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Code Issues Packages Projects Releases Wiki Activity

microservices are able to run (#5)

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This commit is contained in:
Dmitry Afanasyev
2023-09-24 06:32:49 +03:00
committed by GitHub
parent 315284fc38
commit 7e995866ff
171 changed files with 676 additions and 425 deletions
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19
chat_gpt_microservice/g4f/Provider/Provider.py Normal file
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import os
from typing import get_type_hints
url = None
model = None
supports_stream = False
needs_auth = False
def _create_completion(model: str, messages: list, stream: bool, **kwargs):
return
params = f"g4f.Providers.{os.path.basename(__file__)[:-3]} supports: " + "(%s)" % ", ".join(
[
f"{name}: {get_type_hints(_create_completion)[name].__name__}"
for name in _create_completion.__code__.co_varnames[: _create_completion.__code__.co_argcount]
]
)

41
chat_gpt_microservice/g4f/Provider/Providers/AiService.py Normal file
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import os
from typing import get_type_hints
import requests
url = "https://aiservice.vercel.app/api/chat/answer"
model = ["gpt-3.5-turbo"]
supports_stream = False
needs_auth = False
def _create_completion(model: str, messages: list, stream: bool, **kwargs):
base = ""
for message in messages:
base += "%s: %s\n" % (message["role"], message["content"])
base += "assistant:"
headers = {
"accept": "*/*",
"content-type": "text/plain;charset=UTF-8",
"sec-fetch-dest": "empty",
"sec-fetch-mode": "cors",
"sec-fetch-site": "same-origin",
"Referer": "https://aiservice.vercel.app/chat",
}
data = {"input": base}
response = requests.post(url, headers=headers, json=data)
if response.status_code == 200:
_json = response.json()
yield _json["data"]
else:
print(f"Error Occurred::{response.status_code}")
return None
params = f"g4f.Providers.{os.path.basename(__file__)[:-3]} supports: " + "(%s)" % ", ".join(
[
f"{name}: {get_type_hints(_create_completion)[name].__name__}"
for name in _create_completion.__code__.co_varnames[: _create_completion.__code__.co_argcount]
]
)

46
chat_gpt_microservice/g4f/Provider/Providers/Aichat.py Normal file
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import json
import os
from typing import get_type_hints
import requests
url = "https://hteyun.com"
model = [
"gpt-3.5-turbo",
"gpt-3.5-turbo-16k",
"gpt-3.5-turbo-16k-0613",
"gpt-3.5-turbo-0613",
]
supports_stream = True
needs_auth = False
def _create_completion(model: str, messages: list, stream: bool, temperature: float = 0.7, **kwargs):
headers = {
"Content-Type": "application/json",
}
data = {
"model": model,
"temperature": 0.7,
"presence_penalty": 0,
"messages": messages,
}
response = requests.post(url + "/api/chat-stream", json=data, stream=True)
if stream:
for chunk in response.iter_content(chunk_size=None):
chunk = chunk.decode("utf-8")
if chunk.strip():
message = json.loads(chunk)["choices"][0]["message"]["content"]
yield message
else:
message = response.json()["choices"][0]["message"]["content"]
yield message
params = f"g4f.Providers.{os.path.basename(__file__)[:-3]} supports: " + "(%s)" % ", ".join(
[
f"{name}: {get_type_hints(_create_completion)[name].__name__}"
for name in _create_completion.__code__.co_varnames[: _create_completion.__code__.co_argcount]
]
)

96
chat_gpt_microservice/g4f/Provider/Providers/Ails.py Normal file
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import hashlib
import json
import os
import time
import uuid
from datetime import datetime
from typing import Dict, get_type_hints
import requests
from g4f.typing import sha256
url: str = "https://ai.ls"
model: str = "gpt-3.5-turbo"
supports_stream = True
needs_auth = False
working = True
class Utils:
def hash(json_data: Dict[str, str]) -> sha256:
base_string: str = "%s:%s:%s:%s" % (
json_data["t"],
json_data["m"],
"WI,2rU#_r:r~aF4aJ36[.Z(/8Rv93Rf",
len(json_data["m"]),
)
return hashlib.sha256(base_string.encode()).hexdigest()
def format_timestamp(timestamp: int) -> str:
e = timestamp
n = e % 10
r = n + 1 if n % 2 == 0 else n
return str(e - n + r)
def _create_completion(model: str, messages: list, temperature: float = 0.6, stream: bool = False, **kwargs):
headers = {
"authority": "api.caipacity.com",
"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",
"authorization": "Bearer free",
"client-id": str(uuid.uuid4()),
"client-v": "0.1.249",
"content-type": "application/json",
"origin": "https://ai.ls",
"referer": "https://ai.ls/",
"sec-ch-ua": '"Not.A/Brand";v="8", "Chromium";v="114", "Google Chrome";v="114"',
"sec-ch-ua-mobile": "?0",
"sec-ch-ua-platform": '"Windows"',
"sec-fetch-dest": "empty",
"sec-fetch-mode": "cors",
"sec-fetch-site": "cross-site",
"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",
}
timestamp = Utils.format_timestamp(int(time.time() * 1000))
sig = {
"d": datetime.now().strftime("%Y-%m-%d"),
"t": timestamp,
"s": Utils.hash({"t": timestamp, "m": messages[-1]["content"]}),
}
json_data = json.dumps(
separators=(",", ":"),
obj={
"model": "gpt-3.5-turbo",
"temperature": 0.6,
"stream": True,
"messages": messages,
}
| sig,
)
response = requests.post(
"https://api.caipacity.com/v1/chat/completions",
headers=headers,
data=json_data,
stream=True,
)
for token in response.iter_lines():
if b"content" in token:
completion_chunk = json.loads(token.decode().replace("data: ", ""))
token = completion_chunk["choices"][0]["delta"].get("content")
if token != None:
yield token
params = f"g4f.Providers.{os.path.basename(__file__)[:-3]} supports: " + "(%s)" % ", ".join(
[
f"{name}: {get_type_hints(_create_completion)[name].__name__}"
for name in _create_completion.__code__.co_varnames[: _create_completion.__code__.co_argcount]
]
)

87
chat_gpt_microservice/g4f/Provider/Providers/Bard.py Normal file
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import json
import os
import random
import re
from typing import get_type_hints
import browser_cookie3
import requests
url = "https://bard.google.com"
model = ["Palm2"]
supports_stream = False
needs_auth = True
def _create_completion(model: str, messages: list, stream: bool, **kwargs):
psid = {cookie.name: cookie.value for cookie in browser_cookie3.chrome(domain_name=".google.com")}["__Secure-1PSID"]
formatted = "\n".join(["%s: %s" % (message["role"], message["content"]) for message in messages])
prompt = f"{formatted}\nAssistant:"
proxy = kwargs.get("proxy", False)
if proxy == False:
print("warning!, you did not give a proxy, a lot of countries are banned from Google Bard, so it may not work")
snlm0e = None
conversation_id = None
response_id = None
choice_id = None
client = requests.Session()
client.proxies = {"http": f"http://{proxy}", "https": f"http://{proxy}"} if proxy else None
client.headers = {
"authority": "bard.google.com",
"content-type": "application/x-www-form-urlencoded;charset=UTF-8",
"origin": "https://bard.google.com",
"referer": "https://bard.google.com/",
"user-agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/111.0.0.0 Safari/537.36",
"x-same-domain": "1",
"cookie": f"__Secure-1PSID={psid}",
}
snlm0e = (
re.search(r"SNlM0e\":\"(.*?)\"", client.get("https://bard.google.com/").text).group(1) if not snlm0e else snlm0e
)
params = {
"bl": "boq_assistant-bard-web-server_20230326.21_p0",
"_reqid": random.randint(1111, 9999),
"rt": "c",
}
data = {
"at": snlm0e,
"f.req": json.dumps(
[
None,
json.dumps([[prompt], None, [conversation_id, response_id, choice_id]]),
]
),
}
intents = ".".join(["assistant", "lamda", "BardFrontendService"])
response = client.post(
f"https://bard.google.com/_/BardChatUi/data/{intents}/StreamGenerate",
data=data,
params=params,
)
chat_data = json.loads(response.content.splitlines()[3])[0][2]
if chat_data:
json_chat_data = json.loads(chat_data)
yield json_chat_data[0][0]
else:
yield "error"
params = f"g4f.Providers.{os.path.basename(__file__)[:-3]} supports: " + "(%s)" % ", ".join(
[
f"{name}: {get_type_hints(_create_completion)[name].__name__}"
for name in _create_completion.__code__.co_varnames[: _create_completion.__code__.co_argcount]
]
)

64
chat_gpt_microservice/g4f/Provider/Providers/Better.py Normal file
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import json
import os
from typing import get_type_hints
import requests
url = "https://openai-proxy-api.vercel.app/v1/"
model = [
"gpt-3.5-turbo",
"gpt-3.5-turbo-0613",
"gpt-3.5-turbo-16k",
"gpt-3.5-turbo-16k-0613",
"gpt-4",
]
supports_stream = True
needs_auth = False
def _create_completion(model: str, messages: list, stream: bool, **kwargs):
headers = {
"Content-Type": "application/json",
"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 Edg/114.0.1823.58",
"Referer": "https://chat.ylokh.xyz/",
"Origin": "https://chat.ylokh.xyz",
"Connection": "keep-alive",
}
json_data = {
"messages": messages,
"temperature": 1.0,
"model": model,
"stream": stream,
}
response = requests.post(
"https://openai-proxy-api.vercel.app/v1/chat/completions",
headers=headers,
json=json_data,
stream=True,
)
for token in response.iter_lines():
decoded = token.decode("utf-8")
if decoded.startswith("data: "):
data_str = decoded.replace("data: ", "")
data = json.loads(data_str)
if "choices" in data and "delta" in data["choices"][0]:
delta = data["choices"][0]["delta"]
content = delta.get("content", "")
finish_reason = delta.get("finish_reason", "")
if finish_reason == "stop":
break
if content:
yield content
params = f"g4f.Providers.{os.path.basename(__file__)[:-3]} supports: " + "(%s)" % ", ".join(
[
f"{name}: {get_type_hints(_create_completion)[name].__name__}"
for name in _create_completion.__code__.co_varnames[: _create_completion.__code__.co_argcount]
]
)

