> ## Documentation Index
> Fetch the complete documentation index at: https://docs.g4f.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Basic Usage

> Learn how to use G4F in your projects

<Note>`g4f` is very similar to the [*OpenAI Python Sdk*](https://github.com/openai/openai-python), the `g4f` completion syntax was made to work exactly like the sdk with some ClassNames being different.</Note>

## The `Client` Class

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

```jsx theme={null}
from g4f.client import Client

client = Client()
```

The `Client`class accepts several arguments, you can set a default provider there. More on the `Provider` structure of `g4f` further down.

```jsx theme={null}
from g4f.client   import Client
from g4f.Provider import You

client = Client(
    provider = You
)
```

#### `Client(...)` Class Arguments

<ParamField path="provider" type="ProviderType" default="None">
  The provider to use for the client. If not specified, the default provider will be used.
</ParamField>

<ParamField path="image_provider" type="ImageProvider" default="None">
  The image provider provider to use for the client. If not specified, the default provider will be used.
</ParamField>

## 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.

```jsx theme={null}
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

<Note>
  (**For more advanced params and usage** and examples, refer to the [Full Documentation](/docs/core/usage/main))
</Note>

<ParamField path="messages" type="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.

  <Card>
    <ParamField path="role" type="str" default="system|user|assistant" required />

    <ParamField path="content" type="str" required />
  </Card>

  ```json theme={null}
  [
    {
      "role": "user",
      "content": "Hello"
    }
  ]
  ```
</ParamField>

<ParamField path="provider" type="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.
</ParamField>

<ParamField path="stream" type="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.
</ParamField>

## 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.

```jsx theme={null}
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:

```jsx theme={null}
for completion in chat_completion:
    print(completion.choices[0].delta.content or "", end="", flush=True)
```

Full G4F example:

```jsx theme={null}
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](/docs/core/usage/main).