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~ | code styling

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abc
2023-08-27 17:37:44 +02:00
parent 5d08c7201f
commit efd75a11b8
33 changed files with 842 additions and 967 deletions
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5
g4f/Provider/AItianhu.py
View File

@@ -15,9 +15,8 @@ class AItianhu(BaseProvider):
def create_completion( def create_completion(
model: str, model: str,
messages: list[dict[str, str]], messages: list[dict[str, str]],
stream: bool, stream: bool, **kwargs: Any) -> CreateResult:
**kwargs: Any,
) -> CreateResult:
base = "" base = ""
for message in messages: for message in messages:
base += "%s: %s\n" % (message["role"], message["content"]) base += "%s: %s\n" % (message["role"], message["content"])

32
g4f/Provider/Acytoo.py
View File

@@ -7,7 +7,7 @@ from .base_provider import BaseProvider
class Acytoo(BaseProvider): class Acytoo(BaseProvider):
url = "https://chat.acytoo.com/" url = 'https://chat.acytoo.com/'
working = True working = True
supports_gpt_35_turbo = True supports_gpt_35_turbo = True
@@ -16,33 +16,33 @@ class Acytoo(BaseProvider):
cls, cls,
model: str, model: str,
messages: list[dict[str, str]], messages: list[dict[str, str]],
stream: bool, stream: bool, **kwargs: Any) -> CreateResult:
**kwargs: Any,
) -> CreateResult: response = requests.post(f'{cls.url}api/completions',
headers = _create_header() headers=_create_header(), json=_create_payload(messages, kwargs.get('temperature', 0.5)))
payload = _create_payload(messages, kwargs.get('temperature', 0.5))
response = requests.post("{cls.url}api/completions", headers=headers, json=payload)
response.raise_for_status() response.raise_for_status()
response.encoding = "utf-8" response.encoding = 'utf-8'
yield response.text yield response.text
def _create_header(): def _create_header():
return { return {
"accept": "*/*", 'accept': '*/*',
"content-type": "application/json", 'content-type': 'application/json',
} }
def _create_payload(messages: list[dict[str, str]], temperature): def _create_payload(messages: list[dict[str, str]], temperature):
payload_messages = [ payload_messages = [
message | {"createdAt": int(time.time()) * 1000} for message in messages message | {'createdAt': int(time.time()) * 1000} for message in messages
] ]
return { return {
"key": "", 'key' : '',
"model": "gpt-3.5-turbo", 'model' : 'gpt-3.5-turbo',
"messages": payload_messages, 'messages' : payload_messages,
"temperature": temperature, 'temperature' : temperature,
"password": "", 'password' : ''
} }

6
g4f/Provider/Aichat.py
View File

@@ -13,11 +13,9 @@ class Aichat(BaseProvider):
def create_completion( def create_completion(
model: str, model: str,
messages: list[dict[str, str]], messages: list[dict[str, str]],
stream: bool, stream: bool, **kwargs: Any) -> CreateResult:
**kwargs: Any,
) -> CreateResult:
base = ""
base = ""
for message in messages: for message in messages:
base += "%s: %s\n" % (message["role"], message["content"]) base += "%s: %s\n" % (message["role"], message["content"])
base += "assistant:" base += "assistant:"

6
g4f/Provider/Ails.py
View File

@@ -9,7 +9,6 @@ import requests
from ..typing import SHA256, Any, CreateResult from ..typing import SHA256, Any, CreateResult
from .base_provider import BaseProvider from .base_provider import BaseProvider
class Ails(BaseProvider): class Ails(BaseProvider):
url: str = "https://ai.ls" url: str = "https://ai.ls"
working = True working = True
@@ -20,9 +19,8 @@ class Ails(BaseProvider):
def create_completion( def create_completion(
model: str, model: str,
messages: list[dict[str, str]], messages: list[dict[str, str]],
stream: bool, stream: bool, **kwargs: Any) -> CreateResult:
**kwargs: Any,
) -> CreateResult:
headers = { headers = {
"authority": "api.caipacity.com", "authority": "api.caipacity.com",
"accept": "*/*", "accept": "*/*",

4
g4f/Provider/Bard.py
View File

@@ -19,9 +19,7 @@ class Bard(AsyncProvider):
model: str, model: str,
messages: list[dict[str, str]], messages: list[dict[str, str]],
proxy: str = None, proxy: str = None,
cookies: dict = get_cookies(".google.com"), cookies: dict = get_cookies(".google.com"), **kwargs: Any,) -> str:
**kwargs: Any,
) -> str:
formatted = "\n".join( formatted = "\n".join(
["%s: %s" % (message["role"], message["content"]) for message in messages] ["%s: %s" % (message["role"], message["content"]) for message in messages]

15
g4f/Provider/Bing.py
View File

@@ -1,12 +1,6 @@
import asyncio import asyncio, aiohttp, json, os, random
import json
import os
import random
import aiohttp
import asyncio
from aiohttp import ClientSession from aiohttp import ClientSession
from ..typing import Any, AsyncGenerator, CreateResult, Union from ..typing import Any, AsyncGenerator, CreateResult, Union
from .base_provider import AsyncGeneratorProvider, get_cookies from .base_provider import AsyncGeneratorProvider, get_cookies
@@ -15,15 +9,14 @@ class Bing(AsyncGeneratorProvider):
needs_auth = True needs_auth = True
working = True working = True
supports_gpt_4 = True supports_gpt_4 = True
supports_stream=True supports_stream = True
@staticmethod @staticmethod
def create_async_generator( def create_async_generator(
model: str, model: str,
messages: list[dict[str, str]], messages: list[dict[str, str]],
cookies: dict = get_cookies(".bing.com"), cookies: dict = get_cookies(".bing.com"), **kwargs) -> AsyncGenerator:
**kwargs
) -> AsyncGenerator:
if len(messages) < 2: if len(messages) < 2:
prompt = messages[0]["content"] prompt = messages[0]["content"]
context = None context = None

58
g4f/Provider/ChatgptAi.py
View File

@@ -1,13 +1,11 @@
import re import re, requests
import requests
from ..typing import Any, CreateResult from ..typing import Any, CreateResult
from .base_provider import BaseProvider from .base_provider import BaseProvider
class ChatgptAi(BaseProvider): class ChatgptAi(BaseProvider):
url = "https://chatgpt.ai/gpt-4/" url: str = "https://chatgpt.ai/gpt-4/"
working = True working = True
supports_gpt_4 = True supports_gpt_4 = True
@@ -15,9 +13,8 @@ class ChatgptAi(BaseProvider):
def create_completion( def create_completion(
model: str, model: str,
messages: list[dict[str, str]], messages: list[dict[str, str]],
stream: bool, stream: bool, **kwargs: Any) -> CreateResult:
**kwargs: Any,
) -> CreateResult:
chat = "" chat = ""
for message in messages: for message in messages:
chat += "%s: %s\n" % (message["role"], message["content"]) chat += "%s: %s\n" % (message["role"], message["content"])
@@ -26,36 +23,35 @@ class ChatgptAi(BaseProvider):
response = requests.get("https://chatgpt.ai/") response = requests.get("https://chatgpt.ai/")
nonce, post_id, _, bot_id = re.findall( nonce, post_id, _, bot_id = re.findall(
r'data-nonce="(.*)"\n data-post-id="(.*)"\n data-url="(.*)"\n data-bot-id="(.*)"\n data-width', r'data-nonce="(.*)"\n data-post-id="(.*)"\n data-url="(.*)"\n data-bot-id="(.*)"\n data-width',
response.text, response.text)[0]
)[0]
headers = { headers = {
"authority": "chatgpt.ai", "authority" : "chatgpt.ai",
"accept": "*/*", "accept" : "*/*",
"accept-language": "en,fr-FR;q=0.9,fr;q=0.8,es-ES;q=0.7,es;q=0.6,en-US;q=0.5,am;q=0.4,de;q=0.3", "accept-language" : "en,fr-FR;q=0.9,fr;q=0.8,es-ES;q=0.7,es;q=0.6,en-US;q=0.5,am;q=0.4,de;q=0.3",
"cache-control": "no-cache", "cache-control" : "no-cache",
"origin": "https://chatgpt.ai", "origin" : "https://chatgpt.ai",
"pragma": "no-cache", "pragma" : "no-cache",
"referer": "https://chatgpt.ai/gpt-4/", "referer" : "https://chatgpt.ai/gpt-4/",
"sec-ch-ua": '"Not.A/Brand";v="8", "Chromium";v="114", "Google Chrome";v="114"', "sec-ch-ua" : '"Not.A/Brand";v="8", "Chromium";v="114", "Google Chrome";v="114"',
"sec-ch-ua-mobile": "?0", "sec-ch-ua-mobile" : "?0",
"sec-ch-ua-platform": '"Windows"', "sec-ch-ua-platform" : '"Windows"',
"sec-fetch-dest": "empty", "sec-fetch-dest" : "empty",
"sec-fetch-mode": "cors", "sec-fetch-mode" : "cors",
"sec-fetch-site": "same-origin", "sec-fetch-site" : "same-origin",
"user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/114.0.0.0 Safari/537.36", "user-agent" : "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/114.0.0.0 Safari/537.36",
} }
data = { data = {
"_wpnonce": nonce, "_wpnonce" : nonce,
"post_id": post_id, "post_id" : post_id,
"url": "https://chatgpt.ai/gpt-4", "url" : "https://chatgpt.ai/gpt-4",
"action": "wpaicg_chat_shortcode_message", "action" : "wpaicg_chat_shortcode_message",
"message": chat, "message" : chat,
"bot_id": bot_id, "bot_id" : bot_id,
} }
response = requests.post( response = requests.post(
"https://chatgpt.ai/wp-admin/admin-ajax.php", headers=headers, data=data "https://chatgpt.ai/wp-admin/admin-ajax.php", headers=headers, data=data)
)
response.raise_for_status() response.raise_for_status()
yield response.json()["data"] yield response.json()["data"]