355
chat_gpt_microservice/g4f/Provider/Providers/Bing.py Normal file
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import asyncio
import json
import os
import random
import ssl
import uuid
from typing import get_type_hints
import aiohttp
import certifi
import requests
url = "https://bing.com/chat"
model = ["gpt-4"]
supports_stream = True
needs_auth = False
ssl_context = ssl.create_default_context()
ssl_context.load_verify_locations(certifi.where())
class optionsSets:
optionSet: dict = {"tone": str, "optionsSets": list}
jailbreak: dict = {
"optionsSets": [
"saharasugg",
"enablenewsfc",
"clgalileo",
"gencontentv3",
"nlu_direct_response_filter",
"deepleo",
"disable_emoji_spoken_text",
"responsible_ai_policy_235",
"enablemm",
"h3precise"
# "harmonyv3",
"dtappid",
"cricinfo",
"cricinfov2",
"dv3sugg",
"nojbfedge",
]
}
class Defaults:
delimiter = "\x1e"
ip_address = f"13.{random.randint(104, 107)}.{random.randint(0, 255)}.{random.randint(0, 255)}"
allowedMessageTypes = [
"Chat",
"Disengaged",
"AdsQuery",
"SemanticSerp",
"GenerateContentQuery",
"SearchQuery",
"ActionRequest",
"Context",
"Progress",
"AdsQuery",
"SemanticSerp",
]
sliceIds = [
# "222dtappid",
# "225cricinfo",
# "224locals0"
"winmuid3tf",
"osbsdusgreccf",
"ttstmout",
"crchatrev",
"winlongmsgtf",
"ctrlworkpay",
"norespwtf",
"tempcacheread",
"temptacache",
"505scss0",
"508jbcars0",
"515enbotdets0",
"5082tsports",
"515vaoprvs",
"424dagslnv1s0",
"kcimgattcf",
"427startpms0",
]
location = {
"locale": "en-US",
"market": "en-US",
"region": "US",
"locationHints": [
{
"country": "United States",
"state": "California",
"city": "Los Angeles",
"timezoneoffset": 8,
"countryConfidence": 8,
"Center": {"Latitude": 34.0536909, "Longitude": -118.242766},
"RegionType": 2,
"SourceType": 1,
}
],
}
def _format(msg: dict) -> str:
return json.dumps(msg, ensure_ascii=False) + Defaults.delimiter
async def create_conversation():
for _ in range(5):
create = requests.get(
"https://www.bing.com/turing/conversation/create",
headers={
"authority": "edgeservices.bing.com",
"accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.7",
"accept-language": "en-US,en;q=0.9",
"cache-control": "max-age=0",
"sec-ch-ua": '"Chromium";v="110", "Not A(Brand";v="24", "Microsoft Edge";v="110"',
"sec-ch-ua-arch": '"x86"',
"sec-ch-ua-bitness": '"64"',
"sec-ch-ua-full-version": '"110.0.1587.69"',
"sec-ch-ua-full-version-list": '"Chromium";v="110.0.5481.192", "Not A(Brand";v="24.0.0.0", "Microsoft Edge";v="110.0.1587.69"',
"sec-ch-ua-mobile": "?0",
"sec-ch-ua-model": '""',
"sec-ch-ua-platform": '"Windows"',
"sec-ch-ua-platform-version": '"15.0.0"',
"sec-fetch-dest": "document",
"sec-fetch-mode": "navigate",
"sec-fetch-site": "none",
"sec-fetch-user": "?1",
"upgrade-insecure-requests": "1",
"user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/110.0.0.0 Safari/537.36 Edg/110.0.1587.69",
"x-edge-shopping-flag": "1",
"x-forwarded-for": Defaults.ip_address,
},
)
conversationId = create.json().get("conversationId")
clientId = create.json().get("clientId")
conversationSignature = create.json().get("conversationSignature")
if not conversationId or not clientId or not conversationSignature and _ == 4:
raise Exception("Failed to create conversation.")
return conversationId, clientId, conversationSignature
async def stream_generate(
prompt: str,
mode: optionsSets.optionSet = optionsSets.jailbreak,
context: bool or str = False,
):
timeout = aiohttp.ClientTimeout(total=900)
session = aiohttp.ClientSession(timeout=timeout)
conversationId, clientId, conversationSignature = await create_conversation()
wss = await session.ws_connect(
"wss://sydney.bing.com/sydney/ChatHub",
ssl=ssl_context,
autoping=False,
headers={
"accept": "application/json",
"accept-language": "en-US,en;q=0.9",
"content-type": "application/json",
"sec-ch-ua": '"Not_A Brand";v="99", "Microsoft Edge";v="110", "Chromium";v="110"',
"sec-ch-ua-arch": '"x86"',
"sec-ch-ua-bitness": '"64"',
"sec-ch-ua-full-version": '"109.0.1518.78"',
"sec-ch-ua-full-version-list": '"Chromium";v="110.0.5481.192", "Not A(Brand";v="24.0.0.0", "Microsoft Edge";v="110.0.1587.69"',
"sec-ch-ua-mobile": "?0",
"sec-ch-ua-model": "",
"sec-ch-ua-platform": '"Windows"',
"sec-ch-ua-platform-version": '"15.0.0"',
"sec-fetch-dest": "empty",
"sec-fetch-mode": "cors",
"sec-fetch-site": "same-origin",
"x-ms-client-request-id": str(uuid.uuid4()),
"x-ms-useragent": "azsdk-js-api-client-factory/1.0.0-beta.1 core-rest-pipeline/1.10.0 OS/Win32",
"Referer": "https://www.bing.com/search?q=Bing+AI&showconv=1&FORM=hpcodx",
"Referrer-Policy": "origin-when-cross-origin",
"x-forwarded-for": Defaults.ip_address,
},
)
await wss.send_str(_format({"protocol": "json", "version": 1}))
await wss.receive(timeout=900)
struct = {
"arguments": [
{
**mode,
"source": "cib",
"allowedMessageTypes": Defaults.allowedMessageTypes,
"sliceIds": Defaults.sliceIds,
"traceId": os.urandom(16).hex(),
"isStartOfSession": True,
"message": Defaults.location
| {
"author": "user",
"inputMethod": "Keyboard",
"text": prompt,
"messageType": "Chat",
},
"conversationSignature": conversationSignature,
"participant": {"id": clientId},
"conversationId": conversationId,
}
],
"invocationId": "0",
"target": "chat",
"type": 4,
}
if context:
struct["arguments"][0]["previousMessages"] = [
{
"author": "user",
"description": context,
"contextType": "WebPage",
"messageType": "Context",
"messageId": "discover-web--page-ping-mriduna-----",
}
]
await wss.send_str(_format(struct))
final = False
draw = False
resp_txt = ""
result_text = ""
resp_txt_no_link = ""
cache_text = ""
while not final:
msg = await wss.receive(timeout=900)
objects = msg.data.split(Defaults.delimiter)
for obj in objects:
if obj is None or not obj:
continue
response = json.loads(obj)
if response.get("type") == 1 and response["arguments"][0].get(
"messages",
):
if not draw:
if (response["arguments"][0]["messages"][0]["contentOrigin"] != "Apology") and not draw:
resp_txt = result_text + response["arguments"][0]["messages"][0]["adaptiveCards"][0]["body"][
0
].get("text", "")
resp_txt_no_link = result_text + response["arguments"][0]["messages"][0].get("text", "")
if response["arguments"][0]["messages"][0].get(
"messageType",
):
resp_txt = (
resp_txt
+ response["arguments"][0]["messages"][0]["adaptiveCards"][0]["body"][0]["inlines"][
0
].get("text")
+ "\n"
)
result_text = (
result_text
+ response["arguments"][0]["messages"][0]["adaptiveCards"][0]["body"][0]["inlines"][
0
].get("text")
+ "\n"
)
if cache_text.endswith(" "):
final = True
if wss and not wss.closed:
await wss.close()
if session and not session.closed:
await session.close()
yield (resp_txt.replace(cache_text, ""))
cache_text = resp_txt
elif response.get("type") == 2:
if response["item"]["result"].get("error"):
if wss and not wss.closed:
await wss.close()
if session and not session.closed:
await session.close()
raise Exception(f"{response['item']['result']['value']}: {response['item']['result']['message']}")
if draw:
cache = response["item"]["messages"][1]["adaptiveCards"][0]["body"][0]["text"]
response["item"]["messages"][1]["adaptiveCards"][0]["body"][0]["text"] = cache + resp_txt
if response["item"]["messages"][-1]["contentOrigin"] == "Apology" and resp_txt:
response["item"]["messages"][-1]["text"] = resp_txt_no_link
response["item"]["messages"][-1]["adaptiveCards"][0]["body"][0]["text"] = resp_txt
# print('Preserved the message from being deleted', file=sys.stderr)
final = True
if wss and not wss.closed:
await wss.close()
if session and not session.closed:
await session.close()
def run(generator):
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
gen = generator.__aiter__()
while True:
try:
next_val = loop.run_until_complete(gen.__anext__())
yield next_val
except StopAsyncIteration:
break
# print('Done')
def convert(messages):
context = ""
for message in messages:
context += "[%s](#message)\n%s\n\n" % (message["role"], message["content"])
return context
def _create_completion(model: str, messages: list, stream: bool, **kwargs):
if len(messages) < 2:
prompt = messages[0]["content"]
context = False
else:
prompt = messages[-1]["content"]
context = convert(messages[:-1])
response = run(stream_generate(prompt, optionsSets.jailbreak, context))
for token in response:
yield (token)
# print('Done')
params = f"g4f.Providers.{os.path.basename(__file__)[:-3]} supports: " + "(%s)" % ", ".join(
[
f"{name}: {get_type_hints(_create_completion)[name].__name__}"
for name in _create_completion.__code__.co_varnames[: _create_completion.__code__.co_argcount]
]
)

58
chat_gpt_microservice/g4f/Provider/Providers/ChatFree.py Normal file
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import json
import os
from typing import get_type_hints
import requests
url = "https://v.chatfree.cc"
model = ["gpt-3.5-turbo", "gpt-3.5-turbo-16k"]
supports_stream = False
needs_auth = False
def _create_completion(model: str, messages: list, stream: bool, **kwargs):
headers = {
"authority": "chat.dfehub.com",
"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",
"content-type": "application/json",
"origin": "https://v.chatfree.cc",
"referer": "https://v.chatfree.cc/",
"sec-ch-ua": '"Not.A/Brand";v="8", "Chromium";v="114", "Google Chrome";v="114"',
"sec-ch-ua-mobile": "?0",
"sec-ch-ua-platform": '"macOS"',
"sec-fetch-dest": "empty",
"sec-fetch-mode": "cors",
"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",
"x-requested-with": "XMLHttpRequest",
}
json_data = {
"messages": messages,
"stream": True,
"model": model,
"temperature": 0.5,
"presence_penalty": 0,
"frequency_penalty": 0,
"top_p": 1,
}
response = requests.post(
"https://v.chatfree.cc/api/openai/v1/chat/completions",
headers=headers,
json=json_data,
)
for chunk in response.iter_lines():
if b"content" in chunk:
data = json.loads(chunk.decode().split("data: ")[1])
yield (data["choices"][0]["delta"]["content"])
params = f"g4f.Providers.{os.path.basename(__file__)[:-3]} supports: " + "(%s)" % ", ".join(
[
f"{name}: {get_type_hints(_create_completion)[name].__name__}"
for name in _create_completion.__code__.co_varnames[: _create_completion.__code__.co_argcount]
]
)

