אינטגרציה · הגדרה תוך 60 שניות · ללא תוספת מחיר

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.

קבלו את מפתח ה-API שלכם ←LangChain דף הבית ↗

הגדרה

חמישה שלבים.

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.

תצורה

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)

למה לנתב את LangChain דרך 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.

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