Add new Client API with Docs

Use object urls for the preview of image uploads.
Fix upload images in You provider
Fix create image. It's now a single image.
Improve system message for create images.
This commit is contained in:
Heiner Lohaus 2024-02-12 11:41:27 +01:00
parent 9aeae65b9b
commit aba4b96f23
14 changed files with 480 additions and 125 deletions

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@ -24,7 +24,7 @@ jobs:
run: pip install -r requirements-min.txt
- name: Run tests
run: python -m etc.unittest
- name: Set up Python 3.11
- name: Set up Python 3.12
uses: actions/setup-python@v4
with:
python-version: "3.12"

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@ -226,6 +226,23 @@ docker-compose down
## 💡 Usage
### New Client with Image Generation
```python
from g4f.client import Client
client = Client()
response = client.images.generate(
model="gemini",
prompt="a white siamese cat",
...
)
image_url = response.data[0].url
```
Result:
[![Image with cat](/docs/cat.jpeg)](/docs/client.md)
[to the client API](/docs/client.md)
### The Web UI
To start the web interface, type the following codes in the command line.

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71
docs/client.md Normal file
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@ -0,0 +1,71 @@
### Client API
##### from g4f (beta)
#### Start
This new client could:
```python
from g4f.client import Client
```
replaces this:
```python
from openai import OpenAI
```
in your Python Code.
New client have the same API as OpenAI.
#### Client
Create the client with custom providers:
```python
from g4f.client import Client
from g4f.Provider import BingCreateImages, OpenaiChat, Gemini
client = Client(
provider=OpenaiChat,
image_provider=Gemini,
proxies=None
)
```
#### Examples
Use the ChatCompletions:
```python
stream = client.chat.completions.create(
model="gpt-4",
messages=[{"role": "user", "content": "Say this is a test"}],
stream=True,
)
for chunk in stream:
if chunk.choices[0].delta.content is not None:
print(chunk.choices[0].delta.content, end="")
```
Or use it for creating a image:
```python
response = client.images.generate(
model="dall-e-3",
prompt="a white siamese cat",
...
)
image_url = response.data[0].url
```
Also this works with the client:
```python
response = client.images.create_variation(
image=open('cat.jpg')
model="bing",
...
)
image_url = response.data[0].url
```
[to Home](/docs/client.md)

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@ -1,60 +1,22 @@
from __future__ import annotations
import asyncio
import time
import os
from typing import Generator
from ..cookies import get_cookies
from ..webdriver import WebDriver, get_driver_cookies, get_browser
from ..image import ImageResponse
from ..errors import MissingRequirementsError, MissingAuthError
from .bing.create_images import BING_URL, create_images, create_session
from .bing.create_images import create_images, create_session, get_cookies_from_browser
BING_URL = "https://www.bing.com"
TIMEOUT_LOGIN = 1200
def wait_for_login(driver: WebDriver, timeout: int = TIMEOUT_LOGIN) -> None:
"""
Waits for the user to log in within a given timeout period.
Args:
driver (WebDriver): Webdriver for browser automation.
timeout (int): Maximum waiting time in seconds.
Raises:
RuntimeError: If the login process exceeds the timeout.
"""
driver.get(f"{BING_URL}/")
start_time = time.time()
while not driver.get_cookie("_U"):
if time.time() - start_time > timeout:
raise RuntimeError("Timeout error")
time.sleep(0.5)
def get_cookies_from_browser(proxy: str = None) -> dict[str, str]:
"""
Retrieves cookies from the browser using webdriver.
Args:
proxy (str, optional): Proxy configuration.
Returns:
dict[str, str]: Retrieved cookies.
"""
with get_browser(proxy=proxy) as driver:
wait_for_login(driver)
time.sleep(1)
return get_driver_cookies(driver)
class CreateImagesBing:
class BingCreateImages:
"""A class for creating images using Bing."""
def __init__(self, cookies: dict[str, str] = {}, proxy: str = None) -> None:
self.cookies = cookies
self.proxy = proxy
def create_completion(self, prompt: str) -> Generator[ImageResponse, None, None]:
def create(self, prompt: str) -> Generator[ImageResponse, None, None]:
"""
Generator for creating imagecompletion based on a prompt.
@ -91,4 +53,4 @@ class CreateImagesBing:
proxy = self.proxy or os.environ.get("G4F_PROXY")
async with create_session(cookies, proxy) as session:
images = await create_images(session, prompt, proxy)
return ImageResponse(images, prompt, {"preview": "{image}?w=200&h=200"})
return ImageResponse(images, prompt, {"preview": "{image}?w=200&h=200"} if len(images) > 1 else {})