60
chat_gpt_microservice/g4f/Provider/Providers/ChatgptAi.py Normal file
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import os
import re
from typing import get_type_hints
import requests
url = "https://chatgpt.ai/gpt-4/"
model = ["gpt-4"]
supports_stream = True
needs_auth = False
def _create_completion(model: str, messages: list, stream: bool, **kwargs):
chat = ""
for message in messages:
chat += "%s: %s\n" % (message["role"], message["content"])
chat += "assistant: "
response = requests.get("https://chatgpt.ai/")
nonce, post_id, _, bot_id = re.findall(
r'data-nonce="(.*)"\n data-post-id="(.*)"\n data-url="(.*)"\n data-bot-id="(.*)"\n data-width',
response.text,
)[0]
headers = {
"authority": "chatgpt.ai",
"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",
"cache-control": "no-cache",
"origin": "https://chatgpt.ai",
"pragma": "no-cache",
"referer": "https://chatgpt.ai/gpt-4/",
"sec-ch-ua": '"Not.A/Brand";v="8", "Chromium";v="114", "Google Chrome";v="114"',
"sec-ch-ua-mobile": "?0",
"sec-ch-ua-platform": '"Windows"',
"sec-fetch-dest": "empty",
"sec-fetch-mode": "cors",
"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",
}
data = {
"_wpnonce": nonce,
"post_id": post_id,
"url": "https://chatgpt.ai/gpt-4",
"action": "wpaicg_chat_shortcode_message",
"message": chat,
"bot_id": bot_id,
}
response = requests.post("https://chatgpt.ai/wp-admin/admin-ajax.php", headers=headers, data=data)
yield (response.json()["data"])
params = f"g4f.Providers.{os.path.basename(__file__)[:-3]} supports: " + "(%s)" % ", ".join(
[
f"{name}: {get_type_hints(_create_completion)[name].__name__}"
for name in _create_completion.__code__.co_varnames[: _create_completion.__code__.co_argcount]
]
)

113
chat_gpt_microservice/g4f/Provider/Providers/ChatgptLogin.py Normal file
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import base64
import os
import re
from typing import get_type_hints
import requests
url = "https://chatgptlogin.ac"
model = ["gpt-3.5-turbo"]
supports_stream = False
needs_auth = False
def _create_completion(model: str, messages: list, stream: bool, **kwargs):
def get_nonce():
res = requests.get(
"https://chatgptlogin.ac/use-chatgpt-free/",
headers={
"Referer": "https://chatgptlogin.ac/use-chatgpt-free/",
"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",
},
)
src = re.search(
r'class="mwai-chat mwai-chatgpt">.*<span>Send</span></button></div></div></div> <script defer src="(.*?)">',
res.text,
).group(1)
decoded_string = base64.b64decode(src.split(",")[-1]).decode("utf-8")
return re.search(r"let restNonce = '(.*?)';", decoded_string).group(1)
def transform(messages: list) -> list:
def html_encode(string: str) -> str:
table = {
'"': "&quot;",
"'": "&#39;",
"&": "&amp;",
">": "&gt;",
"<": "&lt;",
"\n": "<br>",
"\t": "&nbsp;&nbsp;&nbsp;&nbsp;",
" ": "&nbsp;",
}
for key in table:
string = string.replace(key, table[key])
return string
return [
{
"id": os.urandom(6).hex(),
"role": message["role"],
"content": message["content"],
"who": "AI: " if message["role"] == "assistant" else "User: ",
"html": html_encode(message["content"]),
}
for message in messages
]
headers = {
"authority": "chatgptlogin.ac",
"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",
"content-type": "application/json",
"origin": "https://chatgptlogin.ac",
"referer": "https://chatgptlogin.ac/use-chatgpt-free/",
"sec-ch-ua": '"Not.A/Brand";v="8", "Chromium";v="114", "Google Chrome";v="114"',
"sec-ch-ua-mobile": "?0",
"sec-ch-ua-platform": '"Windows"',
"sec-fetch-dest": "empty",
"sec-fetch-mode": "cors",
"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",
"x-wp-nonce": get_nonce(),
}
conversation = transform(messages)
json_data = {
"env": "chatbot",
"session": "N/A",
"prompt": "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,
"newMessage": messages[-1]["content"],
"userName": '<div class="mwai-name-text">User:</div>',
"aiName": '<div class="mwai-name-text">AI:</div>',
"model": "gpt-3.5-turbo",
"temperature": 0.8,
"maxTokens": 1024,
"maxResults": 1,
"apiKey": "",
"service": "openai",
"embeddingsIndex": "",
"stop": "",
"clientId": os.urandom(6).hex(),
}
response = requests.post(
"https://chatgptlogin.ac/wp-json/ai-chatbot/v1/chat",
headers=headers,
json=json_data,
)
return response.json()["reply"]
params = f"g4f.Providers.{os.path.basename(__file__)[:-3]} supports: " + "(%s)" % ", ".join(
[
f"{name}: {get_type_hints(_create_completion)[name].__name__}"
for name in _create_completion.__code__.co_varnames[: _create_completion.__code__.co_argcount]
]
)

48
chat_gpt_microservice/g4f/Provider/Providers/DeepAi.py Normal file
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import hashlib
import json
import os
import random
from typing import get_type_hints
import requests
url = "https://deepai.org"
model = ["gpt-3.5-turbo"]
supports_stream = True
needs_auth = False
def _create_completion(model: str, messages: list, stream: bool, **kwargs):
def md5(text: str) -> str:
return hashlib.md5(text.encode()).hexdigest()[::-1]
def get_api_key(user_agent: str) -> str:
part1 = str(random.randint(0, 10**11))
part2 = md5(user_agent + md5(user_agent + md5(user_agent + part1 + "x")))
return f"tryit-{part1}-{part2}"
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"
headers = {"api-key": get_api_key(user_agent), "user-agent": user_agent}
files = {"chat_style": (None, "chat"), "chatHistory": (None, json.dumps(messages))}
r = requests.post(
"https://api.deepai.org/chat_response",
headers=headers,
files=files,
stream=True,
)
for chunk in r.iter_content(chunk_size=None):
r.raise_for_status()
yield chunk.decode()
params = f"g4f.Providers.{os.path.basename(__file__)[:-3]} supports: " + "(%s)" % ", ".join(
[
f"{name}: {get_type_hints(_create_completion)[name].__name__}"
for name in _create_completion.__code__.co_varnames[: _create_completion.__code__.co_argcount]
]
)

66
chat_gpt_microservice/g4f/Provider/Providers/Easychat.py Normal file
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import json
import os
from typing import get_type_hints
import requests
url = "https://free.easychat.work"
model = [
"gpt-3.5-turbo",
"gpt-3.5-turbo-16k",
"gpt-3.5-turbo-16k-0613",
"gpt-3.5-turbo-0613",
]
supports_stream = True
needs_auth = False
def _create_completion(model: str, messages: list, stream: bool, **kwargs):
headers = {
"authority": "free.easychat.work",
"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",
"content-type": "application/json",
"endpoint": "",
"origin": "https://free.easychat.work",
"plugins": "0",
"referer": "https://free.easychat.work/",
"sec-ch-ua": '"Not.A/Brand";v="8", "Chromium";v="114", "Google Chrome";v="114"',
"sec-ch-ua-mobile": "?0",
"sec-ch-ua-platform": '"macOS"',
"sec-fetch-dest": "empty",
"sec-fetch-mode": "cors",
"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",
"usesearch": "false",
"x-requested-with": "XMLHttpRequest",
}
json_data = {
"messages": messages,
"stream": True,
"model": model,
"temperature": 0.5,
"presence_penalty": 0,
"frequency_penalty": 0,
"top_p": 1,
}
response = requests.post(
"https://free.easychat.work/api/openai/v1/chat/completions",
headers=headers,
json=json_data,
)
for chunk in response.iter_lines():
if b"content" in chunk:
data = json.loads(chunk.decode().split("data: ")[1])
yield (data["choices"][0]["delta"]["content"])
params = f"g4f.Providers.{os.path.basename(__file__)[:-3]} supports: " + "(%s)" % ", ".join(
[
f"{name}: {get_type_hints(_create_completion)[name].__name__}"
for name in _create_completion.__code__.co_varnames[: _create_completion.__code__.co_argcount]
]
)

46
chat_gpt_microservice/g4f/Provider/Providers/Ezcht.py Normal file
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import json
import os
from typing import get_type_hints
import requests
url = "https://gpt4.ezchat.top"
model = [
"gpt-3.5-turbo",
"gpt-3.5-turbo-16k",
"gpt-3.5-turbo-16k-0613",
"gpt-3.5-turbo-0613",
]
supports_stream = True
needs_auth = False
def _create_completion(model: str, messages: list, stream: bool, temperature: float = 0.7, **kwargs):
headers = {
"Content-Type": "application/json",
}
data = {
"model": model,
"temperature": 0.7,
"presence_penalty": 0,
"messages": messages,
}
response = requests.post(url + "/api/openai/v1/chat/completions", json=data, stream=True)
if stream:
for chunk in response.iter_content(chunk_size=None):
chunk = chunk.decode("utf-8")
if chunk.strip():
message = json.loads(chunk)["choices"][0]["message"]["content"]
yield message
else:
message = response.json()["choices"][0]["message"]["content"]
yield message
params = f"g4f.Providers.{os.path.basename(__file__)[:-3]} supports: " + "(%s)" % ", ".join(
[
f"{name}: {get_type_hints(_create_completion)[name].__name__}"
for name in _create_completion.__code__.co_varnames[: _create_completion.__code__.co_argcount]
]
)

59
chat_gpt_microservice/g4f/Provider/Providers/Fakeopen.py Normal file
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import json
import os
from typing import get_type_hints
import requests
url = "https://ai.fakeopen.com/v1/"
model = [
"gpt-3.5-turbo",
"gpt-3.5-turbo-0613",
"gpt-3.5-turbo-16k",
"gpt-3.5-turbo-16k-0613",
]
supports_stream = True
needs_auth = False
def _create_completion(model: str, messages: list, stream: bool, **kwargs):
headers = {
"Content-Type": "application/json",
"accept": "text/event-stream",
"Cache-Control": "no-cache",
"Proxy-Connection": "keep-alive",
"Authorization": f"Bearer {os.environ.get('FAKE_OPEN_KEY', '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')}",
}
json_data = {
"messages": messages,
"temperature": 1.0,
"model": model,
"stream": stream,
}
response = requests.post(
"https://ai.fakeopen.com/v1/chat/completions",
headers=headers,
json=json_data,
stream=True,
)
for token in response.iter_lines():
decoded = token.decode("utf-8")
if decoded == "[DONE]":
break
if decoded.startswith("data: "):
data_str = decoded.replace("data: ", "")
if data_str != "[DONE]":
data = json.loads(data_str)
if "choices" in data and "delta" in data["choices"][0] and "content" in data["choices"][0]["delta"]:
yield data["choices"][0]["delta"]["content"]
params = f"g4f.Providers.{os.path.basename(__file__)[:-3]} supports: " + "(%s)" % ", ".join(
[
f"{name}: {get_type_hints(_create_completion)[name].__name__}"
for name in _create_completion.__code__.co_varnames[: _create_completion.__code__.co_argcount]
]
)

