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You can use LiteLLM to interact with FriendliAI. If you already use LiteLLM, you can migrate your existing applications with minimal changes.

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How to Use

Before you start, get your FRIENDLIAI_API_KEY from Friendli Suite > Personal Settings > API Keys. Then add the friendliai prefix to your endpoint name in the model parameter.

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Chat Completion

Choose the example for your endpoint type. For Model APIs, you can specify one of the available models. 
import os
from litellm import completion

os.environ['FRIENDLIAI_API_KEY'] = "YOUR_API_KEY"

response = completion(
    model="friendliai/zai-org/GLM-5.2",
    messages=[
        {"role": "user", "content": "hello from litellm"}
    ],
)
print(response)

import os
from litellm import completion

os.environ['FRIENDLIAI_API_KEY'] = "YOUR_API_KEY"
os.environ['FRIENDLI_API_BASE'] = "https://api.friendli.ai/dedicated/v1"

response = completion(
    model="friendliai/YOUR_ENDPOINT_ID",
    messages=[
        {"role": "user", "content": "hello from litellm"}
    ],
)
print(response)

import os
from litellm import completion

os.environ['FRIENDLIAI_API_KEY'] = "YOUR_API_KEY"
os.environ['FRIENDLI_API_BASE'] = "https://api.friendli.ai/dedicated/v1"

response = completion(
    model="friendliai/YOUR_ENDPOINT_ID:YOUR_ADAPTER_ROUTE",
    messages=[
        {"role": "user", "content": "hello from litellm"}
    ],
)
print(response)

​
Chat Completion - Streaming

import os
from litellm import completion

os.environ['FRIENDLIAI_API_KEY'] = "YOUR_API_KEY"

response = completion(
    model="friendliai/zai-org/GLM-5.2",
    messages=[
        {"role": "user", "content": "hello from litellm"}
    ],
    stream=True
)

for chunk in response:
    print(chunk)

import os
from litellm import completion

os.environ['FRIENDLIAI_API_KEY'] = "YOUR_API_KEY"
os.environ['FRIENDLI_API_BASE'] = "https://api.friendli.ai/dedicated/v1"

response = completion(
    model="friendliai/YOUR_ENDPOINT_ID",
    messages=[
        {"role": "user", "content": "hello from litellm"}
    ],
    stream=True
)

for chunk in response:
    print(chunk)

import os
from litellm import completion

os.environ['FRIENDLIAI_API_KEY'] = "YOUR_API_KEY"
os.environ['FRIENDLI_API_BASE'] = "https://api.friendli.ai/dedicated/v1"

response = completion(
    model="friendliai/YOUR_ENDPOINT_ID:YOUR_ADAPTER_ROUTE",
    messages=[
        {"role": "user", "content": "hello from litellm"}
    ],
    stream=True
)

for chunk in response:
    print(chunk)
Last modified on July 7, 2026