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@ -58,9 +58,14 @@ class You(AsyncGeneratorProvider):
"selectedChatMode": chat_mode,
#"chat": json.dumps(chat),
}
params = {
"userFiles": upload,
"selectedChatMode": chat_mode,
}
async with (client.post if chat_mode == "default" else client.get)(
f"{cls.url}/api/streamingSearch",
data=data,
params=params,
headers=headers,
cookies=cookies
) as response:

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@ -53,7 +53,7 @@ from .Vercel import Vercel
from .Ylokh import Ylokh
from .You import You
from .CreateImagesBing import CreateImagesBing
from .BingCreateImages import BingCreateImages
import sys

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@ -21,8 +21,10 @@ from ..create_images import CreateImagesProvider
from ..helper import get_connector
from ...base_provider import ProviderType
from ...errors import MissingRequirementsError
from ...webdriver import WebDriver, get_driver_cookies, get_browser
BING_URL = "https://www.bing.com"
TIMEOUT_LOGIN = 1200
TIMEOUT_IMAGE_CREATION = 300
ERRORS = [
"this prompt is being reviewed",
@ -35,6 +37,39 @@ BAD_IMAGES = [
"https://r.bing.com/rp/TX9QuO3WzcCJz1uaaSwQAz39Kb0.jpg",
]
def wait_for_login(driver: WebDriver, timeout: int = TIMEOUT_LOGIN) -> None:
"""
Waits for the user to log in within a given timeout period.
Args:
driver (WebDriver): Webdriver for browser automation.
timeout (int): Maximum waiting time in seconds.
Raises:
RuntimeError: If the login process exceeds the timeout.
"""
driver.get(f"{BING_URL}/")
start_time = time.time()
while not driver.get_cookie("_U"):
if time.time() - start_time > timeout:
raise RuntimeError("Timeout error")
time.sleep(0.5)
def get_cookies_from_browser(proxy: str = None) -> dict[str, str]:
"""
Retrieves cookies from the browser using webdriver.
Args:
proxy (str, optional): Proxy configuration.
Returns:
dict[str, str]: Retrieved cookies.
"""
with get_browser(proxy=proxy) as driver:
wait_for_login(driver)
time.sleep(1)
return get_driver_cookies(driver)
def create_session(cookies: Dict[str, str], proxy: str = None, connector: BaseConnector = None) -> ClientSession:
"""
Creates a new client session with specified cookies and headers.
@ -141,6 +176,8 @@ def read_images(html_content: str) -> List[str]:
"""
soup = BeautifulSoup(html_content, "html.parser")
tags = soup.find_all("img", class_="mimg")
if not tags:
tags = soup.find_all("img", class_="gir_mmimg")
images = [img["src"].split("?w=")[0] for img in tags]
if any(im in BAD_IMAGES for im in images):
raise RuntimeError("Bad images found")
@ -158,10 +195,10 @@ def patch_provider(provider: ProviderType) -> CreateImagesProvider:
Returns:
CreateImagesProvider: The patched provider with image creation capabilities.
"""
from ..CreateImagesBing import CreateImagesBing
service = CreateImagesBing()
from ..BingCreateImages import BingCreateImages
service = BingCreateImages()
return CreateImagesProvider(
provider,
service.create_completion,
service.create,
service.create_async
)

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@ -7,10 +7,14 @@ from ..typing import CreateResult, Messages
from ..base_provider import BaseProvider, ProviderType
system_message = """
You can generate custom images with the DALL-E 3 image generator.
You can generate images, pictures, photos or img with the DALL-E 3 image generator.
To generate an image with a prompt, do this:
<img data-prompt=\"keywords for the image\">
Don't use images with data uri. It is important to use a prompt instead.
Never use own image links. Don't wrap it in backticks.
It is important to use a only a img tag with a prompt.
<img data-prompt=\"image caption\">
"""

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@ -386,7 +386,6 @@ class OpenaiChat(AsyncGeneratorProvider, ProviderModelMixin):
) as response:
if not response.ok:
raise RuntimeError(f"Response {response.status_code}: {await response.text()}")
try:
last_message: int = 0
async for line in response.iter_lines():
if not line.startswith(b"data: "):
@ -428,8 +427,6 @@ class OpenaiChat(AsyncGeneratorProvider, ProviderModelMixin):
if "finish_details" in line["message"]["metadata"]:
if line["message"]["metadata"]["finish_details"]["type"] == "stop":
end_turn.end()
except Exception as e:
raise e
if not auto_continue:
break
action = "continue"

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@ -16,7 +16,8 @@ def get_model_and_provider(model : Union[Model, str],
stream : bool,
ignored : list[str] = None,
ignore_working: bool = False,
ignore_stream: bool = False) -> tuple[str, ProviderType]:
ignore_stream: bool = False,
**kwargs) -> tuple[str, ProviderType]:
"""
Retrieves the model and provider based on input parameters.

