LiteLLM - FriendliAI Docs

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

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.

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

LlamaIndex

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⌘I

​How to Use

​Chat Completion

​Chat Completion - Streaming

How to Use

Chat Completion

Chat Completion - Streaming