Skip to main content
This will help you get started with FeatherlessAi chat models. For detailed documentation of all ChatFeatherlessAi features and configurations head to the API reference.

​
Overview

​
Integration details

ClassPackageLocalSerializableJS supportDownloadsVersion
ChatFeatherlessAilangchain-featherless-ai✅❌❌PyPI - DownloadsPyPI - Version

​
Model features

Tool callingStructured outputJSON modeImage inputAudio inputVideo inputToken-level streamingNative asyncToken usageLogprobs
❌❌✅❌❌❌✅✅✅❌

​
Setup

To access Featherless AI models you’ll need to create a/an Featherless AI account, get an API key, and install the langchain-featherless-ai integration package.

​
Credentials

Head to featherless.ai/ to sign up to FeatherlessAI and generate an API key. Once you’ve done this set the FEATHERLESSAI_API_KEY environment variable: 
import getpass
import os

if not os.getenv("FEATHERLESSAI_API_KEY"):
    os.environ["FEATHERLESSAI_API_KEY"] = getpass.getpass(
        "Enter your FeatherlessAI API key: "
    )
If you want to get automated tracing of your model calls you can also set your LangSmith API key by uncommenting below: 
os.environ["LANGSMITH_TRACING"] = "true"
os.environ["LANGSMITH_API_KEY"] = getpass.getpass("Enter your LangSmith API key: ")

​
Installation

The LangChain FeatherlessAi integration lives in the langchain-featherless-ai package: 
pip install -qU langchain-featherless-ai

Note: you may need to restart the kernel to use updated packages.

​
Instantiation

Now we can instantiate our model object and generate chat completions: 
from langchain_featherless_ai import ChatFeatherlessAi

llm = ChatFeatherlessAi(
    model="featherless-ai/Qwerky-72B",
    temperature=0.9,
    max_tokens=None,
    timeout=None,
)

​
Invocation

messages = [
    (
        "system",
        "You are a helpful assistant that translates English to French. Translate the user sentence.",
    ),
    ("human", "I love programming."),
]
ai_msg = llm.invoke(messages)
ai_msg

c:\Python311\Lib\site-packages\pydantic\main.py:463: UserWarning: Pydantic serializer warnings:
  PydanticSerializationUnexpectedValue(Expected `int` - serialized value may not be as expected [input_value=1747322408.706, input_type=float])
  return self.__pydantic_serializer__.to_python(

AIMessage(content="J'aime programmer.", additional_kwargs={'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 5, 'prompt_tokens': 27, 'total_tokens': 32, 'completion_tokens_details': None, 'prompt_tokens_details': None}, 'model_name': 'featherless-ai/Qwerky-72B', 'system_fingerprint': '', 'id': 'G1sgui', 'service_tier': None, 'finish_reason': 'stop', 'logprobs': None}, id='run--6ecbe184-c94e-4d03-bf75-9bd85b04ba5b-0', usage_metadata={'input_tokens': 27, 'output_tokens': 5, 'total_tokens': 32, 'input_token_details': {}, 'output_token_details': {}})

print(ai_msg.content)

J'aime programmer.

​
API reference

For detailed documentation of all ChatFeatherlessAi features and configurations head to the API reference
Edit the source of this page on GitHub.
Connect these docs programmatically to Claude, VSCode, and more via MCP for real-time answers.
⌘I