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Merge branch 'main' into feature/docker-setup
This commit is contained in:
Ryan Jordan
GitHub
commit
f81e618958
162
README.md
162
README.md
@ -178,28 +178,102 @@ for message in response:
|
||||
print(message)
|
||||
```
|
||||
|
||||
providers:
|
||||
|
||||
##### Providers:
|
||||
```py
|
||||
from g4f.Provider import (
|
||||
Acytoo,
|
||||
Aichat,
|
||||
Ails,
|
||||
AiService,
|
||||
AItianhu,
|
||||
Bard,
|
||||
Bing,
|
||||
ChatgptAi,
|
||||
ChatgptLogin,
|
||||
DeepAi,
|
||||
GetGpt
|
||||
EasyChat,
|
||||
Equing,
|
||||
GetGpt,
|
||||
H2o,
|
||||
HuggingChat,
|
||||
Opchatgpts,
|
||||
OpenAssistant,
|
||||
OpenaiChat,
|
||||
Raycast,
|
||||
Theb,
|
||||
Vercel,
|
||||
Wewordle,
|
||||
Wuguokai,
|
||||
You,
|
||||
Yqcloud
|
||||
)
|
||||
|
||||
|
||||
# usage:
|
||||
# Usage:
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||||
response = g4f.ChatCompletion.create(..., provider=ProviderName)
|
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```
|
||||
|
||||
##### Needs cookies:
|
||||
|
||||
Many providers need cookies to work.
|
||||
In Bing you need a session, where you have passed the captcha.
|
||||
And in others providers you have to log-in into your account.
|
||||
If you run the g4l package locally,
|
||||
cookies from your browsers are readed with `get_cookies`.
|
||||
Else you have pass them in the parameter `cookies`:
|
||||
```py
|
||||
import g4f
|
||||
from g4f.Provider import (
|
||||
Bard,
|
||||
Bing,
|
||||
H2o,
|
||||
HuggingChat,
|
||||
OpenAssistant,
|
||||
OpenaiChat,
|
||||
You,
|
||||
)
|
||||
# Usage:
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||||
response = g4f.ChatCompletion.create(
|
||||
model=g4f.models.default,
|
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messages=[{"role": "user", "content": "Hello"}],
|
||||
provider=Bard,
|
||||
#cookies=g4f.get_cookies(".google.com"),
|
||||
cookies={"cookie_name": "value", "cookie_name2": "value2"},
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auth=True
|
||||
)
|
||||
```
|
||||
|
||||
##### Async support:
|
||||
|
||||
Run providers `async` to improve speed / performance.
|
||||
The full execution time corresponds to the execution time of the slowest provider.
|
||||
|
||||
```py
|
||||
import g4f, asyncio
|
||||
|
||||
async def run_async():
|
||||
_providers = [
|
||||
g4f.Provider.Bard,
|
||||
g4f.Provider.Bing,
|
||||
g4f.Provider.H2o,
|
||||
g4f.Provider.HuggingChat,
|
||||
g4f.Provider.Liaobots,
|
||||
g4f.Provider.OpenAssistant,
|
||||
g4f.Provider.OpenaiChat,
|
||||
g4f.Provider.You,
|
||||
g4f.Provider.Yqcloud,
|
||||
]
|
||||
responses = [
|
||||
provider.create_async(
|
||||
model=None,
|
||||
messages=[{"role": "user", "content": "Hello"}],
|
||||
)
|
||||
for provider in _providers
|
||||
]
|
||||
responses = await asyncio.gather(*responses)
|
||||
for idx, provider in enumerate(_providers):
|
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print(f"{provider.__name__}:", responses[idx])
|
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|
||||
asyncio.run(run_async())
|
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```
|
||||
|
||||
### interference openai-proxy api (use with openai python package)
|
||||
|
||||
get requirements:
|
||||
@ -247,32 +321,40 @@ if __name__ == "__main__":
|
||||
|
||||
### gpt-3.5 / gpt-4
|
||||
|
||||
| Website | Provider | gpt-3.5 | gpt-4 | Streaming | Status | Auth |
|
||||
| ----------------------------------------------------------------------------- | ------------------------- | ------- | ----- | --------- | ---------------------------------------------------------- | ---- |
|
||||
| [www.aitianhu.com](https://www.aitianhu.com/api/chat-process) | g4f.Provider.AItianhu | ✔️ | ❌ | ❌ |  | ❌ |
|
||||
| [chat.acytoo.com](https://chat.acytoo.com/api/completions) | g4f.Provider.Acytoo | ✔️ | ❌ | ❌ |  | ❌ |
|
||||
| [aiservice.vercel.app](https://aiservice.vercel.app/api/chat/answer) | g4f.Provider.AiService | ✔️ | ❌ | ❌ |  | ❌ |
|
||||
| [chat-gpt.org](https://chat-gpt.org/chat) | g4f.Provider.Aichat | ✔️ | ❌ | ❌ |  | ❌ |
|
||||
| [ai.ls](https://ai.ls) | g4f.Provider.Ails | ✔️ | ❌ | ✔️ |  | ❌ |
|
||||
| [bard.google.com](https://bard.google.com) | g4f.Provider.Bard | ❌ | ❌ | ❌ |  | ✔️ |
|
||||
| [bing.com](https://bing.com/chat) | g4f.Provider.Bing | ❌ | ✔️ | ❌ |  | ❌ |
|
||||
| [chatgpt.ai](https://chatgpt.ai/gpt-4/) | g4f.Provider.ChatgptAi | ❌ | ✔️ | ❌ |  | ❌ |
|
||||
| [chatgptlogin.ac](https://chatgptlogin.ac) | g4f.Provider.ChatgptLogin | ✔️ | ❌ | ❌ |  | ❌ |
|
||||
| [deepai.org](https://deepai.org) | g4f.Provider.DeepAi | ✔️ | ❌ | ✔️ |  | ❌ |
|
||||
| [chat.dfehub.com](https://chat.dfehub.com/api/chat) | g4f.Provider.DfeHub | ✔️ | ❌ | ✔️ |  | ❌ |
|
||||
| [free.easychat.work](https://free.easychat.work) | g4f.Provider.EasyChat | ✔️ | ❌ | ✔️ |  | ❌ |
|
||||
| [forefront.com](https://forefront.com) | g4f.Provider.Forefront | ✔️ | ❌ | ✔️ |  | ❌ |
|
||||
| [chat.getgpt.world](https://chat.getgpt.world/) | g4f.Provider.GetGpt | ✔️ | ❌ | ✔️ |  | ❌ |
|
||||
| [gpt-gm.h2o.ai](https://gpt-gm.h2o.ai) | g4f.Provider.H2o | ❌ | ❌ | ✔️ |  | ❌ |
|
||||
| [liaobots.com](https://liaobots.com) | g4f.Provider.Liaobots | ✔️ | ✔️ | ✔️ |  | ✔️ |
|
||||
| [supertest.lockchat.app](http://supertest.lockchat.app) | g4f.Provider.Lockchat | ✔️ | ✔️ | ✔️ |  | ❌ |
|
||||
| [opchatgpts.net](https://opchatgpts.net) | g4f.Provider.Opchatgpts | ✔️ | ❌ | ❌ |  | ❌ |
|
||||
| [backend.raycast.com](https://backend.raycast.com/api/v1/ai/chat_completions) | g4f.Provider.Raycast | ✔️ | ✔️ | ✔️ |  | ✔️ |
|
||||
| [theb.ai](https://theb.ai) | g4f.Provider.Theb | ✔️ | ❌ | ✔️ |  | ❌ |
|
||||
| [play.vercel.ai](https://play.vercel.ai) | g4f.Provider.Vercel | ✔️ | ❌ | ❌ |  | ❌ |
|
||||
| [wewordle.org](https://wewordle.org/gptapi/v1/android/turbo) | g4f.Provider.Wewordle | ✔️ | ❌ | ❌ |  | ❌ |
|
||||
| [you.com](https://you.com) | g4f.Provider.You | ✔️ | ❌ | ❌ |  | ❌ |
|
||||
| [chat9.yqcloud.top](https://chat9.yqcloud.top/) | g4f.Provider.Yqcloud | ✔️ | ❌ | ❌ |  | ❌ |
|
||||
| Website| Provider| gpt-3.5 | gpt-4 | Streaming | Status | Auth |
|
||||
| ------ | ------- | ------- | ----- | --------- | ------ | ---- |
|
||||
| [chat.acytoo.com](https://chat.acytoo.com/) | g4f.provider.Acytoo | ✔️ | ❌ | ❌ |  | ❌ |
|
||||
| [chat-gpt.org](https://chat-gpt.org/chat) | g4f.provider.Aichat | ✔️ | ❌ | ❌ |  | ❌ |
|
||||
| [ai.ls](https://ai.ls) | g4f.provider.Ails | ✔️ | ❌ | ✔️ |  | ❌ |
|
||||
| [bard.google.com](https://bard.google.com) | g4f.provider.Bard | ❌ | ❌ | ❌ |  | ✔️ |
|
||||
| [bing.com](https://bing.com/chat) | g4f.provider.Bing | ❌ | ✔️ | ✔️ |  | ✔️ |
|
||||
| [chatgpt.ai](https://chatgpt.ai/gpt-4/) | g4f.provider.ChatgptAi | ❌ | ✔️ | ❌ |  | ❌ |
|
||||
| [opchatgpts.net](https://opchatgpts.net) | g4f.provider.ChatgptLogin | ✔️ | ❌ | ❌ |  | ❌ |
|
||||
| [deepai.org](https://deepai.org) | g4f.provider.DeepAi | ✔️ | ❌ | ✔️ |  | ❌ |
|
||||
| [free.easychat.work](https://free.easychat.work) | g4f.provider.EasyChat | ✔️ | ❌ | ✔️ |  | ❌ |
|
||||
| [next.eqing.tech](https://next.eqing.tech/) | g4f.provider.Equing | ✔️ | ❌ | ✔️ |  | ❌ |
|
||||
| [chat.getgpt.world](https://chat.getgpt.world/) | g4f.provider.GetGpt | ✔️ | ❌ | ✔️ |  | ❌ |
|
||||
| [gpt-gm.h2o.ai](https://gpt-gm.h2o.ai) | g4f.provider.H2o | ❌ | ❌ | ✔️ |  | ❌ |
|
||||
| [huggingface.co](https://huggingface.co/chat/) | g4f.provider.HuggingChat | ❌ | ❌ | ❌ |  | ✔️ |
|
||||
| [liaobots.com](https://liaobots.com) | g4f.provider.Liaobots | ✔️ | ✔️ | ✔️ |  | ❌ |
|
||||
| [opchatgpts.net](https://opchatgpts.net) | g4f.provider.Opchatgpts | ✔️ | ❌ | ❌ |  | ❌ |
|
||||
| [open-assistant.io](https://open-assistant.io/chat) | g4f.provider.OpenAssistant | ❌ | ❌ | ❌ |  | ✔️ |
|
||||
| [chat.openai.com](https://chat.openai.com) | g4f.provider.OpenaiChat | ✔️ | ✔️ | ✔️ |  | ✔️ |
|
||||
| [raycast.com](https://raycast.com) | g4f.provider.Raycast | ✔️ | ✔️ | ✔️ |  | ✔️ |
|
||||
| [theb.ai](https://theb.ai) | g4f.provider.Theb | ✔️ | ❌ | ✔️ |  | ✔️ |
|
||||
| [play.vercel.ai](https://play.vercel.ai) | g4f.provider.Vercel | ✔️ | ❌ | ❌ |  | ❌ |
|
||||
| [wewordle.org](https://wewordle.org/) | g4f.provider.Wewordle | ✔️ | ❌ | ❌ |  | ❌ |
|
||||
| [chat.wuguokai.xyz](https://chat.wuguokai.xyz) | g4f.provider.Wuguokai | ✔️ | ❌ | ❌ |  | ❌ |
|
||||
| [you.com](https://you.com) | g4f.provider.You | ✔️ | ❌ | ✔️ |  | ❌ |
|
||||
| [chat9.yqcloud.top](https://chat9.yqcloud.top/) | g4f.provider.Yqcloud | ✔️ | ❌ | ❌ |  | ❌ |
|
||||
| [www.aitianhu.com](https://www.aitianhu.com/) | g4f.provider.AItianhu | ✔️ | ❌ | ❌ |  | ❌ |
|
||||
| [aiservice.vercel.app](https://aiservice.vercel.app/) | g4f.provider.AiService | ✔️ | ❌ | ❌ |  | ❌ |
|
||||
| [chat.dfehub.com](https://chat.dfehub.com/) | g4f.provider.DfeHub | ✔️ | ❌ | ✔️ |  | ❌ |
|
||||
| [chat9.fastgpt.me](https://chat9.fastgpt.me/) | g4f.provider.FastGpt | ✔️ | ❌ | ✔️ |  | ❌ |
|
||||
| [forefront.com](https://forefront.com) | g4f.provider.Forefront | ✔️ | ❌ | ✔️ |  | ❌ |
|
||||
| [supertest.lockchat.app](http://supertest.lockchat.app) | g4f.provider.Lockchat | ✔️ | ✔️ | ✔️ |  | ❌ |
|
||||
| [p5.v50.ltd](https://p5.v50.ltd) | g4f.provider.V50 | ✔️ | ❌ | ❌ |  | ❌ |
|
||||
|
||||
|
||||
### Other Models
|
||||
|
||||
@ -360,6 +442,20 @@ if __name__ == "__main__":
|
||||
<td><a href="https://github.com/HexyeDEV/Telegram-Chatbot-Gpt4Free/issues"><img alt="Issues" src="https://img.shields.io/github/issues/HexyeDEV/Telegram-Chatbot-Gpt4Free?style=flat-square&labelColor=343b41"/></a></td>
|
||||
<td><a href="https://github.com/HexyeDEV/Telegram-Chatbot-Gpt4Free/pulls"><img alt="Pull Requests" src="https://img.shields.io/github/issues-pr/HexyeDEV/Telegram-Chatbot-Gpt4Free?style=flat-square&labelColor=343b41"/></a></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td><a href="https://github.com/Lin-jun-xiang/action-translate-readme"><b>Action Translate Readme</b></a></td>
|
||||
<td><a href="https://github.com/Lin-jun-xiang/action-translate-readme/stargazers"><img alt="Stars" src="https://img.shields.io/github/stars/Lin-jun-xiang/action-translate-readme?style=flat-square&labelColor=343b41"/></a></td>
|
||||
<td><a href="https://github.com/Lin-jun-xiang/action-translate-readme/network/members"><img alt="Forks" src="https://img.shields.io/github/forks/Lin-jun-xiang/action-translate-readme?style=flat-square&labelColor=343b41"/></a></td>
|
||||
<td><a href="https://github.com/Lin-jun-xiang/action-translate-readme/issues"><img alt="Issues" src="https://img.shields.io/github/issues/Lin-jun-xiang/action-translate-readme?style=flat-square&labelColor=343b41"/></a></td>
|
||||
<td><a href="https://github.com/Lin-jun-xiang/action-translate-readme/pulls"><img alt="Pull Requests" src="https://img.shields.io/github/issues-pr/Lin-jun-xiang/action-translate-readme?style=flat-square&labelColor=343b41"/></a></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td><a href="https://github.com/Lin-jun-xiang/docGPT-streamlit"><b>Langchain Document GPT</b></a></td>
|
||||
<td><a href="https://github.com/Lin-jun-xiang/docGPT-streamlit/stargazers"><img alt="Stars" src="https://img.shields.io/github/stars/Lin-jun-xiang/docGPT-streamlit?style=flat-square&labelColor=343b41"/></a></td>
|
||||
<td><a href="https://github.com/Lin-jun-xiang/docGPT-streamlit/network/members"><img alt="Forks" src="https://img.shields.io/github/forks/Lin-jun-xiang/docGPT-streamlit?style=flat-square&labelColor=343b41"/></a></td>
|
||||
<td><a href="https://github.com/Lin-jun-xiang/docGPT-streamlit/issues"><img alt="Issues" src="https://img.shields.io/github/issues/Lin-jun-xiang/docGPT-streamlit?style=flat-square&labelColor=343b41"/></a></td>
|
||||
<td><a href="https://github.com/Lin-jun-xiang/docGPT-streamlit/pulls"><img alt="Pull Requests" src="https://img.shields.io/github/issues-pr/Lin-jun-xiang/docGPT-streamlit?style=flat-square&labelColor=343b41"/></a></td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
|
||||
|
||||
@ -1,3 +1,5 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
|
||||
import requests
|
||||
@ -7,7 +9,7 @@ from .base_provider import BaseProvider
|
||||
|
||||
|
||||
class AItianhu(BaseProvider):
|
||||
url = "https://www.aitianhu.com/api/chat-process"
|
||||
url = "https://www.aitianhu.com/"
|
||||
working = False
|
||||
supports_gpt_35_turbo = True
|
||||
|
||||
@ -15,13 +17,10 @@ class AItianhu(BaseProvider):
|
||||
def create_completion(
|
||||
model: str,
|
||||
messages: list[dict[str, str]],
|
||||
stream: bool,
|
||||
**kwargs: Any,
|
||||
) -> CreateResult:
|
||||
base = ""
|
||||
for message in messages:
|
||||
base += "%s: %s\n" % (message["role"], message["content"])
|
||||
base += "assistant:"
|
||||
stream: bool, **kwargs: Any) -> CreateResult:
|
||||
|
||||
base = "\n".join(f"{message['role']}: {message['content']}" for message in messages)
|
||||
base += "\nassistant: "
|
||||
|
||||
headers = {
|
||||
"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"
|
||||
|
||||
