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Documentation Index

Fetch the complete documentation index at: https://docs.tokenfactory.nebius.com/llms.txt

Use this file to discover all available pages before exploring further.

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Langchain

LangChain is an open-source framework that helps developers build applications powered by Large Language Models (LLMs), by providing tools to connect models with data, APIs, and external systems. Langchain docs
Langchain + Nebius Token Factory docs

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Prerequisites

  1. Create an API key to authorize requests to Nebius Token Factory.
  2. Save the API key into a NEBIUS_API_KEY environment variable: 
    export NEBIUS_API_KEY="<API_key>"
  3. Install the langchain package: 
    pip install langchain-nebius

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Chat Models

from langchain_nebius import ChatNebius

# Initialize the chat model
chat = ChatNebius(
    model="Qwen/Qwen3-30B-A3B-fast",  # Choose from available models
    temperature=0.6,
    top_p=0.95
)

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Embedding Models

from langchain_nebius import NebiusEmbeddings

embeddings = NebiusEmbeddings(
    model="BAAI/bge-en-icl"  # Default embedding model
)

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Retrievers

from langchain_core.documents import Document
from langchain_nebius import NebiusEmbeddings, NebiusRetriever

# Create sample documents
docs = [
    Document(page_content="Paris is the capital of France"),
    Document(page_content="Berlin is the capital of Germany"),
]

# Initialize embeddings
embeddings = NebiusEmbeddings()

# Create retriever
retriever = NebiusRetriever(
    embeddings=embeddings,
    docs=docs,
    k=2  # Number of documents to return
)