zishuo/gpt4free
1
0
Fork 0
mirror of https://github.com/xtekky/gpt4free.git synced 2025-10-05 08:16:58 +08:00
Code Issues Packages Projects Releases Wiki Activity

Show only free providers by default

Browse Source
This commit is contained in:
hlohaus
2025-02-21 06:52:04 +01:00
parent e53483d85b
commit 470b795418
14 changed files with 84 additions and 59 deletions
Download Patch File Download Diff File Expand all files Collapse all files

9
g4f/Provider/PollinationsAI.py
View File

@@ -123,9 +123,6 @@ class PollinationsAI(AsyncGeneratorProvider, ProviderModelMixin):
if model not in cls.image_models:
raise
if not cache and seed is None:
seed = random.randint(1000, 999999)
if model in cls.image_models:
async for chunk in cls._generate_image(
model=model,
@@ -134,6 +131,7 @@ class PollinationsAI(AsyncGeneratorProvider, ProviderModelMixin):
width=width,
height=height,
seed=seed,
cache=cache,
nologo=nologo,
private=private,
enhance=enhance,
@@ -165,11 +163,14 @@ class PollinationsAI(AsyncGeneratorProvider, ProviderModelMixin):
width: int,
height: int,
seed: Optional[int],
cache: bool,
nologo: bool,
private: bool,
enhance: bool,
safe: bool
) -> AsyncResult:
if not cache and seed is None:
seed = random.randint(9999, 99999999)
params = {
"seed": str(seed) if seed is not None else None,
"width": str(width),
@@ -207,6 +208,8 @@ class PollinationsAI(AsyncGeneratorProvider, ProviderModelMixin):
seed: Optional[int],
cache: bool
) -> AsyncResult:
if not cache and seed is None:
seed = random.randint(9999, 99999999)
json_mode = False
if response_format and response_format.get("type") == "json_object":
json_mode = True

2
g4f/Provider/PollinationsImage.py
View File

@@ -28,6 +28,7 @@ class PollinationsImage(PollinationsAI):
width: int = 1024,
height: int = 1024,
seed: Optional[int] = None,
cache: bool = False,
nologo: bool = True,
private: bool = False,
enhance: bool = False,
@@ -41,6 +42,7 @@ class PollinationsImage(PollinationsAI):
width=width,
height=height,
seed=seed,
cache=cache,
nologo=nologo,
private=private,
enhance=enhance,

3
g4f/Provider/hf/HuggingChat.py
View File

@@ -8,7 +8,8 @@ import base64
from typing import AsyncIterator
try:
from curl_cffi.requests import Session, CurlMime
from curl_cffi.requests import Session
from curl_cffi import CurlMime
has_curl_cffi = True
except ImportError:
has_curl_cffi = False

16
g4f/Provider/hf/HuggingFaceAPI.py
View File

@@ -4,6 +4,7 @@ from ...providers.types import Messages
from ...typing import ImagesType
from ...requests import StreamSession, raise_for_status
from ...errors import ModelNotSupportedError
from ...providers.helper import get_last_user_message
from ..template.OpenaiTemplate import OpenaiTemplate
from .models import model_aliases, vision_models, default_vision_model
from .HuggingChat import HuggingChat
@@ -22,7 +23,7 @@ class HuggingFaceAPI(OpenaiTemplate):
vision_models = vision_models
model_aliases = model_aliases
pipeline_tag: dict[str, str] = {}
pipeline_tags: dict[str, str] = {}
@classmethod
def get_models(cls, **kwargs):
@@ -36,8 +37,8 @@ class HuggingFaceAPI(OpenaiTemplate):
@classmethod
async def get_pipline_tag(cls, model: str, api_key: str = None):
if model in cls.pipeline_tag:
return cls.pipeline_tag[model]
if model in cls.pipeline_tags:
return cls.pipeline_tags[model]
async with StreamSession(
timeout=30,
headers=cls.get_headers(False, api_key),
@@ -45,8 +46,8 @@ class HuggingFaceAPI(OpenaiTemplate):
async with session.get(f"https://huggingface.co/api/models/{model}") as response:
await raise_for_status(response)
model_data = await response.json()
cls.pipeline_tag[model] = model_data.get("pipeline_tag")
return cls.pipeline_tag[model]
cls.pipeline_tags[model] = model_data.get("pipeline_tag")
return cls.pipeline_tags[model]
@classmethod
async def create_async_generator(
@@ -73,10 +74,11 @@ class HuggingFaceAPI(OpenaiTemplate):
if len(messages) > 6:
messages = messages[:3] + messages[-3:]
if calculate_lenght(messages) > max_inputs_lenght:
last_user_message = [{"role": "user", "content": get_last_user_message(messages)}]
if len(messages) > 2:
messages = [m for m in messages if m["role"] == "system"] + messages[-1:]
messages = [m for m in messages if m["role"] == "system"] + last_user_message
if len(messages) > 1 and calculate_lenght(messages) > max_inputs_lenght:
messages = [messages[-1]]
messages = last_user_message
debug.log(f"Messages trimmed from: {start} to: {calculate_lenght(messages)}")
async for chunk in super().create_async_generator(model, messages, api_base=api_base, api_key=api_key, max_tokens=max_tokens, images=images, **kwargs):
yield chunk