@ -1,3 +1,5 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import time
|
||||
|
||||
import requests
|
||||
@ -7,42 +9,42 @@ from .base_provider import BaseProvider
|
||||
|
||||
|
||||
class Acytoo(BaseProvider):
|
||||
url = "https://chat.acytoo.com/api/completions"
|
||||
working = True
|
||||
url = 'https://chat.acytoo.com/'
|
||||
working = True
|
||||
supports_gpt_35_turbo = True
|
||||
|
||||
@staticmethod
|
||||
@classmethod
|
||||
def create_completion(
|
||||
cls,
|
||||
model: str,
|
||||
messages: list[dict[str, str]],
|
||||
stream: bool,
|
||||
**kwargs: Any,
|
||||
) -> CreateResult:
|
||||
headers = _create_header()
|
||||
payload = _create_payload(messages, kwargs.get('temperature', 0.5))
|
||||
stream: bool, **kwargs: Any) -> CreateResult:
|
||||
|
||||
url = "https://chat.acytoo.com/api/completions"
|
||||
response = requests.post(url=url, headers=headers, json=payload)
|
||||
response = requests.post(f'{cls.url}api/completions',
|
||||
headers=_create_header(), json=_create_payload(messages, kwargs.get('temperature', 0.5)))
|
||||
|
||||
response.raise_for_status()
|
||||
response.encoding = "utf-8"
|
||||
response.encoding = 'utf-8'
|
||||
|
||||
yield response.text
|
||||
|
||||
|
||||
def _create_header():
|
||||
return {
|
||||
"accept": "*/*",
|
||||
"content-type": "application/json",
|
||||
'accept': '*/*',
|
||||
'content-type': 'application/json',
|
||||
}
|
||||
|
||||
|
||||
def _create_payload(messages: list[dict[str, str]], temperature):
|
||||
payload_messages = [
|
||||
message | {"createdAt": int(time.time()) * 1000} for message in messages
|
||||
message | {'createdAt': int(time.time()) * 1000} for message in messages
|
||||
]
|
||||
|
||||
return {
|
||||
"key": "",
|
||||
"model": "gpt-3.5-turbo",
|
||||
"messages": payload_messages,
|
||||
"temperature": temperature,
|
||||
"password": "",
|
||||
}
|
||||
'key' : '',
|
||||
'model' : 'gpt-3.5-turbo',
|
||||
'messages' : payload_messages,
|
||||
'temperature' : temperature,
|
||||
'password' : ''
|
||||
}
|
||||
@ -1,3 +1,5 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import requests
|
||||
|
||||
from ..typing import Any, CreateResult
|
||||
@ -5,7 +7,7 @@ from .base_provider import BaseProvider
|
||||
|
||||
|
||||
class AiService(BaseProvider):
|
||||
url = "https://aiservice.vercel.app/api/chat/answer"
|
||||
url = "https://aiservice.vercel.app/"
|
||||
working = False
|
||||
supports_gpt_35_turbo = True
|
||||
|
||||
@ -16,10 +18,8 @@ class AiService(BaseProvider):
|
||||
stream: bool,
|
||||
**kwargs: Any,
|
||||
) -> CreateResult:
|
||||
base = ""
|
||||
for message in messages:
|
||||
base += "%s: %s\n" % (message["role"], message["content"])
|
||||
base += "assistant:"
|
||||
base = "\n".join(f"{message['role']}: {message['content']}" for message in messages)
|
||||
base += "\nassistant: "
|
||||
|
||||
headers = {
|
||||
"accept": "*/*",
|
||||
|
||||
@ -1,3 +1,5 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import requests
|
||||
|
||||
from ..typing import Any, CreateResult
|
||||
@ -5,22 +7,18 @@ from .base_provider import BaseProvider
|
||||
|
||||
|
||||
class Aichat(BaseProvider):
|
||||
url = "https://chat-gpt.org/chat"
|
||||
working = True
|
||||
url = "https://chat-gpt.org/chat"
|
||||
working = True
|
||||
supports_gpt_35_turbo = True
|
||||
|
||||
@staticmethod
|
||||
def create_completion(
|
||||
model: str,
|
||||
messages: list[dict[str, str]],
|
||||
stream: bool,
|
||||
**kwargs: Any,
|
||||
) -> CreateResult:
|
||||
base = ""
|
||||
|
||||
for message in messages:
|
||||
base += "%s: %s\n" % (message["role"], message["content"])
|
||||
base += "assistant:"
|
||||
stream: bool, **kwargs: Any) -> CreateResult:
|
||||
|
||||
chat = "\n".join(f"{message['role']}: {message['content']}" for message in messages)
|
||||
chat += "\nassistant: "
|
||||
|
||||
headers = {
|
||||
"authority": "chat-gpt.org",
|
||||
|
||||
@ -1,3 +1,5 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import hashlib
|
||||
import json
|
||||
import time
|
||||
@ -11,18 +13,17 @@ from .base_provider import BaseProvider
|
||||
|
||||
|
||||
class Ails(BaseProvider):
|
||||
url: str = "https://ai.ls"
|
||||
working = True
|
||||
supports_stream = True
|
||||
url: str = "https://ai.ls"
|
||||
working = True
|
||||
supports_stream = True
|
||||
supports_gpt_35_turbo = True
|
||||
|
||||
@staticmethod
|
||||
def create_completion(
|
||||
model: str,
|
||||
messages: list[dict[str, str]],
|
||||
stream: bool,
|
||||
**kwargs: Any,
|
||||
) -> CreateResult:
|
||||
stream: bool, **kwargs: Any) -> CreateResult:
|
||||
|
||||
headers = {
|
||||
"authority": "api.caipacity.com",
|
||||
"accept": "*/*",
|
||||
@ -72,6 +73,8 @@ class Ails(BaseProvider):
|
||||
if b"content" in token:
|
||||
completion_chunk = json.loads(token.decode().replace("data: ", ""))
|
||||
token = completion_chunk["choices"][0]["delta"].get("content")
|
||||
if "ai.ls" in token.lower() or "ai.ci" in token.lower():
|
||||
raise Exception("Response Error: " + token)
|
||||
if token != None:
|
||||
yield token
|
||||
|
||||
|
||||
@ -1,51 +1,33 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import random
|
||||
import re
|
||||
|
||||
import browser_cookie3
|
||||
from aiohttp import ClientSession
|
||||
import asyncio
|
||||
|
||||
from ..typing import Any, CreateResult
|
||||
from .base_provider import BaseProvider
|
||||
from .base_provider import AsyncProvider, format_prompt, get_cookies
|
||||
|
||||
class Bard(BaseProvider):
|
||||
|
||||
class Bard(AsyncProvider):
|
||||
url = "https://bard.google.com"
|
||||
needs_auth = True
|
||||
working = True
|
||||
|
||||
@classmethod
|
||||
def create_completion(
|
||||
cls,
|
||||
model: str,
|
||||
messages: list[dict[str, str]],
|
||||
stream: bool,
|
||||
proxy: str = None,
|
||||
cookies: dict = {},
|
||||
**kwargs: Any,
|
||||
) -> CreateResult:
|
||||
yield asyncio.run(cls.create_async(str, messages, proxy, cookies))
|
||||
|
||||
@classmethod
|
||||
async def create_async(
|
||||
cls,
|
||||
model: str,
|
||||
messages: list[dict[str, str]],
|
||||
proxy: str = None,
|
||||
cookies: dict = {},
|
||||
**kwargs: Any,
|
||||
cookies: dict = None,
|
||||
**kwargs
|
||||
) -> str:
|
||||
if not cookies:
|
||||
for cookie in browser_cookie3.load(domain_name='.google.com'):
|
||||
cookies[cookie.name] = cookie.value
|
||||
|
||||
formatted = "\n".join(
|
||||
["%s: %s" % (message["role"], message["content"]) for message in messages]
|
||||
)
|
||||
prompt = f"{formatted}\nAssistant:"
|
||||
|
||||
prompt = format_prompt(messages)
|
||||
if proxy and "://" not in proxy:
|
||||
proxy = f"http://{proxy}"
|
||||
if not cookies:
|
||||
cookies = get_cookies(".google.com")
|
||||
|
||||
headers = {
|
||||
'authority': 'bard.google.com',
|
||||
@ -62,10 +44,11 @@ class Bard(BaseProvider):
|
||||
) as session:
|
||||
async with session.get(cls.url, proxy=proxy) as response:
|
||||
text = await response.text()
|
||||
|
||||
|
||||
match = re.search(r'SNlM0e\":\"(.*?)\"', text)
|
||||
if match:
|
||||
snlm0e = match.group(1)
|
||||
if not match:
|
||||
raise RuntimeError("No snlm0e value.")
|
||||
snlm0e = match.group(1)
|
||||
|
||||
params = {
|
||||
'bl': 'boq_assistant-bard-web-server_20230326.21_p0',
|
||||
|
||||
@ -1,294 +1,94 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import asyncio
|
||||
import json
|
||||
import os
|
||||
import random
|
||||
import ssl
|
||||
import uuid
|
||||
|
||||
import aiohttp
|
||||
import certifi
|
||||
import requests
|
||||
from aiohttp import ClientSession
|
||||
|
||||
from ..typing import Any, AsyncGenerator, CreateResult, Tuple, Union
|
||||
from .base_provider import BaseProvider
|
||||
from ..typing import Any, AsyncGenerator, CreateResult, Union
|
||||
from .base_provider import AsyncGeneratorProvider, get_cookies
|
||||
|
||||
|
||||
class Bing(BaseProvider):
|
||||
url = "https://bing.com/chat"
|
||||
supports_gpt_4 = True
|
||||
|
||||
class Bing(AsyncGeneratorProvider):
|
||||
url = "https://bing.com/chat"
|
||||
needs_auth = True
|
||||
working = True
|
||||
supports_gpt_4 = True
|
||||
supports_stream = True
|
||||
|
||||
@staticmethod
|
||||
def create_completion(
|
||||
model: str,
|
||||
messages: list[dict[str, str]],
|
||||
stream: bool,
|
||||
**kwargs: Any,
|
||||
) -> CreateResult:
|
||||
def create_async_generator(
|
||||
model: str,
|
||||
messages: list[dict[str, str]],
|
||||
cookies: dict = None, **kwargs) -> AsyncGenerator:
|
||||
|
||||
if not cookies:
|
||||
cookies = get_cookies(".bing.com")
|
||||
if len(messages) < 2:
|
||||
prompt = messages[0]["content"]
|
||||
context = False
|
||||
|
||||
context = None
|
||||
else:
|
||||
prompt = messages[-1]["content"]
|
||||
context = convert(messages[:-1])
|
||||
context = create_context(messages[:-1])
|
||||
|
||||
if cookies and "SRCHD" in cookies:
|
||||
#TODO: Will implement proper cookie retrieval later and use a try-except mechanism in 'stream_generate' instead of defaulting the cookie value like this
|
||||
cookies_dict = {
|
||||
'SRCHD' : cookies["SRCHD"],
|
||||
'PPLState' : '1',
|
||||
'KievRPSSecAuth': '',
|
||||
'SUID' : '',
|
||||
'SRCHUSR' : '',
|
||||
'SRCHHPGUSR' : '',
|
||||
}
|
||||
|
||||
return stream_generate(prompt, context, cookies_dict)
|
||||
|
||||
response = run(stream_generate(prompt, jailbreak, context))
|
||||
for token in response:
|
||||
yield token
|
||||
|
||||
|
||||
def convert(messages: list[dict[str, str]]):
|
||||
context = ""
|
||||
|
||||
for message in messages:
|
||||
context += "[%s](#message)\n%s\n\n" % (message["role"], message["content"])
|
||||
def create_context(messages: list[dict[str, str]]):
|
||||
context = "".join(f"[{message['role']}](#message)\n{message['content']}\n\n" for message in messages)
|
||||
|
||||
return context
|
||||
|
||||
class Conversation():
|
||||
def __init__(self, conversationId: str, clientId: str, conversationSignature: str) -> None:
|
||||
self.conversationId = conversationId
|
||||
self.clientId = clientId
|
||||
self.conversationSignature = conversationSignature
|
||||
|
||||
jailbreak = {
|
||||
"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",
|
||||
]
|
||||
}
|
||||
async def create_conversation(session: ClientSession) -> Conversation:
|
||||
url = 'https://www.bing.com/turing/conversation/create'
|
||||
async with await session.get(url) as response:
|
||||
response = await response.json()
|
||||
conversationId = response.get('conversationId')
|
||||
clientId = response.get('clientId')
|
||||
conversationSignature = response.get('conversationSignature')
|
||||
|
||||
if not conversationId or not clientId or not conversationSignature:
|
||||
raise Exception('Failed to create conversation.')
|
||||
|
||||
return Conversation(conversationId, clientId, conversationSignature)
|
||||
|
||||
ssl_context = ssl.create_default_context()
|
||||
ssl_context.load_verify_locations(certifi.where())
|
||||
|
||||
|
||||
def _format(msg: dict[str, Any]) -> str:
|
||||
return json.dumps(msg, ensure_ascii=False) + Defaults.delimiter
|
||||
|
||||
|
||||
async def stream_generate(
|
||||
prompt: str,
|
||||
mode: dict[str, list[str]] = jailbreak,
|
||||
context: Union[bool, 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)
|
||||
|
||||
argument: dict[str, Any] = {
|
||||
**mode,
|
||||
async def list_conversations(session: ClientSession) -> list:
|
||||
url = "https://www.bing.com/turing/conversation/chats"
|
||||
async with session.get(url) as response:
|
||||
response = await response.json()
|
||||
return response["chats"]
|
||||
|
||||
async def delete_conversation(session: ClientSession, conversation: Conversation) -> list:
|
||||
url = "https://sydney.bing.com/sydney/DeleteSingleConversation"
|
||||
json = {
|
||||
"conversationId": conversation.conversationId,
|
||||
"conversationSignature": conversation.conversationSignature,
|
||||
"participant": {"id": conversation.clientId},
|
||||
"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,
|
||||
"optionsSets": ["autosave"]
|
||||
}
|
||||
|
||||
if context:
|
||||
argument["previousMessages"] = [
|
||||
{
|
||||
"author": "user",
|
||||
"description": context,
|
||||
"contextType": "WebPage",
|
||||
"messageType": "Context",
|
||||
"messageId": "discover-web--page-ping-mriduna-----",
|
||||
}
|
||||
]
|
||||
|
||||
struct: dict[str, list[dict[str, Any]] | str | int] = {
|
||||
"arguments": [argument],
|
||||
"invocationId": "0",
|
||||
"target": "chat",
|
||||
"type": 4,
|
||||
}
|
||||
|
||||
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) # type: ignore
|
||||
|
||||
for obj in objects: # type: ignore
|
||||
if obj is None or not obj:
|
||||
continue
|
||||
|
||||
response = json.loads(obj) # type: ignore
|
||||
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()
|
||||
|
||||
|
||||
async def create_conversation() -> Tuple[str, str, str]:
|
||||
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:
|
||||
raise Exception("Failed to create conversation.")