114
g4f/Provider/ChatgptLogin.py
View File

@@ -1,8 +1,4 @@
import base64 import base64, os, re, requests
import os
import re
import requests
from ..typing import Any, CreateResult from ..typing import Any, CreateResult
from .base_provider import BaseProvider from .base_provider import BaseProvider
@@ -17,53 +13,50 @@ class ChatgptLogin(BaseProvider):
def create_completion( def create_completion(
model: str, model: str,
messages: list[dict[str, str]], messages: list[dict[str, str]],
stream: bool, stream: bool, **kwargs: Any) -> CreateResult:
**kwargs: Any,
) -> CreateResult:
headers = { headers = {
"authority": "chatgptlogin.ac", "authority" : "chatgptlogin.ac",
"accept": "*/*", "accept" : "*/*",
"accept-language": "en,fr-FR;q=0.9,fr;q=0.8,es-ES;q=0.7,es;q=0.6,en-US;q=0.5,am;q=0.4,de;q=0.3", "accept-language" : "en,fr-FR;q=0.9,fr;q=0.8,es-ES;q=0.7,es;q=0.6,en-US;q=0.5,am;q=0.4,de;q=0.3",
"content-type": "application/json", "content-type" : "application/json",
"origin": "https://opchatgpts.net", "origin" : "https://opchatgpts.net",
"referer": "https://opchatgpts.net/chatgpt-free-use/", "referer" : "https://opchatgpts.net/chatgpt-free-use/",
"sec-ch-ua": '"Chromium";v="116", "Not)A;Brand";v="24", "Google Chrome";v="116"', "sec-ch-ua" : '"Chromium";v="116", "Not)A;Brand";v="24", "Google Chrome";v="116"',
"sec-ch-ua-mobile": "?0", "sec-ch-ua-mobile" : "?0",
"sec-ch-ua-platform": '"Windows"', "sec-ch-ua-platform" : '"Windows"',
"sec-fetch-dest": "empty", "sec-fetch-dest" : "empty",
"sec-fetch-mode": "cors", "sec-fetch-mode" : "cors",
"sec-fetch-site": "same-origin", "sec-fetch-site" : "same-origin",
"user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/116.0.0.0 Safari/537.36", "user-agent" : "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/116.0.0.0 Safari/537.36",
"x-wp-nonce": _get_nonce(), "x-wp-nonce" : _get_nonce(),
} }
conversation = _transform(messages) conversation = _transform(messages)
json_data = { json_data = {
"env": "chatbot", "env" : "chatbot",
"session": "N/A", "session" : "N/A",
"prompt": "Converse as if you were an AI assistant. Be friendly, creative.", "prompt" : "Converse as if you were an AI assistant. Be friendly, creative.",
"context": "Converse as if you were an AI assistant. Be friendly, creative.", "context" : "Converse as if you were an AI assistant. Be friendly, creative.",
"messages": conversation, "messages" : conversation,
"newMessage": messages[-1]["content"], "newMessage" : messages[-1]["content"],
"userName": '<div class="mwai-name-text">User:</div>', "userName" : '<div class="mwai-name-text">User:</div>',
"aiName": '<div class="mwai-name-text">AI:</div>', "aiName" : '<div class="mwai-name-text">AI:</div>',
"model": "gpt-3.5-turbo", "model" : "gpt-3.5-turbo",
"temperature": kwargs.get("temperature", 0.8), "temperature" : kwargs.get("temperature", 0.8),
"maxTokens": 1024, "maxTokens" : 1024,
"maxResults": 1, "maxResults" : 1,
"apiKey": "", "apiKey" : "",
"service": "openai", "service" : "openai",
"embeddingsIndex": "", "embeddingsIndex": "",
"stop": "", "stop" : "",
"clientId": os.urandom(6).hex(), "clientId" : os.urandom(6).hex()
} }
response = requests.post( response = requests.post("https://opchatgpts.net/wp-json/ai-chatbot/v1/chat",
"https://opchatgpts.net/wp-json/ai-chatbot/v1/chat", headers=headers, json=json_data)
headers=headers,
json=json_data,
)
response.raise_for_status() response.raise_for_status()
yield response.json()["reply"] yield response.json()["reply"]
@@ -81,18 +74,15 @@ class ChatgptLogin(BaseProvider):
def _get_nonce() -> str: def _get_nonce() -> str:
res = requests.get( res = requests.get("https://opchatgpts.net/chatgpt-free-use/",
"https://opchatgpts.net/chatgpt-free-use/", headers = {
headers={ "Referer" : "https://opchatgpts.net/chatgpt-free-use/",
"Referer": "https://opchatgpts.net/chatgpt-free-use/", "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/114.0.0.0 Safari/537.36"})
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/114.0.0.0 Safari/537.36",
},
)
result = re.search( result = re.search(
r'class="mwai-chat mwai-chatgpt">.*<span>Send</span></button></div></div></div> <script defer src="(.*?)">', r'class="mwai-chat mwai-chatgpt">.*<span>Send</span></button></div></div></div> <script defer src="(.*?)">',
res.text, res.text)
)
if result is None: if result is None:
return "" return ""
@@ -106,11 +96,11 @@ def _get_nonce() -> str:
def _transform(messages: list[dict[str, str]]) -> list[dict[str, Any]]: def _transform(messages: list[dict[str, str]]) -> list[dict[str, Any]]:
return [ return [
{ {
"id": os.urandom(6).hex(), "id" : os.urandom(6).hex(),
"role": message["role"], "role" : message["role"],
"content": message["content"], "content": message["content"],
"who": "AI: " if message["role"] == "assistant" else "User: ", "who" : "AI: " if message["role"] == "assistant" else "User: ",
"html": _html_encode(message["content"]), "html" : _html_encode(message["content"]),
} }
for message in messages for message in messages
] ]
@@ -118,14 +108,14 @@ def _transform(messages: list[dict[str, str]]) -> list[dict[str, Any]]:
def _html_encode(string: str) -> str: def _html_encode(string: str) -> str:
table = { table = {
'"': "&quot;", '"' : "&quot;",
"'": "&#39;", "'" : "&#39;",
"&": "&amp;", "&" : "&amp;",
">": "&gt;", ">" : "&gt;",
"<": "&lt;", "<" : "&lt;",
"\n": "<br>", "\n": "<br>",
"\t": "&nbsp;&nbsp;&nbsp;&nbsp;", "\t": "&nbsp;&nbsp;&nbsp;&nbsp;",
" ": "&nbsp;", " " : "&nbsp;",
} }
for key in table: for key in table:

17
g4f/Provider/DeepAi.py
View File

@@ -1,14 +1,11 @@
import json import json, js2py, requests
import js2py
import requests
from ..typing import Any, CreateResult from ..typing import Any, CreateResult
from .base_provider import BaseProvider from .base_provider import BaseProvider
class DeepAi(BaseProvider): class DeepAi(BaseProvider):
url = "https://deepai.org" url: str = "https://deepai.org"
working = True working = True
supports_stream = True supports_stream = True
supports_gpt_35_turbo = True supports_gpt_35_turbo = True
@@ -17,10 +14,8 @@ class DeepAi(BaseProvider):
def create_completion( def create_completion(
model: str, model: str,
messages: list[dict[str, str]], messages: list[dict[str, str]],
stream: bool, stream: bool, **kwargs: Any) -> CreateResult:
**kwargs: Any,
) -> CreateResult:
url = "https://api.deepai.org/make_me_a_pizza"
token_js = """ token_js = """
var agent = 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/115.0.0.0 Safari/537.36' var agent = 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/115.0.0.0 Safari/537.36'
var a, b, c, d, e, h, f, l, g, k, m, n, r, x, C, E, N, F, T, O, P, w, D, G, Q, R, W, I, aa, fa, na, oa, ha, ba, X, ia, ja, ka, J, la, K, L, ca, S, U, M, ma, B, da, V, Y; var a, b, c, d, e, h, f, l, g, k, m, n, r, x, C, E, N, F, T, O, P, w, D, G, Q, R, W, I, aa, fa, na, oa, ha, ba, X, ia, ja, ka, J, la, K, L, ca, S, U, M, ma, B, da, V, Y;
@@ -54,7 +49,9 @@ f = function () {
"User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/115.0.0.0 Safari/537.36", "User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/115.0.0.0 Safari/537.36",
} }
response = requests.post(url, headers=headers, data=payload, stream=True) response = requests.post("https://api.deepai.org/make_me_a_pizza",
headers=headers, data=payload, stream=True)
for chunk in response.iter_content(chunk_size=None): for chunk in response.iter_content(chunk_size=None):
response.raise_for_status() response.raise_for_status()
yield chunk.decode() yield chunk.decode()

60
g4f/Provider/DfeHub.py
View File

@@ -1,8 +1,4 @@
import json import json, re, time , requests
import re
import time
import requests
from ..typing import Any, CreateResult from ..typing import Any, CreateResult
from .base_provider import BaseProvider from .base_provider import BaseProvider
@@ -17,41 +13,37 @@ class DfeHub(BaseProvider):
def create_completion( def create_completion(
model: str, model: str,
messages: list[dict[str, str]], messages: list[dict[str, str]],
stream: bool, stream: bool, **kwargs: Any) -> CreateResult:
**kwargs: Any,
) -> CreateResult:
headers = { headers = {
"authority": "chat.dfehub.com", "authority" : "chat.dfehub.com",
"accept": "*/*", "accept" : "*/*",
"accept-language": "en,fr-FR;q=0.9,fr;q=0.8,es-ES;q=0.7,es;q=0.6,en-US;q=0.5,am;q=0.4,de;q=0.3", "accept-language" : "en,fr-FR;q=0.9,fr;q=0.8,es-ES;q=0.7,es;q=0.6,en-US;q=0.5,am;q=0.4,de;q=0.3",
"content-type": "application/json", "content-type" : "application/json",
"origin": "https://chat.dfehub.com", "origin" : "https://chat.dfehub.com",
"referer": "https://chat.dfehub.com/", "referer" : "https://chat.dfehub.com/",
"sec-ch-ua": '"Not.A/Brand";v="8", "Chromium";v="114", "Google Chrome";v="114"', "sec-ch-ua" : '"Not.A/Brand";v="8", "Chromium";v="114", "Google Chrome";v="114"',
"sec-ch-ua-mobile": "?0", "sec-ch-ua-mobile" : "?0",
"sec-ch-ua-platform": '"macOS"', "sec-ch-ua-platform": '"macOS"',
"sec-fetch-dest": "empty", "sec-fetch-dest" : "empty",
"sec-fetch-mode": "cors", "sec-fetch-mode" : "cors",
"sec-fetch-site": "same-origin", "sec-fetch-site" : "same-origin",
"user-agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/114.0.0.0 Safari/537.36", "user-agent" : "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/114.0.0.0 Safari/537.36",
"x-requested-with": "XMLHttpRequest", "x-requested-with" : "XMLHttpRequest",
} }
json_data = { json_data = {
"messages": messages, "messages" : messages,
"model": "gpt-3.5-turbo", "model" : "gpt-3.5-turbo",
"temperature": kwargs.get("temperature", 0.5), "temperature" : kwargs.get("temperature", 0.5),
"presence_penalty": kwargs.get("presence_penalty", 0), "presence_penalty" : kwargs.get("presence_penalty", 0),
"frequency_penalty": kwargs.get("frequency_penalty", 0), "frequency_penalty" : kwargs.get("frequency_penalty", 0),
"top_p": kwargs.get("top_p", 1), "top_p" : kwargs.get("top_p", 1),
"stream": True, "stream" : True
} }
response = requests.post(
"https://chat.dfehub.com/api/openai/v1/chat/completions", response = requests.post("https://chat.dfehub.com/api/openai/v1/chat/completions",
headers=headers, headers=headers, json=json_data, timeout=3)
json=json_data,
timeout=3
)
for chunk in response.iter_lines(): for chunk in response.iter_lines():
if b"detail" in chunk: if b"detail" in chunk:

74
g4f/Provider/EasyChat.py
View File

@@ -1,13 +1,11 @@
import json import json, requests, random
import requests
from ..typing import Any, CreateResult from ..typing import Any, CreateResult
from .base_provider import BaseProvider from .base_provider import BaseProvider
class EasyChat(BaseProvider): class EasyChat(BaseProvider):
url = "https://free.easychat.work" url: str = "https://free.easychat.work"
supports_stream = True supports_stream = True
supports_gpt_35_turbo = True supports_gpt_35_turbo = True
working = True working = True
@@ -16,9 +14,8 @@ class EasyChat(BaseProvider):
def create_completion( def create_completion(
model: str, model: str,
messages: list[dict[str, str]], messages: list[dict[str, str]],
stream: bool, stream: bool, **kwargs: Any) -> CreateResult:
**kwargs: Any,
) -> CreateResult:
active_servers = [ active_servers = [
"https://chat10.fastgpt.me", "https://chat10.fastgpt.me",
"https://chat9.fastgpt.me", "https://chat9.fastgpt.me",
@@ -28,59 +25,62 @@ class EasyChat(BaseProvider):
"https://chat4.fastgpt.me", "https://chat4.fastgpt.me",
"https://gxos1h1ddt.fastgpt.me" "https://gxos1h1ddt.fastgpt.me"
] ]
server = active_servers[kwargs.get("active_server", 0)]
server = active_servers[kwargs.get("active_server", random.randint(0, 5))]
headers = { headers = {
"authority": f"{server}".replace("https://", ""), "authority" : f"{server}".replace("https://", ""),
"accept": "text/event-stream", "accept" : "text/event-stream",
"accept-language": "en,fr-FR;q=0.9,fr;q=0.8,es-ES;q=0.7,es;q=0.6,en-US;q=0.5,am;q=0.4,de;q=0.3,fa=0.2", "accept-language" : "en,fr-FR;q=0.9,fr;q=0.8,es-ES;q=0.7,es;q=0.6,en-US;q=0.5,am;q=0.4,de;q=0.3,fa=0.2",
"content-type": "application/json", "content-type" : "application/json",
"origin": f"{server}", "origin" : f"{server}",
"referer": f"{server}/", "referer" : f"{server}/",
"x-requested-with": "XMLHttpRequest", "x-requested-with" : "XMLHttpRequest",
'plugins': '0', 'plugins' : '0',
'sec-ch-ua': '"Chromium";v="116", "Not)A;Brand";v="24", "Google Chrome";v="116"', 'sec-ch-ua' : '"Chromium";v="116", "Not)A;Brand";v="24", "Google Chrome";v="116"',
'sec-ch-ua-mobile': '?0', 'sec-ch-ua-mobile' : '?0',
'sec-ch-ua-platform': '"Windows"', 'sec-ch-ua-platform': '"Windows"',
'sec-fetch-dest': 'empty', 'sec-fetch-dest' : 'empty',
'sec-fetch-mode': 'cors', 'sec-fetch-mode' : 'cors',
'sec-fetch-site': 'same-origin', 'sec-fetch-site' : 'same-origin',
'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/116.0.0.0 Safari/537.36', 'user-agent' : 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/116.0.0.0 Safari/537.36',
'usesearch': 'false', 'usesearch' : 'false',
'x-requested-with': 'XMLHttpRequest' 'x-requested-with' : 'XMLHttpRequest'
} }
json_data = { json_data = {
"messages": messages, "messages" : messages,
"stream": stream, "stream" : stream,
"model": model, "model" : model,
"temperature": kwargs.get("temperature", 0.5), "temperature" : kwargs.get("temperature", 0.5),
"presence_penalty": kwargs.get("presence_penalty", 0), "presence_penalty" : kwargs.get("presence_penalty", 0),
"frequency_penalty": kwargs.get("frequency_penalty", 0), "frequency_penalty" : kwargs.get("frequency_penalty", 0),
"top_p": kwargs.get("top_p", 1), "top_p" : kwargs.get("top_p", 1)
} }
session = requests.Session() session = requests.Session()
# init cookies from server # init cookies from server
session.get(f"{server}/") session.get(f"{server}/")
response = session.post( response = session.post(f"{server}/api/openai/v1/chat/completions",
f"{server}/api/openai/v1/chat/completions", headers=headers, json=json_data, stream=stream)
headers=headers,
json=json_data,
stream=stream,
)
if response.status_code == 200: if response.status_code == 200:
if stream == False: if stream == False:
json_data = response.json() json_data = response.json()
if "choices" in json_data: if "choices" in json_data:
yield json_data["choices"][0]["message"]["content"] yield json_data["choices"][0]["message"]["content"]
else: else:
raise Exception("No response from server") raise Exception("No response from server")
else: else:
for chunk in response.iter_lines(): for chunk in response.iter_lines():
if b"content" in chunk: if b"content" in chunk:
splitData = chunk.decode().split("data:") splitData = chunk.decode().split("data:")
if len(splitData) > 1: if len(splitData) > 1:
yield json.loads(splitData[1])["choices"][0]["delta"]["content"] yield json.loads(splitData[1])["choices"][0]["delta"]["content"]
else: else:

54
g4f/Provider/Equing.py
View File

@@ -1,6 +1,6 @@
import requests, json import requests, json
from abc import ABC, abstractmethod
from abc import ABC, abstractmethod
from ..typing import Any, CreateResult from ..typing import Any, CreateResult
@@ -17,42 +17,42 @@ class Equing(ABC):
def create_completion( def create_completion(
model: str, model: str,
messages: list[dict[str, str]], messages: list[dict[str, str]],
stream: bool, stream: bool, **kwargs: Any) -> CreateResult:
**kwargs: Any) -> CreateResult:
headers = { headers = {
'authority': 'next.eqing.tech', 'authority' : 'next.eqing.tech',
'accept': 'text/event-stream', 'accept' : 'text/event-stream',
'accept-language': 'en,fr-FR;q=0.9,fr;q=0.8,es-ES;q=0.7,es;q=0.6,en-US;q=0.5,am;q=0.4,de;q=0.3', 'accept-language' : 'en,fr-FR;q=0.9,fr;q=0.8,es-ES;q=0.7,es;q=0.6,en-US;q=0.5,am;q=0.4,de;q=0.3',
'cache-control': 'no-cache', 'cache-control' : 'no-cache',
'content-type': 'application/json', 'content-type' : 'application/json',
'origin': 'https://next.eqing.tech', 'origin' : 'https://next.eqing.tech',
'plugins': '0', 'plugins' : '0',
'pragma': 'no-cache', 'pragma' : 'no-cache',
'referer': 'https://next.eqing.tech/', 'referer' : 'https://next.eqing.tech/',
'sec-ch-ua': '"Not/A)Brand";v="99", "Google Chrome";v="115", "Chromium";v="115"', 'sec-ch-ua' : '"Not/A)Brand";v="99", "Google Chrome";v="115", "Chromium";v="115"',
'sec-ch-ua-mobile': '?0', 'sec-ch-ua-mobile' : '?0',
'sec-ch-ua-platform': '"macOS"', 'sec-ch-ua-platform': '"macOS"',
'sec-fetch-dest': 'empty', 'sec-fetch-dest' : 'empty',
'sec-fetch-mode': 'cors', 'sec-fetch-mode' : 'cors',
'sec-fetch-site': 'same-origin', 'sec-fetch-site' : 'same-origin',
'user-agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/115.0.0.0 Safari/537.36', 'user-agent' : 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/115.0.0.0 Safari/537.36',
'usesearch': 'false', 'usesearch' : 'false',
'x-requested-with': 'XMLHttpRequest', 'x-requested-with' : 'XMLHttpRequest'
} }
json_data = { json_data = {
'messages': messages, 'messages' : messages,
'stream': stream, 'stream' : stream,
'model': model, 'model' : model,
'temperature': kwargs.get('temperature', 0.5), 'temperature' : kwargs.get('temperature', 0.5),
'presence_penalty': kwargs.get('presence_penalty', 0), 'presence_penalty' : kwargs.get('presence_penalty', 0),
'frequency_penalty': kwargs.get('frequency_penalty', 0), 'frequency_penalty' : kwargs.get('frequency_penalty', 0),
'top_p': kwargs.get('top_p', 1), 'top_p' : kwargs.get('top_p', 1),
} }
response = requests.post('https://next.eqing.tech/api/openai/v1/chat/completions', response = requests.post('https://next.eqing.tech/api/openai/v1/chat/completions',
headers=headers, json=json_data, stream=stream) headers=headers, json=json_data, stream=stream)
if not stream: if not stream:
yield response.json()["choices"][0]["message"]["content"] yield response.json()["choices"][0]["message"]["content"]
return return

52
g4f/Provider/FastGpt.py
View File

@@ -17,39 +17,37 @@ class FastGpt(ABC):
def create_completion( def create_completion(
model: str, model: str,
messages: list[dict[str, str]], messages: list[dict[str, str]],
stream: bool, stream: bool, **kwargs: Any) -> CreateResult:
**kwargs: Any) -> CreateResult:
headers = { headers = {
'authority': 'chat9.fastgpt.me', 'authority' : 'chat9.fastgpt.me',
'accept': 'text/event-stream', 'accept' : 'text/event-stream',
'accept-language': 'en,fr-FR;q=0.9,fr;q=0.8,es-ES;q=0.7,es;q=0.6,en-US;q=0.5,am;q=0.4,de;q=0.3', 'accept-language' : 'en,fr-FR;q=0.9,fr;q=0.8,es-ES;q=0.7,es;q=0.6,en-US;q=0.5,am;q=0.4,de;q=0.3',
'cache-control': 'no-cache', 'cache-control' : 'no-cache',
'content-type': 'application/json', 'content-type' : 'application/json',
# 'cookie': 'cf_clearance=idIAwtoSCn0uCzcWLGuD.KtiAJv9a1GsPduEOqIkyHU-1692278595-0-1-cb11fd7a.ab1546d4.ccf35fd7-0.2.1692278595; Hm_lvt_563fb31e93813a8a7094966df6671d3f=1691966491,1692278597; Hm_lpvt_563fb31e93813a8a7094966df6671d3f=1692278597', 'origin' : 'https://chat9.fastgpt.me',
'origin': 'https://chat9.fastgpt.me', 'plugins' : '0',
'plugins': '0', 'pragma' : 'no-cache',
'pragma': 'no-cache', 'referer' : 'https://chat9.fastgpt.me/',
'referer': 'https://chat9.fastgpt.me/', 'sec-ch-ua' : '"Not/A)Brand";v="99", "Google Chrome";v="115", "Chromium";v="115"',
'sec-ch-ua': '"Not/A)Brand";v="99", "Google Chrome";v="115", "Chromium";v="115"', 'sec-ch-ua-mobile' : '?0',
'sec-ch-ua-mobile': '?0',
'sec-ch-ua-platform': '"macOS"', 'sec-ch-ua-platform': '"macOS"',
'sec-fetch-dest': 'empty', 'sec-fetch-dest' : 'empty',
'sec-fetch-mode': 'cors', 'sec-fetch-mode' : 'cors',
'sec-fetch-site': 'same-origin', 'sec-fetch-site' : 'same-origin',
'user-agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/115.0.0.0 Safari/537.36', 'user-agent' : 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/115.0.0.0 Safari/537.36',
'usesearch': 'false', 'usesearch' : 'false',
'x-requested-with': 'XMLHttpRequest', 'x-requested-with' : 'XMLHttpRequest',
} }
json_data = { json_data = {
'messages': messages, 'messages' : messages,
'stream': stream, 'stream' : stream,
'model': model, 'model' : model,
'temperature': kwargs.get('temperature', 0.5), 'temperature' : kwargs.get('temperature', 0.5),
'presence_penalty': kwargs.get('presence_penalty', 0), 'presence_penalty' : kwargs.get('presence_penalty', 0),
'frequency_penalty': kwargs.get('frequency_penalty', 0), 'frequency_penalty' : kwargs.get('frequency_penalty', 0),
'top_p': kwargs.get('top_p', 1), 'top_p' : kwargs.get('top_p', 1),
} }
subdomain = random.choice([ subdomain = random.choice([