41
chat_gpt_microservice/g4f/Provider/Providers/Forefront.py Normal file
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import json
import os
from typing import get_type_hints
import requests
url = "https://forefront.com"
model = ["gpt-3.5-turbo"]
supports_stream = True
needs_auth = False
def _create_completion(model: str, messages: list, stream: bool, **kwargs):
json_data = {
"text": messages[-1]["content"],
"action": "noauth",
"id": "",
"parentId": "",
"workspaceId": "",
"messagePersona": "607e41fe-95be-497e-8e97-010a59b2e2c0",
"model": "gpt-4",
"messages": messages[:-1] if len(messages) > 1 else [],
"internetMode": "auto",
}
response = requests.post(
"https://streaming.tenant-forefront-default.knative.chi.coreweave.com/free-chat",
json=json_data,
stream=True,
)
for token in response.iter_lines():
if b"delta" in token:
token = json.loads(token.decode().split("data: ")[1])["delta"]
yield (token)
params = f"g4f.Providers.{os.path.basename(__file__)[:-3]} supports: " + "(%s)" % ", ".join(
[
f"{name}: {get_type_hints(_create_completion)[name].__name__}"
for name in _create_completion.__code__.co_varnames[: _create_completion.__code__.co_argcount]
]
)

68
chat_gpt_microservice/g4f/Provider/Providers/GetGpt.py Normal file
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import json
import os
import uuid
from typing import get_type_hints
import requests
from Crypto.Cipher import AES
url = "https://chat.getgpt.world/"
model = ["gpt-3.5-turbo"]
supports_stream = True
needs_auth = False
def _create_completion(model: str, messages: list, stream: bool, **kwargs):
def encrypt(e):
t = os.urandom(8).hex().encode("utf-8")
n = os.urandom(8).hex().encode("utf-8")
r = e.encode("utf-8")
cipher = AES.new(t, AES.MODE_CBC, n)
ciphertext = cipher.encrypt(pad_data(r))
return ciphertext.hex() + t.decode("utf-8") + n.decode("utf-8")
def pad_data(data: bytes) -> bytes:
block_size = AES.block_size
padding_size = block_size - len(data) % block_size
padding = bytes([padding_size] * padding_size)
return data + padding
headers = {
"Content-Type": "application/json",
"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",
}
data = json.dumps(
{
"messages": messages,
"frequency_penalty": kwargs.get("frequency_penalty", 0),
"max_tokens": kwargs.get("max_tokens", 4000),
"model": "gpt-3.5-turbo",
"presence_penalty": kwargs.get("presence_penalty", 0),
"temperature": kwargs.get("temperature", 1),
"top_p": kwargs.get("top_p", 1),
"stream": True,
"uuid": str(uuid.uuid4()),
}
)
res = requests.post(
"https://chat.getgpt.world/api/chat/stream",
headers=headers,
json={"signature": encrypt(data)},
stream=True,
)
for line in res.iter_lines():
if b"content" in line:
line_json = json.loads(line.decode("utf-8").split("data: ")[1])
yield (line_json["choices"][0]["delta"]["content"])
params = f"g4f.Providers.{os.path.basename(__file__)[:-3]} supports: " + "(%s)" % ", ".join(
[
f"{name}: {get_type_hints(_create_completion)[name].__name__}"
for name in _create_completion.__code__.co_varnames[: _create_completion.__code__.co_argcount]
]
)

32
chat_gpt_microservice/g4f/Provider/Providers/Gravityengine.py Normal file
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import os
from typing import get_type_hints
import requests
url = "https://gpt4.xunika.uk/"
model = ["gpt-3.5-turbo-16k", "gpt-3.5-turbo-0613"]
supports_stream = True
needs_auth = False
def _create_completion(model: str, messages: list, stream: bool, temperature: float = 0.7, **kwargs):
headers = {
"Content-Type": "application/json",
}
data = {
"model": model,
"temperature": 0.7,
"presence_penalty": 0,
"messages": messages,
}
response = requests.post(url + "/api/openai/v1/chat/completions", json=data, stream=True)
yield response.json()["choices"][0]["message"]["content"]
params = f"g4f.Providers.{os.path.basename(__file__)[:-3]} supports: " + "(%s)" % ", ".join(
[
f"{name}: {get_type_hints(_create_completion)[name].__name__}"
for name in _create_completion.__code__.co_varnames[: _create_completion.__code__.co_argcount]
]
)

114
chat_gpt_microservice/g4f/Provider/Providers/H2o.py Normal file
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import os
from json import loads
from typing import get_type_hints
from uuid import uuid4
from requests import Session
url = "https://gpt-gm.h2o.ai"
model = ["falcon-40b", "falcon-7b", "llama-13b"]
supports_stream = True
needs_auth = False
models = {
"falcon-7b": "h2oai/h2ogpt-gm-oasst1-en-2048-falcon-7b-v3",
"falcon-40b": "h2oai/h2ogpt-gm-oasst1-en-2048-falcon-40b-v1",
"llama-13b": "h2oai/h2ogpt-gm-oasst1-en-2048-open-llama-13b",
}
def _create_completion(model: str, messages: list, stream: bool, **kwargs):
conversation = "instruction: this is a conversation beween, a user and an AI assistant, respond to the latest message, referring to the conversation if needed\n"
for message in messages:
conversation += "%s: %s\n" % (message["role"], message["content"])
conversation += "assistant:"
client = Session()
client.headers = {
"authority": "gpt-gm.h2o.ai",
"origin": "https://gpt-gm.h2o.ai",
"referer": "https://gpt-gm.h2o.ai/",
"sec-ch-ua": '"Not.A/Brand";v="8", "Chromium";v="114", "Google Chrome";v="114"',
"sec-ch-ua-mobile": "?0",
"sec-ch-ua-platform": '"Windows"',
"sec-fetch-dest": "document",
"sec-fetch-mode": "navigate",
"sec-fetch-site": "same-origin",
"sec-fetch-user": "?1",
"upgrade-insecure-requests": "1",
"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",
}
client.get("https://gpt-gm.h2o.ai/")
response = client.post(
"https://gpt-gm.h2o.ai/settings",
data={
"ethicsModalAccepted": "true",
"shareConversationsWithModelAuthors": "true",
"ethicsModalAcceptedAt": "",
"activeModel": "h2oai/h2ogpt-gm-oasst1-en-2048-falcon-40b-v1",
"searchEnabled": "true",
},
)
headers = {
"authority": "gpt-gm.h2o.ai",
"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",
"origin": "https://gpt-gm.h2o.ai",
"referer": "https://gpt-gm.h2o.ai/",
"sec-ch-ua": '"Not.A/Brand";v="8", "Chromium";v="114", "Google Chrome";v="114"',
"sec-ch-ua-mobile": "?0",
"sec-ch-ua-platform": '"Windows"',
"sec-fetch-dest": "empty",
"sec-fetch-mode": "cors",
"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",
}
json_data = {"model": models[model]}
response = client.post("https://gpt-gm.h2o.ai/conversation", headers=headers, json=json_data)
conversationId = response.json()["conversationId"]
completion = client.post(
f"https://gpt-gm.h2o.ai/conversation/{conversationId}",
stream=True,
json={
"inputs": conversation,
"parameters": {
"temperature": kwargs.get("temperature", 0.4),
"truncate": kwargs.get("truncate", 2048),
"max_new_tokens": kwargs.get("max_new_tokens", 1024),
"do_sample": kwargs.get("do_sample", True),
"repetition_penalty": kwargs.get("repetition_penalty", 1.2),
"return_full_text": kwargs.get("return_full_text", False),
},
"stream": True,
"options": {
"id": kwargs.get("id", str(uuid4())),
"response_id": kwargs.get("response_id", str(uuid4())),
"is_retry": False,
"use_cache": False,
"web_search_id": "",
},
},
)
for line in completion.iter_lines():
if b"data" in line:
line = loads(line.decode("utf-8").replace("data:", ""))
token = line["token"]["text"]
if token == "<|endoftext|>":
break
else:
yield (token)
params = f"g4f.Providers.{os.path.basename(__file__)[:-3]} supports: " + "(%s)" % ", ".join(
[
f"{name}: {get_type_hints(_create_completion)[name].__name__}"
for name in _create_completion.__code__.co_varnames[: _create_completion.__code__.co_argcount]
]
)

60
chat_gpt_microservice/g4f/Provider/Providers/Liaobots.py Normal file
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import os
from typing import get_type_hints
import requests
url = "https://liaobots.com"
model = ["gpt-3.5-turbo", "gpt-3.5-turbo-16k", "gpt-4"]
supports_stream = True
needs_auth = True
working = False
models = {
"gpt-4": {"id": "gpt-4", "name": "GPT-4", "maxLength": 24000, "tokenLimit": 8000},
"gpt-3.5-turbo": {
"id": "gpt-3.5-turbo",
"name": "GPT-3.5",
"maxLength": 12000,
"tokenLimit": 4000,
},
"gpt-3.5-turbo-16k": {
"id": "gpt-3.5-turbo-16k",
"name": "GPT-3.5-16k",
"maxLength": 48000,
"tokenLimit": 16000,
},
}
def _create_completion(model: str, messages: list, stream: bool, chatId: str, **kwargs):
print(kwargs)
headers = {
"authority": "liaobots.com",
"content-type": "application/json",
"origin": "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",
"x-auth-code": "qlcUMVn1KLMhd",
}
json_data = {
"conversationId": chatId,
"model": models[model],
"messages": messages,
"key": "",
"prompt": "You are ChatGPT, a large language model trained by OpenAI. Follow the user's instructions carefully. Respond using markdown.",
}
response = requests.post("https://liaobots.com/api/chat", headers=headers, json=json_data, stream=True)
for token in response.iter_content(chunk_size=2046):
yield (token.decode("utf-8"))
params = f"g4f.Providers.{os.path.basename(__file__)[:-3]} supports: " + "(%s)" % ", ".join(
[
f"{name}: {get_type_hints(_create_completion)[name].__name__}"
for name in _create_completion.__code__.co_varnames[: _create_completion.__code__.co_argcount]
]
)

