You can use LlamaIndex to interact with FriendliAI. This makes migration of existing applications already using LlamaIndex particularly easy.

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How to use

Before you start, ensure you’ve already obtained the FRIENDLI_TOKEN from the Friendli Suite. 
pip install llama-index llama-index-llms-friendli

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Instantiation

Now we can instantiate our model object and generate chat completions. The default model (i.e. meta-llama-3.3-70b-instruct) will be used if no model is specified. 
import os
from llama_index.llms.friendli import Friendli

os.environ['FRIENDLI_TOKEN'] = "YOUR_FRIENDLI_TOKEN"

llm = Friendli(model="meta-llama-3.3-70b-instruct")

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Chat completion

Generate a response from a given conversation. 
from llama_index.core.llms import ChatMessage, MessageRole

message = ChatMessage(role=MessageRole.USER, content="Tell me a joke.")
resp = llm.chat([message])

print(resp)

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Completion

Generate a response from a given prompt. 
prompt = "Draft a cover letter for a role in software engineering."
resp = llm.complete(prompt)

print(resp)