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Integrations/LangChain
🦜

LangChain

Framework

LangChain is the most popular framework for building LLM-powered applications. Because Qubax is OpenAI-compatible, you can use ChatOpenAI with a custom base_url and route your entire chain through Qubax.

Official docs

Install

Shell
pip install langchain-openai

Quickstart

Python
from langchain_openai import ChatOpenAI

llm = ChatOpenAI(
    model="gpt-5",
    base_url="https://api.qubax.ai/v1",
    api_key="YOUR_API_KEY",
    temperature=0.7,
)

response = llm.invoke("Explain quantum entanglement in one sentence.")
print(response.content)

With a chain

Python
from langchain_core.prompts import ChatPromptTemplate
from langchain_openai import ChatOpenAI

llm = ChatOpenAI(
    model="gpt-5",
    base_url="https://api.qubax.ai/v1",
    api_key="YOUR_API_KEY",
)

prompt = ChatPromptTemplate.from_messages([
    ("system", "You are a helpful assistant that answers concisely."),
    ("human", "{question}"),
])

chain = prompt | llm
response = chain.invoke({"question": "What is the speed of light?"})
print(response.content)

Setup steps

  1. 1

    Install the integration

    Run pip install langchain-openai. This pulls in langchain-core and the openai SDK as dependencies.

  2. 2

    Configure ChatOpenAI

    Instantiate ChatOpenAI with model="gpt-5", base_url="https://api.qubax.ai/v1", and api_key set to your Qubax key.

  3. 3

    Use it in a chain

    Pass the LLM to any LangChain chain, agent, or LCEL pipeline. Streaming, tool calling, and structured output all work.

💡
Set OPENAI_API_KEY and OPENAI_BASE_URL environment variables to avoid repeating config across LLM instances.

Test your connection

Paste your Qubax API key and send a live request to verify everything is wired up. Don't have a key yet?

Create one in the dashboard
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