|
||||
|
||||
return conversationId, clientId, conversationSignature
|
||||
|
||||
async with session.post(url, json=json) as response:
|
||||
response = await response.json()
|
||||
return response["result"]["value"] == "Success"
|
||||
|
||||
class Defaults:
|
||||
delimiter = "\x1e"
|
||||
@ -309,9 +109,6 @@ class Defaults:
|
||||
]
|
||||
|
||||
sliceIds = [
|
||||
# "222dtappid",
|
||||
# "225cricinfo",
|
||||
# "224locals0"
|
||||
"winmuid3tf",
|
||||
"osbsdusgreccf",
|
||||
"ttstmout",
|
||||
@ -349,6 +146,149 @@ class Defaults:
|
||||
],
|
||||
}
|
||||
|
||||
headers = {
|
||||
'accept': '*/*',
|
||||
'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': ip_address,
|
||||
}
|
||||
|
||||
optionsSets = {
|
||||
"optionsSets": [
|
||||
'saharasugg',
|
||||
'enablenewsfc',
|
||||
'clgalileo',
|
||||
'gencontentv3',
|
||||
"nlu_direct_response_filter",
|
||||
"deepleo",
|
||||
"disable_emoji_spoken_text",
|
||||
"responsible_ai_policy_235",
|
||||
"enablemm",
|
||||
"h3precise"
|
||||
"dtappid",
|
||||
"cricinfo",
|
||||
"cricinfov2",
|
||||
"dv3sugg",
|
||||
"nojbfedge"
|
||||
]
|
||||
}
|
||||
|
||||
def format_message(msg: dict) -> str:
|
||||
return json.dumps(msg, ensure_ascii=False) + Defaults.delimiter
|
||||
|
||||
def create_message(conversation: Conversation, prompt: str, context: str=None) -> str:
|
||||
struct = {
|
||||
'arguments': [
|
||||
{
|
||||
**Defaults.optionsSets,
|
||||
'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': conversation.conversationSignature,
|
||||
'participant': {
|
||||
'id': conversation.clientId
|
||||
},
|
||||
'conversationId': conversation.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-----"
|
||||
}]
|
||||
return format_message(struct)
|
||||
|
||||
async def stream_generate(
|
||||
prompt: str,
|
||||
context: str=None,
|
||||
cookies: dict=None
|
||||
):
|
||||
async with ClientSession(
|
||||
timeout=aiohttp.ClientTimeout(total=900),
|
||||
cookies=cookies,
|
||||
headers=Defaults.headers,
|
||||
) as session:
|
||||
conversation = await create_conversation(session)
|
||||
try:
|
||||
async with session.ws_connect(
|
||||
'wss://sydney.bing.com/sydney/ChatHub',
|
||||
autoping=False,
|
||||
) as wss:
|
||||
|
||||
await wss.send_str(format_message({'protocol': 'json', 'version': 1}))
|
||||
msg = await wss.receive(timeout=900)
|
||||
|
||||
await wss.send_str(create_message(conversation, prompt, context))
|
||||
|
||||
response_txt = ''
|
||||
result_text = ''
|
||||
returned_text = ''
|
||||
final = False
|
||||
|
||||
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'):
|
||||
message = response['arguments'][0]['messages'][0]
|
||||
if (message['contentOrigin'] != 'Apology'):
|
||||
response_txt = result_text + \
|
||||
message['adaptiveCards'][0]['body'][0].get('text', '')
|
||||
|
||||
if message.get('messageType'):
|
||||
inline_txt = message['adaptiveCards'][0]['body'][0]['inlines'][0].get('text')
|
||||
response_txt += inline_txt + '\n'
|
||||
result_text += inline_txt + '\n'
|
||||
|
||||
if response_txt.startswith(returned_text):
|
||||
new = response_txt[len(returned_text):]
|
||||
if new != "\n":
|
||||
yield new
|
||||
returned_text = response_txt
|
||||
elif response.get('type') == 2:
|
||||
result = response['item']['result']
|
||||
if result.get('error'):
|
||||
raise Exception(f"{result['value']}: {result['message']}")
|
||||
final = True
|
||||
break
|
||||
finally:
|
||||
await delete_conversation(session, conversation)
|
||||
|
||||
def run(generator: AsyncGenerator[Union[Any, str], Any]):
|
||||
loop = asyncio.get_event_loop()
|
||||
@ -360,3 +300,4 @@ def run(generator: AsyncGenerator[Union[Any, str], Any]):
|
||||
|
||||
except StopAsyncIteration:
|
||||
break
|
||||
|
||||
|
||||
@ -1,3 +1,5 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import re
|
||||
|
||||
import requests
|
||||
@ -7,55 +9,51 @@ from .base_provider import BaseProvider
|
||||
|
||||
|
||||
class ChatgptAi(BaseProvider):
|
||||
url = "https://chatgpt.ai/gpt-4/"
|
||||
working = True
|
||||
supports_gpt_4 = True
|
||||
url: str = "https://chatgpt.ai/gpt-4/"
|
||||
working = True
|
||||
supports_gpt_4 = True
|
||||
|
||||
@staticmethod
|
||||
def create_completion(
|
||||
model: str,
|
||||
messages: list[dict[str, str]],
|
||||
stream: bool,
|
||||
**kwargs: Any,
|
||||
) -> CreateResult:
|
||||
chat = ""
|
||||
for message in messages:
|
||||
chat += "%s: %s\n" % (message["role"], message["content"])
|
||||
chat += "assistant: "
|
||||
stream: bool, **kwargs: Any) -> CreateResult:
|
||||
|
||||
chat = "\n".join(f"{message['role']}: {message['content']}" for message in messages)
|
||||
chat += "\nassistant: "
|
||||
|
||||
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]
|
||||
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",
|
||||
"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,
|
||||
"_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
|
||||
)
|
||||
"https://chatgpt.ai/wp-admin/admin-ajax.php", headers=headers, data=data)
|
||||
|
||||
response.raise_for_status()
|
||||
yield response.json()["data"]
|
||||
yield response.json()["data"]
|
||||
@ -1,3 +1,5 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import base64
|
||||
import os
|
||||
import re
|
||||
@ -9,61 +11,58 @@ from .base_provider import BaseProvider
|
||||
|
||||
|
||||
class ChatgptLogin(BaseProvider):
|
||||
url = "https://opchatgpts.net"
|
||||
url = "https://opchatgpts.net"
|
||||
supports_gpt_35_turbo = True
|
||||
working = True
|
||||
working = True
|
||||
|
||||
@staticmethod
|
||||
def create_completion(
|
||||
model: str,
|
||||
messages: list[dict[str, str]],
|
||||
stream: bool,
|
||||
**kwargs: Any,
|
||||
) -> CreateResult:
|
||||
stream: bool, **kwargs: Any) -> CreateResult:
|
||||
|
||||
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://opchatgpts.net",
|
||||
"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-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/116.0.0.0 Safari/537.36",
|
||||
"x-wp-nonce": _get_nonce(),
|
||||
"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://opchatgpts.net",
|
||||
"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-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/116.0.0.0 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": kwargs.get("temperature", 0.8),
|
||||
"maxTokens": 1024,
|
||||
"maxResults": 1,
|
||||
"apiKey": "",
|
||||
"service": "openai",
|
||||
"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" : kwargs.get("temperature", 0.8),
|
||||
"maxTokens" : 1024,
|
||||
"maxResults" : 1,
|
||||
"apiKey" : "",
|
||||
"service" : "openai",
|
||||
"embeddingsIndex": "",
|
||||
"stop": "",
|
||||
"clientId": os.urandom(6).hex(),
|
||||
"stop" : "",
|
||||
"clientId" : os.urandom(6).hex()
|
||||
}
|
||||
|
||||
response = requests.post(
|
||||
"https://opchatgpts.net/wp-json/ai-chatbot/v1/chat",
|
||||
headers=headers,
|
||||
json=json_data,
|
||||
)
|
||||
response = requests.post("https://opchatgpts.net/wp-json/ai-chatbot/v1/chat",
|
||||
headers=headers, json=json_data)
|
||||
|
||||
response.raise_for_status()
|
||||
yield response.json()["reply"]
|
||||
|
||||
@ -81,24 +80,21 @@ class ChatgptLogin(BaseProvider):
|
||||
|
||||
|
||||
def _get_nonce() -> str:
|
||||
res = requests.get(
|
||||
"https://opchatgpts.net/chatgpt-free-use/",
|
||||
headers={
|
||||
"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",
|
||||
},
|
||||
)
|
||||
res = requests.get("https://opchatgpts.net/chatgpt-free-use/",
|
||||
headers = {
|
||||
"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"})
|
||||
|
||||
result = re.search(
|
||||
r'class="mwai-chat mwai-chatgpt">.*<span>Send</span></button></div></div></div> <script defer src="(.*?)">',
|
||||
res.text,
|
||||
)
|
||||
res.text)
|
||||
|
||||
if result is None:
|
||||
return ""
|
||||
|
||||
src = result.group(1)
|
||||
|
||||
src = result.group(1)
|
||||
decoded_string = base64.b64decode(src.split(",")[-1]).decode("utf-8")
|
||||
result = re.search(r"let restNonce = '(.*?)';", decoded_string)
|
||||
result = re.search(r"let restNonce = '(.*?)';", decoded_string)
|
||||
|
||||
return "" if result is None else result.group(1)
|
||||
|
||||
@ -106,11 +102,11 @@ def _get_nonce() -> str:
|
||||
def _transform(messages: list[dict[str, str]]) -> list[dict[str, Any]]:
|
||||
return [
|
||||
{
|
||||
"id": os.urandom(6).hex(),
|
||||
"role": message["role"],
|
||||
"id" : os.urandom(6).hex(),
|
||||
"role" : message["role"],
|
||||
"content": message["content"],
|
||||
"who": "AI: " if message["role"] == "assistant" else "User: ",
|
||||
"html": _html_encode(message["content"]),
|
||||
"who" : "AI: " if message["role"] == "assistant" else "User: ",
|
||||
"html" : _html_encode(message["content"]),
|
||||
}
|
||||
for message in messages
|
||||
]
|
||||
@ -118,14 +114,14 @@ def _transform(messages: list[dict[str, str]]) -> list[dict[str, Any]]:
|
||||
|
||||
def _html_encode(string: str) -> str:
|
||||
table = {
|
||||
'"': """,
|
||||
"'": "'",
|
||||
"&": "&",
|
||||
">": ">",
|
||||
"<": "<",
|
||||
'"' : """,
|
||||
"'" : "'",
|
||||
"&" : "&",
|
||||
">" : ">",
|
||||
"<" : "<",
|
||||
"\n": "<br>",
|
||||
"\t": " ",
|
||||
" ": " ",
|
||||
" " : " ",
|
||||
}
|
||||
|
||||
for key in table:
|
||||
|
||||
@ -1,3 +1,5 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
|
||||
import js2py
|
||||
@ -8,19 +10,17 @@ from .base_provider import BaseProvider
|
||||
|
||||
|
||||
class DeepAi(BaseProvider):
|
||||
url = "https://deepai.org"
|
||||
working = True
|
||||
supports_stream = True
|
||||
url: str = "https://deepai.org"
|
||||
working = True
|
||||
supports_stream = True
|
||||
supports_gpt_35_turbo = True
|
||||
|
||||
@staticmethod
|
||||
def create_completion(
|
||||
model: str,
|
||||
messages: list[dict[str, str]],
|
||||
stream: bool,
|
||||
**kwargs: Any,
|
||||
) -> CreateResult:
|
||||
url = "https://api.deepai.org/make_me_a_pizza"
|
||||
stream: bool, **kwargs: Any) -> CreateResult:
|
||||
|
||||
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 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 +54,9 @@ 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",
|
||||
}
|
||||
|
||||
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):
|
||||
response.raise_for_status()
|
||||
yield chunk.decode()
|
||||
|
||||
@ -1,3 +1,5 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import re
|
||||
import time
|
||||
@ -9,48 +11,45 @@ from .base_provider import BaseProvider
|
||||
|
||||
|
||||
class DfeHub(BaseProvider):
|
||||
url = "https://chat.dfehub.com/api/chat"
|
||||
supports_stream = True
|
||||
url = "https://chat.dfehub.com/"
|
||||
supports_stream = True
|
||||
supports_gpt_35_turbo = True
|
||||
|
||||
@staticmethod
|
||||
def create_completion(
|
||||
model: str,
|
||||
messages: list[dict[str, str]],
|
||||
stream: bool,
|
||||
**kwargs: Any,
|
||||
) -> CreateResult:
|
||||
stream: bool, **kwargs: Any) -> CreateResult:
|
||||
|
||||
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://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-mobile": "?0",
|
||||
"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://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-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",
|
||||
"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,
|
||||
"model": "gpt-3.5-turbo",
|
||||
"temperature": kwargs.get("temperature", 0.5),
|
||||
"presence_penalty": kwargs.get("presence_penalty", 0),
|
||||
"frequency_penalty": kwargs.get("frequency_penalty", 0),
|
||||
"top_p": kwargs.get("top_p", 1),
|
||||
"stream": True,
|
||||
"messages" : messages,
|
||||
"model" : "gpt-3.5-turbo",
|
||||
"temperature" : kwargs.get("temperature", 0.5),
|
||||
"presence_penalty" : kwargs.get("presence_penalty", 0),
|
||||
"frequency_penalty" : kwargs.get("frequency_penalty", 0),
|
||||
"top_p" : kwargs.get("top_p", 1),
|
||||
"stream" : True
|
||||
}
|
||||
response = requests.post(
|
||||
"https://chat.dfehub.com/api/openai/v1/chat/completions",
|
||||
headers=headers,
|
||||
json=json_data,
|
||||
)
|
||||
|
||||
response = requests.post("https://chat.dfehub.com/api/openai/v1/chat/completions",
|
||||
headers=headers, json=json_data, timeout=3)
|
||||
|
||||
for chunk in response.iter_lines():
|
||||
if b"detail" in chunk:
|
||||
|
||||
@ -1,4 +1,7 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import random
|
||||
|
||||
import requests
|
||||
|
||||
@ -7,18 +10,17 @@ from .base_provider import BaseProvider
|
||||
|
||||
|
||||
class EasyChat(BaseProvider):
|
||||
url = "https://free.easychat.work"
|
||||
supports_stream = True
|
||||
url: str = "https://free.easychat.work"
|
||||
supports_stream = True
|
||||
supports_gpt_35_turbo = True
|
||||
working = True
|
||||
working = True
|
||||
|
||||
@staticmethod
|
||||
def create_completion(
|
||||
model: str,
|
||||
messages: list[dict[str, str]],
|
||||
stream: bool,
|
||||
**kwargs: Any,
|
||||
) -> CreateResult:
|
||||
stream: bool, **kwargs: Any) -> CreateResult:
|
||||
|
||||
active_servers = [
|
||||
"https://chat10.fastgpt.me",
|
||||
"https://chat9.fastgpt.me",
|
||||
@ -28,64 +30,69 @@ class EasyChat(BaseProvider):
|
||||
"https://chat4.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 = {
|
||||
"authority": f"{server}".replace("https://", ""),
|
||||
"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",
|
||||
"content-type": "application/json",
|
||||
"origin": f"{server}",
|
||||
"referer": f"{server}/",
|
||||
"x-requested-with": "XMLHttpRequest",
|
||||
'plugins': '0',
|
||||
'sec-ch-ua': '"Chromium";v="116", "Not)A;Brand";v="24", "Google Chrome";v="116"',
|
||||
'sec-ch-ua-mobile': '?0',
|
||||
"authority" : f"{server}".replace("https://", ""),
|
||||