267
g4f/client.py Normal file
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@ -0,0 +1,267 @@
from __future__ import annotations
import re
from .typing import Union, Generator, AsyncGenerator, Messages, ImageType
from .base_provider import BaseProvider, ProviderType
from .Provider.base_provider import AsyncGeneratorProvider
from .image import ImageResponse as ImageProviderResponse
from .Provider import BingCreateImages, Gemini, OpenaiChat
from .errors import NoImageResponseError
from . import get_model_and_provider
ImageProvider = Union[BaseProvider, object]
Proxies = Union[dict, str]
def read_json(text: str) -> dict:
"""
Parses JSON code block from a string.
Args:
text (str): A string containing a JSON code block.
Returns:
dict: A dictionary parsed from the JSON code block.
"""
match = re.search(r"```(json|)\n(?P<code>[\S\s]+?)\n```", text)
if match:
return match.group("code")
return text
def iter_response(
response: iter,
stream: bool,
response_format: dict = None,
max_tokens: int = None,
stop: list = None
) -> Generator:
content = ""
idx = 1
chunk = None
finish_reason = "stop"
for idx, chunk in enumerate(response):
content += str(chunk)
if max_tokens is not None and idx > max_tokens:
finish_reason = "max_tokens"
break
first = -1
word = None
if stop is not None:
for word in list(stop):
first = content.find(word)
if first != -1:
content = content[:first]
break
if stream:
if first != -1:
first = chunk.find(word)
if first != -1:
chunk = chunk[:first]
else:
first = 0
yield ChatCompletionChunk([ChatCompletionDeltaChoice(ChatCompletionDelta(chunk))])
if first != -1:
break
if not stream:
if response_format is not None and "type" in response_format:
if response_format["type"] == "json_object":
response = read_json(response)
yield ChatCompletion([ChatCompletionChoice(ChatCompletionMessage(response, finish_reason))])
async def aiter_response(
response: aiter,
stream: bool,
response_format: dict = None,
max_tokens: int = None,
stop: list = None
) -> AsyncGenerator:
content = ""
try:
idx = 0
chunk = None
async for chunk in response:
content += str(chunk)
if max_tokens is not None and idx > max_tokens:
break
first = -1
word = None
if stop is not None:
for word in list(stop):
first = content.find(word)
if first != -1:
content = content[:first]
break
if stream:
if first != -1:
first = chunk.find(word)
if first != -1:
chunk = chunk[:first]
else:
first = 0
yield ChatCompletionChunk([ChatCompletionDeltaChoice(ChatCompletionDelta(chunk))])
if first != -1:
break
idx += 1
except:
...
if not stream:
if response_format is not None and "type" in response_format:
if response_format["type"] == "json_object":
response = read_json(response)
yield ChatCompletion([ChatCompletionChoice(ChatCompletionMessage(response))])
class Model():
def __getitem__(self, item):
return getattr(self, item)
class ChatCompletion(Model):
def __init__(self, choices: list):
self.choices = choices
class ChatCompletionChunk(Model):
def __init__(self, choices: list):
self.choices = choices
class ChatCompletionChoice(Model):
def __init__(self, message: ChatCompletionMessage):
self.message = message
class ChatCompletionMessage(Model):
def __init__(self, content: str, finish_reason: str):
self.content = content
self.finish_reason = finish_reason
self.index = 0
self.logprobs = None
class ChatCompletionDelta(Model):
def __init__(self, content: str):
self.content = content
class ChatCompletionDeltaChoice(Model):
def __init__(self, delta: ChatCompletionDelta):
self.delta = delta
class Client():
proxies: Proxies = None
chat: Chat
def __init__(
self,
provider: ProviderType = None,
image_provider: ImageProvider = None,
proxies: Proxies = None,
**kwargs
) -> None:
self.proxies: Proxies = proxies
self.images = Images(self, image_provider)
self.chat = Chat(self, provider)
def get_proxy(self) -> Union[str, None]:
if isinstance(self.proxies, str) or self.proxies is None:
return self.proxies
elif "all" in self.proxies:
return self.proxies["all"]
elif "https" in self.proxies:
return self.proxies["https"]
return None
class Completions():
def __init__(self, client: Client, provider: ProviderType = None):
self.client: Client = client
self.provider: ProviderType = provider
def create(
self,
messages: Messages,
model: str,
provider: ProviderType = None,
stream: bool = False,
response_format: dict = None,
max_tokens: int = None,
stop: list = None,
**kwargs
) -> Union[dict, Generator]:
if max_tokens is not None:
kwargs["max_tokens"] = max_tokens
if stop:
kwargs["stop"] = list(stop)
model, provider = get_model_and_provider(
model,
self.provider if provider is None else provider,
stream,
**kwargs
)
response = provider.create_completion(model, messages, stream=stream, **kwargs)
if isinstance(provider, type) and issubclass(provider, AsyncGeneratorProvider):
response = iter_response(response, stream, response_format) # max_tokens, stop
else:
response = iter_response(response, stream, response_format, max_tokens, stop)
return response if stream else next(response)
class Chat():
completions: Completions
def __init__(self, client: Client, provider: ProviderType = None):
self.completions = Completions(client, provider)
class ImageModels():
gemini = Gemini
openai = OpenaiChat
def __init__(self, client: Client) -> None:
self.client = client
self.default = BingCreateImages(proxy=self.client.get_proxy())
def get(self, name: str) -> ImageProvider:
return getattr(self, name) if hasattr(self, name) else self.default
class ImagesResponse(Model):
data: list[Image]
def __init__(self, data: list) -> None:
self.data = data
class Image(Model):
url: str
def __init__(self, url: str) -> None:
self.url = url
class Images():
def __init__(self, client: Client, provider: ImageProvider = None):
self.client: Client = client
self.provider: ImageProvider = provider
self.models: ImageModels = ImageModels(client)
def generate(self, prompt, model: str = None, **kwargs):
provider = self.models.get(model) if model else self.provider or self.models.get(model)
if isinstance(provider, BaseProvider) or isinstance(provider, type) and issubclass(provider, BaseProvider):
prompt = f"create a image: {prompt}"
response = provider.create_completion(
"",
[{"role": "user", "content": prompt}],
True,
proxy=self.client.get_proxy()
)
else:
response = provider.create(prompt)
for chunk in response:
if isinstance(chunk, ImageProviderResponse):
return ImagesResponse([Image(image)for image in list(chunk.images)])
raise NoImageResponseError()
def create_variation(self, image: ImageType, model: str = None, **kwargs):
provider = self.models.get(model) if model else self.provider
if isinstance(provider, BaseProvider):
response = provider.create_completion(
"",
[{"role": "user", "content": "create a image like this"}],
True,
image=image,
proxy=self.client.get_proxy()
)
for chunk in response:
if isinstance(chunk, ImageProviderResponse):
return ImagesResponse([Image(image)for image in list(chunk.images)])
raise NoImageResponseError()