50
chat_gpt_microservice/g4f/Provider/Providers/Lockchat.py Normal file
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import json
import os
from typing import get_type_hints
import requests
url = "http://supertest.lockchat.app"
model = ["gpt-4", "gpt-3.5-turbo"]
supports_stream = True
needs_auth = False
def _create_completion(model: str, messages: list, stream: bool, temperature: float = 0.7, **kwargs):
payload = {
"temperature": 0.7,
"messages": messages,
"model": model,
"stream": True,
}
headers = {
"user-agent": "ChatX/39 CFNetwork/1408.0.4 Darwin/22.5.0",
}
response = requests.post(
"http://supertest.lockchat.app/v1/chat/completions",
json=payload,
headers=headers,
stream=True,
)
for token in response.iter_lines():
if b"The model: `gpt-4` does not exist" in token:
print("error, retrying...")
_create_completion(
model=model,
messages=messages,
stream=stream,
temperature=temperature,
**kwargs,
)
if b"content" in token:
token = json.loads(token.decode("utf-8").split("data: ")[1])["choices"][0]["delta"].get("content")
if token:
yield (token)
params = f"g4f.Providers.{os.path.basename(__file__)[:-3]} supports: " + "(%s)" % ", ".join(
[
f"{name}: {get_type_hints(_create_completion)[name].__name__}"
for name in _create_completion.__code__.co_varnames[: _create_completion.__code__.co_argcount]
]
)

26
chat_gpt_microservice/g4f/Provider/Providers/Mishalsgpt.py Normal file
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import os
from typing import get_type_hints
import requests
url = "https://mishalsgpt.vercel.app"
model = ["gpt-3.5-turbo-16k-0613", "gpt-3.5-turbo"]
supports_stream = True
needs_auth = False
def _create_completion(model: str, messages: list, stream: bool, **kwargs):
headers = {
"Content-Type": "application/json",
}
data = {"model": model, "temperature": 0.7, "messages": messages}
response = requests.post(url + "/api/openai/v1/chat/completions", headers=headers, json=data, stream=True)
yield response.json()["choices"][0]["message"]["content"]
params = f"g4f.Providers.{os.path.basename(__file__)[:-3]} supports: " + "(%s)" % ", ".join(
[
f"{name}: {get_type_hints(_create_completion)[name].__name__}"
for name in _create_completion.__code__.co_varnames[: _create_completion.__code__.co_argcount]
]
)

37
chat_gpt_microservice/g4f/Provider/Providers/Phind.py Normal file
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import json
import os
import subprocess
from typing import get_type_hints
url = "https://phind.com"
model = ["gpt-4"]
supports_stream = True
def _create_completion(model: str, messages: list, stream: bool, **kwargs):
path = os.path.dirname(os.path.realpath(__file__))
config = json.dumps({"model": model, "messages": messages}, separators=(",", ":"))
cmd = ["python", f"{path}/helpers/phind.py", config]
p = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.STDOUT)
for line in iter(p.stdout.readline, b""):
if b"<title>Just a moment...</title>" in line:
os.system("clear" if os.name == "posix" else "cls")
yield "Clouflare error, please try again..."
os._exit(0)
else:
if b"ping - 2023-" in line:
continue
yield line.decode("cp1251") # [:-1]
params = f"g4f.Providers.{os.path.basename(__file__)[:-3]} supports: " + "(%s)" % ", ".join(
[
f"{name}: {get_type_hints(_create_completion)[name].__name__}"
for name in _create_completion.__code__.co_varnames[: _create_completion.__code__.co_argcount]
]
)

29
chat_gpt_microservice/g4f/Provider/Providers/Theb.py Normal file
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import json
import os
import subprocess
from typing import get_type_hints
url = "https://theb.ai"
model = ["gpt-3.5-turbo"]
supports_stream = True
needs_auth = False
def _create_completion(model: str, messages: list, stream: bool, **kwargs):
path = os.path.dirname(os.path.realpath(__file__))
config = json.dumps({"messages": messages, "model": model}, separators=(",", ":"))
cmd = ["python3", f"{path}/helpers/theb.py", config]
p = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.STDOUT)
for line in iter(p.stdout.readline, b""):
yield line.decode("utf-8")
params = f"g4f.Providers.{os.path.basename(__file__)[:-3]} supports: " + "(%s)" % ", ".join(
[
f"{name}: {get_type_hints(_create_completion)[name].__name__}"
for name in _create_completion.__code__.co_varnames[: _create_completion.__code__.co_argcount]
]
)

