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Featherless AI LLM

docs/examples/llm/featherlessai.ipynb

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Featherless AI LLM

This notebook shows how to use Featherless AI as an LLM. Check out the full list of models featherless.ai.

Visit https://www.featherless.ai/ and sign up to get an API key.

Setup

If you're opening this Notebook on colab, you will probably need to install LlamaIndex 🦙.

python
%pip install llama-index-llms-featherlessai
python
!pip install llama-index
python
from llama_index.llms.featherlessai import FeatherlessLLM
python
# set api key in env or in llm
# import os
# os.environ["FEATHERLESS_API_KEY"] = "your api key"

llm = FeatherlessLLM(model="Qwen/Qwen3-32B", api_key="your api key")
python
resp = llm.complete("Is 9.9 or 9.11 bigger?")
python
print(resp)

Call chat with a list of messages

python
from llama_index.core.llms import ChatMessage

messages = [
    ChatMessage(
        role="system", content="You are a pirate with a colorful personality"
    ),
    ChatMessage(role="user", content="What is your name"),
]
resp = llm.chat(messages)
python
print(resp)

Streaming

Using stream_complete endpoint

python
response = llm.stream_complete("Who is Paul Graham?")
python
for r in response:
    print(r.delta, end="")

Using stream_chat endpoint

python
from llama_index.core.llms import ChatMessage

messages = [
    ChatMessage(
        role="system", content="You are a pirate with a colorful personality"
    ),
    ChatMessage(role="user", content="What is your name"),
]
resp = llm.stream_chat(messages)
python
for r in resp:
    print(r.delta, end="")