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g4f is very similar to the OpenAI Python Sdk, the g4f completion syntax was made to work exactly like the sdk with some ClassNames being different.

​
The Client Class

As of the new v1 library of the OpenAi sdk, g4f is initialised with the g4f.client.Client class. 
from g4f.client import Client

client = Client()
The Clientclass accepts several arguments, you can set a default provider there. More on the Provider structure of g4f further down. 
from g4f.client   import Client
from g4f.Provider import You

client = Client(
    provider = You
)

​
Client(...) Class Arguments

​
provider
ProviderType
default:"None"
The provider to use for the client. If not specified, the default provider will be used.
​
image_provider
ImageProvider
default:"None"
The image provider provider to use for the client. If not specified, the default provider will be used.

​
Create completions

Once initialised, you can use the client object to create chat completions. Here again, client.chat.completions.create works like the OpenAI sdk, with the same parameters. 
chat_completion = client.chat.completions.create(
    model="gpt-3.5-turbo",
    messages=[{"role": "user", "content": "Hello"}],
)

print(chat_completion.choices[0].message.content or "")

​
create(...) basic Params

(For more advanced params and usage and examples, refer to the Full Documentation)
​
messages
list
required
A list of messages to use for the chat completion. Each message should be a dictionary with the keys role and content. It represents the conversation between a user and an assistant.

​
role
str
default:"system|user|assistant"
required
​
content
str
required
[
  {
    "role": "user",
    "content": "Hello"
  }
]
​
provider
ProviderType
default:"Auto"
The provider to use for the chat completion. Imported from g4f.Provider.ProviderName. Different working providers are outlined in the g4f README.
​
stream
bool
default:"False"
If set, the completion will be streamed, i.e. Tokens will be sent sequentially as soon as generated.
create will return a generator.

​
Stream completions

You may want to use g4f with streaming Response, you can do this with stream=True in the client.chat.completions.create method. 
chat_completion = client.chat.completions.create(model='gpt-3.5-turbo',
    messages=[{"role": "user", "content": "Hello"}], 
    stream=True
)

for completion in chat_completion:
    print(completion.choices[0].delta.content or "")
If you dont want the words to start at a newline every time: 
for completion in chat_completion:
    print(completion.choices[0].delta.content or "", end="", flush=True)
Full g4f example: 
from g4f.client import Client

client = Client()

chat_completion = client.chat.completions.create(model="gpt-3.5-turbo",
    messages=[{"role": "user", "content": "Hello"}], stream=True)

for completion in chat_completion:
    print(completion.choices[0].delta.content or "", end="", flush=True)

user@mac-air:~$ python3 main.py
Hi
 there
!
 How
 can
 I
 assist
 you
 today
?
For more advanced usage and examples, refer to the Full Documentation.