514
chat_gpt_microservice/g4f/Provider/Providers/Vercel.py Normal file
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import base64
import json
import os
import queue
import threading
from typing import get_type_hints
import execjs
from curl_cffi import requests
url = "https://play.vercel.ai"
supports_stream = True
needs_auth = False
models = {
"claude-instant-v1": "anthropic:claude-instant-v1",
"claude-v1": "anthropic:claude-v1",
"alpaca-7b": "replicate:replicate/alpaca-7b",
"stablelm-tuned-alpha-7b": "replicate:stability-ai/stablelm-tuned-alpha-7b",
"bloom": "huggingface:bigscience/bloom",
"bloomz": "huggingface:bigscience/bloomz",
"flan-t5-xxl": "huggingface:google/flan-t5-xxl",
"flan-ul2": "huggingface:google/flan-ul2",
"gpt-neox-20b": "huggingface:EleutherAI/gpt-neox-20b",
"oasst-sft-4-pythia-12b-epoch-3.5": "huggingface:OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5",
"santacoder": "huggingface:bigcode/santacoder",
"command-medium-nightly": "cohere:command-medium-nightly",
"command-xlarge-nightly": "cohere:command-xlarge-nightly",
"code-cushman-001": "openai:code-cushman-001",
"code-davinci-002": "openai:code-davinci-002",
"gpt-3.5-turbo": "openai:gpt-3.5-turbo",
"text-ada-001": "openai:text-ada-001",
"text-babbage-001": "openai:text-babbage-001",
"text-curie-001": "openai:text-curie-001",
"text-davinci-002": "openai:text-davinci-002",
"text-davinci-003": "openai:text-davinci-003",
}
model = models.keys()
vercel_models = {
"anthropic:claude-instant-v1": {
"id": "anthropic:claude-instant-v1",
"provider": "anthropic",
"providerHumanName": "Anthropic",
"makerHumanName": "Anthropic",
"minBillingTier": "hobby",
"parameters": {
"temperature": {"value": 1, "range": [0, 1]},
"maximumLength": {"value": 200, "range": [50, 1024]},
"topP": {"value": 1, "range": [0.1, 1]},
"topK": {"value": 1, "range": [1, 500]},
"presencePenalty": {"value": 1, "range": [0, 1]},
"frequencyPenalty": {"value": 1, "range": [0, 1]},
"stopSequences": {"value": ["\n\nHuman:"], "range": []},
},
"name": "claude-instant-v1",
},
"anthropic:claude-v1": {
"id": "anthropic:claude-v1",
"provider": "anthropic",
"providerHumanName": "Anthropic",
"makerHumanName": "Anthropic",
"minBillingTier": "hobby",
"parameters": {
"temperature": {"value": 1, "range": [0, 1]},
"maximumLength": {"value": 200, "range": [50, 1024]},
"topP": {"value": 1, "range": [0.1, 1]},
"topK": {"value": 1, "range": [1, 500]},
"presencePenalty": {"value": 1, "range": [0, 1]},
"frequencyPenalty": {"value": 1, "range": [0, 1]},
"stopSequences": {"value": ["\n\nHuman:"], "range": []},
},
"name": "claude-v1",
},
"replicate:replicate/alpaca-7b": {
"id": "replicate:replicate/alpaca-7b",
"provider": "replicate",
"providerHumanName": "Replicate",
"makerHumanName": "Stanford",
"parameters": {
"temperature": {"value": 0.75, "range": [0.01, 5]},
"maximumLength": {"value": 200, "range": [50, 512]},
"topP": {"value": 0.95, "range": [0.01, 1]},
"presencePenalty": {"value": 0, "range": [0, 1]},
"frequencyPenalty": {"value": 0, "range": [0, 1]},
"repetitionPenalty": {"value": 1.1765, "range": [0.01, 5]},
"stopSequences": {"value": [], "range": []},
},
"version": "2014ee1247354f2e81c0b3650d71ca715bc1e610189855f134c30ecb841fae21",
"name": "alpaca-7b",
},
"replicate:stability-ai/stablelm-tuned-alpha-7b": {
"id": "replicate:stability-ai/stablelm-tuned-alpha-7b",
"provider": "replicate",
"makerHumanName": "StabilityAI",
"providerHumanName": "Replicate",
"parameters": {
"temperature": {"value": 0.75, "range": [0.01, 5]},
"maximumLength": {"value": 200, "range": [50, 512]},
"topP": {"value": 0.95, "range": [0.01, 1]},
"presencePenalty": {"value": 0, "range": [0, 1]},
"frequencyPenalty": {"value": 0, "range": [0, 1]},
"repetitionPenalty": {"value": 1.1765, "range": [0.01, 5]},
"stopSequences": {"value": [], "range": []},
},
"version": "4a9a32b4fd86c2d047f1d271fa93972683ec6ef1cf82f402bd021f267330b50b",
"name": "stablelm-tuned-alpha-7b",
},
"huggingface:bigscience/bloom": {
"id": "huggingface:bigscience/bloom",
"provider": "huggingface",
"providerHumanName": "HuggingFace",
"makerHumanName": "BigScience",
"instructions": "Do NOT talk to Bloom as an entity, it's not a chatbot but a webpage/blog/article completion model. For the best results: mimic a few words of a webpage similar to the content you want to generate. Start a sentence as if YOU were writing a blog, webpage, math post, coding article and Bloom will generate a coherent follow-up.",
"parameters": {
"temperature": {"value": 0.5, "range": [0.1, 1]},
"maximumLength": {"value": 200, "range": [50, 1024]},
"topP": {"value": 0.95, "range": [0.01, 0.99]},
"topK": {"value": 4, "range": [1, 500]},
"repetitionPenalty": {"value": 1.03, "range": [0.1, 2]},
},
"name": "bloom",
},
"huggingface:bigscience/bloomz": {
"id": "huggingface:bigscience/bloomz",
"provider": "huggingface",
"providerHumanName": "HuggingFace",
"makerHumanName": "BigScience",
"instructions": 'We recommend using the model to perform tasks expressed in natural language. For example, given the prompt "Translate to English: Je t\'aime.", the model will most likely answer "I love you.".',
"parameters": {
"temperature": {"value": 0.5, "range": [0.1, 1]},
"maximumLength": {"value": 200, "range": [50, 1024]},
"topP": {"value": 0.95, "range": [0.01, 0.99]},
"topK": {"value": 4, "range": [1, 500]},
"repetitionPenalty": {"value": 1.03, "range": [0.1, 2]},
},
"name": "bloomz",
},
"huggingface:google/flan-t5-xxl": {
"id": "huggingface:google/flan-t5-xxl",
"provider": "huggingface",
"makerHumanName": "Google",
"providerHumanName": "HuggingFace",
"name": "flan-t5-xxl",
"parameters": {
"temperature": {"value": 0.5, "range": [0.1, 1]},
"maximumLength": {"value": 200, "range": [50, 1024]},
"topP": {"value": 0.95, "range": [0.01, 0.99]},
"topK": {"value": 4, "range": [1, 500]},
"repetitionPenalty": {"value": 1.03, "range": [0.1, 2]},
},
},
"huggingface:google/flan-ul2": {
"id": "huggingface:google/flan-ul2",
"provider": "huggingface",
"providerHumanName": "HuggingFace",
"makerHumanName": "Google",
"parameters": {
"temperature": {"value": 0.5, "range": [0.1, 1]},
"maximumLength": {"value": 200, "range": [50, 1024]},
"topP": {"value": 0.95, "range": [0.01, 0.99]},
"topK": {"value": 4, "range": [1, 500]},
"repetitionPenalty": {"value": 1.03, "range": [0.1, 2]},
},
"name": "flan-ul2",
},
"huggingface:EleutherAI/gpt-neox-20b": {
"id": "huggingface:EleutherAI/gpt-neox-20b",
"provider": "huggingface",
"providerHumanName": "HuggingFace",
"makerHumanName": "EleutherAI",
"parameters": {
"temperature": {"value": 0.5, "range": [0.1, 1]},
"maximumLength": {"value": 200, "range": [50, 1024]},
"topP": {"value": 0.95, "range": [0.01, 0.99]},
"topK": {"value": 4, "range": [1, 500]},
"repetitionPenalty": {"value": 1.03, "range": [0.1, 2]},
"stopSequences": {"value": [], "range": []},
},
"name": "gpt-neox-20b",
},
"huggingface:OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5": {
"id": "huggingface:OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5",
"provider": "huggingface",
"providerHumanName": "HuggingFace",
"makerHumanName": "OpenAssistant",
"parameters": {
"maximumLength": {"value": 200, "range": [50, 1024]},
"typicalP": {"value": 0.2, "range": [0.1, 0.99]},
"repetitionPenalty": {"value": 1, "range": [0.1, 2]},
},
"name": "oasst-sft-4-pythia-12b-epoch-3.5",
},
"huggingface:bigcode/santacoder": {
"id": "huggingface:bigcode/santacoder",
"provider": "huggingface",
"providerHumanName": "HuggingFace",
"makerHumanName": "BigCode",
"instructions": 'The model was trained on GitHub code. As such it is not an instruction model and commands like "Write a function that computes the square root." do not work well. You should phrase commands like they occur in source code such as comments (e.g. # the following function computes the sqrt) or write a function signature and docstring and let the model complete the function body.',
"parameters": {
"temperature": {"value": 0.5, "range": [0.1, 1]},
"maximumLength": {"value": 200, "range": [50, 1024]},
"topP": {"value": 0.95, "range": [0.01, 0.99]},
"topK": {"value": 4, "range": [1, 500]},
"repetitionPenalty": {"value": 1.03, "range": [0.1, 2]},
},
"name": "santacoder",
},
"cohere:command-medium-nightly": {
"id": "cohere:command-medium-nightly",
"provider": "cohere",
"providerHumanName": "Cohere",
"makerHumanName": "Cohere",
"name": "command-medium-nightly",
"parameters": {
"temperature": {"value": 0.9, "range": [0, 2]},
"maximumLength": {"value": 200, "range": [50, 1024]},
"topP": {"value": 1, "range": [0, 1]},
"topK": {"value": 0, "range": [0, 500]},
"presencePenalty": {"value": 0, "range": [0, 1]},
"frequencyPenalty": {"value": 0, "range": [0, 1]},
"stopSequences": {"value": [], "range": []},
},
},
"cohere:command-xlarge-nightly": {
"id": "cohere:command-xlarge-nightly",
"provider": "cohere",
"providerHumanName": "Cohere",
"makerHumanName": "Cohere",
"name": "command-xlarge-nightly",
"parameters": {
"temperature": {"value": 0.9, "range": [0, 2]},
"maximumLength": {"value": 200, "range": [50, 1024]},
"topP": {"value": 1, "range": [0, 1]},
"topK": {"value": 0, "range": [0, 500]},
"presencePenalty": {"value": 0, "range": [0, 1]},
"frequencyPenalty": {"value": 0, "range": [0, 1]},
"stopSequences": {"value": [], "range": []},
},
},
"openai:gpt-4": {
"id": "openai:gpt-4",
"provider": "openai",
"providerHumanName": "OpenAI",
"makerHumanName": "OpenAI",
"name": "gpt-4",
"minBillingTier": "pro",
"parameters": {
"temperature": {"value": 0.7, "range": [0.1, 1]},
"maximumLength": {"value": 200, "range": [50, 1024]},
"topP": {"value": 1, "range": [0.1, 1]},
"presencePenalty": {"value": 0, "range": [0, 1]},
"frequencyPenalty": {"value": 0, "range": [0, 1]},
"stopSequences": {"value": [], "range": []},
},
},
"openai:code-cushman-001": {
"id": "openai:code-cushman-001",
"provider": "openai",
"providerHumanName": "OpenAI",
"makerHumanName": "OpenAI",
"parameters": {
"temperature": {"value": 0.5, "range": [0.1, 1]},
"maximumLength": {"value": 200, "range": [50, 1024]},
"topP": {"value": 1, "range": [0.1, 1]},
"presencePenalty": {"value": 0, "range": [0, 1]},
"frequencyPenalty": {"value": 0, "range": [0, 1]},
"stopSequences": {"value": [], "range": []},
},
"name": "code-cushman-001",
},
"openai:code-davinci-002": {
"id": "openai:code-davinci-002",
"provider": "openai",
"providerHumanName": "OpenAI",
"makerHumanName": "OpenAI",
"parameters": {
"temperature": {"value": 0.5, "range": [0.1, 1]},
"maximumLength": {"value": 200, "range": [50, 1024]},
"topP": {"value": 1, "range": [0.1, 1]},
"presencePenalty": {"value": 0, "range": [0, 1]},
"frequencyPenalty": {"value": 0, "range": [0, 1]},
"stopSequences": {"value": [], "range": []},
},
"name": "code-davinci-002",
},
"openai:gpt-3.5-turbo": {
"id": "openai:gpt-3.5-turbo",
"provider": "openai",
"providerHumanName": "OpenAI",
"makerHumanName": "OpenAI",
"parameters": {
"temperature": {"value": 0.7, "range": [0, 1]},
"maximumLength": {"value": 200, "range": [50, 1024]},
"topP": {"value": 1, "range": [0.1, 1]},
"topK": {"value": 1, "range": [1, 500]},
"presencePenalty": {"value": 1, "range": [0, 1]},
"frequencyPenalty": {"value": 1, "range": [0, 1]},
"stopSequences": {"value": [], "range": []},
},
"name": "gpt-3.5-turbo",
},
"openai:text-ada-001": {
"id": "openai:text-ada-001",
"provider": "openai",
"providerHumanName": "OpenAI",
"makerHumanName": "OpenAI",
"name": "text-ada-001",
"parameters": {
"temperature": {"value": 0.5, "range": [0.1, 1]},
"maximumLength": {"value": 200, "range": [50, 1024]},
"topP": {"value": 1, "range": [0.1, 1]},
"presencePenalty": {"value": 0, "range": [0, 1]},
"frequencyPenalty": {"value": 0, "range": [0, 1]},
"stopSequences": {"value": [], "range": []},
},
},
"openai:text-babbage-001": {
"id": "openai:text-babbage-001",
"provider": "openai",
"providerHumanName": "OpenAI",
"makerHumanName": "OpenAI",
"name": "text-babbage-001",
"parameters": {
"temperature": {"value": 0.5, "range": [0.1, 1]},
"maximumLength": {"value": 200, "range": [50, 1024]},
"topP": {"value": 1, "range": [0.1, 1]},
"presencePenalty": {"value": 0, "range": [0, 1]},
"frequencyPenalty": {"value": 0, "range": [0, 1]},
"stopSequences": {"value": [], "range": []},
},
},
"openai:text-curie-001": {
"id": "openai:text-curie-001",
"provider": "openai",
"providerHumanName": "OpenAI",
"makerHumanName": "OpenAI",
"name": "text-curie-001",
"parameters": {
"temperature": {"value": 0.5, "range": [0.1, 1]},
"maximumLength": {"value": 200, "range": [50, 1024]},
"topP": {"value": 1, "range": [0.1, 1]},
"presencePenalty": {"value": 0, "range": [0, 1]},
"frequencyPenalty": {"value": 0, "range": [0, 1]},
"stopSequences": {"value": [], "range": []},
},
},
"openai:text-davinci-002": {
"id": "openai:text-davinci-002",
"provider": "openai",
"providerHumanName": "OpenAI",
"makerHumanName": "OpenAI",
"name": "text-davinci-002",
"parameters": {
"temperature": {"value": 0.5, "range": [0.1, 1]},
"maximumLength": {"value": 200, "range": [50, 1024]},
"topP": {"value": 1, "range": [0.1, 1]},
"presencePenalty": {"value": 0, "range": [0, 1]},
"frequencyPenalty": {"value": 0, "range": [0, 1]},
"stopSequences": {"value": [], "range": []},
},
},
"openai:text-davinci-003": {
"id": "openai:text-davinci-003",
"provider": "openai",
"providerHumanName": "OpenAI",
"makerHumanName": "OpenAI",
"name": "text-davinci-003",
"parameters": {
"temperature": {"value": 0.5, "range": [0.1, 1]},
"maximumLength": {"value": 200, "range": [50, 1024]},
"topP": {"value": 1, "range": [0.1, 1]},
"presencePenalty": {"value": 0, "range": [0, 1]},
"frequencyPenalty": {"value": 0, "range": [0, 1]},
"stopSequences": {"value": [], "range": []},
},
},
}
# based on https://github.com/ading2210/vercel-llm-api // modified
class Client:
def __init__(self):
self.session = requests.Session()
self.headers = {
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/110 Safari/537.36",
"Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,*/*;q=0.8",
"Accept-Encoding": "gzip, deflate, br",
"Accept-Language": "en-US,en;q=0.5",
"Te": "trailers",
"Upgrade-Insecure-Requests": "1",
}
self.session.headers.update(self.headers)
def get_token(self):
b64 = self.session.get("https://sdk.vercel.ai/openai.jpeg").text
data = json.loads(base64.b64decode(b64))
code = "const globalThis = {data: `sentinel`}; function token() {return (%s)(%s)}" % (data["c"], data["a"])
token_string = json.dumps(
separators=(",", ":"),
obj={"r": execjs.compile(code).call("token"), "t": data["t"]},
)
return base64.b64encode(token_string.encode()).decode()
def get_default_params(self, model_id):
return {key: param["value"] for key, param in vercel_models[model_id]["parameters"].items()}
def generate(self, model_id: str, prompt: str, params: dict = {}):
if not ":" in model_id:
model_id = models[model_id]
defaults = self.get_default_params(model_id)
payload = (
defaults
| params
| {
"prompt": prompt,
"model": model_id,
}
)
headers = self.headers | {
"Accept-Encoding": "gzip, deflate, br",
"Custom-Encoding": self.get_token(),
"Host": "sdk.vercel.ai",
"Origin": "https://sdk.vercel.ai",
"Referrer": "https://sdk.vercel.ai",
"Sec-Fetch-Dest": "empty",
"Sec-Fetch-Mode": "cors",
"Sec-Fetch-Site": "same-origin",
}
chunks_queue = queue.Queue()
error = None
response = None
def callback(data):
chunks_queue.put(data.decode())
def request_thread():
nonlocal response, error
for _ in range(3):
try:
response = self.session.post(
"https://sdk.vercel.ai/api/generate",
json=payload,
headers=headers,
content_callback=callback,
)
response.raise_for_status()
except Exception as e:
if _ == 2:
error = e
else:
continue
thread = threading.Thread(target=request_thread, daemon=True)
thread.start()
text = ""
index = 0
while True:
try:
chunk = chunks_queue.get(block=True, timeout=0.1)
except queue.Empty:
if error:
raise error
elif response:
break
else:
continue
text += chunk
lines = text.split("\n")
if len(lines) - 1 > index:
new = lines[index:-1]
for word in new:
yield json.loads(word)
index = len(lines) - 1
def _create_completion(model: str, messages: list, stream: bool, **kwargs):
yield "Vercel is currently not working."
return
conversation = "This is a conversation between a human and a language model, respond to the last message accordingly, referring to the past history of messages if needed.\n"
for message in messages:
conversation += "%s: %s\n" % (message["role"], message["content"])
conversation += "assistant: "
completion = Client().generate(model, conversation)
for token in completion:
yield token
params = f"g4f.Providers.{os.path.basename(__file__)[:-3]} supports: " + "(%s)" % ", ".join(
[
f"{name}: {get_type_hints(_create_completion)[name].__name__}"
for name in _create_completion.__code__.co_varnames[: _create_completion.__code__.co_argcount]
]
)