"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",
|
||||
"content-type" : "application/json",
|
||||
"origin" : f"{server}",
|
||||
"referer" : f"{server}/",
|
||||
"x-requested-with" : "XMLHttpRequest",
|
||||
'plugins' : '0',
|
||||
'sec-ch-ua' : '"Chromium";v="116", "Not)A;Brand";v="24", "Google Chrome";v="116"',
|
||||
'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/116.0.0.0 Safari/537.36',
|
||||
'usesearch': 'false',
|
||||
'x-requested-with': 'XMLHttpRequest'
|
||||
'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/116.0.0.0 Safari/537.36',
|
||||
'usesearch' : 'false',
|
||||
'x-requested-with' : 'XMLHttpRequest'
|
||||
}
|
||||
|
||||
json_data = {
|
||||
"messages": messages,
|
||||
"stream": stream,
|
||||
"model": model,
|
||||
"temperature": kwargs.get("temperature", 0.5),
|
||||
"presence_penalty": kwargs.get("presence_penalty", 0),
|
||||
"frequency_penalty": kwargs.get("frequency_penalty", 0),
|
||||
"top_p": kwargs.get("top_p", 1),
|
||||
"messages" : messages,
|
||||
"stream" : stream,
|
||||
"model" : model,
|
||||
"temperature" : kwargs.get("temperature", 0.5),
|
||||
"presence_penalty" : kwargs.get("presence_penalty", 0),
|
||||
"frequency_penalty" : kwargs.get("frequency_penalty", 0),
|
||||
"top_p" : kwargs.get("top_p", 1)
|
||||
}
|
||||
|
||||
session = requests.Session()
|
||||
# init cookies from server
|
||||
session.get(f"{server}/")
|
||||
|
||||
response = session.post(
|
||||
f"{server}/api/openai/v1/chat/completions",
|
||||
headers=headers,
|
||||
json=json_data,
|
||||
stream=stream,
|
||||
)
|
||||
response = session.post(f"{server}/api/openai/v1/chat/completions",
|
||||
headers=headers, json=json_data, stream=stream)
|
||||
|
||||
if response.status_code == 200:
|
||||
|
||||
if stream == False:
|
||||
json_data = response.json()
|
||||
|
||||
if "choices" in json_data:
|
||||
yield json_data["choices"][0]["message"]["content"]
|
||||
else:
|
||||
yield Exception("No response from server")
|
||||
raise Exception("No response from server")
|
||||
|
||||
else:
|
||||
|
||||
for chunk in response.iter_lines():
|
||||
|
||||
if b"content" in chunk:
|
||||
splitData = chunk.decode().split("data: ")
|
||||
splitData = chunk.decode().split("data:")
|
||||
|
||||
if len(splitData) > 1:
|
||||
yield json.loads(splitData[1])["choices"][0]["delta"]["content"]
|
||||
else:
|
||||
continue
|
||||
else:
|
||||
yield Exception(f"Error {response.status_code} from server")
|
||||
|
||||
raise Exception(f"Error {response.status_code} from server : {response.reason}")
|
||||
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
|
||||
@ -1,58 +1,62 @@
|
||||
import requests, json
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
from abc import ABC, abstractmethod
|
||||
|
||||
import requests
|
||||
|
||||
from ..typing import Any, CreateResult
|
||||
|
||||
|
||||
class Equing(ABC):
|
||||
url: str = 'https://next.eqing.tech/'
|
||||
working = True
|
||||
needs_auth = False
|
||||
supports_stream = True
|
||||
url: str = 'https://next.eqing.tech/'
|
||||
working = True
|
||||
needs_auth = False
|
||||
supports_stream = True
|
||||
supports_gpt_35_turbo = True
|
||||
supports_gpt_4 = False
|
||||
supports_gpt_4 = False
|
||||
|
||||
@staticmethod
|
||||
@abstractmethod
|
||||
def create_completion(
|
||||
model: str,
|
||||
messages: list[dict[str, str]],
|
||||
stream: bool,
|
||||
**kwargs: Any) -> CreateResult:
|
||||
stream: bool, **kwargs: Any) -> CreateResult:
|
||||
|
||||
headers = {
|
||||
'authority': 'next.eqing.tech',
|
||||
'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',
|
||||
'cache-control': 'no-cache',
|
||||
'content-type': 'application/json',
|
||||
'origin': 'https://next.eqing.tech',
|
||||
'plugins': '0',
|
||||
'pragma': 'no-cache',
|
||||
'referer': 'https://next.eqing.tech/',
|
||||
'sec-ch-ua': '"Not/A)Brand";v="99", "Google Chrome";v="115", "Chromium";v="115"',
|
||||
'sec-ch-ua-mobile': '?0',
|
||||
'authority' : 'next.eqing.tech',
|
||||
'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',
|
||||
'cache-control' : 'no-cache',
|
||||
'content-type' : 'application/json',
|
||||
'origin' : 'https://next.eqing.tech',
|
||||
'plugins' : '0',
|
||||
'pragma' : 'no-cache',
|
||||
'referer' : 'https://next.eqing.tech/',
|
||||
'sec-ch-ua' : '"Not/A)Brand";v="99", "Google Chrome";v="115", "Chromium";v="115"',
|
||||
'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/115.0.0.0 Safari/537.36',
|
||||
'usesearch': 'false',
|
||||
'x-requested-with': 'XMLHttpRequest',
|
||||
'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/115.0.0.0 Safari/537.36',
|
||||
'usesearch' : 'false',
|
||||
'x-requested-with' : 'XMLHttpRequest'
|
||||
}
|
||||
|
||||
json_data = {
|
||||
'messages': messages,
|
||||
'stream': stream,
|
||||
'model': model,
|
||||
'temperature': kwargs.get('temperature', 0.5),
|
||||
'presence_penalty': kwargs.get('presence_penalty', 0),
|
||||
'frequency_penalty': kwargs.get('frequency_penalty', 0),
|
||||
'top_p': kwargs.get('top_p', 1),
|
||||
'messages' : messages,
|
||||
'stream' : stream,
|
||||
'model' : model,
|
||||
'temperature' : kwargs.get('temperature', 0.5),
|
||||
'presence_penalty' : kwargs.get('presence_penalty', 0),
|
||||
'frequency_penalty' : kwargs.get('frequency_penalty', 0),
|
||||
'top_p' : kwargs.get('top_p', 1),
|
||||
}
|
||||
|
||||
response = requests.post('https://next.eqing.tech/api/openai/v1/chat/completions',
|
||||
headers=headers, json=json_data, stream=stream)
|
||||
|
||||
if not stream:
|
||||
yield response.json()["choices"][0]["message"]["content"]
|
||||
return
|
||||
|
||||
@ -1,55 +1,58 @@
|
||||
import requests, json, random
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import random
|
||||
from abc import ABC, abstractmethod
|
||||
|
||||
import requests
|
||||
|
||||
from ..typing import Any, CreateResult
|
||||
|
||||
|
||||
class FastGpt(ABC):
|
||||
url: str = 'https://chat9.fastgpt.me/'
|
||||
working = True
|
||||
needs_auth = False
|
||||
supports_stream = True
|
||||
supports_gpt_35_turbo = True
|
||||
supports_gpt_4 = False
|
||||
url: str = 'https://chat9.fastgpt.me/'
|
||||
working = False
|
||||
needs_auth = False
|
||||
supports_stream = True
|
||||
supports_gpt_35_turbo = True
|
||||
supports_gpt_4 = False
|
||||
|
||||
@staticmethod
|
||||
@abstractmethod
|
||||
def create_completion(
|
||||
model: str,
|
||||
messages: list[dict[str, str]],
|
||||
stream: bool,
|
||||
**kwargs: Any) -> CreateResult:
|
||||
stream: bool, **kwargs: Any) -> CreateResult:
|
||||
|
||||
headers = {
|
||||
'authority': 'chat9.fastgpt.me',
|
||||
'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',
|
||||
'cache-control': 'no-cache',
|
||||
'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',
|
||||
'plugins': '0',
|
||||
'pragma': 'no-cache',
|
||||
'referer': 'https://chat9.fastgpt.me/',
|
||||
'sec-ch-ua': '"Not/A)Brand";v="99", "Google Chrome";v="115", "Chromium";v="115"',
|
||||
'sec-ch-ua-mobile': '?0',
|
||||
'authority' : 'chat9.fastgpt.me',
|
||||
'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',
|
||||
'cache-control' : 'no-cache',
|
||||
'content-type' : 'application/json',
|
||||
'origin' : 'https://chat9.fastgpt.me',
|
||||
'plugins' : '0',
|
||||
'pragma' : 'no-cache',
|
||||
'referer' : 'https://chat9.fastgpt.me/',
|
||||
'sec-ch-ua' : '"Not/A)Brand";v="99", "Google Chrome";v="115", "Chromium";v="115"',
|
||||
'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/115.0.0.0 Safari/537.36',
|
||||
'usesearch': 'false',
|
||||
'x-requested-with': 'XMLHttpRequest',
|
||||
'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/115.0.0.0 Safari/537.36',
|
||||
'usesearch' : 'false',
|
||||
'x-requested-with' : 'XMLHttpRequest',
|
||||
}
|
||||
|
||||
json_data = {
|
||||
'messages': messages,
|
||||
'stream': stream,
|
||||
'model': model,
|
||||
'temperature': kwargs.get('temperature', 0.5),
|
||||
'presence_penalty': kwargs.get('presence_penalty', 0),
|
||||
'frequency_penalty': kwargs.get('frequency_penalty', 0),
|
||||
'top_p': kwargs.get('top_p', 1),
|
||||
'messages' : messages,
|
||||
'stream' : stream,
|
||||
'model' : model,
|
||||
'temperature' : kwargs.get('temperature', 0.5),
|
||||
'presence_penalty' : kwargs.get('presence_penalty', 0),
|
||||
'frequency_penalty' : kwargs.get('frequency_penalty', 0),
|
||||
'top_p' : kwargs.get('top_p', 1),
|
||||
}
|
||||
|
||||
subdomain = random.choice([
|
||||
@ -58,7 +61,7 @@ class FastGpt(ABC):
|
||||
])
|
||||
|
||||
response = requests.post(f'https://{subdomain}.fastgpt.me/api/openai/v1/chat/completions',
|
||||
headers=headers, json=json_data, stream=stream)
|
||||
headers=headers, json=json_data, stream=stream)
|
||||
|
||||
for line in response.iter_lines():
|
||||
if line:
|
||||
|
||||
@ -1,3 +1,5 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
|
||||
import requests
|
||||
@ -7,34 +9,31 @@ from .base_provider import BaseProvider
|
||||
|
||||
|
||||
class Forefront(BaseProvider):
|
||||
url = "https://forefront.com"
|
||||
supports_stream = True
|
||||
url = "https://forefront.com"
|
||||
supports_stream = True
|
||||
supports_gpt_35_turbo = True
|
||||
|
||||
@staticmethod
|
||||
def create_completion(
|
||||
model: str,
|
||||
messages: list[dict[str, str]],
|
||||
stream: bool,
|
||||
**kwargs: Any,
|
||||
) -> CreateResult:
|
||||
stream: bool, **kwargs: Any) -> CreateResult:
|
||||
|
||||
json_data = {
|
||||
"text": messages[-1]["content"],
|
||||
"action": "noauth",
|
||||
"id": "",
|
||||
"parentId": "",
|
||||
"workspaceId": "",
|
||||
"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",
|
||||
"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,
|
||||
)
|
||||
response = requests.post("https://streaming.tenant-forefront-default.knative.chi.coreweave.com/free-chat",
|
||||
json=json_data, stream=True)
|
||||
|
||||
response.raise_for_status()
|
||||
for token in response.iter_lines():
|
||||
if b"delta" in token:
|
||||
|
||||
@ -1,3 +1,5 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import os
|
||||
import uuid
|
||||
@ -10,78 +12,77 @@ from .base_provider import BaseProvider
|
||||
|
||||
|
||||
class GetGpt(BaseProvider):
|
||||
url = "https://chat.getgpt.world/"
|
||||
supports_stream = True
|
||||
working = True
|
||||
url = 'https://chat.getgpt.world/'
|
||||
supports_stream = True
|
||||
working = True
|
||||
supports_gpt_35_turbo = True
|
||||
|
||||
@staticmethod
|
||||
def create_completion(
|
||||
model: str,
|
||||
messages: list[dict[str, str]],
|
||||
stream: bool,
|
||||
**kwargs: Any,
|
||||
) -> CreateResult:
|
||||
stream: bool, **kwargs: Any) -> CreateResult:
|
||||
|
||||
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",
|
||||
'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()),
|
||||
'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,
|
||||
)
|
||||
res = requests.post('https://chat.getgpt.world/api/chat/stream',
|
||||
headers=headers, json={'signature': _encrypt(data)}, stream=True)
|
||||
|
||||
res.raise_for_status()
|
||||
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"])
|
||||
if b'content' in line:
|
||||
line_json = json.loads(line.decode('utf-8').split('data: ')[1])
|
||||
yield (line_json['choices'][0]['delta']['content'])
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def params(cls):
|
||||
params = [
|
||||
("model", "str"),
|
||||
("messages", "list[dict[str, str]]"),
|
||||
("stream", "bool"),
|
||||
("temperature", "float"),
|
||||
("presence_penalty", "int"),
|
||||
("frequency_penalty", "int"),
|
||||
("top_p", "int"),
|
||||
("max_tokens", "int"),
|
||||
('model', 'str'),
|
||||
('messages', 'list[dict[str, str]]'),
|
||||
('stream', 'bool'),
|
||||
('temperature', 'float'),
|
||||
('presence_penalty', 'int'),
|
||||
('frequency_penalty', 'int'),
|
||||
('top_p', 'int'),
|
||||
('max_tokens', 'int'),
|
||||
]
|
||||
param = ", ".join([": ".join(p) for p in params])
|
||||
return f"g4f.provider.{cls.__name__} supports: ({param})"
|
||||
param = ', '.join([': '.join(p) for p in params])
|
||||
return f'g4f.provider.{cls.__name__} supports: ({param})'
|
||||
|
||||
|
||||
def _encrypt(e: str):
|
||||
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)
|
||||
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")
|
||||
|
||||
return ciphertext.hex() + t.decode('utf-8') + n.decode('utf-8')
|
||||
|
||||
|
||||
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 = bytes([padding_size] * padding_size)
|
||||
padding = bytes([padding_size] * padding_size)
|
||||
|
||||
return data + padding
|
||||
|
||||
@ -1,86 +1,88 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import uuid
|
||||
|
||||
import requests
|
||||
from aiohttp import ClientSession
|
||||
|
||||
from ..typing import Any, CreateResult
|
||||
from .base_provider import BaseProvider
|
||||
from ..typing import AsyncGenerator
|
||||
from .base_provider import AsyncGeneratorProvider, format_prompt
|
||||
|
||||
|
||||
class H2o(BaseProvider):
|
||||
class H2o(AsyncGeneratorProvider):
|
||||
url = "https://gpt-gm.h2o.ai"
|
||||
working = True
|
||||
supports_stream = True
|
||||
model = "h2oai/h2ogpt-gm-oasst1-en-2048-falcon-40b-v1"
|
||||
|
||||
@staticmethod
|
||||
def create_completion(
|
||||
@classmethod
|
||||
async def create_async_generator(
|
||||
cls,
|
||||
model: str,
|
||||
messages: list[dict[str, str]],
|
||||
stream: bool,
|
||||
**kwargs: Any,
|
||||
) -> CreateResult:
|
||||
conversation = ""
|
||||
for message in messages:
|
||||
conversation += "%s: %s\n" % (message["role"], message["content"])
|
||||
conversation += "assistant: "
|
||||
|
||||
session = requests.Session()
|
||||
|
||||
headers = {"Referer": "https://gpt-gm.h2o.ai/r/jGfKSwU"}
|
||||
data = {
|
||||
"ethicsModalAccepted": "true",