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@ -1,35 +1,38 @@
class ProviderNotFoundError(Exception):
pass
...
class ProviderNotWorkingError(Exception):
pass
...
class StreamNotSupportedError(Exception):
pass
...
class ModelNotFoundError(Exception):
pass
...
class ModelNotAllowedError(Exception):
pass
...
class RetryProviderError(Exception):
pass
...
class RetryNoProviderError(Exception):
pass
...
class VersionNotFoundError(Exception):
pass
...
class NestAsyncioError(Exception):
pass
...
class ModelNotSupportedError(Exception):
pass
...
class MissingRequirementsError(Exception):
pass
...
class MissingAuthError(Exception):
pass
...
class NoImageResponseError(Exception):
...

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@ -52,6 +52,12 @@ const handle_ask = async () => {
}
await add_message(window.conversation_id, "user", message);
window.token = message_id();
if (imageInput.dataset.src) URL.revokeObjectURL(imageInput.dataset.src);
const input = imageInput && imageInput.files.length > 0 ? imageInput : cameraInput
if (input.files.length > 0) imageInput.dataset.src = URL.createObjectURL(input.files[0]);
else delete imageInput.dataset.src
message_box.innerHTML += `
<div class="message">
<div class="user">
@ -64,10 +70,6 @@ const handle_ask = async () => {
? '<img src="' + imageInput.dataset.src + '" alt="Image upload">'
: ''
}
${cameraInput.dataset.src
? '<img src="' + cameraInput.dataset.src + '" alt="Image capture">'
: ''
}
</div>
</div>
`;
@ -683,24 +685,13 @@ observer.observe(message_input, { attributes: true });
document.getElementById("version_text").innerHTML = text
})()
for (const el of [imageInput, cameraInput]) {
console.log(el.files);
el.addEventListener('click', async () => {
el.value = '';
delete el.dataset.src;
});
do_load = async () => {
if (el.files.length) {
delete imageInput.dataset.src;
delete cameraInput.dataset.src;
const reader = new FileReader();
reader.addEventListener('load', (event) => {
el.dataset.src = event.target.result;
});
reader.readAsDataURL(el.files[0]);
if (imageInput.dataset.src) {
URL.revokeObjectURL(imageInput.dataset.src);
delete imageInput.dataset.src
}
}
do_load()
el.addEventListener('change', do_load);
});
}
fileInput.addEventListener('click', async (event) => {
fileInput.value = '';