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IntegrationIntegrationsAgent Frameworks

LangChain (gateway)

Route LangChain’s underlying LLM calls through the Respan gateway to use 1000+ models from different providers. Only your Respan API key is needed — no separate provider keys required.

Setup

1

Install packages

pip install langchain langchain-openai python-dotenv
2

Set environment variables

export RESPAN_API_KEY="YOUR_RESPAN_API_KEY"

No OPENAI_API_KEY needed — the Respan gateway handles provider authentication.

3

Point LangChain to the Respan gateway

import os
from langchain_openai import ChatOpenAI
llm = ChatOpenAI(
    api_key=os.environ["RESPAN_API_KEY"],
    base_url="https://api.respan.ai/api",
    model="gpt-5.5",
)
response = llm.invoke("Say hello through the Respan gateway.")
print(response.content)

Switch models

Change the model parameter on ChatOpenAI to use another OpenAI model through the same gateway-backed endpoint.

llm = ChatOpenAI(
    api_key=os.environ["RESPAN_API_KEY"],
    base_url="https://api.respan.ai/api",
    model="gpt-5.5",
)
llm = ChatOpenAI(
    api_key=os.environ["RESPAN_API_KEY"],
    base_url="https://api.respan.ai/api",
    model="gpt-5-mini",
)

ChatOpenAI is LangChain’s OpenAI-compatible chat adapter. This page avoids showing Claude or Gemini inside that OpenAI-named adapter; use the Respan API or OpenAI SDK gateway pages for provider-neutral Claude and Gemini examples.

See the full model list.

Respan parameters

Pass additional Respan parameters via extra_body for gateway features.

llm = ChatOpenAI(
    base_url="https://api.respan.ai/api/",
    api_key=os.environ["RESPAN_API_KEY"],
    model="gpt-5.5",
    extra_body={
        "customer_identifier": "user_123",
        "fallback_models": ["gpt-5-mini"],
        "metadata": {"session_id": "abc123"},
        "thread_identifier": "conversation_456",
    },
)

See Respan params & metadata for the full list.