29
g4f/Provider/Forefront.py
View File

@@ -15,26 +15,23 @@ class Forefront(BaseProvider):
def create_completion( def create_completion(
model: str, model: str,
messages: list[dict[str, str]], messages: list[dict[str, str]],
stream: bool, stream: bool, **kwargs: Any) -> CreateResult:
**kwargs: Any,
) -> CreateResult:
json_data = { json_data = {
"text": messages[-1]["content"], "text" : messages[-1]["content"],
"action": "noauth", "action" : "noauth",
"id": "", "id" : "",
"parentId": "", "parentId" : "",
"workspaceId": "", "workspaceId" : "",
"messagePersona": "607e41fe-95be-497e-8e97-010a59b2e2c0", "messagePersona": "607e41fe-95be-497e-8e97-010a59b2e2c0",
"model": "gpt-4", "model" : "gpt-4",
"messages": messages[:-1] if len(messages) > 1 else [], "messages" : messages[:-1] if len(messages) > 1 else [],
"internetMode": "auto", "internetMode" : "auto",
} }
response = requests.post( response = requests.post("https://streaming.tenant-forefront-default.knative.chi.coreweave.com/free-chat",
"https://streaming.tenant-forefront-default.knative.chi.coreweave.com/free-chat", json=json_data, stream=True)
json=json_data,
stream=True,
)
response.raise_for_status() response.raise_for_status()
for token in response.iter_lines(): for token in response.iter_lines():
if b"delta" in token: if b"delta" in token:

83
g4f/Provider/GetGpt.py
View File

@@ -1,16 +1,12 @@
import json import os, json, uuid, requests
import os
import uuid
import requests
from Crypto.Cipher import AES from Crypto.Cipher import AES
from ..typing import Any, CreateResult from ..typing import Any, CreateResult
from .base_provider import BaseProvider from .base_provider import BaseProvider
class GetGpt(BaseProvider): class GetGpt(BaseProvider):
url = "https://chat.getgpt.world/" url = 'https://chat.getgpt.world/'
supports_stream = True supports_stream = True
working = True working = True
supports_gpt_35_turbo = True supports_gpt_35_turbo = True
@@ -19,69 +15,68 @@ class GetGpt(BaseProvider):
def create_completion( def create_completion(
model: str, model: str,
messages: list[dict[str, str]], messages: list[dict[str, str]],
stream: bool, stream: bool, **kwargs: Any) -> CreateResult:
**kwargs: Any,
) -> CreateResult:
headers = { headers = {
"Content-Type": "application/json", 'Content-Type' : 'application/json',
"Referer": "https://chat.getgpt.world/", 'Referer' : 'https://chat.getgpt.world/',
"user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/114.0.0.0 Safari/537.36", 'user-agent' : 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/114.0.0.0 Safari/537.36',
} }
data = json.dumps( data = json.dumps(
{ {
"messages": messages, 'messages' : messages,
"frequency_penalty": kwargs.get("frequency_penalty", 0), 'frequency_penalty' : kwargs.get('frequency_penalty', 0),
"max_tokens": kwargs.get("max_tokens", 4000), 'max_tokens' : kwargs.get('max_tokens', 4000),
"model": "gpt-3.5-turbo", 'model' : 'gpt-3.5-turbo',
"presence_penalty": kwargs.get("presence_penalty", 0), 'presence_penalty' : kwargs.get('presence_penalty', 0),
"temperature": kwargs.get("temperature", 1), 'temperature' : kwargs.get('temperature', 1),
"top_p": kwargs.get("top_p", 1), 'top_p' : kwargs.get('top_p', 1),
"stream": True, 'stream' : True,
"uuid": str(uuid.uuid4()), 'uuid' : str(uuid.uuid4())
} }
) )
res = requests.post( res = requests.post('https://chat.getgpt.world/api/chat/stream',
"https://chat.getgpt.world/api/chat/stream", headers=headers, json={'signature': _encrypt(data)}, stream=True)
headers=headers,
json={"signature": _encrypt(data)},
stream=True,
)
res.raise_for_status() res.raise_for_status()
for line in res.iter_lines(): for line in res.iter_lines():
if b"content" in line: if b'content' in line:
line_json = json.loads(line.decode("utf-8").split("data: ")[1]) line_json = json.loads(line.decode('utf-8').split('data: ')[1])
yield (line_json["choices"][0]["delta"]["content"]) yield (line_json['choices'][0]['delta']['content'])
@classmethod @classmethod
@property @property
def params(cls): def params(cls):
params = [ params = [
("model", "str"), ('model', 'str'),
("messages", "list[dict[str, str]]"), ('messages', 'list[dict[str, str]]'),
("stream", "bool"), ('stream', 'bool'),
("temperature", "float"), ('temperature', 'float'),
("presence_penalty", "int"), ('presence_penalty', 'int'),
("frequency_penalty", "int"), ('frequency_penalty', 'int'),
("top_p", "int"), ('top_p', 'int'),
("max_tokens", "int"), ('max_tokens', 'int'),
] ]
param = ", ".join([": ".join(p) for p in params]) param = ', '.join([': '.join(p) for p in params])
return f"g4f.provider.{cls.__name__} supports: ({param})" return f'g4f.provider.{cls.__name__} supports: ({param})'
def _encrypt(e: str): def _encrypt(e: str):
t = os.urandom(8).hex().encode("utf-8") t = os.urandom(8).hex().encode('utf-8')
n = os.urandom(8).hex().encode("utf-8") n = os.urandom(8).hex().encode('utf-8')
r = e.encode("utf-8") r = e.encode('utf-8')
cipher = AES.new(t, AES.MODE_CBC, n) cipher = AES.new(t, AES.MODE_CBC, n)
ciphertext = cipher.encrypt(_pad_data(r)) ciphertext = cipher.encrypt(_pad_data(r))
return ciphertext.hex() + t.decode("utf-8") + n.decode("utf-8")
return ciphertext.hex() + t.decode('utf-8') + n.decode('utf-8')
def _pad_data(data: bytes) -> bytes: def _pad_data(data: bytes) -> bytes:
block_size = AES.block_size block_size = AES.block_size
padding_size = block_size - len(data) % block_size padding_size = block_size - len(data) % block_size
padding = bytes([padding_size] * padding_size) padding = bytes([padding_size] * padding_size)
return data + padding return data + padding

62
g4f/Provider/H2o.py
View File

@@ -1,7 +1,4 @@
import json import json, uuid, requests
import uuid
import requests
from ..typing import Any, CreateResult from ..typing import Any, CreateResult
from .base_provider import BaseProvider from .base_provider import BaseProvider
@@ -17,9 +14,8 @@ class H2o(BaseProvider):
def create_completion( def create_completion(
model: str, model: str,
messages: list[dict[str, str]], messages: list[dict[str, str]],
stream: bool, stream: bool, **kwargs: Any) -> CreateResult:
**kwargs: Any,
) -> CreateResult:
conversation = "" conversation = ""
for message in messages: for message in messages:
conversation += "%s: %s\n" % (message["role"], message["content"]) conversation += "%s: %s\n" % (message["role"], message["content"])
@@ -29,54 +25,48 @@ class H2o(BaseProvider):
headers = {"Referer": "https://gpt-gm.h2o.ai/r/jGfKSwU"} headers = {"Referer": "https://gpt-gm.h2o.ai/r/jGfKSwU"}
data = { data = {
"ethicsModalAccepted": "true", "ethicsModalAccepted" : "true",
"shareConversationsWithModelAuthors": "true", "shareConversationsWithModelAuthors": "true",
"ethicsModalAcceptedAt": "", "ethicsModalAcceptedAt" : "",
"activeModel": model, "activeModel" : model,
"searchEnabled": "true", "searchEnabled" : "true",
} }
session.post(
"https://gpt-gm.h2o.ai/settings", session.post("https://gpt-gm.h2o.ai/settings",
headers=headers, headers=headers, data=data)
data=data,
)
headers = {"Referer": "https://gpt-gm.h2o.ai/"} headers = {"Referer": "https://gpt-gm.h2o.ai/"}
data = {"model": model} data = {"model": model}
response = session.post( response = session.post("https://gpt-gm.h2o.ai/conversation",
"https://gpt-gm.h2o.ai/conversation", headers=headers, json=data).json()
headers=headers,
json=data,
).json()
if "conversationId" not in response: if "conversationId" not in response:
return return
data = { data = {
"inputs": conversation, "inputs": conversation,
"parameters": { "parameters": {
"temperature": kwargs.get("temperature", 0.4), "temperature" : kwargs.get("temperature", 0.4),
"truncate": kwargs.get("truncate", 2048), "truncate" : kwargs.get("truncate", 2048),
"max_new_tokens": kwargs.get("max_new_tokens", 1024), "max_new_tokens" : kwargs.get("max_new_tokens", 1024),
"do_sample": kwargs.get("do_sample", True), "do_sample" : kwargs.get("do_sample", True),
"repetition_penalty": kwargs.get("repetition_penalty", 1.2), "repetition_penalty": kwargs.get("repetition_penalty", 1.2),
"return_full_text": kwargs.get("return_full_text", False), "return_full_text" : kwargs.get("return_full_text", False),
}, },
"stream": True, "stream" : True,
"options": { "options": {
"id": kwargs.get("id", str(uuid.uuid4())), "id" : kwargs.get("id", str(uuid.uuid4())),
"response_id": kwargs.get("response_id", str(uuid.uuid4())), "response_id" : kwargs.get("response_id", str(uuid.uuid4())),
"is_retry": False, "is_retry" : False,
"use_cache": False, "use_cache" : False,
"web_search_id": "", "web_search_id": "",
}, },
} }
response = session.post( response = session.post(f"https://gpt-gm.h2o.ai/conversation/{response['conversationId']}",
f"https://gpt-gm.h2o.ai/conversation/{response['conversationId']}", headers=headers, json=data)
headers=headers,
json=data,
)
response.raise_for_status() response.raise_for_status()
response.encoding = "utf-8" response.encoding = "utf-8"
generated_text = response.text.replace("\n", "").split("data:") generated_text = response.text.replace("\n", "").split("data:")

8
g4f/Provider/Hugchat.py
View File

@@ -20,12 +20,10 @@ class Hugchat(BaseProvider):
messages: list[dict[str, str]], messages: list[dict[str, str]],
stream: bool = False, stream: bool = False,
proxy: str = None, proxy: str = None,
cookies: str = get_cookies(".huggingface.co"), cookies: str = get_cookies(".huggingface.co"), **kwargs) -> CreateResult:
**kwargs
) -> CreateResult:
bot = ChatBot( bot = ChatBot(
cookies=cookies cookies=cookies)
)
if proxy and "://" not in proxy: if proxy and "://" not in proxy:
proxy = f"http://{proxy}" proxy = f"http://{proxy}"

