import g4f
g4f.debug.logging = True # Enable debug logging
g4f.debug.version_check = False # Disable automatic version checking
print(g4f.Provider.Bing.params) # Print supported args for Bing
# Using automatic a provider for the given model
## Streamed completion
response = g4f.ChatCompletion.create(
model="gpt-3.5-turbo",
messages=[{"role": "user", "content": "Hello"}],
stream=True,
)
for message in response:
print(message, flush=True, end='')
## Normal response
response = g4f.ChatCompletion.create(
model=g4f.models.gpt_4,
messages=[{"role": "user", "content": "Hello"}],
) # Alternative model setting
print(response)
import g4f
allowed_models = [
'code-davinci-002',
'text-ada-001',
'text-babbage-001',
'text-curie-001',
'text-davinci-002',
'text-davinci-003'
]
response = g4f.Completion.create(
model='text-davinci-003',
prompt='say this is a test'
)
print(response)
import g4f
# Print all available providers
print([
provider.__name__
for provider in g4f.Provider.__providers__
if provider.working
])
# Execute with a specific provider
response = g4f.ChatCompletion.create(
model="gpt-3.5-turbo",
provider=g4f.Provider.Aichat,
messages=[{"role": "user", "content": "Hello"}],
stream=True,
)
for message in response:
print(message)
Image upload and generation are supported by three main providers:
import g4f
# Setting up the request for image creation
response = g4f.ChatCompletion.create(
model=g4f.models.default, # Using the default model
provider=g4f.Provider.Gemini, # Specifying the provider as Gemini
messages=[{"role": "user", "content": "Create an image like this"}],
image=open("images/g4f.png", "rb"), # Image input can be a data URI, bytes, PIL Image, or IO object
image_name="g4f.png" # Optional: specifying the filename
)
# Displaying the response
print(response)
from g4f.image import ImageResponse
# Get image links from response
for chunk in g4f.ChatCompletion.create(
model=g4f.models.default, # Using the default model
provider=g4f.Provider.OpenaiChat, # Specifying the provider as OpenaiChat
messages=[{"role": "user", "content": "Create images with dogs"}],
access_token="...", # Need a access token from a plus user
stream=True,
ignore_stream=True
):
if isinstance(chunk, ImageResponse):
print(chunk.images) # Print generated image links
print(chunk.alt) # Print used prompt for image generation
Some providers using a browser to bypass the bot protection. They using the selenium webdriver to control the browser. The browser settings and the login data are saved in a custom directory. If the headless mode is enabled, the browser windows are loaded invisibly. For performance reasons, it is recommended to reuse the browser instances and close them yourself at the end:
import g4f
from undetected_chromedriver import Chrome, ChromeOptions
from g4f.Provider import (
Bard,
Poe,
AItianhuSpace,
MyShell,
PerplexityAi,
)
options = ChromeOptions()
options.add_argument("--incognito");
webdriver = Chrome(options=options, headless=True)
for idx in range(10):
response = g4f.ChatCompletion.create(
model=g4f.models.default,
provider=g4f.Provider.MyShell,
messages=[{"role": "user", "content": "Suggest me a name."}],
webdriver=webdriver
)
print(f"{idx}:", response)
webdriver.quit()
To enhance speed and overall performance, execute providers asynchronously. The total execution time will be determined by the duration of the slowest provider's execution.
import g4f
import asyncio
_providers = [
g4f.Provider.Aichat,
g4f.Provider.ChatBase,
g4f.Provider.Bing,
g4f.Provider.GptGo,
g4f.Provider.You,
g4f.Provider.Yqcloud,
]
async def run_provider(provider: g4f.Provider.BaseProvider):
try:
response = await g4f.ChatCompletion.create_async(
model=g4f.models.default,
messages=[{"role": "user", "content": "Hello"}],
provider=provider,
)
print(f"{provider.__name__}:", response)
except Exception as e:
print(f"{provider.__name__}:", e)
async def run_all():
calls = [
run_provider(provider) for provider in _providers
]
await asyncio.gather(*calls)
asyncio.run(run_all())
All providers support specifying a proxy and increasing timeout in the create functions.
import g4f
response = g4f.ChatCompletion.create(
model=g4f.models.default,
messages=[{"role": "user", "content": "Hello"}],
proxy="http://host:port",
# or socks5://user:pass@host:port
timeout=120, # in secs
)
print(f"Result:", response)