|
||||
"shareConversationsWithModelAuthors": "true",
|
||||
"ethicsModalAcceptedAt": "",
|
||||
"activeModel": model,
|
||||
"searchEnabled": "true",
|
||||
}
|
||||
session.post(
|
||||
"https://gpt-gm.h2o.ai/settings",
|
||||
headers=headers,
|
||||
data=data,
|
||||
)
|
||||
|
||||
proxy: str = None,
|
||||
**kwargs
|
||||
) -> AsyncGenerator:
|
||||
model = model if model else cls.model
|
||||
headers = {"Referer": "https://gpt-gm.h2o.ai/"}
|
||||
data = {"model": model}
|
||||
|
||||
response = session.post(
|
||||
"https://gpt-gm.h2o.ai/conversation",
|
||||
headers=headers,
|
||||
json=data,
|
||||
)
|
||||
conversation_id = response.json()["conversationId"]
|
||||
async with ClientSession(
|
||||
headers=headers
|
||||
) as session:
|
||||
data = {
|
||||
"ethicsModalAccepted": "true",
|
||||
"shareConversationsWithModelAuthors": "true",
|
||||
"ethicsModalAcceptedAt": "",
|
||||
"activeModel": model,
|
||||
"searchEnabled": "true",
|
||||
}
|
||||
async with session.post(
|
||||
"https://gpt-gm.h2o.ai/settings",
|
||||
proxy=proxy,
|
||||
data=data
|
||||
) as response:
|
||||
response.raise_for_status()
|
||||
|
||||
data = {
|
||||
"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(uuid.uuid4())),
|
||||
"response_id": kwargs.get("response_id", str(uuid.uuid4())),
|
||||
"is_retry": False,
|
||||
"use_cache": False,
|
||||
"web_search_id": "",
|
||||
},
|
||||
}
|
||||
async with session.post(
|
||||
"https://gpt-gm.h2o.ai/conversation",
|
||||
proxy=proxy,
|
||||
json={"model": model},
|
||||
) as response:
|
||||
response.raise_for_status()
|
||||
conversationId = (await response.json())["conversationId"]
|
||||
|
||||
response = session.post(
|
||||
f"https://gpt-gm.h2o.ai/conversation/{conversation_id}",
|
||||
headers=headers,
|
||||
json=data,
|
||||
)
|
||||
response.raise_for_status()
|
||||
response.encoding = "utf-8"
|
||||
generated_text = response.text.replace("\n", "").split("data:")
|
||||
generated_text = json.loads(generated_text[-1])
|
||||
|
||||
yield generated_text["generated_text"]
|
||||
data = {
|
||||
"inputs": format_prompt(messages),
|
||||
"parameters": {
|
||||
"temperature": 0.4,
|
||||
"truncate": 2048,
|
||||
"max_new_tokens": 1024,
|
||||
"do_sample": True,
|
||||
"repetition_penalty": 1.2,
|
||||
"return_full_text": False,
|
||||
**kwargs
|
||||
},
|
||||
"stream": True,
|
||||
"options": {
|
||||
"id": str(uuid.uuid4()),
|
||||
"response_id": str(uuid.uuid4()),
|
||||
"is_retry": False,
|
||||
"use_cache": False,
|
||||
"web_search_id": "",
|
||||
},
|
||||
}
|
||||
async with session.post(
|
||||
f"https://gpt-gm.h2o.ai/conversation/{conversationId}",
|
||||
proxy=proxy,
|
||||
json=data
|
||||
) as response:
|
||||
start = "data:"
|
||||
async for line in response.content:
|
||||
line = line.decode("utf-8")
|
||||
if line and line.startswith(start):
|
||||
line = json.loads(line[len(start):-1])
|
||||
if not line["token"]["special"]:
|
||||
yield line["token"]["text"]
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
|
||||
110
g4f/Provider/HuggingChat.py
Normal file
110
g4f/Provider/HuggingChat.py
Normal file
@ -0,0 +1,110 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
|
||||
from aiohttp import ClientSession
|
||||
|
||||
from ..typing import AsyncGenerator
|
||||
from .base_provider import AsyncGeneratorProvider, format_prompt, get_cookies
|
||||
|
||||
|
||||
class HuggingChat(AsyncGeneratorProvider):
|
||||
url = "https://huggingface.co/chat/"
|
||||
needs_auth = True
|
||||
working = True
|
||||
model = "OpenAssistant/oasst-sft-6-llama-30b-xor"
|
||||
|
||||
@classmethod
|
||||
async def create_async_generator(
|
||||
cls,
|
||||
model: str,
|
||||
messages: list[dict[str, str]],
|
||||
stream: bool = True,
|
||||
proxy: str = None,
|
||||
cookies: dict = None,
|
||||
**kwargs
|
||||
) -> AsyncGenerator:
|
||||
if not cookies:
|
||||
cookies = get_cookies(".huggingface.co")
|
||||
model = model if model else cls.model
|
||||
if proxy and "://" not in proxy:
|
||||
proxy = f"http://{proxy}"
|
||||
|
||||
headers = {
|
||||
'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',
|
||||
}
|
||||
async with ClientSession(
|
||||
cookies=cookies,
|
||||
headers=headers
|
||||
) as session:
|
||||
async with session.post("https://huggingface.co/chat/conversation", proxy=proxy, json={"model": model}) as response:
|
||||
conversation_id = (await response.json())["conversationId"]
|
||||
|
||||
send = {
|
||||
"inputs": format_prompt(messages),
|
||||
"parameters": {
|
||||
"temperature": 0.2,
|
||||
"truncate": 1000,
|
||||
"max_new_tokens": 1024,
|
||||
"stop": ["</s>"],
|
||||
"top_p": 0.95,
|
||||
"repetition_penalty": 1.2,
|
||||
"top_k": 50,
|
||||
"return_full_text": False,
|
||||
**kwargs
|
||||
},
|
||||
"stream": stream,
|
||||
"options": {
|
||||
"id": "9e9b8bc4-6604-40c6-994e-8eb78fa32e37",
|
||||
"response_id": "04ce2602-3bea-45e8-8efc-cef00680376a",
|
||||
"is_retry": False,
|
||||
"use_cache": False,
|
||||
"web_search_id": ""
|
||||
}
|
||||
}
|
||||
start = "data:"
|
||||
first = True
|
||||
async with session.post(f"https://huggingface.co/chat/conversation/{conversation_id}", proxy=proxy, json=send) as response:
|
||||
async for line in response.content:
|
||||
line = line.decode("utf-8")
|
||||
if not line:
|
||||
continue
|
||||
if not stream:
|
||||
try:
|
||||
data = json.loads(line)
|
||||
except json.decoder.JSONDecodeError:
|
||||
raise RuntimeError(f"No json: {line}")
|
||||
if "error" in data:
|
||||
raise RuntimeError(data["error"])
|
||||
elif isinstance(data, list):
|
||||
yield data[0]["generated_text"]
|
||||
else:
|
||||
raise RuntimeError(f"Response: {line}")
|
||||
elif line.startswith(start):
|
||||
line = json.loads(line[len(start):-1])
|
||||
if not line:
|
||||
continue
|
||||
if "token" not in line:
|
||||
raise RuntimeError(f"Response: {line}")
|
||||
if not line["token"]["special"]:
|
||||
if first:
|
||||
yield line["token"]["text"].lstrip()
|
||||
first = False
|
||||
else:
|
||||
yield line["token"]["text"]
|
||||
|
||||
async with session.delete(f"https://huggingface.co/chat/conversation/{conversation_id}", proxy=proxy) as response:
|
||||
response.raise_for_status()
|
||||
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def params(cls):
|
||||
params = [
|
||||
("model", "str"),
|
||||
("messages", "list[dict[str, str]]"),
|
||||
("stream", "bool"),
|
||||
("proxy", "str"),
|
||||
]
|
||||
param = ", ".join([": ".join(p) for p in params])
|
||||
return f"g4f.provider.{cls.__name__} supports: ({param})"
|
||||
@ -1,64 +1,81 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import uuid
|
||||
|
||||
import requests
|
||||
from aiohttp import ClientSession
|
||||
|
||||
from ..typing import Any, CreateResult
|
||||
from .base_provider import BaseProvider
|
||||
from ..typing import AsyncGenerator
|
||||
from .base_provider import AsyncGeneratorProvider
|
||||
|
||||
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,
|
||||
},
|
||||
}
|
||||
|
||||
class Liaobots(BaseProvider):
|
||||
class Liaobots(AsyncGeneratorProvider):
|
||||
url = "https://liaobots.com"
|
||||
working = True
|
||||
supports_stream = True
|
||||
needs_auth = True
|
||||
supports_gpt_35_turbo = True
|
||||
supports_gpt_4 = True
|
||||
_auth_code = None
|
||||
|
||||
@staticmethod
|
||||
def create_completion(
|
||||
@classmethod
|
||||
async def create_async_generator(
|
||||
cls,
|
||||
model: str,
|
||||
messages: list[dict[str, str]],
|
||||
stream: bool,
|
||||
**kwargs: Any,
|
||||
) -> CreateResult:
|
||||
auth: str = None,
|
||||
proxy: str = None,
|
||||
**kwargs
|
||||
) -> AsyncGenerator:
|
||||
if proxy and "://" not in proxy:
|
||||
proxy = f"http://{proxy}"
|
||||
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": str(kwargs.get("auth")),
|
||||
}
|
||||
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,
|
||||
},
|
||||
}
|
||||
json_data = {
|
||||
"conversationId": str(uuid.uuid4()),
|
||||
"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.",
|
||||
}
|
||||
async with ClientSession(
|
||||
headers=headers
|
||||
) as session:
|
||||
model = model if model in models else "gpt-3.5-turbo"
|
||||
auth_code = auth if isinstance(auth, str) else cls._auth_code
|
||||
if not auth_code:
|
||||
async with session.post("https://liaobots.com/api/user", proxy=proxy, json={"authcode": ""}) as response:
|
||||
response.raise_for_status()
|
||||
auth_code = cls._auth_code = json.loads((await response.text()))["authCode"]
|
||||
data = {
|
||||
"conversationId": str(uuid.uuid4()),
|
||||
"model": models[model],
|
||||
"messages": messages,
|
||||
"key": "",
|
||||
"prompt": "You are ChatGPT, a large language model trained by OpenAI. Follow the user's instructions carefully.",
|
||||
}
|
||||
async with session.post("https://liaobots.com/api/chat", proxy=proxy, json=data, headers={"x-auth-code": auth_code}) as response:
|
||||
response.raise_for_status()
|
||||
async for line in response.content:
|
||||
yield line.decode("utf-8")
|
||||
|
||||
response = requests.post(
|
||||
"https://liaobots.com/api/chat",
|
||||
headers=headers,
|
||||
json=json_data,
|
||||
stream=True,
|
||||
)
|
||||
response.raise_for_status()
|
||||
for token in response.iter_content(chunk_size=2046):
|
||||
yield token.decode("utf-8")
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
@ -67,6 +84,7 @@ class Liaobots(BaseProvider):
|
||||
("model", "str"),
|
||||
("messages", "list[dict[str, str]]"),
|
||||
("stream", "bool"),
|
||||
("proxy", "str"),
|
||||
("auth", "str"),
|
||||
]
|
||||
param = ", ".join([": ".join(p) for p in params])
|
||||
|
||||
@ -1,3 +1,5 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
|
||||
import requests
|
||||
@ -7,46 +9,42 @@ from .base_provider import BaseProvider
|
||||
|
||||
|
||||
class Lockchat(BaseProvider):
|
||||
url = "http://supertest.lockchat.app"
|
||||
supports_stream = True
|
||||
url: str = "http://supertest.lockchat.app"
|
||||
supports_stream = True
|
||||
supports_gpt_35_turbo = True
|
||||
supports_gpt_4 = True
|
||||
supports_gpt_4 = True
|
||||
|
||||
@staticmethod
|
||||
def create_completion(
|
||||
model: str,
|
||||
messages: list[dict[str, str]],
|
||||
stream: bool,
|
||||
**kwargs: Any,
|
||||
) -> CreateResult:
|
||||
stream: bool, **kwargs: Any) -> CreateResult:
|
||||
|
||||
temperature = float(kwargs.get("temperature", 0.7))
|
||||
payload = {
|
||||
"temperature": temperature,
|
||||
"messages": messages,
|
||||
"model": model,
|
||||
"stream": True,
|
||||
"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,
|
||||
)
|
||||
response = requests.post("http://supertest.lockchat.app/v1/chat/completions",
|
||||
json=payload, headers=headers, stream=True)
|
||||
|
||||
response.raise_for_status()
|
||||
for token in response.iter_lines():
|
||||
if b"The model: `gpt-4` does not exist" in token:
|
||||
print("error, retrying...")
|
||||
Lockchat.create_completion(
|
||||
model=model,
|
||||
messages=messages,
|
||||
stream=stream,
|
||||
temperature=temperature,
|
||||
**kwargs,
|
||||
)
|
||||
model = model,
|
||||
messages = messages,
|
||||
stream = stream,
|
||||
temperature = temperature,
|
||||
**kwargs)
|
||||
|
||||
if b"content" in token:
|
||||
token = json.loads(token.decode("utf-8").split("data: ")[1])
|
||||
token = token["choices"][0]["delta"].get("content")
|
||||
|
||||
@ -1,3 +1,5 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import requests
|
||||
|
||||
from ..typing import Any, CreateResult
|
||||
@ -5,33 +7,30 @@ from .base_provider import BaseProvider
|
||||
|
||||
|
||||
class Opchatgpts(BaseProvider):
|
||||
url = "https://opchatgpts.net"
|
||||
working = True
|
||||
url = "https://opchatgpts.net"
|
||||
working = True
|
||||
supports_gpt_35_turbo = True
|
||||
|
||||
@staticmethod
|
||||
def create_completion(
|
||||
model: str,
|
||||
messages: list[dict[str, str]],
|
||||
stream: bool,
|
||||
**kwargs: Any,
|
||||
) -> CreateResult:
|
||||
temperature = kwargs.get("temperature", 0.8)
|
||||
max_tokens = kwargs.get("max_tokens", 1024)
|
||||
stream: bool, **kwargs: Any) -> CreateResult:
|
||||
|
||||
temperature = kwargs.get("temperature", 0.8)
|
||||
max_tokens = kwargs.get("max_tokens", 1024)
|
||||
system_prompt = kwargs.get(
|
||||
"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(
|
||||
messages=messages,
|
||||
temperature=temperature,
|
||||
max_tokens=max_tokens,
|
||||
system_prompt=system_prompt,
|
||||
)
|
||||
messages = messages,
|
||||
temperature = temperature,
|
||||
max_tokens = max_tokens,
|
||||
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()
|
||||
yield response.json()["reply"]
|
||||
|
||||
@ -39,24 +38,23 @@ class Opchatgpts(BaseProvider):
|
||||
def _create_payload(
|
||||
messages: list[dict[str, str]],
|
||||
temperature: float,
|
||||
max_tokens: int,
|
||||
system_prompt: str,
|
||||
):
|
||||
max_tokens: int, system_prompt: str) -> dict:
|
||||
|
||||
return {
|
||||
"env": "chatbot",
|
||||
"session": "N/A",
|
||||
"prompt": "\n",
|
||||
"context": system_prompt,
|
||||
"messages": messages,
|
||||
"newMessage": messages[::-1][0]["content"],
|
||||
"userName": '<div class="mwai-name-text">User:</div>',
|
||||
"aiName": '<div class="mwai-name-text">AI:</div>',
|
||||
"model": "gpt-3.5-turbo",
|
||||
"temperature": temperature,
|
||||
"maxTokens": max_tokens,
|
||||
"maxResults": 1,
|
||||
"apiKey": "",
|
||||
"service": "openai",
|
||||
"embeddingsIndex": "",
|
||||
"stop": "",
|
||||
"env" : "chatbot",
|
||||
"session" : "N/A",
|
||||
"prompt" : "\n",
|
||||
"context" : system_prompt,
|
||||
"messages" : messages,
|
||||
"newMessage" : messages[::-1][0]["content"],
|
||||
"userName" : '<div class="mwai-name-text">User:</div>',
|
||||
"aiName" : '<div class="mwai-name-text">AI:</div>',