39
chat_gpt_microservice/g4f/Provider/Providers/Weuseing.py Normal file
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import os
from typing import get_type_hints
import requests
url = "https://api.gptplus.one"
model = [
"gpt-3.5-turbo",
"gpt-3.5-turbo-16k",
"gpt-3.5-turbo-16k-0613",
"gpt-3.5-turbo-0613",
]
supports_stream = True
needs_auth = False
def _create_completion(model: str, messages: list, stream: bool, temperature: float = 0.7, **kwargs):
headers = {
"Content-Type": "application/json",
"Accept": "*/*",
"Accept-Language": "ru-RU,ru;q=0.9,en-US;q=0.8,en;q=0.7,ja;q=0.6,zh-TW;q=0.5,zh;q=0.4",
}
data = {
"messages": messages,
"model": model,
}
response = requests.post("https://api.gptplus.one/chat-process", json=data, stream=True)
print(response)
for token in response.iter_content(chunk_size=None):
yield (token.decode("utf-8"))
params = f"g4f.Providers.{os.path.basename(__file__)[:-3]} supports: " + "(%s)" % ", ".join(
[
f"{name}: {get_type_hints(_create_completion)[name].__name__}"
for name in _create_completion.__code__.co_varnames[: _create_completion.__code__.co_argcount]
]
)

72
chat_gpt_microservice/g4f/Provider/Providers/Wewordle.py Normal file
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import json
import os
import random
import string
import time
from typing import get_type_hints
import requests
url = "https://wewordle.org/gptapi/v1/android/turbo"
model = ["gpt-3.5-turbo"]
supports_stream = False
needs_auth = False
def _create_completion(model: str, messages: list, stream: bool, **kwargs):
base = ""
for message in messages:
base += "%s: %s\n" % (message["role"], message["content"])
base += "assistant:"
# randomize user id and app id
_user_id = "".join(random.choices(f"{string.ascii_lowercase}{string.digits}", k=16))
_app_id = "".join(random.choices(f"{string.ascii_lowercase}{string.digits}", k=31))
# make current date with format utc
_request_date = time.strftime("%Y-%m-%dT%H:%M:%S.000Z", time.gmtime())
headers = {
"accept": "*/*",
"pragma": "no-cache",
"Content-Type": "application/json",
"Connection": "keep-alive",
}
data = {
"user": _user_id,
"messages": [{"role": "user", "content": base}],
"subscriber": {
"originalPurchaseDate": None,
"originalApplicationVersion": None,
"allPurchaseDatesMillis": {},
"entitlements": {"active": {}, "all": {}},
"allPurchaseDates": {},
"allExpirationDatesMillis": {},
"allExpirationDates": {},
"originalAppUserId": f"$RCAnonymousID:{_app_id}",
"latestExpirationDate": None,
"requestDate": _request_date,
"latestExpirationDateMillis": None,
"nonSubscriptionTransactions": [],
"originalPurchaseDateMillis": None,
"managementURL": None,
"allPurchasedProductIdentifiers": [],
"firstSeen": _request_date,
"activeSubscriptions": [],
},
}
response = requests.post(url, headers=headers, data=json.dumps(data))
if response.status_code == 200:
_json = response.json()
if "message" in _json:
message_content = _json["message"]["content"]
message_content = message_content.replace("**assistant:** ", "")
yield message_content
else:
print(f"Error Occurred::{response.status_code}")
return None
params = f"g4f.Providers.{os.path.basename(__file__)[:-3]} supports: " + "(%s)" % ", ".join(
[
f"{name}: {get_type_hints(_create_completion)[name].__name__}"
for name in _create_completion.__code__.co_varnames[: _create_completion.__code__.co_argcount]
]
)

46
chat_gpt_microservice/g4f/Provider/Providers/Xiaor.py Normal file
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import json
import os
from typing import get_type_hints
import requests
url = "https://xiaor.eu.org"
model = [
"gpt-3.5-turbo",
"gpt-3.5-turbo-16k",
"gpt-3.5-turbo-16k-0613",
"gpt-3.5-turbo-0613",
]
supports_stream = True
needs_auth = False
def _create_completion(model: str, messages: list, stream: bool, temperature: float = 0.7, **kwargs):
headers = {
"Content-Type": "application/json",
}
data = {
"model": model,
"temperature": 0.7,
"presence_penalty": 0,
"messages": messages,
}
response = requests.post(url + "/p1/v1/chat/completions", json=data, stream=True)
if stream:
for chunk in response.iter_content(chunk_size=None):
chunk = chunk.decode("utf-8")
if chunk.strip():
message = json.loads(chunk)["choices"][0]["message"]["content"]
yield message
else:
message = response.json()["choices"][0]["message"]["content"]
yield message
params = f"g4f.Providers.{os.path.basename(__file__)[:-3]} supports: " + "(%s)" % ", ".join(
[
f"{name}: {get_type_hints(_create_completion)[name].__name__}"
for name in _create_completion.__code__.co_varnames[: _create_completion.__code__.co_argcount]
]
)

20
chat_gpt_microservice/g4f/Provider/Providers/You.py Normal file
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import json
import os
import subprocess
url = "https://you.com"
model = "gpt-3.5-turbo"
supports_stream = True
needs_auth = False
def _create_completion(model: str, messages: list, stream: bool, **kwargs):
path = os.path.dirname(os.path.realpath(__file__))
config = json.dumps({"messages": messages}, separators=(",", ":"))
cmd = ["python3", f"{path}/helpers/you.py", config]
p = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.STDOUT)
for line in iter(p.stdout.readline, b""):
yield line.decode("utf-8") # [:-1]

45
chat_gpt_microservice/g4f/Provider/Providers/Yqcloud.py Normal file
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import os
from typing import get_type_hints
import requests
url = "https://chat9.yqcloud.top/"
model = [
"gpt-3.5-turbo",
]
supports_stream = True
needs_auth = False
def _create_completion(model: str, messages: list, stream: bool, chatId: str, **kwargs):
headers = {
"authority": "api.aichatos.cloud",
"origin": "https://chat9.yqcloud.top",
"referer": "https://chat9.yqcloud.top/",
"user-agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/112.0.0.0 Safari/537.36",
}
json_data = {
"prompt": str(messages),
"userId": f"#/chat/{chatId}",
"network": True,
"apikey": "",
"system": "",
"withoutContext": False,
}
response = requests.post(
"https://api.aichatos.cloud/api/generateStream",
headers=headers,
json=json_data,
stream=True,
)
for token in response.iter_content(chunk_size=2046):
yield (token.decode("utf-8"))
params = f"g4f.Providers.{os.path.basename(__file__)[:-3]} supports: " + "(%s)" % ", ".join(
[
f"{name}: {get_type_hints(_create_completion)[name].__name__}"
for name in _create_completion.__code__.co_varnames[: _create_completion.__code__.co_argcount]
]
)

63
chat_gpt_microservice/g4f/Provider/Providers/Zeabur.py Normal file
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import os
from typing import get_type_hints
import requests
url = "https://gptleg.zeabur.app"
model = [
"gpt-3.5-turbo",
"gpt-3.5-turbo-0301",
"gpt-3.5-turbo-16k",
"gpt-4",
"gpt-4-0613",
]
supports_stream = True
needs_auth = False
def _create_completion(model: str, messages: list, stream: bool, **kwargs):
headers = {
"Authority": "chat.dfehub.com",
"Content-Type": "application/json",
"Method": "POST",
"Path": "/api/openai/v1/chat/completions",
"Scheme": "https",
"Accept": "text/event-stream",
"Accept-Language": "pt-BR,pt;q=0.9,en-US;q=0.8,en;q=0.7,zh-CN;q=0.6,zh;q=0.5",
"Content-Type": "application/json",
"Origin": "https://gptleg.zeabur.app",
"Referer": "https://gptleg.zeabur.app/",
"Sec-Ch-Ua": '"Not.A/Brand";v="8", "Chromium";v="114", "Google Chrome";v="114"',
"Sec-Ch-Ua-Mobile": "?0",
"Sec-Ch-Ua-Platform": '"Windows"',
"Sec-Fetch-Dest": "empty",
"Sec-Fetch-Mode": "cors",
"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",
"X-Requested-With": "XMLHttpRequest",
}
data = {
"model": model,
"temperature": 0.7,
"max_tokens": "16000",
"presence_penalty": 0,
"messages": messages,
}
response = requests.post(
url + "/api/openai/v1/chat/completions",
headers=headers,
json=data,
stream=stream,
)
yield response.json()["choices"][0]["message"]["content"]
params = f"g4f.Providers.{os.path.basename(__file__)[:-3]} supports: " + "(%s)" % ", ".join(
[
f"{name}: {get_type_hints(_create_completion)[name].__name__}"
for name in _create_completion.__code__.co_varnames[: _create_completion.__code__.co_argcount]
]
)