73
g4f/Provider/hf/HuggingFaceInference.py
View File

@@ -7,7 +7,7 @@ import requests
from ...typing import AsyncResult, Messages
from ..base_provider import AsyncGeneratorProvider, ProviderModelMixin, format_prompt
from ...errors import ModelNotFoundError, ModelNotSupportedError, ResponseError
from ...errors import ModelNotSupportedError, ResponseError
from ...requests import StreamSession, raise_for_status
from ...providers.response import FinishReason, ImageResponse
from ..helper import format_image_prompt, get_last_user_message
@@ -24,6 +24,8 @@ class HuggingFaceInference(AsyncGeneratorProvider, ProviderModelMixin):
model_aliases = model_aliases
image_models = image_models
model_data: dict[str, dict] = {}
@classmethod
def get_models(cls) -> list[str]:
if not cls.models:
@@ -43,6 +45,17 @@ class HuggingFaceInference(AsyncGeneratorProvider, ProviderModelMixin):
cls.models = models
return cls.models
@classmethod
async def get_model_data(cls, session: StreamSession, model: str) -> str:
if model in cls.model_data:
return cls.model_data[model]
async with session.get(f"https://huggingface.co/api/models/{model}") as response:
if response.status == 404:
raise ModelNotSupportedError(f"Model is not supported: {model} in: {cls.__name__}")
await raise_for_status(response)
cls.model_data[model] = await response.json()
return cls.model_data[model]
@classmethod
async def create_async_generator(
cls,
@@ -96,41 +109,37 @@ class HuggingFaceInference(AsyncGeneratorProvider, ProviderModelMixin):
timeout=600
) as session:
if payload is None:
async with session.get(f"https://huggingface.co/api/models/{model}") as response:
if response.status == 404:
raise ModelNotSupportedError(f"Model is not supported: {model} in: {cls.__name__}")
await raise_for_status(response)
model_data = await response.json()
pipeline_tag = model_data.get("pipeline_tag")
if pipeline_tag == "text-to-image":
stream = False
inputs = format_image_prompt(messages, prompt)
payload = {"inputs": inputs, "parameters": {"seed": random.randint(0, 2**32) if seed is None else seed, **extra_data}}
elif pipeline_tag in ("text-generation", "image-text-to-text"):
model_type = None
if "config" in model_data and "model_type" in model_data["config"]:
model_type = model_data["config"]["model_type"]
debug.log(f"Model type: {model_type}")
model_data = await cls.get_model_data(session, model)
pipeline_tag = model_data.get("pipeline_tag")
if pipeline_tag == "text-to-image":
stream = False
inputs = format_image_prompt(messages, prompt)
payload = {"inputs": inputs, "parameters": {"seed": random.randint(0, 2**32) if seed is None else seed, **extra_data}}
elif pipeline_tag in ("text-generation", "image-text-to-text"):
model_type = None
if "config" in model_data and "model_type" in model_data["config"]:
model_type = model_data["config"]["model_type"]
debug.log(f"Model type: {model_type}")
inputs = get_inputs(messages, model_data, model_type, do_continue)
debug.log(f"Inputs len: {len(inputs)}")
if len(inputs) > 4096:
if len(messages) > 6:
messages = messages[:3] + messages[-3:]
else:
messages = [m for m in messages if m["role"] == "system"] + [{"role": "user", "content": get_last_user_message(messages)}]
inputs = get_inputs(messages, model_data, model_type, do_continue)
debug.log(f"Inputs len: {len(inputs)}")
if len(inputs) > 4096:
if len(messages) > 6:
messages = messages[:3] + messages[-3:]
else:
messages = [m for m in messages if m["role"] == "system"] + [get_last_user_message(messages)]
inputs = get_inputs(messages, model_data, model_type, do_continue)
debug.log(f"New len: {len(inputs)}")
if model_type == "gpt2" and max_tokens >= 1024:
params["max_new_tokens"] = 512
if seed is not None:
params["seed"] = seed
payload = {"inputs": inputs, "parameters": params, "stream": stream}
else:
raise ModelNotSupportedError(f"Model is not supported: {model} in: {cls.__name__} pipeline_tag: {pipeline_tag}")
debug.log(f"New len: {len(inputs)}")
if model_type == "gpt2" and max_tokens >= 1024:
params["max_new_tokens"] = 512
if seed is not None:
params["seed"] = seed
payload = {"inputs": inputs, "parameters": params, "stream": stream}
else:
raise ModelNotSupportedError(f"Model is not supported: {model} in: {cls.__name__} pipeline_tag: {pipeline_tag}")
async with session.post(f"{api_base.rstrip('/')}/models/{model}", json=payload) as response:
if response.status == 404:
raise ModelNotFoundError(f"Model is not supported: {model}")
raise ModelNotSupportedError(f"Model is not supported: {model}")
await raise_for_status(response)
if stream:
first = True