|
||||
"model" : "gpt-3.5-turbo",
|
||||
"temperature" : temperature,
|
||||
"maxTokens" : max_tokens,
|
||||
"maxResults" : 1,
|
||||
"apiKey" : "",
|
||||
"service" : "openai",
|
||||
"embeddingsIndex" : "",
|
||||
"stop" : "",
|
||||
}
|
||||
|
||||
102
g4f/Provider/OpenAssistant.py
Normal file
102
g4f/Provider/OpenAssistant.py
Normal file
@ -0,0 +1,102 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
|
||||
from aiohttp import ClientSession
|
||||
|
||||
from ..typing import Any, AsyncGenerator
|
||||
from .base_provider import AsyncGeneratorProvider, format_prompt, get_cookies
|
||||
|
||||
|
||||
class OpenAssistant(AsyncGeneratorProvider):
|
||||
url = "https://open-assistant.io/chat"
|
||||
needs_auth = True
|
||||
working = True
|
||||
model = "OA_SFT_Llama_30B_6"
|
||||
|
||||
@classmethod
|
||||
async def create_async_generator(
|
||||
cls,
|
||||
model: str,
|
||||
messages: list[dict[str, str]],
|
||||
proxy: str = None,
|
||||
cookies: dict = None,
|
||||
**kwargs: Any
|
||||
) -> AsyncGenerator:
|
||||
if proxy and "://" not in proxy:
|
||||
proxy = f"http://{proxy}"
|
||||
if not cookies:
|
||||
cookies = get_cookies("open-assistant.io")
|
||||
|
||||
headers = {
|
||||
'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',
|
||||
}
|
||||
async with ClientSession(
|
||||
cookies=cookies,
|
||||
headers=headers
|
||||
) as session:
|
||||
async with session.post("https://open-assistant.io/api/chat", proxy=proxy) as response:
|
||||
chat_id = (await response.json())["id"]
|
||||
|
||||
data = {
|
||||
"chat_id": chat_id,
|
||||
"content": f"<s>[INST]\n{format_prompt(messages)}\n[/INST]",
|
||||
"parent_id": None
|
||||
}
|
||||
async with session.post("https://open-assistant.io/api/chat/prompter_message", proxy=proxy, json=data) as response:
|
||||
parent_id = (await response.json())["id"]
|
||||
|
||||
data = {
|
||||
"chat_id": chat_id,
|
||||
"parent_id": parent_id,
|
||||
"model_config_name": model if model else cls.model,
|
||||
"sampling_parameters":{
|
||||
"top_k": 50,
|
||||
"top_p": None,
|
||||
"typical_p": None,
|
||||
"temperature": 0.35,
|
||||
"repetition_penalty": 1.1111111111111112,
|
||||
"max_new_tokens": 1024,
|
||||
**kwargs
|
||||
},
|
||||
"plugins":[]
|
||||
}
|
||||
async with session.post("https://open-assistant.io/api/chat/assistant_message", proxy=proxy, json=data) as response:
|
||||
data = await response.json()
|
||||
if "id" in data:
|
||||
message_id = data["id"]
|
||||
elif "message" in data:
|
||||
raise RuntimeError(data["message"])
|
||||
else:
|
||||
response.raise_for_status()
|
||||
|
||||
params = {
|
||||
'chat_id': chat_id,
|
||||
'message_id': message_id,
|
||||
}
|
||||
async with session.post("https://open-assistant.io/api/chat/events", proxy=proxy, params=params) as response:
|
||||
start = "data: "
|
||||
async for line in response.content:
|
||||
line = line.decode("utf-8")
|
||||
if line and line.startswith(start):
|
||||
line = json.loads(line[len(start):])
|
||||
if line["event_type"] == "token":
|
||||
yield line["text"]
|
||||
|
||||
params = {
|
||||
'chat_id': chat_id,
|
||||
}
|
||||
async with session.delete("https://open-assistant.io/api/chat", proxy=proxy, params=params) as response:
|
||||
response.raise_for_status()
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def params(cls):
|
||||
params = [
|
||||
("model", "str"),
|
||||
("messages", "list[dict[str, str]]"),
|
||||
("stream", "bool"),
|
||||
("proxy", "str"),
|
||||
]
|
||||
param = ", ".join([": ".join(p) for p in params])
|
||||
return f"g4f.provider.{cls.__name__} supports: ({param})"
|
||||
86
g4f/Provider/OpenaiChat.py
Normal file
86
g4f/Provider/OpenaiChat.py
Normal file
@ -0,0 +1,86 @@
|
||||
from __future__ import annotations
|
||||
|
||||
has_module = True
|
||||
try:
|
||||
from revChatGPT.V1 import AsyncChatbot
|
||||
except ImportError:
|
||||
has_module = False
|
||||
|
||||
import json
|
||||
|
||||
from httpx import AsyncClient
|
||||
|
||||
from ..typing import AsyncGenerator
|
||||
from .base_provider import AsyncGeneratorProvider, format_prompt, get_cookies
|
||||
|
||||
|
||||
class OpenaiChat(AsyncGeneratorProvider):
|
||||
url = "https://chat.openai.com"
|
||||
needs_auth = True
|
||||
working = has_module
|
||||
supports_gpt_35_turbo = True
|
||||
supports_gpt_4 = True
|
||||
supports_stream = True
|
||||
_access_token = None
|
||||
|
||||
@classmethod
|
||||
async def create_async_generator(
|
||||
cls,
|
||||
model: str,
|
||||
messages: list[dict[str, str]],
|
||||
proxy: str = None,
|
||||
access_token: str = _access_token,
|
||||
cookies: dict = None,
|
||||
**kwargs: dict
|
||||
) -> AsyncGenerator:
|
||||
|
||||
config = {"access_token": access_token, "model": model}
|
||||
if proxy:
|
||||
if "://" not in proxy:
|
||||
proxy = f"http://{proxy}"
|
||||
config["proxy"] = proxy
|
||||
|
||||
bot = AsyncChatbot(
|
||||
config=config
|
||||
)
|
||||
|
||||
if not access_token:
|
||||
cookies = cookies if cookies else get_cookies("chat.openai.com")
|
||||
cls._access_token = await get_access_token(bot.session, cookies)
|
||||
bot.set_access_token(cls._access_token)
|
||||
|
||||
returned = None
|
||||
async for message in bot.ask(format_prompt(messages)):
|
||||
message = message["message"]
|
||||
if returned:
|
||||
if message.startswith(returned):
|
||||
new = message[len(returned):]
|
||||
if new:
|
||||
yield new
|
||||
else:
|
||||
yield message
|
||||
returned = message
|
||||
|
||||
await bot.delete_conversation(bot.conversation_id)
|
||||
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def params(cls):
|
||||
params = [
|
||||
("model", "str"),
|
||||
("messages", "list[dict[str, str]]"),
|
||||
("stream", "bool"),
|
||||
("proxy", "str"),
|
||||
]
|
||||
param = ", ".join([": ".join(p) for p in params])
|
||||
return f"g4f.provider.{cls.__name__} supports: ({param})"
|
||||
|
||||
|
||||
async def get_access_token(session: AsyncClient, cookies: dict):
|
||||
response = await session.get("https://chat.openai.com/api/auth/session", cookies=cookies)
|
||||
response.raise_for_status()
|
||||
try:
|
||||
return response.json()["accessToken"]
|
||||
except json.decoder.JSONDecodeError:
|
||||
raise RuntimeError(f"Response: {response.text}")
|
||||
@ -1,17 +1,20 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
|
||||
import requests
|
||||
|
||||
from ..typing import Any, CreateResult
|
||||
from .base_provider import BaseProvider
|
||||
|
||||
|
||||
class Raycast(BaseProvider):
|
||||
url = "https://raycast.com"
|
||||
# model = ['gpt-3.5-turbo', 'gpt-4']
|
||||
supports_gpt_35_turbo = True
|
||||
supports_gpt_4 = True
|
||||
supports_stream = True
|
||||
needs_auth = True
|
||||
working = True
|
||||
url = "https://raycast.com"
|
||||
supports_gpt_35_turbo = True
|
||||
supports_gpt_4 = True
|
||||
supports_stream = True
|
||||
needs_auth = True
|
||||
working = True
|
||||
|
||||
@staticmethod
|
||||
def create_completion(
|
||||
|
||||
@ -1,74 +1,75 @@
|
||||
import json,random,requests
|
||||
# from curl_cffi import requests
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import random
|
||||
|
||||
import requests
|
||||
|
||||
from ..typing import Any, CreateResult
|
||||
from .base_provider import BaseProvider
|
||||
|
||||
|
||||
class Theb(BaseProvider):
|
||||
url = "https://theb.ai"
|
||||
working = True
|
||||
supports_stream = True
|
||||
supports_gpt_35_turbo = True
|
||||
needs_auth = True
|
||||
url = "https://theb.ai"
|
||||
working = True
|
||||
supports_stream = True
|
||||
supports_gpt_35_turbo = True
|
||||
needs_auth = True
|
||||
|
||||
@staticmethod
|
||||
def create_completion(
|
||||
model: str,
|
||||
messages: list[dict[str, str]],
|
||||
stream: bool,
|
||||
**kwargs: Any,
|
||||
) -> CreateResult:
|
||||
conversation = ''
|
||||
for message in messages:
|
||||
conversation += '%s: %s\n' % (message['role'], message['content'])
|
||||
stream: bool, **kwargs: Any) -> CreateResult:
|
||||
|
||||
conversation = "\n".join(f"{message['role']}: {message['content']}" for message in messages)
|
||||
conversation += "\nassistant: "
|
||||
|
||||
conversation += 'assistant: '
|
||||
auth = kwargs.get("auth", {
|
||||
"bearer_token":"free",
|
||||
"org_id":"theb",
|
||||
})
|
||||
|
||||
bearer_token = auth["bearer_token"]
|
||||
org_id = auth["org_id"]
|
||||
org_id = auth["org_id"]
|
||||
|
||||
headers = {
|
||||
'authority': 'beta.theb.ai',
|
||||
'accept': 'text/event-stream',
|
||||
'accept-language': 'id-ID,id;q=0.9,en-US;q=0.8,en;q=0.7',
|
||||
'authorization': 'Bearer '+bearer_token,
|
||||
'content-type': 'application/json',
|
||||
'origin': 'https://beta.theb.ai',
|
||||
'referer': 'https://beta.theb.ai/home',
|
||||
'sec-ch-ua': '"Chromium";v="116", "Not)A;Brand";v="24", "Google Chrome";v="116"',
|
||||
'sec-ch-ua-mobile': '?0',
|
||||
'authority' : 'beta.theb.ai',
|
||||
'accept' : 'text/event-stream',
|
||||
'accept-language' : 'id-ID,id;q=0.9,en-US;q=0.8,en;q=0.7',
|
||||
'authorization' : 'Bearer '+bearer_token,
|
||||
'content-type' : 'application/json',
|
||||
'origin' : 'https://beta.theb.ai',
|
||||
'referer' : 'https://beta.theb.ai/home',
|
||||
'sec-ch-ua' : '"Chromium";v="116", "Not)A;Brand";v="24", "Google Chrome";v="116"',
|
||||
'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/116.0.0.0 Safari/537.36',
|
||||
'x-ai-model': 'ee8d4f29cb7047f78cbe84313ed6ace8',
|
||||
'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/116.0.0.0 Safari/537.36',
|
||||
'x-ai-model' : 'ee8d4f29cb7047f78cbe84313ed6ace8',
|
||||
}
|
||||
# generate 10 random number
|
||||
# 0.1 - 0.9
|
||||
|
||||
req_rand = random.randint(100000000, 9999999999)
|
||||
|
||||
json_data: dict[str, Any] = {
|
||||
"text": conversation,
|
||||
"category": "04f58f64a4aa4191a957b47290fee864",
|
||||
"model": "ee8d4f29cb7047f78cbe84313ed6ace8",
|
||||
"text" : conversation,
|
||||
"category" : "04f58f64a4aa4191a957b47290fee864",
|
||||
"model" : "ee8d4f29cb7047f78cbe84313ed6ace8",
|
||||
"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}}",
|
||||
"temperature": kwargs.get("temperature", 1),
|
||||
"top_p": kwargs.get("top_p", 1),
|
||||
"frequency_penalty": kwargs.get("frequency_penalty", 0),
|
||||
"presence_penalty": kwargs.get("presence_penalty", 0),
|
||||
"long_term_memory": "auto"
|
||||
"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),
|
||||
"top_p" : kwargs.get("top_p", 1),
|
||||
"frequency_penalty" : kwargs.get("frequency_penalty", 0),
|
||||
"presence_penalty" : kwargs.get("presence_penalty", 0),
|
||||
"long_term_memory" : "auto"
|
||||
}
|
||||
}
|
||||
response = requests.post(
|
||||
"https://beta.theb.ai/api/conversation?org_id="+org_id+"&req_rand="+str(req_rand),
|
||||
headers=headers,
|
||||
json=json_data,
|
||||
stream=True,
|
||||
)
|
||||
|
||||
response = requests.post(f"https://beta.theb.ai/api/conversation?org_id={org_id}&req_rand={req_rand}",
|
||||
headers=headers, json=json_data, stream=True)
|
||||
|
||||
response.raise_for_status()
|
||||
content = ""
|
||||
next_content = ""
|
||||
|
||||
@ -1,52 +1,57 @@
|
||||
import uuid, requests
|
||||
from __future__ import annotations
|
||||
|
||||
import uuid
|
||||
|
||||
import requests
|
||||
|
||||
from ..typing import Any, CreateResult
|
||||
from .base_provider import BaseProvider
|
||||
|
||||
|
||||
class V50(BaseProvider):
|
||||
url = 'https://p5.v50.ltd'
|
||||
supports_gpt_35_turbo = True
|
||||
supports_stream = False
|
||||
needs_auth = False
|
||||
working = True
|
||||
url = 'https://p5.v50.ltd'
|
||||
supports_gpt_35_turbo = True
|
||||
supports_stream = False
|
||||
needs_auth = False
|
||||
working = False
|
||||
|
||||
@staticmethod
|
||||
def create_completion(
|
||||
model: str,
|
||||
messages: list[dict[str, str]],
|
||||
stream: bool,
|
||||
**kwargs: Any,
|
||||
) -> CreateResult:
|
||||
conversation = ''
|
||||
for message in messages:
|
||||
conversation += '%s: %s\n' % (message['role'], message['content'])
|
||||
stream: bool, **kwargs: Any) -> CreateResult:
|
||||
|
||||
conversation += 'assistant: '
|
||||
conversation = "\n".join(f"{message['role']}: {message['content']}" for message in messages)
|
||||
conversation += "\nassistant: "
|
||||
|
||||
payload = {
|
||||
"prompt": conversation,
|
||||
"options": {},
|
||||
"systemMessage": ".",
|
||||
"temperature": kwargs.get("temperature", 0.4),
|
||||
"top_p": kwargs.get("top_p", 0.4),
|
||||
"model": model,
|
||||
"user": str(uuid.uuid4())
|
||||
"prompt" : conversation,
|
||||
"options" : {},
|
||||
"systemMessage" : ".",
|
||||
"temperature" : kwargs.get("temperature", 0.4),
|
||||
"top_p" : kwargs.get("top_p", 0.4),
|
||||
"model" : model,
|
||||
"user" : str(uuid.uuid4())
|
||||
}
|
||||
|
||||
headers = {
|
||||
'authority': 'p5.v50.ltd',
|
||||
'accept': 'application/json, text/plain, */*',
|
||||
'accept-language': 'id-ID,id;q=0.9,en-US;q=0.8,en;q=0.7',
|
||||
'content-type': 'application/json',
|
||||
'origin': 'https://p5.v50.ltd',
|
||||
'referer': 'https://p5.v50.ltd/',
|
||||
'authority' : 'p5.v50.ltd',
|
||||
'accept' : 'application/json, text/plain, */*',
|
||||
'accept-language' : 'id-ID,id;q=0.9,en-US;q=0.8,en;q=0.7',
|
||||
'content-type' : 'application/json',
|
||||
'origin' : 'https://p5.v50.ltd',
|
||||
'referer' : 'https://p5.v50.ltd/',
|
||||
'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/116.0.0.0 Safari/537.36'
|
||||
'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/116.0.0.0 Safari/537.36'
|
||||
}
|
||||
response = requests.post("https://p5.v50.ltd/api/chat-process",
|
||||
json=payload, headers=headers, proxies=kwargs['proxy'] if 'proxy' in kwargs else {})
|
||||
yield response.text
|
||||
|
||||
if "https://fk1.v50.ltd" not in response.text:
|
||||
yield response.text