41
g4f/Provider/Liaobots.py
View File

@@ -1,13 +1,11 @@
import uuid import uuid, requests
import requests
from ..typing import Any, CreateResult from ..typing import Any, CreateResult
from .base_provider import BaseProvider from .base_provider import BaseProvider
class Liaobots(BaseProvider): class Liaobots(BaseProvider):
url = "https://liaobots.com" url: str = "https://liaobots.com"
supports_stream = True supports_stream = True
needs_auth = True needs_auth = True
supports_gpt_35_turbo = True supports_gpt_35_turbo = True
@@ -17,17 +15,17 @@ class Liaobots(BaseProvider):
def create_completion( def create_completion(
model: str, model: str,
messages: list[dict[str, str]], messages: list[dict[str, str]],
stream: bool, stream: bool, **kwargs: Any) -> CreateResult:
**kwargs: Any,
) -> CreateResult:
headers = { headers = {
"authority": "liaobots.com", "authority" : "liaobots.com",
"content-type": "application/json", "content-type" : "application/json",
"origin": "https://liaobots.com", "origin" : "https://liaobots.com",
"referer": "https://liaobots.com/", "referer" : "https://liaobots.com/",
"user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/112.0.0.0 Safari/537.36", "user-agent" : "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/112.0.0.0 Safari/537.36",
"x-auth-code": str(kwargs.get("auth")), "x-auth-code" : str(kwargs.get("auth")),
} }
models = { models = {
"gpt-4": { "gpt-4": {
"id": "gpt-4", "id": "gpt-4",
@@ -44,18 +42,15 @@ class Liaobots(BaseProvider):
} }
json_data = { json_data = {
"conversationId": str(uuid.uuid4()), "conversationId": str(uuid.uuid4()),
"model": models[model], "model" : models[model],
"messages": messages, "messages" : messages,
"key": "", "key" : "",
"prompt": "You are ChatGPT, a large language model trained by OpenAI. Follow the user's instructions carefully. Respond using markdown.", "prompt" : "You are ChatGPT, a large language model trained by OpenAI. Follow the user's instructions carefully. Respond using markdown.",
} }
response = requests.post( response = requests.post("https://liaobots.com/api/chat",
"https://liaobots.com/api/chat", headers=headers, json=json_data, stream=True)
headers=headers,
json=json_data,
stream=True,
)
response.raise_for_status() response.raise_for_status()
for token in response.iter_content(chunk_size=2046): for token in response.iter_content(chunk_size=2046):
yield token.decode("utf-8") yield token.decode("utf-8")

38
g4f/Provider/Lockchat.py
View File

@@ -1,13 +1,11 @@
import json import json, requests
import requests
from ..typing import Any, CreateResult from ..typing import Any, CreateResult
from .base_provider import BaseProvider from .base_provider import BaseProvider
class Lockchat(BaseProvider): class Lockchat(BaseProvider):
url = "http://supertest.lockchat.app" url: str = "http://supertest.lockchat.app"
supports_stream = True supports_stream = True
supports_gpt_35_turbo = True supports_gpt_35_turbo = True
supports_gpt_4 = True supports_gpt_4 = True
@@ -16,37 +14,33 @@ class Lockchat(BaseProvider):
def create_completion( def create_completion(
model: str, model: str,
messages: list[dict[str, str]], messages: list[dict[str, str]],
stream: bool, stream: bool, **kwargs: Any) -> CreateResult:
**kwargs: Any,
) -> CreateResult:
temperature = float(kwargs.get("temperature", 0.7)) temperature = float(kwargs.get("temperature", 0.7))
payload = { payload = {
"temperature": temperature, "temperature": temperature,
"messages": messages, "messages" : messages,
"model": model, "model" : model,
"stream": True, "stream" : True,
} }
headers = { headers = {
"user-agent": "ChatX/39 CFNetwork/1408.0.4 Darwin/22.5.0", "user-agent": "ChatX/39 CFNetwork/1408.0.4 Darwin/22.5.0",
} }
response = requests.post( response = requests.post("http://supertest.lockchat.app/v1/chat/completions",
"http://supertest.lockchat.app/v1/chat/completions", json=payload, headers=headers, stream=True)
json=payload,
headers=headers,
stream=True,
)
response.raise_for_status() response.raise_for_status()
for token in response.iter_lines(): for token in response.iter_lines():
if b"The model: `gpt-4` does not exist" in token: if b"The model: `gpt-4` does not exist" in token:
print("error, retrying...") print("error, retrying...")
Lockchat.create_completion( Lockchat.create_completion(
model=model, model = model,
messages=messages, messages = messages,
stream=stream, stream = stream,
temperature=temperature, temperature = temperature,
**kwargs, **kwargs)
)
if b"content" in token: if b"content" in token:
token = json.loads(token.decode("utf-8").split("data: ")[1]) token = json.loads(token.decode("utf-8").split("data: ")[1])
token = token["choices"][0]["delta"].get("content") token = token["choices"][0]["delta"].get("content")

62
g4f/Provider/Opchatgpts.py
View File

@@ -13,25 +13,22 @@ class Opchatgpts(BaseProvider):
def create_completion( def create_completion(
model: str, model: str,
messages: list[dict[str, str]], messages: list[dict[str, str]],
stream: bool, stream: bool, **kwargs: Any) -> CreateResult:
**kwargs: Any,
) -> CreateResult:
temperature = kwargs.get("temperature", 0.8) temperature = kwargs.get("temperature", 0.8)
max_tokens = kwargs.get("max_tokens", 1024) max_tokens = kwargs.get("max_tokens", 1024)
system_prompt = kwargs.get( system_prompt = kwargs.get(
"system_prompt", "system_prompt",
"Converse as if you were an AI assistant. Be friendly, creative.", "Converse as if you were an AI assistant. Be friendly, creative.")
)
payload = _create_payload( payload = _create_payload(
messages=messages, messages = messages,
temperature=temperature, temperature = temperature,
max_tokens=max_tokens, max_tokens = max_tokens,
system_prompt=system_prompt, system_prompt = system_prompt)
)
response = requests.post("https://opchatgpts.net/wp-json/ai-chatbot/v1/chat", json=payload)
response = requests.post(
"https://opchatgpts.net/wp-json/ai-chatbot/v1/chat", json=payload
)
response.raise_for_status() response.raise_for_status()
yield response.json()["reply"] yield response.json()["reply"]
@@ -39,24 +36,23 @@ class Opchatgpts(BaseProvider):
def _create_payload( def _create_payload(
messages: list[dict[str, str]], messages: list[dict[str, str]],
temperature: float, temperature: float,
max_tokens: int, max_tokens: int, system_prompt: str) -> dict:
system_prompt: str,
):
return { return {
"env": "chatbot", "env" : "chatbot",
"session": "N/A", "session" : "N/A",
"prompt": "\n", "prompt" : "\n",
"context": system_prompt, "context" : system_prompt,
"messages": messages, "messages" : messages,
"newMessage": messages[::-1][0]["content"], "newMessage" : messages[::-1][0]["content"],
"userName": '<div class="mwai-name-text">User:</div>', "userName" : '<div class="mwai-name-text">User:</div>',
"aiName": '<div class="mwai-name-text">AI:</div>', "aiName" : '<div class="mwai-name-text">AI:</div>',
"model": "gpt-3.5-turbo", "model" : "gpt-3.5-turbo",
"temperature": temperature, "temperature" : temperature,
"maxTokens": max_tokens, "maxTokens" : max_tokens,
"maxResults": 1, "maxResults" : 1,
"apiKey": "", "apiKey" : "",
"service": "openai", "service" : "openai",
"embeddingsIndex": "", "embeddingsIndex" : "",
"stop": "", "stop" : "",
} }

1
g4f/Provider/OpenaiChat.py
View File

@@ -3,6 +3,7 @@ try:
from revChatGPT.V1 import AsyncChatbot from revChatGPT.V1 import AsyncChatbot
except ImportError: except ImportError:
has_module = False has_module = False
from .base_provider import AsyncGeneratorProvider, get_cookies from .base_provider import AsyncGeneratorProvider, get_cookies
from ..typing import AsyncGenerator from ..typing import AsyncGenerator

5
g4f/Provider/Raycast.py
View File

@@ -1,12 +1,11 @@
import json import json, requests
import requests
from ..typing import Any, CreateResult from ..typing import Any, CreateResult
from .base_provider import BaseProvider from .base_provider import BaseProvider
class Raycast(BaseProvider): class Raycast(BaseProvider):
url = "https://raycast.com" url = "https://raycast.com"
# model = ['gpt-3.5-turbo', 'gpt-4']
supports_gpt_35_turbo = True supports_gpt_35_turbo = True
supports_gpt_4 = True supports_gpt_4 = True
supports_stream = True supports_stream = True

72
g4f/Provider/Theb.py
View File

@@ -1,5 +1,5 @@
import json,random,requests import json, random, requests
# from curl_cffi import requests
from ..typing import Any, CreateResult from ..typing import Any, CreateResult
from .base_provider import BaseProvider from .base_provider import BaseProvider
@@ -15,60 +15,58 @@ class Theb(BaseProvider):
def create_completion( def create_completion(
model: str, model: str,
messages: list[dict[str, str]], messages: list[dict[str, str]],
stream: bool, stream: bool, **kwargs: Any) -> CreateResult:
**kwargs: Any,
) -> CreateResult:
conversation = '' conversation = ''
for message in messages: for message in messages:
conversation += '%s: %s\n' % (message['role'], message['content']) conversation += '%s: %s\n' % (message['role'], message['content'])
conversation += 'assistant: ' conversation += 'assistant: '
auth = kwargs.get("auth", { auth = kwargs.get("auth", {
"bearer_token":"free", "bearer_token":"free",
"org_id":"theb", "org_id":"theb",
}) })
bearer_token = auth["bearer_token"] bearer_token = auth["bearer_token"]
org_id = auth["org_id"] org_id = auth["org_id"]
headers = { headers = {
'authority': 'beta.theb.ai', 'authority' : 'beta.theb.ai',
'accept': 'text/event-stream', 'accept' : 'text/event-stream',
'accept-language': 'id-ID,id;q=0.9,en-US;q=0.8,en;q=0.7', 'accept-language' : 'id-ID,id;q=0.9,en-US;q=0.8,en;q=0.7',
'authorization': 'Bearer '+bearer_token, 'authorization' : 'Bearer '+bearer_token,
'content-type': 'application/json', 'content-type' : 'application/json',
'origin': 'https://beta.theb.ai', 'origin' : 'https://beta.theb.ai',
'referer': 'https://beta.theb.ai/home', 'referer' : 'https://beta.theb.ai/home',
'sec-ch-ua': '"Chromium";v="116", "Not)A;Brand";v="24", "Google Chrome";v="116"', 'sec-ch-ua' : '"Chromium";v="116", "Not)A;Brand";v="24", "Google Chrome";v="116"',
'sec-ch-ua-mobile': '?0', 'sec-ch-ua-mobile' : '?0',
'sec-ch-ua-platform': '"Windows"', 'sec-ch-ua-platform': '"Windows"',
'sec-fetch-dest': 'empty', 'sec-fetch-dest' : 'empty',
'sec-fetch-mode': 'cors', 'sec-fetch-mode' : 'cors',
'sec-fetch-site': 'same-origin', 'sec-fetch-site' : 'same-origin',
'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/116.0.0.0 Safari/537.36', 'user-agent' : 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/116.0.0.0 Safari/537.36',
'x-ai-model': 'ee8d4f29cb7047f78cbe84313ed6ace8', 'x-ai-model' : 'ee8d4f29cb7047f78cbe84313ed6ace8',
} }
# generate 10 random number
# 0.1 - 0.9
req_rand = random.randint(100000000, 9999999999) req_rand = random.randint(100000000, 9999999999)
json_data: dict[str, Any] = { json_data: dict[str, Any] = {
"text": conversation, "text" : conversation,
"category": "04f58f64a4aa4191a957b47290fee864", "category" : "04f58f64a4aa4191a957b47290fee864",
"model": "ee8d4f29cb7047f78cbe84313ed6ace8", "model" : "ee8d4f29cb7047f78cbe84313ed6ace8",
"model_params": { "model_params": {
"system_prompt": "You are ChatGPT, a large language model trained by OpenAI, based on the GPT-3.5 architecture.\nKnowledge cutoff: 2021-09\nCurrent date: {{YYYY-MM-DD}}", "system_prompt" : "You are ChatGPT, a large language model trained by OpenAI, based on the GPT-3.5 architecture.\nKnowledge cutoff: 2021-09\nCurrent date: {{YYYY-MM-DD}}",
"temperature": kwargs.get("temperature", 1), "temperature" : kwargs.get("temperature", 1),
"top_p": kwargs.get("top_p", 1), "top_p" : kwargs.get("top_p", 1),
"frequency_penalty": kwargs.get("frequency_penalty", 0), "frequency_penalty" : kwargs.get("frequency_penalty", 0),
"presence_penalty": kwargs.get("presence_penalty", 0), "presence_penalty" : kwargs.get("presence_penalty", 0),
"long_term_memory": "auto" "long_term_memory" : "auto"
} }
} }
response = requests.post(
"https://beta.theb.ai/api/conversation?org_id="+org_id+"&req_rand="+str(req_rand), response = requests.post(f"https://beta.theb.ai/api/conversation?org_id={org_id}&req_rand={req_rand}",
headers=headers, headers=headers, json=json_data, stream=True)
json=json_data,
stream=True,
)
response.raise_for_status() response.raise_for_status()
content = "" content = ""
next_content = "" next_content = ""