2
g4f/Provider/hf/__init__.py
View File

@@ -36,7 +36,7 @@ class HuggingFace(AsyncGeneratorProvider, ProviderModelMixin):
messages: Messages,
**kwargs
) -> AsyncResult:
if "api_key" not in kwargs and "images" not in kwargs and random.random() >= 0.5:
if "images" not in kwargs and "deepseek" in model or random.random() >= 0.5:
try:
is_started = False
async for chunk in HuggingFaceInference.create_async_generator(model, messages, **kwargs):

1
g4f/Provider/needs_auth/DeepSeekAPI.py
View File

@@ -13,7 +13,6 @@ from ...errors import MissingAuthError
from ...requests import get_args_from_nodriver, get_nodriver
from ...providers.response import AuthResult, RequestLogin, Reasoning, JsonConversation, FinishReason
from ...typing import AsyncResult, Messages
from ... import debug
try:
from curl_cffi import requests
from dsk.api import DeepSeekAPI, AuthenticationError, DeepSeekPOW

1
g4f/Provider/needs_auth/OpenaiAccount.py
View File

@@ -5,3 +5,4 @@ from .OpenaiChat import OpenaiChat
class OpenaiAccount(OpenaiChat):
needs_auth = True
parent = "OpenaiChat"
use_nodriver = False # Show (Auth) in the model name

2
g4f/Provider/template/OpenaiTemplate.py
View File

@@ -65,7 +65,7 @@ class OpenaiTemplate(AsyncGeneratorProvider, ProviderModelMixin, RaiseErrorMixin
prompt: str = None,
headers: dict = None,
impersonate: str = None,
extra_parameters: list[str] = ["tools", "parallel_tool_calls", "", "reasoning_effort", "logit_bias"],
extra_parameters: list[str] = ["tools", "parallel_tool_calls", "tool_choice", "reasoning_effort", "logit_bias"],
extra_data: dict = {},
**kwargs
) -> AsyncResult:

4
g4f/client/__init__.py
View File

@@ -365,7 +365,7 @@ class Images:
break
except Exception as e:
error = e
debug.error(e, name=f"{provider.__name__} {type(e).__name__}")
debug.error(f"{provider.__name__} {type(e).__name__}: {e}")
else:
response = await self._generate_image_response(provider_handler, provider_name, model, prompt, **kwargs)
@@ -460,7 +460,7 @@ class Images:
break
except Exception as e:
error = e
debug.error(e, name=f"{provider.__name__} {type(e).__name__}")
debug.error(f"{provider.__name__} {type(e).__name__}: {e}")
else:
response = await self._generate_image_response(provider_handler, provider_name, model, prompt, **kwargs)

