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Overview

LangChain is the most popular LLM application development framework, supporting both Python and JavaScript.

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Python Configuration

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Installation

pip install langchain-openai langchain-community

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Chat Model

from langchain_openai import ChatOpenAI

llm = ChatOpenAI(
    model="gpt-4o",
    api_key="sk-xxx",
    base_url="https://crazyrouter.com/v1",
    temperature=0.7
)

response = llm.invoke("What is LangChain?")
print(response.content)

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Embeddings

from langchain_openai import OpenAIEmbeddings

embeddings = OpenAIEmbeddings(
    model="text-embedding-3-large",
    api_key="sk-xxx",
    base_url="https://crazyrouter.com/v1"
)

vectors = embeddings.embed_documents(["Text one", "Text two"])

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Chain

from langchain_openai import ChatOpenAI
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.output_parsers import StrOutputParser

llm = ChatOpenAI(
    model="gpt-4o",
    api_key="sk-xxx",
    base_url="https://crazyrouter.com/v1"
)

prompt = ChatPromptTemplate.from_template("Explain {topic} in simple terms")
chain = prompt | llm | StrOutputParser()

result = chain.invoke({"topic": "quantum computing"})
print(result)

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RAG Example

from langchain_openai import ChatOpenAI, OpenAIEmbeddings
from langchain_community.vectorstores import FAISS
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.runnables import RunnablePassthrough

llm = ChatOpenAI(model="gpt-4o", api_key="sk-xxx", base_url="https://crazyrouter.com/v1")
embeddings = OpenAIEmbeddings(model="text-embedding-3-large", api_key="sk-xxx", base_url="https://crazyrouter.com/v1")

# Create vector store
texts = ["Crazyrouter supports 300+ AI models", "API is pay-per-use, flexible and affordable"]
vectorstore = FAISS.from_texts(texts, embeddings)
retriever = vectorstore.as_retriever()

# RAG chain
prompt = ChatPromptTemplate.from_template("Answer the question based on the following context:\n{context}\n\nQuestion: {question}")
chain = {"context": retriever, "question": RunnablePassthrough()} | prompt | llm

result = chain.invoke("How many models does Crazyrouter support?")
print(result.content)

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JavaScript Configuration

npm install @langchain/openai

import { ChatOpenAI } from '@langchain/openai';

const llm = new ChatOpenAI({
  modelName: 'gpt-4o',
  openAIApiKey: 'sk-xxx',
  configuration: {
    baseURL: 'https://crazyrouter.com/v1',
  },
});

const response = await llm.invoke('Hello');
console.log(response.content);
All LangChain components based on OpenAI can connect to Crazyrouter by simply changing the base_url and api_key, with no additional adaptation needed.