Configure LangChain ChatOpenAI for Router One
Connect LangChain's ChatOpenAI to Router One for models served on Chat Completions. You can reuse the configuration across compatible model IDs; endpoint-specific features still need verification. LangChain runs the chain or agent, while Router One traces the cost and status of each model request.
Configure LangChain to use the Router One base URL
Pass the base URL and key to ChatOpenAI. This Python example explicitly selects Chat Completions with use_responses_api=False. In JS/TS, the corresponding option is useResponsesApi: false. Enable Responses only after checking the model and required features against the gateway's compatibility documentation:
from langchain_openai import ChatOpenAI
llm = ChatOpenAI(
base_url="https://api.router.one/v1",
api_key="sk-your-router-one-key",
model="<model-id-from-/models>",
use_responses_api=False,
)
print(llm.invoke("Hello!").content)Which model ID should LangChain send?
Copy the exact model ID from /models, preserving case, hyphens, and version suffixes; do not substitute a display name. Open its detail page and match the supported API endpoints, context window, and capabilities such as tool calling to the provider and features selected in LangChain. A catalog listing does not mean the client can use every feature of that model. Give each tool a dedicated API key with a maxSpend cap.
Which API protocol is LangChain using?
OpenAI-compatible describes an interface format; it does not make Chat Completions (/v1/chat/completions), Responses (/v1/responses), and Anthropic Messages (/v1/messages) interchangeable. Check the installed client version, provider configuration, and actual request path against the model detail page and API compatibility fact sheet. A successful plain-text chat does not establish support for hosted tools, conversation state, or file-editing features.
Verify the LangChain call in your request trace
Send a simple text request from LangChain, then match its trace in Dashboard → Logs by time, model, and request_id: tokens, cost, latency, and status. Next, test streaming, tool calls, and multi-turn history separately. For failures, retain the actual request path, full error message, and request_id. If there is no matching log, check client configuration and connectivity before attributing the error to the gateway or upstream.
FAQ
Do I still need langchain-anthropic or other provider packages?
ChatOpenAI can call models served on the gateway's Chat Completions endpoint. Native Anthropic features or non-standard provider fields need a matching integration and supported endpoint. LangChain can switch to Responses for built-in tools or conversation-state features, so recheck compatibility when enabling them; changing only the model string is not sufficient for every workload.
Which models can LangChain use through the gateway?
Choose a current catalog model that supports both the endpoint and the features LangChain uses. Check /models and the model detail page for the exact ID, current rates, and capabilities; a family name such as GPT or Claude is not a compatibility guarantee. Seeing a model in the picker confirms discovery, so verify an actual request too.
Models are listed, but requests fail with 400 or 404. What should I check?
Record the actual request path and error message, then check the exact model ID. A 400 can indicate invalid parameters, unsupported tools, or a model/endpoint mismatch; a 404 can indicate an incorrect path or missing resource, so it does not by itself establish that a model was retired. If the error says must be called via, use the named endpoint or select a model supported on the current endpoint. Do not add or remove /v1 or /chat/completions across all clients indiscriminately.
Does this work from Mainland China?
Yes. The gateway is reachable from Mainland China without a VPN, and the configuration is identical to the global setup.
How do I debug a 401/402/403/429?
Match the request and error message in Dashboard → Logs. For 401, check whether the key was sent and is valid; for 402, check wallet balance and maxSpend; for 403, check key permissions and access restrictions. For 429, distinguish request/token limits from upstream throttling using the error details. Keep the request_id and follow the error-codes reference.