43
g4f/Provider/V50.py
View File

@@ -1,8 +1,8 @@
import uuid, requests import uuid, requests
from ..typing import Any, CreateResult from ..typing import Any, CreateResult
from .base_provider import BaseProvider from .base_provider import BaseProvider
class V50(BaseProvider): class V50(BaseProvider):
url = 'https://p5.v50.ltd' url = 'https://p5.v50.ltd'
supports_gpt_35_turbo = True supports_gpt_35_turbo = True
@@ -14,38 +14,39 @@ class V50(BaseProvider):
def create_completion( def create_completion(
model: str, model: str,
messages: list[dict[str, str]], messages: list[dict[str, str]],
stream: bool, stream: bool, **kwargs: Any) -> CreateResult:
**kwargs: Any,
) -> CreateResult:
conversation = '' conversation = ''
for message in messages: for message in messages:
conversation += '%s: %s\n' % (message['role'], message['content']) conversation += '%s: %s\n' % (message['role'], message['content'])
conversation += 'assistant: ' conversation += 'assistant: '
payload = { payload = {
"prompt": conversation, "prompt" : conversation,
"options": {}, "options" : {},
"systemMessage": ".", "systemMessage" : ".",
"temperature": kwargs.get("temperature", 0.4), "temperature" : kwargs.get("temperature", 0.4),
"top_p": kwargs.get("top_p", 0.4), "top_p" : kwargs.get("top_p", 0.4),
"model": model, "model" : model,
"user": str(uuid.uuid4()) "user" : str(uuid.uuid4())
} }
headers = { headers = {
'authority': 'p5.v50.ltd', 'authority' : 'p5.v50.ltd',
'accept': 'application/json, text/plain, */*', 'accept' : 'application/json, text/plain, */*',
'accept-language': 'id-ID,id;q=0.9,en-US;q=0.8,en;q=0.7', 'accept-language' : 'id-ID,id;q=0.9,en-US;q=0.8,en;q=0.7',
'content-type': 'application/json', 'content-type' : 'application/json',
'origin': 'https://p5.v50.ltd', 'origin' : 'https://p5.v50.ltd',
'referer': 'https://p5.v50.ltd/', 'referer' : 'https://p5.v50.ltd/',
'sec-ch-ua-platform': '"Windows"', 'sec-ch-ua-platform': '"Windows"',
'sec-fetch-dest': 'empty', 'sec-fetch-dest' : 'empty',
'sec-fetch-mode': 'cors', 'sec-fetch-mode' : 'cors',
'sec-fetch-site': 'same-origin', 'sec-fetch-site' : 'same-origin',
'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/116.0.0.0 Safari/537.36' 'user-agent' : 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/116.0.0.0 Safari/537.36'
} }
response = requests.post("https://p5.v50.ltd/api/chat-process", response = requests.post("https://p5.v50.ltd/api/chat-process",
json=payload, headers=headers, proxies=kwargs['proxy'] if 'proxy' in kwargs else {}) json=payload, headers=headers, proxies=kwargs['proxy'] if 'proxy' in kwargs else {})
if "https://fk1.v50.ltd" not in response.text: if "https://fk1.v50.ltd" not in response.text:
yield response.text yield response.text

15
g4f/Provider/Vercel.py
View File

@@ -1,10 +1,6 @@
import base64 import base64, json, uuid, quickjs
import json
import uuid
import quickjs
from curl_cffi import requests from curl_cffi import requests
from ..typing import Any, CreateResult, TypedDict from ..typing import Any, CreateResult, TypedDict
from .base_provider import BaseProvider from .base_provider import BaseProvider
@@ -18,9 +14,8 @@ class Vercel(BaseProvider):
def create_completion( def create_completion(
model: str, model: str,
messages: list[dict[str, str]], messages: list[dict[str, str]],
stream: bool, stream: bool, **kwargs: Any) -> CreateResult:
**kwargs: Any,
) -> CreateResult:
if model in ["gpt-3.5-turbo", "gpt-4"]: if model in ["gpt-3.5-turbo", "gpt-4"]:
model = "openai:" + model model = "openai:" + model
yield _chat(model_id=model, messages=messages) yield _chat(model_id=model, messages=messages)
@@ -44,15 +39,13 @@ def _create_payload(model_id: str, messages: list[dict[str, str]]) -> dict[str,
"messages": messages, "messages": messages,
"playgroundId": str(uuid.uuid4()), "playgroundId": str(uuid.uuid4()),
"chatIndex": 0, "chatIndex": 0,
"model": model_id, "model": model_id} | default_params
} | default_params
def _create_header(session: requests.Session): def _create_header(session: requests.Session):
custom_encoding = _get_custom_encoding(session) custom_encoding = _get_custom_encoding(session)
return {"custom-encoding": custom_encoding} return {"custom-encoding": custom_encoding}
# based on https://github.com/ading2210/vercel-llm-api # based on https://github.com/ading2210/vercel-llm-api
def _get_custom_encoding(session: requests.Session): def _get_custom_encoding(session: requests.Session):
url = "https://sdk.vercel.ai/openai.jpeg" url = "https://sdk.vercel.ai/openai.jpeg"

71
g4f/Provider/Wewordle.py
View File

@@ -1,9 +1,4 @@
import json import json, random, string, time, requests
import random
import string
import time
import requests
from ..typing import Any, CreateResult from ..typing import Any, CreateResult
from .base_provider import BaseProvider from .base_provider import BaseProvider
@@ -19,51 +14,53 @@ class Wewordle(BaseProvider):
cls, cls,
model: str, model: str,
messages: list[dict[str, str]], messages: list[dict[str, str]],
stream: bool, stream: bool, **kwargs: Any) -> CreateResult:
**kwargs: Any,
) -> CreateResult:
# randomize user id and app id # randomize user id and app id
_user_id = "".join( _user_id = "".join(
random.choices(f"{string.ascii_lowercase}{string.digits}", k=16) random.choices(f"{string.ascii_lowercase}{string.digits}", k=16))
)
_app_id = "".join( _app_id = "".join(
random.choices(f"{string.ascii_lowercase}{string.digits}", k=31) random.choices(f"{string.ascii_lowercase}{string.digits}", k=31))
)
# make current date with format utc # make current date with format utc
_request_date = time.strftime("%Y-%m-%dT%H:%M:%S.000Z", time.gmtime()) _request_date = time.strftime("%Y-%m-%dT%H:%M:%S.000Z", time.gmtime())
headers = { headers = {
"accept": "*/*", "accept" : "*/*",
"pragma": "no-cache", "pragma" : "no-cache",
"Content-Type": "application/json", "Content-Type" : "application/json",
"Connection": "keep-alive" "Connection" : "keep-alive"
# user agent android client # user agent android client
# 'User-Agent': 'Dalvik/2.1.0 (Linux; U; Android 10; SM-G975F Build/QP1A.190711.020)', # 'User-Agent': 'Dalvik/2.1.0 (Linux; U; Android 10; SM-G975F Build/QP1A.190711.020)',
} }
data: dict[str, Any] = { data: dict[str, Any] = {
"user": _user_id, "user" : _user_id,
"messages": messages, "messages" : messages,
"subscriber": { "subscriber": {
"originalPurchaseDate": None, "originalPurchaseDate" : None,
"originalApplicationVersion": None, "originalApplicationVersion" : None,
"allPurchaseDatesMillis": {}, "allPurchaseDatesMillis" : {},
"entitlements": {"active": {}, "all": {}}, "entitlements" : {"active": {}, "all": {}},
"allPurchaseDates": {}, "allPurchaseDates" : {},
"allExpirationDatesMillis": {}, "allExpirationDatesMillis" : {},
"allExpirationDates": {}, "allExpirationDates" : {},
"originalAppUserId": f"$RCAnonymousID:{_app_id}", "originalAppUserId" : f"$RCAnonymousID:{_app_id}",
"latestExpirationDate": None, "latestExpirationDate" : None,
"requestDate": _request_date, "requestDate" : _request_date,
"latestExpirationDateMillis": None, "latestExpirationDateMillis" : None,
"nonSubscriptionTransactions": [], "nonSubscriptionTransactions" : [],
"originalPurchaseDateMillis": None, "originalPurchaseDateMillis" : None,
"managementURL": None, "managementURL" : None,
"allPurchasedProductIdentifiers": [], "allPurchasedProductIdentifiers": [],
"firstSeen": _request_date, "firstSeen" : _request_date,
"activeSubscriptions": [], "activeSubscriptions" : [],
}, }
} }
response = requests.post(f"{cls.url}gptapi/v1/android/turbo", headers=headers, data=json.dumps(data)) response = requests.post(f"{cls.url}gptapi/v1/android/turbo",
headers=headers, data=json.dumps(data))
response.raise_for_status() response.raise_for_status()
_json = response.json() _json = response.json()
if "message" in _json: if "message" in _json:

20
g4f/Provider/You.py
View File

@@ -1,9 +1,6 @@
import re import urllib.parse, json
import urllib.parse
import json
from curl_cffi import requests from curl_cffi import requests
from ..typing import Any, CreateResult from ..typing import Any, CreateResult
from .base_provider import BaseProvider from .base_provider import BaseProvider
@@ -17,17 +14,14 @@ class You(BaseProvider):
def create_completion( def create_completion(
model: str, model: str,
messages: list[dict[str, str]], messages: list[dict[str, str]],
stream: bool, stream: bool, **kwargs: Any) -> CreateResult:
**kwargs: Any,
) -> CreateResult:
url_param = _create_url_param(messages, kwargs.get("history", [])) url_param = _create_url_param(messages, kwargs.get("history", []))
headers = _create_header() headers = _create_header()
url = f"https://you.com/api/streamingSearch?{url_param}"
response = requests.get( response = requests.get(f"https://you.com/api/streamingSearch?{url_param}",
url, headers=headers, impersonate="chrome107")
headers=headers,
impersonate="chrome107",
)
response.raise_for_status() response.raise_for_status()
start = 'data: {"youChatToken": ' start = 'data: {"youChatToken": '

25
g4f/Provider/Yqcloud.py
View File

@@ -13,14 +13,14 @@ class Yqcloud(BaseProvider):
def create_completion( def create_completion(
model: str, model: str,
messages: list[dict[str, str]], messages: list[dict[str, str]],
stream: bool, stream: bool, **kwargs: Any) -> CreateResult:
**kwargs: Any,
) -> CreateResult:
headers = _create_header() headers = _create_header()
payload = _create_payload(messages) payload = _create_payload(messages)
url = "https://api.aichatos.cloud/api/generateStream" response = requests.post("https://api.aichatos.cloud/api/generateStream",
response = requests.post(url=url, headers=headers, json=payload) headers=headers, json=payload)
response.raise_for_status() response.raise_for_status()
response.encoding = 'utf-8' response.encoding = 'utf-8'
yield response.text yield response.text
@@ -28,9 +28,9 @@ class Yqcloud(BaseProvider):
def _create_header(): def _create_header():
return { return {
"accept": "application/json, text/plain, */*", "accept" : "application/json, text/plain, */*",
"content-type": "application/json", "content-type" : "application/json",
"origin": "https://chat9.yqcloud.top", "origin" : "https://chat9.yqcloud.top",
} }
@@ -39,10 +39,11 @@ def _create_payload(messages: list[dict[str, str]]):
for message in messages: for message in messages:
prompt += "%s: %s\n" % (message["role"], message["content"]) prompt += "%s: %s\n" % (message["role"], message["content"])
prompt += "assistant:" prompt += "assistant:"
return { return {
"prompt": prompt, "prompt" : prompt,
"network": True, "network" : True,
"system": "", "system" : "",
"withoutContext": False, "withoutContext": False,
"stream": False, "stream" : False,
} }

65
g4f/Provider/__init__.py
View File

@@ -4,7 +4,6 @@ from .Ails import Ails
from .AiService import AiService from .AiService import AiService
from .AItianhu import AItianhu from .AItianhu import AItianhu
from .Bard import Bard from .Bard import Bard
from .base_provider import BaseProvider
from .Bing import Bing from .Bing import Bing
from .ChatgptAi import ChatgptAi from .ChatgptAi import ChatgptAi
from .ChatgptLogin import ChatgptLogin from .ChatgptLogin import ChatgptLogin
@@ -30,36 +29,38 @@ from .FastGpt import FastGpt
from .V50 import V50 from .V50 import V50
from .Wuguokai import Wuguokai from .Wuguokai import Wuguokai
from .base_provider import BaseProvider
__all__ = [ __all__ = [
"BaseProvider", 'BaseProvider',
"Acytoo", 'Acytoo',
"Aichat", 'Aichat',
"Ails", 'Ails',
"AiService", 'AiService',
"AItianhu", 'AItianhu',
"Bard", 'Bard',
"Bing", 'Bing',
"ChatgptAi", 'ChatgptAi',
"ChatgptLogin", 'ChatgptLogin',
"DeepAi", 'DeepAi',
"DfeHub", 'DfeHub',
"EasyChat", 'EasyChat',
"Forefront", 'Forefront',
"GetGpt", 'GetGpt',
"H2o", 'H2o',
"Hugchat", 'Hugchat',
"Liaobots", 'Liaobots',
"Lockchat", 'Lockchat',
"Opchatgpts", 'Opchatgpts',
"Raycast", 'Raycast',
"OpenaiChat", 'OpenaiChat',
"Theb", 'Theb',
"Vercel", 'Vercel',
"Wewordle", 'Wewordle',
"You", 'You',
"Yqcloud", 'Yqcloud',
"Equing", 'Equing',
"FastGpt", 'FastGpt',
"Wuguokai" 'Wuguokai',
"V50" 'V50'
] ]

30
g4f/Provider/base_provider.py
View File

@@ -20,9 +20,8 @@ class BaseProvider(ABC):
def create_completion( def create_completion(
model: str, model: str,
messages: list[dict[str, str]], messages: list[dict[str, str]],
stream: bool, stream: bool, **kwargs: Any) -> CreateResult:
**kwargs: Any,
) -> CreateResult:
raise NotImplementedError() raise NotImplementedError()
@classmethod @classmethod
@@ -42,8 +41,10 @@ _cookies = {}
def get_cookies(cookie_domain: str) -> dict: def get_cookies(cookie_domain: str) -> dict:
if cookie_domain not in _cookies: if cookie_domain not in _cookies:
_cookies[cookie_domain] = {} _cookies[cookie_domain] = {}
for cookie in browser_cookie3.load(cookie_domain): for cookie in browser_cookie3.load(cookie_domain):
_cookies[cookie_domain][cookie.name] = cookie.value _cookies[cookie_domain][cookie.name] = cookie.value
return _cookies[cookie_domain] return _cookies[cookie_domain]
@@ -53,18 +54,15 @@ class AsyncProvider(BaseProvider):
cls, cls,
model: str, model: str,
messages: list[dict[str, str]], messages: list[dict[str, str]],
stream: bool = False, stream: bool = False, **kwargs: Any) -> CreateResult:
**kwargs: Any
) -> CreateResult:
yield asyncio.run(cls.create_async(model, messages, **kwargs)) yield asyncio.run(cls.create_async(model, messages, **kwargs))
@staticmethod @staticmethod
@abstractmethod @abstractmethod
async def create_async( async def create_async(
model: str, model: str,
messages: list[dict[str, str]], messages: list[dict[str, str]], **kwargs: Any) -> str:
**kwargs: Any,
) -> str:
raise NotImplementedError() raise NotImplementedError()
@@ -74,9 +72,8 @@ class AsyncGeneratorProvider(AsyncProvider):
cls, cls,
model: str, model: str,
messages: list[dict[str, str]], messages: list[dict[str, str]],
stream: bool = True, stream: bool = True, **kwargs: Any) -> CreateResult:
**kwargs: Any
) -> CreateResult:
if stream: if stream:
yield from run_generator(cls.create_async_generator(model, messages, **kwargs)) yield from run_generator(cls.create_async_generator(model, messages, **kwargs))
else: else:
@@ -86,9 +83,8 @@ class AsyncGeneratorProvider(AsyncProvider):
async def create_async( async def create_async(
cls, cls,
model: str, model: str,
messages: list[dict[str, str]], messages: list[dict[str, str]], **kwargs: Any) -> str:
**kwargs: Any,
) -> str:
chunks = [chunk async for chunk in cls.create_async_generator(model, messages, **kwargs)] chunks = [chunk async for chunk in cls.create_async_generator(model, messages, **kwargs)]
if chunks: if chunks:
return "".join(chunks) return "".join(chunks)
@@ -97,8 +93,8 @@ class AsyncGeneratorProvider(AsyncProvider):
@abstractmethod @abstractmethod
def create_async_generator( def create_async_generator(
model: str, model: str,
messages: list[dict[str, str]], messages: list[dict[str, str]]) -> AsyncGenerator:
) -> AsyncGenerator:
raise NotImplementedError() raise NotImplementedError()

31
g4f/__init__.py
View File

@@ -4,42 +4,39 @@ from .typing import Any, CreateResult, Union
logging = False logging = False
class ChatCompletion: class ChatCompletion:
@staticmethod @staticmethod
def create( def create(
model: Union[models.Model, str], model : Union[models.Model, str],
messages: list[dict[str, str]], messages : list[dict[str, str]],
provider: Union[type[BaseProvider], None] = None, provider : Union[type[BaseProvider], None] = None,
stream: bool = False, stream : bool = False,
auth: Union[str, None] = None, auth : Union[str, None] = None, **kwargs: Any) -> Union[CreateResult, str]:
**kwargs: Any,
) -> Union[CreateResult, str]:
if isinstance(model, str): if isinstance(model, str):
try: try:
model = models.ModelUtils.convert[model] model = models.ModelUtils.convert[model]
except KeyError: except KeyError:
raise Exception(f"The model: {model} does not exist") raise Exception(f'The model: {model} does not exist')
provider = model.best_provider if provider == None else provider provider = model.best_provider if provider == None else provider
if not provider.working: if not provider.working:
raise Exception(f"{provider.__name__} is not working") raise Exception(f'{provider.__name__} is not working')
if provider.needs_auth and not auth: if provider.needs_auth and not auth:
raise Exception( raise Exception(
f'ValueError: {provider.__name__} requires authentication (use auth="cookie or token or jwt ..." param)' f'ValueError: {provider.__name__} requires authentication (use auth=\'cookie or token or jwt ...\' param)')
)
if provider.needs_auth: if provider.needs_auth:
kwargs["auth"] = auth kwargs['auth'] = auth
if not provider.supports_stream and stream: if not provider.supports_stream and stream:
raise Exception( raise Exception(
f"ValueError: {provider.__name__} does not support 'stream' argument" f'ValueError: {provider.__name__} does not support "stream" argument')
)
if logging: if logging:
print(f"Using {provider.__name__} provider") print(f'Using {provider.__name__} provider')
result = provider.create_completion(model.name, messages, stream, **kwargs) result = provider.create_completion(model.name, messages, stream, **kwargs)
return result if stream else "".join(result) return result if stream else ''.join(result)