0
chat_gpt_microservice/g4f/Provider/Providers/__init__.py Normal file
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0
chat_gpt_microservice/g4f/Provider/Providers/helpers/__init__.py Normal file
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53
chat_gpt_microservice/g4f/Provider/Providers/helpers/gpt4love.py Normal file
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import json
import sys
from re import findall
from curl_cffi import requests
config = json.loads(sys.argv[1])
prompt = config["messages"][-1]["content"]
headers = {
"authority": "api.gptplus.one",
"accept": "application/json, text/plain, */*",
"accept-language": "ru-RU,ru;q=0.9,en-US;q=0.8,en;q=0.7,ja;q=0.6,zh-TW;q=0.5,zh;q=0.4",
"content-type": "application/octet-stream",
"origin": "https://ai.gptforlove.com/",
"referer": "https://ai.gptforlove.com/",
"sec-ch-ua": '"Google Chrome";v="113", "Chromium";v="113", "Not-A.Brand";v="24"',
"sec-ch-ua-mobile": "?0",
"sec-ch-ua-platform": '"macOS"',
"sec-fetch-dest": "empty",
"sec-fetch-mode": "cors",
"sec-fetch-site": "cross-site",
"user-agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/113.0.0.0 Safari/537.36",
}
json_data = {"prompt": prompt, "options": {}}
def format(chunk):
try:
completion_chunk = findall(r'content":"(.*)"},"fin', chunk.decode())[0]
print(completion_chunk, flush=True, end="")
except Exception:
print(f"[ERROR] an error occured, retrying... | [[{chunk.decode()}]]", flush=True)
return
while True:
try:
response = requests.post(
"https://api.gptplus.one/api/chat-process",
headers=headers,
json=json_data,
content_callback=format,
impersonate="chrome110",
)
exit(0)
except Exception as e:
print("[ERROR] an error occured, retrying... |", e, flush=True)
continue

81
chat_gpt_microservice/g4f/Provider/Providers/helpers/phind.py Normal file
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import datetime
import json
import sys
import urllib.parse
from curl_cffi import requests
config = json.loads(sys.argv[1])
prompt = config["messages"][-1]["content"]
skill = "expert" if config["model"] == "gpt-4" else "intermediate"
json_data = json.dumps(
{
"question": prompt,
"options": {
"skill": skill,
"date": datetime.datetime.now().strftime("%d/%m/%Y"),
"language": "en",
"detailed": True,
"creative": True,
"customLinks": [],
},
},
separators=(",", ":"),
)
headers = {
"Content-Type": "application/json",
"Pragma": "no-cache",
"Accept": "*/*",
"Sec-Fetch-Site": "same-origin",
"Accept-Language": "en-GB,en;q=0.9",
"Cache-Control": "no-cache",
"Sec-Fetch-Mode": "cors",
"Content-Length": str(len(json_data)),
"Origin": "https://www.phind.com",
"User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/16.4 Safari/605.1.15",
"Referer": f"https://www.phind.com/search?q={urllib.parse.quote(prompt)}&source=searchbox",
"Connection": "keep-alive",
"Host": "www.phind.com",
"Sec-Fetch-Dest": "empty",
}
def output(chunk):
try:
if b"PHIND_METADATA" in chunk:
return
if chunk == b"data: \r\ndata: \r\ndata: \r\n\r\n":
chunk = b"data: \n\r\n\r\n"
chunk = chunk.decode()
chunk = chunk.replace("data: \r\n\r\ndata: ", "data: \n")
chunk = chunk.replace("\r\ndata: \r\ndata: \r\n\r\n", "\n\r\n\r\n")
chunk = chunk.replace("data: ", "").replace("\r\n\r\n", "")
print(chunk, flush=True, end="")
except json.decoder.JSONDecodeError:
pass
while True:
try:
response = requests.post(
"https://www.phind.com/api/infer/answer",
headers=headers,
data=json_data,
content_callback=output,
timeout=999999,
impersonate="safari15_5",
)
exit(0)
except Exception as e:
print("an error occured, retrying... |", e, flush=True)
continue

53
chat_gpt_microservice/g4f/Provider/Providers/helpers/theb.py Normal file
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@@ -0,0 +1,53 @@
import json
import sys
from re import findall
from curl_cffi import requests
config = json.loads(sys.argv[1])
prompt = config["messages"][-1]["content"]
headers = {
"authority": "chatbot.theb.ai",
"accept": "application/json, text/plain, */*",
"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",
"origin": "https://chatbot.theb.ai",
"referer": "https://chatbot.theb.ai/",
"sec-ch-ua": '"Google Chrome";v="113", "Chromium";v="113", "Not-A.Brand";v="24"',
"sec-ch-ua-mobile": "?0",
"sec-ch-ua-platform": '"macOS"',
"sec-fetch-dest": "empty",
"sec-fetch-mode": "cors",
"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/113.0.0.0 Safari/537.36",
}
json_data = {"prompt": prompt, "options": {}}
def format(chunk):
try:
completion_chunk = findall(r'content":"(.*)"},"fin', chunk.decode())[0]
print(completion_chunk, flush=True, end="")
except Exception:
print(f"[ERROR] an error occured, retrying... | [[{chunk.decode()}]]", flush=True)
return
while True:
try:
response = requests.post(
"https://chatbot.theb.ai/api/chat-process",
headers=headers,
json=json_data,
content_callback=format,
impersonate="chrome110",
)
exit(0)
except Exception as e:
print("[ERROR] an error occured, retrying... |", e, flush=True)
continue

82
chat_gpt_microservice/g4f/Provider/Providers/helpers/you.py Normal file
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import json
import sys
import urllib.parse
from curl_cffi import requests
config = json.loads(sys.argv[1])
messages = config["messages"]
prompt = ""
def transform(messages: list) -> list:
result = []
i = 0
while i < len(messages):
if messages[i]["role"] == "user":
question = messages[i]["content"]
i += 1
if i < len(messages) and messages[i]["role"] == "assistant":
answer = messages[i]["content"]
i += 1
else:
answer = ""
result.append({"question": question, "answer": answer})
elif messages[i]["role"] == "assistant":
result.append({"question": "", "answer": messages[i]["content"]})
i += 1
elif messages[i]["role"] == "system":
result.append({"question": messages[i]["content"], "answer": ""})
i += 1
return result
headers = {
"Content-Type": "application/x-www-form-urlencoded",
"Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8",
"Sec-Fetch-Site": "same-origin",
"Accept-Language": "en-GB,en;q=0.9",
"Sec-Fetch-Mode": "navigate",
"Host": "you.com",
"Origin": "https://you.com",
"User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/16.4 Safari/605.1.15",
"Referer": "https://you.com/api/streamingSearch?q=nice&safeSearch=Moderate&onShoppingPage=false&mkt=&responseFilter=WebPages,Translations,TimeZone,Computation,RelatedSearches&domain=youchat&queryTraceId=7a6671f8-5881-404d-8ea3-c3f8301f85ba&chat=%5B%7B%22question%22%3A%22hi%22%2C%22answer%22%3A%22Hello!%20How%20can%20I%20assist%20you%20today%3F%22%7D%5D&chatId=7a6671f8-5881-404d-8ea3-c3f8301f85ba&__cf_chl_tk=ex2bw6vn5vbLsUm8J5rDYUC0Bjzc1XZqka6vUl6765A-1684108495-0-gaNycGzNDtA",
"Connection": "keep-alive",
"Sec-Fetch-Dest": "document",
"Priority": "u=0, i",
}
if messages[-1]["role"] == "user":
prompt = messages[-1]["content"]
messages = messages[:-1]
params = urllib.parse.urlencode({"q": prompt, "domain": "youchat", "chat": transform(messages)})
def output(chunk):
if b'"youChatToken"' in chunk:
chunk_json = json.loads(chunk.decode().split("data: ")[1])
print(chunk_json["youChatToken"], flush=True, end="")
while True:
try:
response = requests.get(
f"https://you.com/api/streamingSearch?{params}",
headers=headers,
content_callback=output,
impersonate="safari15_5",
)
exit(0)
except Exception as e:
print("an error occured, retrying... |", e, flush=True)
continue

44
chat_gpt_microservice/g4f/Provider/Providers/hteyun.py Normal file
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import os
from typing import get_type_hints
import requests
url = "https://hteyun.com"
model = [
"gpt-3.5-turbo",
"gpt-3.5-turbo-16k",
"gpt-3.5-turbo-16k-0613",
"gpt-3.5-turbo-0613",
]
supports_stream = True
needs_auth = False
def _create_completion(model: str, messages: list, stream: bool, temperature: float = 0.7, **kwargs):
headers = {
"Content-Type": "application/json",
"Accept": "application/json, text/plain, */*",
"Accept-Language": "ru-RU,ru;q=0.9,en-US;q=0.8,en;q=0.7,ja;q=0.6,zh-TW;q=0.5,zh;q=0.4",
"Origin": "https://hteyun.com",
"Referer": "https://hteyun.com/chat/",
}
data = {
"messages": messages,
"model": model,
"systemMessage": "You are ChatGPT, a large language model trained by OpenAI. Follow the user's instructions carefully. Respond using russian language.",
"temperature": 0.7,
"presence_penalty": 0,
}
response = requests.post(url + "/api/chat-stream", json=data, headers=headers, stream=True)
print(response.json())
# Извлечение текста из response
return response.json()["text"]
params = f"g4f.Providers.{os.path.basename(__file__)[:-3]} supports: " + "(%s)" % ", ".join(
[
f"{name}: {get_type_hints(_create_completion)[name].__name__}"
for name in _create_completion.__code__.co_varnames[: _create_completion.__code__.co_argcount]
]
)

35
chat_gpt_microservice/g4f/Provider/__init__.py Normal file
View File

@@ -0,0 +1,35 @@
from . import Provider
from .Providers import (
Aichat,
Ails,
AiService,
Bard,
Better,
Bing,
ChatFree,
ChatgptAi,
ChatgptLogin,
DeepAi,
Easychat,
Ezcht,
Fakeopen,
Forefront,
GetGpt,
Gravityengine,
H2o,
Liaobots,
Lockchat,
Mishalsgpt,
Phind,
Theb,
Vercel,
Weuseing,
Wewordle,
Xiaor,
You,
Yqcloud,
Zeabur,
hteyun,
)
Palm = Bard