.
- 1.Install: pip install langchain-openai
- 2.Import ChatOpenAI from langchain_openai
- 3.Construct with base_url='https://api.orcarouter.ai/v1' and api_key='sk-orca-…'
- 4.Set the model to any OrcaRouter-supported model ID.
- 5.Use it anywhere LangChain expects a chat model — chains, agents, tools.
Configuración
from langchain_openai import ChatOpenAI
llm = ChatOpenAI(
base_url="https://api.orcarouter.ai/v1",
api_key="sk-orca-...",
model="claude-sonnet-4",
temperature=0,
)
response = llm.invoke("Explain retrieval-augmented generation in one paragraph.")
print(response.content)¿Por qué enrutar LangChain a través de OrcaRouter?
LangChain agents do lots of short, bursty calls that are sensitive to rate limits. OrcaRouter spreads those calls across healthy providers automatically and gives you one cost-attribution view for the whole chain.
Otras integraciones
Enruta LangChain a través de OrcaRouter ahora mismo.
Regístrate en un minuto, obtén una clave sk-orca-…, pégala en LangChain. Tokens sin margen y failover automático entre todos los proveedores.