268
g4f/models.py
View File

@@ -1,8 +1,6 @@
from dataclasses import dataclass from dataclasses import dataclass
from .Provider import Bard, BaseProvider, GetGpt, H2o, Liaobots, Vercel, Equing from .Provider import Bard, BaseProvider, GetGpt, H2o, Liaobots, Vercel, Equing
@dataclass @dataclass
class Model: class Model:
name: str name: str
@@ -12,214 +10,190 @@ class Model:
# GPT-3.5 / GPT-4 # GPT-3.5 / GPT-4
gpt_35_turbo = Model( gpt_35_turbo = Model(
name="gpt-3.5-turbo", name = 'gpt-3.5-turbo',
base_provider="openai", base_provider = 'openai',
best_provider=GetGpt, best_provider = GetGpt)
)
gpt_4 = Model( gpt_4 = Model(
name="gpt-4", name = 'gpt-4',
base_provider="openai", base_provider = 'openai',
best_provider=Liaobots, best_provider = Liaobots)
)
# Bard # Bard
palm = Model( palm = Model(
name="palm", name = 'palm',
base_provider="google", base_provider = 'google',
best_provider=Bard, best_provider = Bard)
)
# H2o # H2o
falcon_7b = Model( falcon_7b = Model(
name="h2oai/h2ogpt-gm-oasst1-en-2048-falcon-7b-v3", name = 'h2oai/h2ogpt-gm-oasst1-en-2048-falcon-7b-v3',
base_provider="huggingface", base_provider = 'huggingface',
best_provider=H2o, best_provider = H2o)
)
falcon_40b = Model( falcon_40b = Model(
name="h2oai/h2ogpt-gm-oasst1-en-2048-falcon-40b-v1", name = 'h2oai/h2ogpt-gm-oasst1-en-2048-falcon-40b-v1',
base_provider="huggingface", base_provider = 'huggingface',
best_provider=H2o, best_provider = H2o)
)
llama_13b = Model( llama_13b = Model(
name="h2oai/h2ogpt-gm-oasst1-en-2048-open-llama-13b", name = 'h2oai/h2ogpt-gm-oasst1-en-2048-open-llama-13b',
base_provider="huggingface", base_provider = 'huggingface',
best_provider=H2o, best_provider = H2o)
)
# Vercel # Vercel
claude_instant_v1 = Model( claude_instant_v1 = Model(
name="anthropic:claude-instant-v1", name = 'anthropic:claude-instant-v1',
base_provider="anthropic", base_provider = 'anthropic',
best_provider=Vercel, best_provider = Vercel)
)
claude_v1 = Model( claude_v1 = Model(
name="anthropic:claude-v1", name = 'anthropic:claude-v1',
base_provider="anthropic", base_provider = 'anthropic',
best_provider=Vercel, best_provider = Vercel)
)
claude_v2 = Model( claude_v2 = Model(
name="anthropic:claude-v2", name = 'anthropic:claude-v2',
base_provider="anthropic", base_provider = 'anthropic',
best_provider=Vercel, best_provider = Vercel)
)
command_light_nightly = Model( command_light_nightly = Model(
name="cohere:command-light-nightly", name = 'cohere:command-light-nightly',
base_provider="cohere", base_provider = 'cohere',
best_provider=Vercel, best_provider = Vercel)
)
command_nightly = Model( command_nightly = Model(
name="cohere:command-nightly", name = 'cohere:command-nightly',
base_provider="cohere", base_provider = 'cohere',
best_provider=Vercel, best_provider = Vercel)
)
gpt_neox_20b = Model( gpt_neox_20b = Model(
name="huggingface:EleutherAI/gpt-neox-20b", name = 'huggingface:EleutherAI/gpt-neox-20b',
base_provider="huggingface", base_provider = 'huggingface',
best_provider=Vercel, best_provider = Vercel)
)
oasst_sft_1_pythia_12b = Model( oasst_sft_1_pythia_12b = Model(
name="huggingface:OpenAssistant/oasst-sft-1-pythia-12b", name = 'huggingface:OpenAssistant/oasst-sft-1-pythia-12b',
base_provider="huggingface", base_provider = 'huggingface',
best_provider=Vercel, best_provider = Vercel)
)
oasst_sft_4_pythia_12b_epoch_35 = Model( oasst_sft_4_pythia_12b_epoch_35 = Model(
name="huggingface:OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5", name = 'huggingface:OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5',
base_provider="huggingface", base_provider = 'huggingface',
best_provider=Vercel, best_provider = Vercel)
)
santacoder = Model( santacoder = Model(
name="huggingface:bigcode/santacoder", name = 'huggingface:bigcode/santacoder',
base_provider="huggingface", base_provider = 'huggingface',
best_provider=Vercel, best_provider = Vercel)
)
bloom = Model( bloom = Model(
name="huggingface:bigscience/bloom", name = 'huggingface:bigscience/bloom',
base_provider="huggingface", base_provider = 'huggingface',
best_provider=Vercel, best_provider = Vercel)
)
flan_t5_xxl = Model( flan_t5_xxl = Model(
name="huggingface:google/flan-t5-xxl", name = 'huggingface:google/flan-t5-xxl',
base_provider="huggingface", base_provider = 'huggingface',
best_provider=Vercel, best_provider = Vercel)
)
code_davinci_002 = Model( code_davinci_002 = Model(
name="openai:code-davinci-002", name = 'openai:code-davinci-002',
base_provider="openai", base_provider = 'openai',
best_provider=Vercel, best_provider = Vercel)
)
gpt_35_turbo_16k = Model( gpt_35_turbo_16k = Model(
name="openai:gpt-3.5-turbo-16k", name = 'openai:gpt-3.5-turbo-16k',
base_provider="openai", base_provider = 'openai',
best_provider=Vercel, best_provider = Vercel)
)
gpt_35_turbo_16k_0613 = Model( gpt_35_turbo_16k_0613 = Model(
name="openai:gpt-3.5-turbo-16k-0613", name = 'openai:gpt-3.5-turbo-16k-0613',
base_provider="openai", base_provider = 'openai',
best_provider=Equing, best_provider = Equing)
)
gpt_4_0613 = Model( gpt_4_0613 = Model(
name="openai:gpt-4-0613", name = 'openai:gpt-4-0613',
base_provider="openai", base_provider = 'openai',
best_provider=Vercel, best_provider = Vercel)
)
text_ada_001 = Model( text_ada_001 = Model(
name="openai:text-ada-001", name = 'openai:text-ada-001',
base_provider="openai", base_provider = 'openai',
best_provider=Vercel, best_provider = Vercel)
)
text_babbage_001 = Model( text_babbage_001 = Model(
name="openai:text-babbage-001", name = 'openai:text-babbage-001',
base_provider="openai", base_provider = 'openai',
best_provider=Vercel, best_provider = Vercel)
)
text_curie_001 = Model( text_curie_001 = Model(
name="openai:text-curie-001", name = 'openai:text-curie-001',
base_provider="openai", base_provider = 'openai',
best_provider=Vercel, best_provider = Vercel)
)
text_davinci_002 = Model( text_davinci_002 = Model(
name="openai:text-davinci-002", name = 'openai:text-davinci-002',
base_provider="openai", base_provider = 'openai',
best_provider=Vercel, best_provider = Vercel)
)
text_davinci_003 = Model( text_davinci_003 = Model(
name="openai:text-davinci-003", name = 'openai:text-davinci-003',
base_provider="openai", base_provider = 'openai',
best_provider=Vercel, best_provider = Vercel)
)
llama13b_v2_chat = Model( llama13b_v2_chat = Model(
name="replicate:a16z-infra/llama13b-v2-chat", name = 'replicate:a16z-infra/llama13b-v2-chat',
base_provider="replicate", base_provider = 'replicate',
best_provider=Vercel, best_provider = Vercel)
)
llama7b_v2_chat = Model( llama7b_v2_chat = Model(
name="replicate:a16z-infra/llama7b-v2-chat", name = 'replicate:a16z-infra/llama7b-v2-chat',
base_provider="replicate", base_provider = 'replicate',
best_provider=Vercel, best_provider = Vercel)
)
class ModelUtils: class ModelUtils:
convert: dict[str, Model] = { convert: dict[str, Model] = {
# GPT-3.5 / GPT-4 # GPT-3.5 / GPT-4
"gpt-3.5-turbo": gpt_35_turbo, 'gpt-3.5-turbo' : gpt_35_turbo,
"gpt-4": gpt_4, 'gpt-4' : gpt_4,
# Bard # Bard
"palm2": palm, 'palm2' : palm,
"palm": palm, 'palm' : palm,
"google": palm, 'google' : palm,
"google-bard": palm, 'google-bard' : palm,
"google-palm": palm, 'google-palm' : palm,
"bard": palm, 'bard' : palm,
# H2o # H2o
"falcon-40b": falcon_40b, 'falcon-40b' : falcon_40b,
"falcon-7b": falcon_7b, 'falcon-7b' : falcon_7b,
"llama-13b": llama_13b, 'llama-13b' : llama_13b,
# Vercel # Vercel
"claude-instant-v1": claude_instant_v1, 'claude-instant-v1' : claude_instant_v1,
"claude-v1": claude_v1, 'claude-v1' : claude_v1,
"claude-v2": claude_v2, 'claude-v2' : claude_v2,
"command-light-nightly": command_light_nightly, 'command-nightly' : command_nightly,
"command-nightly": command_nightly, 'gpt-neox-20b' : gpt_neox_20b,
"gpt-neox-20b": gpt_neox_20b, 'santacoder' : santacoder,
"oasst-sft-1-pythia-12b": oasst_sft_1_pythia_12b, 'bloom' : bloom,
"oasst-sft-4-pythia-12b-epoch-3.5": oasst_sft_4_pythia_12b_epoch_35, 'flan-t5-xxl' : flan_t5_xxl,
"santacoder": santacoder, 'code-davinci-002' : code_davinci_002,
"bloom": bloom, 'gpt-3.5-turbo-16k' : gpt_35_turbo_16k,
"flan-t5-xxl": flan_t5_xxl, 'gpt-4-0613' : gpt_4_0613,
"code-davinci-002": code_davinci_002, 'text-ada-001' : text_ada_001,
"gpt-3.5-turbo-16k": gpt_35_turbo_16k, 'text-babbage-001' : text_babbage_001,
"gpt-3.5-turbo-16k-0613": gpt_35_turbo_16k_0613, 'text-curie-001' : text_curie_001,
"gpt-4-0613": gpt_4_0613, 'text-davinci-002' : text_davinci_002,
"text-ada-001": text_ada_001, 'text-davinci-003' : text_davinci_003,
"text-babbage-001": text_babbage_001, 'llama13b-v2-chat' : llama13b_v2_chat,
"text-curie-001": text_curie_001, 'llama7b-v2-chat' : llama7b_v2_chat,
"text-davinci-002": text_davinci_002,
"text-davinci-003": text_davinci_003, 'oasst-sft-1-pythia-12b' : oasst_sft_1_pythia_12b,
"llama13b-v2-chat": llama13b_v2_chat, 'oasst-sft-4-pythia-12b-epoch-3.5' : oasst_sft_4_pythia_12b_epoch_35,
"llama7b-v2-chat": llama7b_v2_chat, 'command-light-nightly' : command_light_nightly,
'gpt-3.5-turbo-16k-0613' : gpt_35_turbo_16k_0613,
} }

17
g4f/typing.py
View File

@@ -1,15 +1,14 @@
from typing import Any, AsyncGenerator, Generator, NewType, Tuple, TypedDict, Union from typing import Any, AsyncGenerator, Generator, NewType, Tuple, TypedDict, Union
SHA256 = NewType("sha_256_hash", str) SHA256 = NewType('sha_256_hash', str)
CreateResult = Generator[str, None, None] CreateResult = Generator[str, None, None]
__all__ = [ __all__ = [
"Any", 'Any',
"AsyncGenerator", 'AsyncGenerator',
"Generator", 'Generator',
"Tuple", 'Tuple',
"TypedDict", 'TypedDict',
"SHA256", 'SHA256',
"CreateResult", 'CreateResult',
] ]