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
|
||||
@ -1,3 +1,5 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import base64
|
||||
import json
|
||||
import uuid
|
||||
@ -10,17 +12,16 @@ from .base_provider import BaseProvider
|
||||
|
||||
|
||||
class Vercel(BaseProvider):
|
||||
url = "https://play.vercel.ai"
|
||||
working = True
|
||||
url = "https://play.vercel.ai"
|
||||
working = True
|
||||
supports_gpt_35_turbo = True
|
||||
|
||||
@staticmethod
|
||||
def create_completion(
|
||||
model: str,
|
||||
messages: list[dict[str, str]],
|
||||
stream: bool,
|
||||
**kwargs: Any,
|
||||
) -> CreateResult:
|
||||
stream: bool, **kwargs: Any) -> CreateResult:
|
||||
|
||||
if model in ["gpt-3.5-turbo", "gpt-4"]:
|
||||
model = "openai:" + model
|
||||
yield _chat(model_id=model, messages=messages)
|
||||
@ -29,8 +30,8 @@ class Vercel(BaseProvider):
|
||||
def _chat(model_id: str, messages: list[dict[str, str]]) -> str:
|
||||
session = requests.Session(impersonate="chrome107")
|
||||
|
||||
url = "https://sdk.vercel.ai/api/generate"
|
||||
header = _create_header(session)
|
||||
url = "https://sdk.vercel.ai/api/generate"
|
||||
header = _create_header(session)
|
||||
payload = _create_payload(model_id, messages)
|
||||
|
||||
response = session.post(url=url, headers=header, json=payload)
|
||||
@ -44,15 +45,13 @@ def _create_payload(model_id: str, messages: list[dict[str, str]]) -> dict[str,
|
||||
"messages": messages,
|
||||
"playgroundId": str(uuid.uuid4()),
|
||||
"chatIndex": 0,
|
||||
"model": model_id,
|
||||
} | default_params
|
||||
"model": model_id} | default_params
|
||||
|
||||
|
||||
def _create_header(session: requests.Session):
|
||||
custom_encoding = _get_custom_encoding(session)
|
||||
return {"custom-encoding": custom_encoding}
|
||||
|
||||
|
||||
# based on https://github.com/ading2210/vercel-llm-api
|
||||
def _get_custom_encoding(session: requests.Session):
|
||||
url = "https://sdk.vercel.ai/openai.jpeg"
|
||||
|
||||
@ -1,3 +1,5 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import random
|
||||
import string
|
||||
@ -10,65 +12,62 @@ from .base_provider import BaseProvider
|
||||
|
||||
|
||||
class Wewordle(BaseProvider):
|
||||
url = "https://wewordle.org/gptapi/v1/android/turbo"
|
||||
working = True
|
||||
supports_gpt_35_turbo = True
|
||||
url = "https://wewordle.org/"
|
||||
working = True
|
||||
supports_gpt_35_turbo = True
|
||||
|
||||
@staticmethod
|
||||
@classmethod
|
||||
def create_completion(
|
||||
cls,
|
||||
model: str,
|
||||
messages: list[dict[str, str]],
|
||||
stream: bool,
|
||||
**kwargs: Any,
|
||||
) -> CreateResult:
|
||||
base = ""
|
||||
|
||||
for message in messages:
|
||||
base += "%s: %s\n" % (message["role"], message["content"])
|
||||
base += "assistant:"
|
||||
stream: bool, **kwargs: Any) -> CreateResult:
|
||||
|
||||
# randomize user id and app id
|
||||
_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(
|
||||
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
|
||||
_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"
|
||||
"accept" : "*/*",
|
||||
"pragma" : "no-cache",
|
||||
"Content-Type" : "application/json",
|
||||
"Connection" : "keep-alive"
|
||||
# user agent android client
|
||||
# 'User-Agent': 'Dalvik/2.1.0 (Linux; U; Android 10; SM-G975F Build/QP1A.190711.020)',
|
||||
}
|
||||
|
||||
data: dict[str, Any] = {
|
||||
"user": _user_id,
|
||||
"messages": [{"role": "user", "content": base}],
|
||||
"user" : _user_id,
|
||||
"messages" : messages,
|
||||
"subscriber": {
|
||||
"originalPurchaseDate": None,
|
||||
"originalApplicationVersion": None,
|
||||
"allPurchaseDatesMillis": {},
|
||||
"entitlements": {"active": {}, "all": {}},
|
||||
"allPurchaseDates": {},
|
||||
"allExpirationDatesMillis": {},
|
||||
"allExpirationDates": {},
|
||||
"originalAppUserId": f"$RCAnonymousID:{_app_id}",
|
||||
"latestExpirationDate": None,
|
||||
"requestDate": _request_date,
|
||||
"latestExpirationDateMillis": None,
|
||||
"nonSubscriptionTransactions": [],
|
||||
"originalPurchaseDateMillis": None,
|
||||
"managementURL": None,
|
||||
"originalPurchaseDate" : None,
|
||||
"originalApplicationVersion" : None,
|
||||
"allPurchaseDatesMillis" : {},
|
||||
"entitlements" : {"active": {}, "all": {}},
|
||||
"allPurchaseDates" : {},
|
||||
"allExpirationDatesMillis" : {},
|
||||
"allExpirationDates" : {},
|
||||
"originalAppUserId" : f"$RCAnonymousID:{_app_id}",
|
||||
"latestExpirationDate" : None,
|
||||
"requestDate" : _request_date,
|
||||
"latestExpirationDateMillis" : None,
|
||||
"nonSubscriptionTransactions" : [],
|
||||
"originalPurchaseDateMillis" : None,
|
||||
"managementURL" : None,
|
||||
"allPurchasedProductIdentifiers": [],
|
||||
"firstSeen": _request_date,
|
||||
"activeSubscriptions": [],
|
||||
},
|
||||
"firstSeen" : _request_date,
|
||||
"activeSubscriptions" : [],
|
||||
}
|
||||
}
|
||||
|
||||
url = "https://wewordle.org/gptapi/v1/android/turbo"
|
||||
response = requests.post(url, 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()
|
||||
_json = response.json()
|
||||
if "message" in _json:
|
||||
|
||||
68
g4f/Provider/Wuguokai.py
Normal file
68
g4f/Provider/Wuguokai.py
Normal file
@ -0,0 +1,68 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import random
|
||||
|
||||
import requests
|
||||
|
||||
from ..typing import Any, CreateResult
|
||||
from .base_provider import BaseProvider
|
||||
|
||||
|
||||
class Wuguokai(BaseProvider):
|
||||
url = 'https://chat.wuguokai.xyz'
|
||||
supports_gpt_35_turbo = True
|
||||
working = True
|
||||
|
||||
@staticmethod
|
||||
def create_completion(
|
||||
model: str,
|
||||
messages: list[dict[str, str]],
|
||||
stream: bool,
|
||||
**kwargs: Any,
|
||||
) -> CreateResult:
|
||||
base = ''
|
||||
for message in messages:
|
||||
base += '%s: %s\n' % (message['role'], message['content'])
|
||||
base += 'assistant:'
|
||||
|
||||
headers = {
|
||||
'authority': 'ai-api.wuguokai.xyz',
|
||||
'accept': 'application/json, text/plain, */*',
|
||||
'accept-language': 'id-ID,id;q=0.9,en-US;q=0.8,en;q=0.7',
|
||||
'content-type': 'application/json',
|
||||
'origin': 'https://chat.wuguokai.xyz',
|
||||
'referer': 'https://chat.wuguokai.xyz/',
|
||||
'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-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'
|
||||
}
|
||||
data ={
|
||||
"prompt": base,
|
||||
"options": {},
|
||||
"userId": f"#/chat/{random.randint(1,99999999)}",
|
||||
"usingContext": True
|
||||
}
|
||||
response = requests.post("https://ai-api20.wuguokai.xyz/api/chat-process", headers=headers, timeout=3, json=data, proxies=kwargs['proxy'] if 'proxy' in kwargs else {})
|
||||
_split = response.text.split("> 若回答失败请重试或多刷新几次界面后重试")
|
||||
if response.status_code == 200:
|
||||
if len(_split) > 1:
|
||||
yield _split[1].strip()
|
||||
else:
|
||||
yield _split[0].strip()
|
||||
else:
|
||||
raise Exception(f"Error: {response.status_code} {response.reason}")
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def params(cls):
|
||||
params = [
|
||||
("model", "str"),
|
||||
("messages", "list[dict[str, str]]"),
|
||||
("stream", "bool")
|
||||
]
|
||||
param = ", ".join([": ".join(p) for p in params])
|
||||
return f"g4f.provider.{cls.__name__} supports: ({param})"
|
||||
@ -1,59 +1,40 @@
|
||||
import re
|
||||
import urllib.parse
|
||||
from __future__ import annotations
|
||||
|
||||
from curl_cffi import requests
|
||||
import json
|
||||
|
||||
from ..typing import Any, CreateResult
|
||||
from .base_provider import BaseProvider
|
||||
from aiohttp import ClientSession
|
||||
|
||||
from ..typing import AsyncGenerator
|
||||
from .base_provider import AsyncGeneratorProvider, format_prompt, get_cookies
|
||||
|
||||
|
||||
class You(BaseProvider):
|
||||
class You(AsyncGeneratorProvider):
|
||||
url = "https://you.com"
|
||||
working = True
|
||||
supports_gpt_35_turbo = True
|
||||
supports_stream = True
|
||||
|
||||
@staticmethod
|
||||
def create_completion(
|
||||
async def create_async_generator(
|
||||
model: str,
|
||||
messages: list[dict[str, str]],
|
||||
stream: bool,
|
||||
**kwargs: Any,
|
||||
) -> CreateResult:
|
||||
url_param = _create_url_param(messages)
|
||||
headers = _create_header()
|
||||
url = f"https://you.com/api/streamingSearch?{url_param}"
|
||||
response = requests.get(
|
||||
url,
|
||||
headers=headers,
|
||||
impersonate="chrome107",
|
||||
)
|
||||
response.raise_for_status()
|
||||
yield _parse_output(response.text)
|
||||
|
||||
|
||||
def _create_url_param(messages: list[dict[str, str]]):
|
||||
prompt = messages.pop()["content"]
|
||||
chat = _convert_chat(messages)
|
||||
param = {"q": prompt, "domain": "youchat", "chat": chat}
|
||||
return urllib.parse.urlencode(param)
|
||||
|
||||
|
||||
def _convert_chat(messages: list[dict[str, str]]):
|
||||
message_iter = iter(messages)
|
||||
return [
|
||||
{"question": user["content"], "answer": assistant["content"]}
|
||||
for user, assistant in zip(message_iter, message_iter)
|
||||
]
|
||||
|
||||
|
||||
def _create_header():
|
||||
return {
|
||||
"accept": "text/event-stream",
|
||||
"referer": "https://you.com/search?fromSearchBar=true&tbm=youchat",
|
||||
}
|
||||
|
||||
|
||||
def _parse_output(output: str) -> str:
|
||||
regex = r"^data:\s{\"youChatToken\": \"(.*)\"}$"
|
||||
tokens = [token for token in re.findall(regex, output, re.MULTILINE)]
|
||||
return "".join(tokens)
|
||||
cookies: dict = None,
|
||||
**kwargs,
|
||||
) -> AsyncGenerator:
|
||||
if not cookies:
|
||||
cookies = get_cookies("you.com")
|
||||
headers = {
|
||||
"Accept": "text/event-stream",
|
||||
"Referer": "https://you.com/search?fromSearchBar=true&tbm=youchat",
|
||||
"User-Agent": "Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:109.0) Gecko/20100101 Firefox/116.0"
|
||||
}
|
||||
async with ClientSession(headers=headers, cookies=cookies) as session:
|
||||
async with session.get(
|
||||
"https://you.com/api/streamingSearch",
|
||||
params={"q": format_prompt(messages), "domain": "youchat", "chat": ""},
|
||||
) as response:
|
||||
start = 'data: {"youChatToken": '
|
||||
async for line in response.content:
|
||||
line = line.decode('utf-8')
|
||||
if line.startswith(start):
|
||||
yield json.loads(line[len(start): -2])
|
||||
@ -1,45 +1,45 @@
|
||||
import requests
|
||||
from __future__ import annotations
|
||||
|
||||
from ..typing import Any, CreateResult
|
||||
from .base_provider import BaseProvider
|
||||
from aiohttp import ClientSession
|
||||
|
||||
from .base_provider import AsyncProvider, format_prompt
|
||||
|
||||
|
||||
class Yqcloud(BaseProvider):
|
||||
class Yqcloud(AsyncProvider):
|
||||
url = "https://chat9.yqcloud.top/"
|
||||
working = True
|
||||
supports_gpt_35_turbo = True
|
||||
|
||||
@staticmethod
|
||||
def create_completion(
|
||||
async def create_async(
|
||||
model: str,
|
||||
messages: list[dict[str, str]],
|
||||
stream: bool,
|
||||
**kwargs: Any,
|
||||
) -> CreateResult:
|
||||
headers = _create_header()
|
||||
payload = _create_payload(messages)
|
||||
|
||||
url = "https://api.aichatos.cloud/api/generateStream"
|
||||
response = requests.post(url=url, headers=headers, json=payload)
|
||||
response.raise_for_status()
|
||||
response.encoding = 'utf-8'
|
||||
yield response.text
|
||||
proxy: str = None,
|
||||
**kwargs,
|
||||
) -> str:
|
||||
async with ClientSession(
|
||||
headers=_create_header()
|
||||
) as session:
|
||||
payload = _create_payload(messages)
|
||||
async with session.post("https://api.aichatos.cloud/api/generateStream", proxy=proxy, json=payload) as response:
|
||||
response.raise_for_status()
|
||||
return await response.text()
|
||||
|
||||
|
||||
def _create_header():
|
||||
return {
|
||||
"accept": "application/json, text/plain, */*",
|
||||
"content-type": "application/json",
|
||||
"origin": "https://chat9.yqcloud.top",
|
||||
"accept" : "application/json, text/plain, */*",
|
||||
"content-type" : "application/json",
|
||||
"origin" : "https://chat9.yqcloud.top",
|
||||
}
|
||||
|
||||
|
||||
def _create_payload(messages: list[dict[str, str]]):
|
||||
prompt = messages[-1]["content"]
|
||||
return {
|
||||
"prompt": prompt,
|
||||
"prompt": format_prompt(messages),
|
||||
"network": True,
|
||||
"system": "",
|
||||
"withoutContext": False,
|
||||
"stream": False,
|
||||
"userId": "#/chat/1693025544336"
|
||||
}
|
||||
|
||||
@ -1,59 +1,69 @@
|
||||
from .Acytoo import Acytoo
|
||||
from .Aichat import Aichat
|
||||
from .Ails import Ails
|
||||
from .AiService import AiService
|
||||
from .AItianhu import AItianhu
|
||||
from .Bard import Bard
|
||||
from .base_provider import BaseProvider
|
||||
from .Bing import Bing
|
||||
from .ChatgptAi import ChatgptAi
|
||||
from .ChatgptLogin import ChatgptLogin
|
||||
from .DeepAi import DeepAi
|
||||
from .DfeHub import DfeHub
|
||||
from .EasyChat import EasyChat
|
||||
from .Forefront import Forefront
|
||||
from .GetGpt import GetGpt
|
||||
from .H2o import H2o
|
||||
from .Liaobots import Liaobots
|
||||
from .Lockchat import Lockchat
|
||||
from .Opchatgpts import Opchatgpts
|
||||
from .Raycast import Raycast
|
||||
from .Theb import Theb
|
||||
from .Vercel import Vercel
|
||||
from .Wewordle import Wewordle
|
||||
from .You import You
|
||||
from .Yqcloud import Yqcloud
|
||||
from .Equing import Equing
|
||||
from .FastGpt import FastGpt
|
||||
from .V50 import V50
|
||||
from __future__ import annotations
|
||||
from .Acytoo import Acytoo
|
||||
from .Aichat import Aichat
|
||||
from .Ails import Ails
|
||||
from .AiService import AiService
|
||||
from .AItianhu import AItianhu
|
||||
from .Bard import Bard
|
||||
from .Bing import Bing
|
||||
from .ChatgptAi import ChatgptAi
|
||||
from .ChatgptLogin import ChatgptLogin