20
g4f/gui/client/static/js/chat.v1.js
View File

@@ -1932,7 +1932,7 @@ const load_provider_option = (input, provider_name) => {
providerSelect.querySelectorAll(`option[data-parent="${provider_name}"]`).forEach(
(el) => el.removeAttribute("disabled")
);
settings.querySelector(`.field:has(#${provider_name}-api_key)`)?.classList.remove("hidden");
//settings.querySelector(`.field:has(#${provider_name}-api_key)`)?.classList.remove("hidden");
} else {
modelSelect.querySelectorAll(`option[data-providers*="${provider_name}"]`).forEach(
(el) => {
@@ -1947,7 +1947,7 @@ const load_provider_option = (input, provider_name) => {
providerSelect.querySelectorAll(`option[data-parent="${provider_name}"]`).forEach(
(el) => el.setAttribute("disabled", "disabled")
);
settings.querySelector(`.field:has(#${provider_name}-api_key)`)?.classList.add("hidden");
//settings.querySelector(`.field:has(#${provider_name}-api_key)`)?.classList.add("hidden");
}
};
@@ -2039,13 +2039,13 @@ async function on_api() {
if (provider.parent) {
if (!login_urls[provider.parent]) {
login_urls[provider.parent] = [provider.label, provider.login_url, [provider.name]];
login_urls[provider.parent] = [provider.label, provider.login_url, [provider.name], provider.auth];
} else {
login_urls[provider.parent][2].push(provider.name);
}
} else if (provider.login_url) {
if (!login_urls[provider.name]) {
login_urls[provider.name] = [provider.label, provider.login_url, []];
login_urls[provider.name] = [provider.label, provider.login_url, [], provider.auth];
} else {
login_urls[provider.name][0] = provider.label;
login_urls[provider.name][1] = provider.login_url;
@@ -2068,9 +2068,10 @@ async function on_api() {
if (!provider.parent) {
let option = document.createElement("div");
option.classList.add("provider-item");
let api_key = appStorage.getItem(`${provider.name}-api_key`);
option.innerHTML = `
<span class="label">Enable ${provider.label}</span>
<input id="Provider${provider.name}" type="checkbox" name="Provider${provider.name}" value="${provider.name}" class="provider" checked="">
<input id="Provider${provider.name}" type="checkbox" name="Provider${provider.name}" value="${provider.name}" class="provider" ${'checked="checked"' ? !provider.auth || api_key : ''}/>
<label for="Provider${provider.name}" class="toogle" title="Remove provider from dropdown"></label>
`;
option.querySelector("input").addEventListener("change", (event) => load_provider_option(event.target, provider.name));
@@ -2102,7 +2103,7 @@ async function on_api() {
`;
settings.querySelector(".paper").appendChild(providersListContainer);
for (let [name, [label, login_url, childs]] of Object.entries(login_urls)) {
for (let [name, [label, login_url, childs, auth]] of Object.entries(login_urls)) {
if (!login_url && !is_demo) {
continue;
}
@@ -2113,6 +2114,13 @@ async function on_api() {
<label for="${name}-api_key" class="label" title="">${label}:</label>
<input type="text" id="${name}-api_key" name="${name}[api_key]" class="${childs}" placeholder="api_key" autocomplete="off"/>
` + (login_url ? `<a href="${login_url}" target="_blank" title="Login to ${label}">Get API key</a>` : "");
if (auth) {
providerBox.querySelector("input").addEventListener("input", (event) => {
const input = document.getElementById(`Provider${name}`);
input.checked = !!event.target.value;
load_provider_option(input, name);
});
}
providersListContainer.querySelector(".collapsible-content").appendChild(providerBox);
}

4
g4f/gui/server/api.py
View File

@@ -143,7 +143,7 @@ class Api:
def decorated_log(text: str, file = None):
debug.logs.append(text)
if debug.logging:
debug.log_handler(text, file)
debug.log_handler(text, file=file)
debug.log = decorated_log
proxy = os.environ.get("G4F_PROXY")
provider = kwargs.get("provider")
@@ -187,7 +187,7 @@ class Api:
yield self._format_json("conversation_id", conversation_id)
elif isinstance(chunk, Exception):
logger.exception(chunk)
debug.error(e)
debug.error(chunk)
yield self._format_json('message', get_error_message(chunk), error=type(chunk).__name__)
elif isinstance(chunk, PreviewResponse):
yield self._format_json("preview", chunk.to_string())

2
g4f/image/copy_images.py
View File

@@ -123,7 +123,7 @@ async def copy_images(
return f"/images/{url_filename}{'?url=' + quote(image) if add_url and not image.startswith('data:') else ''}"
except (ClientError, IOError, OSError) as e:
debug.error(f"Image processing failed: {type(e).__name__}: {e}")
debug.error(f"Image copying failed: {type(e).__name__}: {e}")
if target_path and os.path.exists(target_path):
os.unlink(target_path)
return get_source_url(image, image)

2
g4f/providers/retry_provider.py
View File

@@ -105,7 +105,7 @@ class IterListProvider(BaseRetryProvider):
return
except Exception as e:
exceptions[provider.__name__] = e
debug.error(name=f"{provider.__name__} {type(e).__name__}: {e}")
debug.error(f"{provider.__name__} {type(e).__name__}: {e}")
if started:
raise e
yield e