Python and JS framework
How to use LangChain with Rapid Router
ChatOpenAI takes a base_url. Nothing else in a LangChain app changes: chains, tools and agents run against Rapid Router models with the same code.
Setup
- Install langchain-openai (Python) or @langchain/openai (JS).
- Construct ChatOpenAI with base_url and api_key as below.
- Use it anywhere a chat model is expected.
from langchain_openai import ChatOpenAI
llm = ChatOpenAI(
model="anthropic/claude-sonnet-5",
base_url="https://rapidrouter.ai/api/v1",
api_key="<your Rapid Router key>",
)
print(llm.invoke("Namaste, in one line").content)Field names as in LangChain at the time of writing; their UI moves, the three values do not. LangChain site.
Pick a model
The catalog lists every live model with its price per million tokens. For a coding tool, a strong model for edits and a cheap one for questions is the usual pair; the cost calculator shows what a month of your usage costs on each.
Common questions
Which model string do I put in LangChain?
Any id from the catalog, in the vendor/model shape, for example anthropic/claude-sonnet-5. The models page lists every live id with its price; copy it exactly.
Does LangChain need anything else to work with Rapid Router?
No. Rapid Router exposes the OpenAI chat completions API at https://rapidrouter.ai/api/v1, which is the shape LangChain already sends. Streaming, tool calling and JSON mode work where the model supports them.
How is usage from LangChain billed?
Per request at the provider's list price per million tokens, debited from your prepaid balance. Create a separate key for LangChain and the dashboard shows its spend on its own; you can cap it monthly.
Is there a free allowance to test with?
Yes. Every account gets a daily allowance of free requests on eligible models before any top-up, so the first session costs nothing.