|
||||
from .DeepAi import DeepAi
|
||||
from .DfeHub import DfeHub
|
||||
from .EasyChat import EasyChat
|
||||
from .Forefront import Forefront
|
||||
from .GetGpt import GetGpt
|
||||
from .H2o import H2o
|
||||
from .HuggingChat import HuggingChat
|
||||
from .Liaobots import Liaobots
|
||||
from .Lockchat import Lockchat
|
||||
from .Opchatgpts import Opchatgpts
|
||||
from .OpenaiChat import OpenaiChat
|
||||
from .OpenAssistant import OpenAssistant
|
||||
from .Raycast import Raycast
|
||||
from .Theb import Theb
|
||||
from .Vercel import Vercel
|
||||
from .Wewordle import Wewordle
|
||||
from .You import You
|
||||
from .Yqcloud import Yqcloud
|
||||
from .Equing import Equing
|
||||
from .FastGpt import FastGpt
|
||||
from .V50 import V50
|
||||
from .Wuguokai import Wuguokai
|
||||
|
||||
from .base_provider import BaseProvider, AsyncProvider, AsyncGeneratorProvider
|
||||
|
||||
__all__ = [
|
||||
"BaseProvider",
|
||||
"Acytoo",
|
||||
"Aichat",
|
||||
"Ails",
|
||||
"AiService",
|
||||
"AItianhu",
|
||||
"Bard",
|
||||
"Bing",
|
||||
"ChatgptAi",
|
||||
"ChatgptLogin",
|
||||
"DeepAi",
|
||||
"DfeHub",
|
||||
"EasyChat",
|
||||
"Forefront",
|
||||
"GetGpt",
|
||||
"H2o",
|
||||
"Liaobots",
|
||||
"Lockchat",
|
||||
"Opchatgpts",
|
||||
"Raycast",
|
||||
"Theb",
|
||||
"Vercel",
|
||||
"Wewordle",
|
||||
"You",
|
||||
"Yqcloud",
|
||||
"Equing",
|
||||
"FastGpt",
|
||||
"V50"
|
||||
'BaseProvider',
|
||||
'Acytoo',
|
||||
'Aichat',
|
||||
'Ails',
|
||||
'AiService',
|
||||
'AItianhu',
|
||||
'Bard',
|
||||
'Bing',
|
||||
'ChatgptAi',
|
||||
'ChatgptLogin',
|
||||
'DeepAi',
|
||||
'DfeHub',
|
||||
'EasyChat',
|
||||
'Forefront',
|
||||
'GetGpt',
|
||||
'H2o',
|
||||
'HuggingChat',
|
||||
'Liaobots',
|
||||
'Lockchat',
|
||||
'Opchatgpts',
|
||||
'Raycast',
|
||||
'OpenaiChat',
|
||||
'OpenAssistant',
|
||||
'Theb',
|
||||
'Vercel',
|
||||
'Wewordle',
|
||||
'You',
|
||||
'Yqcloud',
|
||||
'Equing',
|
||||
'FastGpt',
|
||||
'Wuguokai',
|
||||
'V50'
|
||||
]
|
||||
|
||||
@ -1,24 +1,28 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import asyncio
|
||||
from abc import ABC, abstractmethod
|
||||
|
||||
from ..typing import Any, CreateResult
|
||||
import browser_cookie3
|
||||
|
||||
from ..typing import Any, AsyncGenerator, CreateResult, Union
|
||||
|
||||
|
||||
class BaseProvider(ABC):
|
||||
url: str
|
||||
working = False
|
||||
needs_auth = False
|
||||
supports_stream = False
|
||||
working = False
|
||||
needs_auth = False
|
||||
supports_stream = False
|
||||
supports_gpt_35_turbo = False
|
||||
supports_gpt_4 = False
|
||||
supports_gpt_4 = False
|
||||
|
||||
@staticmethod
|
||||
@abstractmethod
|
||||
def create_completion(
|
||||
model: str,
|
||||
messages: list[dict[str, str]],
|
||||
stream: bool,
|
||||
**kwargs: Any,
|
||||
) -> CreateResult:
|
||||
stream: bool, **kwargs: Any) -> CreateResult:
|
||||
|
||||
raise NotImplementedError()
|
||||
|
||||
@classmethod
|
||||
@ -30,4 +34,89 @@ class BaseProvider(ABC):
|
||||
("stream", "bool"),
|
||||
]
|
||||
param = ", ".join([": ".join(p) for p in params])
|
||||
return f"g4f.provider.{cls.__name__} supports: ({param})"
|
||||
return f"g4f.provider.{cls.__name__} supports: ({param})"
|
||||
|
||||
|
||||
_cookies = {}
|
||||
|
||||
def get_cookies(cookie_domain: str) -> dict:
|
||||
if cookie_domain not in _cookies:
|
||||
_cookies[cookie_domain] = {}
|
||||
|
||||
for cookie in browser_cookie3.load(cookie_domain):
|
||||
_cookies[cookie_domain][cookie.name] = cookie.value
|
||||
|
||||
return _cookies[cookie_domain]
|
||||
|
||||
|
||||
def format_prompt(messages: list[dict[str, str]], add_special_tokens=False):
|
||||
if add_special_tokens or len(messages) > 1:
|
||||
formatted = "\n".join(
|
||||
["%s: %s" % ((message["role"]).capitalize(), message["content"]) for message in messages]
|
||||
)
|
||||
return f"{formatted}\nAssistant:"
|
||||
else:
|
||||
return messages.pop()["content"]
|
||||
|
||||
|
||||
|
||||
class AsyncProvider(BaseProvider):
|
||||
@classmethod
|
||||
def create_completion(
|
||||
cls,
|
||||
model: str,
|
||||
messages: list[dict[str, str]],
|
||||
stream: bool = False, **kwargs: Any) -> CreateResult:
|
||||
|
||||
yield asyncio.run(cls.create_async(model, messages, **kwargs))
|
||||
|
||||
@staticmethod
|
||||
@abstractmethod
|
||||
async def create_async(
|
||||
model: str,
|
||||
messages: list[dict[str, str]], **kwargs: Any) -> str:
|
||||
raise NotImplementedError()
|
||||
|
||||
|
||||
class AsyncGeneratorProvider(AsyncProvider):
|
||||
@classmethod
|
||||
def create_completion(
|
||||
cls,
|
||||
model: str,
|
||||
messages: list[dict[str, str]],
|
||||
stream: bool = True,
|
||||
**kwargs
|
||||
) -> CreateResult:
|
||||
yield from run_generator(cls.create_async_generator(model, messages, stream=stream, **kwargs))
|
||||
|
||||
@classmethod
|
||||
async def create_async(
|
||||
cls,
|
||||
model: str,
|
||||
messages: list[dict[str, str]],
|
||||
**kwargs
|
||||
) -> str:
|
||||
chunks = [chunk async for chunk in cls.create_async_generator(model, messages, stream=False, **kwargs)]
|
||||
if chunks:
|
||||
return "".join(chunks)
|
||||
|
||||
@staticmethod
|
||||
@abstractmethod
|
||||
def create_async_generator(
|
||||
model: str,
|
||||
messages: list[dict[str, str]],
|
||||
**kwargs
|
||||
) -> AsyncGenerator:
|
||||
raise NotImplementedError()
|
||||
|
||||
|
||||
def run_generator(generator: AsyncGenerator[Union[Any, str], Any]):
|
||||
loop = asyncio.new_event_loop()
|
||||
gen = generator.__aiter__()
|
||||
|
||||
while True:
|
||||
try:
|
||||
yield loop.run_until_complete(gen.__anext__())
|
||||
|
||||
except StopAsyncIteration:
|
||||
break
|
||||
|
||||
@ -1,45 +1,43 @@
|
||||
from . import models
|
||||
from .Provider import BaseProvider
|
||||
from .typing import Any, CreateResult, Union
|
||||
from __future__ import annotations
|
||||
from . import models
|
||||
from .Provider import BaseProvider
|
||||
from .typing import Any, CreateResult, Union
|
||||
|
||||
logging = False
|
||||
|
||||
|
||||
class ChatCompletion:
|
||||
@staticmethod
|
||||
def create(
|
||||
model: Union[models.Model, str],
|
||||
messages: list[dict[str, str]],
|
||||
provider: Union[type[BaseProvider], None] = None,
|
||||
stream: bool = False,
|
||||
auth: Union[str, None] = None,
|
||||
**kwargs: Any,
|
||||
) -> Union[CreateResult, str]:
|
||||
model : Union[models.Model, str],
|
||||
messages : list[dict[str, str]],
|
||||
provider : Union[type[BaseProvider], None] = None,
|
||||
stream : bool = False,
|
||||
auth : Union[str, None] = None, **kwargs: Any) -> Union[CreateResult, str]:
|
||||
|
||||
if isinstance(model, str):
|
||||
try:
|
||||
model = models.ModelUtils.convert[model]
|
||||
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
|
||||
|
||||
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:
|
||||
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:
|
||||
kwargs["auth"] = auth
|
||||
kwargs['auth'] = auth
|
||||
|
||||
if not provider.supports_stream and stream:
|
||||
raise Exception(
|
||||
f"ValueError: {provider.__name__} does not support 'stream' argument"
|
||||
)
|
||||
f'ValueError: {provider.__name__} does not support "stream" argument')
|
||||
|
||||
if logging:
|
||||
print(f"Using {provider.__name__} provider")
|
||||
print(f'Using {provider.__name__} provider')
|
||||
|
||||
result = provider.create_completion(model.name, messages, stream, **kwargs)
|
||||
return result if stream else "".join(result)
|
||||
return result if stream else ''.join(result)
|
||||
|
||||
278
g4f/models.py
278
g4f/models.py
@ -1,225 +1,207 @@
|
||||
from __future__ import annotations
|
||||
from dataclasses import dataclass
|
||||
|
||||
from .Provider import Bard, BaseProvider, GetGpt, H2o, Liaobots, Vercel, Equing
|
||||
|
||||
|
||||
@dataclass
|
||||
class Model:
|
||||
name: str
|
||||
base_provider: str
|
||||
best_provider: type[BaseProvider]
|
||||
|
||||
# Config for HuggingChat, OpenAssistant
|
||||
# Works for Liaobots, H2o, OpenaiChat, Yqcloud, You
|
||||
default = Model(
|
||||
name="",
|
||||
base_provider="huggingface",
|
||||
best_provider=H2o,
|
||||
)
|
||||
|
||||
# GPT-3.5 / GPT-4
|
||||
gpt_35_turbo = Model(
|
||||
name="gpt-3.5-turbo",
|
||||
base_provider="openai",
|
||||
best_provider=GetGpt,
|
||||
)
|
||||
name = 'gpt-3.5-turbo',
|
||||
base_provider = 'openai',
|
||||
best_provider = GetGpt)
|
||||
|
||||
gpt_4 = Model(
|
||||
name="gpt-4",
|
||||
base_provider="openai",
|
||||
best_provider=Liaobots,
|
||||
)
|
||||
name = 'gpt-4',
|
||||
base_provider = 'openai',
|
||||
best_provider = Liaobots)
|
||||
|
||||
# Bard
|
||||
palm = Model(
|
||||
name="palm",
|
||||
base_provider="google",
|
||||
best_provider=Bard,
|
||||
)
|
||||
name = 'palm',
|
||||
base_provider = 'google',
|
||||
best_provider = Bard)
|
||||
|
||||
# H2o
|
||||
falcon_7b = Model(
|
||||
name="h2oai/h2ogpt-gm-oasst1-en-2048-falcon-7b-v3",
|
||||
base_provider="huggingface",
|
||||
best_provider=H2o,
|
||||
)
|
||||
name = 'h2oai/h2ogpt-gm-oasst1-en-2048-falcon-7b-v3',
|
||||
base_provider = 'huggingface',
|
||||
best_provider = H2o)
|
||||
|
||||
falcon_40b = Model(
|
||||
name="h2oai/h2ogpt-gm-oasst1-en-2048-falcon-40b-v1",
|
||||
base_provider="huggingface",
|
||||
best_provider=H2o,
|
||||
)
|
||||
name = 'h2oai/h2ogpt-gm-oasst1-en-2048-falcon-40b-v1',
|
||||
base_provider = 'huggingface',
|
||||
best_provider = H2o)
|
||||
|
||||
llama_13b = Model(
|
||||
name="h2oai/h2ogpt-gm-oasst1-en-2048-open-llama-13b",
|
||||
base_provider="huggingface",
|
||||
best_provider=H2o,
|
||||
)
|
||||
name = 'h2oai/h2ogpt-gm-oasst1-en-2048-open-llama-13b',
|
||||
base_provider = 'huggingface',
|
||||
best_provider = H2o)
|
||||
|
||||
# Vercel
|
||||
claude_instant_v1 = Model(
|
||||
name="anthropic:claude-instant-v1",
|
||||
base_provider="anthropic",
|
||||
best_provider=Vercel,
|
||||
)
|
||||
name = 'anthropic:claude-instant-v1',
|
||||
base_provider = 'anthropic',
|
||||
best_provider = Vercel)
|
||||
|
||||
claude_v1 = Model(
|
||||
name="anthropic:claude-v1",
|
||||
base_provider="anthropic",
|
||||
best_provider=Vercel,
|
||||
)
|
||||
name = 'anthropic:claude-v1',
|
||||
base_provider = 'anthropic',
|
||||
best_provider = Vercel)
|
||||
|
||||
claude_v2 = Model(
|
||||
name="anthropic:claude-v2",
|
||||
base_provider="anthropic",
|
||||
best_provider=Vercel,
|
||||
)
|
||||
name = 'anthropic:claude-v2',
|
||||
base_provider = 'anthropic',
|
||||
best_provider = Vercel)
|
||||
|
||||
command_light_nightly = Model(
|
||||
name="cohere:command-light-nightly",
|
||||
base_provider="cohere",
|
||||
best_provider=Vercel,
|
||||
)
|
||||
name = 'cohere:command-light-nightly',
|
||||
base_provider = 'cohere',
|
||||
best_provider = Vercel)
|
||||
|
||||
command_nightly = Model(
|
||||
name="cohere:command-nightly",
|
||||
base_provider="cohere",
|
||||
best_provider=Vercel,
|
||||
)
|
||||
name = 'cohere:command-nightly',
|
||||
base_provider = 'cohere',
|
||||
best_provider = Vercel)
|
||||
|
||||
gpt_neox_20b = Model(
|
||||
name="huggingface:EleutherAI/gpt-neox-20b",
|
||||
base_provider="huggingface",
|
||||
best_provider=Vercel,
|
||||
)
|
||||
name = 'huggingface:EleutherAI/gpt-neox-20b',
|
||||
base_provider = 'huggingface',
|
||||
best_provider = Vercel)
|
||||
|
||||
oasst_sft_1_pythia_12b = Model(
|
||||
name="huggingface:OpenAssistant/oasst-sft-1-pythia-12b",
|
||||
base_provider="huggingface",
|
||||
best_provider=Vercel,
|
||||
)
|
||||
name = 'huggingface:OpenAssistant/oasst-sft-1-pythia-12b',
|
||||
base_provider = 'huggingface',
|
||||
best_provider = Vercel)
|
||||
|
||||
oasst_sft_4_pythia_12b_epoch_35 = Model(
|
||||
name="huggingface:OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5",
|
||||
base_provider="huggingface",
|
||||
best_provider=Vercel,
|
||||
)
|
||||
name = 'huggingface:OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5',
|
||||
base_provider = 'huggingface',
|
||||
best_provider = Vercel)
|
||||
|
||||
santacoder = Model(
|
||||
name="huggingface:bigcode/santacoder",
|
||||
base_provider="huggingface",
|
||||
best_provider=Vercel,
|
||||
)
|
||||
name = 'huggingface:bigcode/santacoder',
|
||||
base_provider = 'huggingface',
|
||||
best_provider = Vercel)
|
||||
|
||||
bloom = Model(
|
||||
name="huggingface:bigscience/bloom",
|
||||
base_provider="huggingface",
|
||||
best_provider=Vercel,
|
||||
)
|
||||
name = 'huggingface:bigscience/bloom',
|
||||
base_provider = 'huggingface',
|
||||
best_provider = Vercel)
|
||||
|
||||
flan_t5_xxl = Model(
|
||||
name="huggingface:google/flan-t5-xxl",
|
||||
base_provider="huggingface",
|
||||
best_provider=Vercel,
|
||||
)
|
||||
name = 'huggingface:google/flan-t5-xxl',
|
||||
base_provider = 'huggingface',
|
||||
best_provider = Vercel)
|
||||
|
||||
code_davinci_002 = Model(
|
||||
name="openai:code-davinci-002",
|
||||
base_provider="openai",
|
||||
best_provider=Vercel,
|
||||
)
|
||||
name = 'openai:code-davinci-002',
|
||||
base_provider = 'openai',
|
||||
best_provider = Vercel)
|
||||
|
||||
gpt_35_turbo_16k = Model(
|
||||
name="openai:gpt-3.5-turbo-16k",
|
||||
base_provider="openai",
|
||||
best_provider=Vercel,
|
||||
)
|
||||
name = 'openai:gpt-3.5-turbo-16k',
|
||||
base_provider = 'openai',
|
||||
best_provider = Vercel)
|
||||
|
||||
gpt_35_turbo_16k_0613 = Model(
|
||||
name="openai:gpt-3.5-turbo-16k-0613",
|
||||
base_provider="openai",
|
||||
best_provider=Equing,
|
||||
)
|
||||
name = 'openai:gpt-3.5-turbo-16k-0613',
|
||||
base_provider = 'openai',
|
||||
best_provider = Equing)
|
||||
|
||||
gpt_4_0613 = Model(
|
||||
name="openai:gpt-4-0613",
|
||||
base_provider="openai",
|
||||
best_provider=Vercel,
|
||||
)
|
||||
name = 'openai:gpt-4-0613',
|
||||
base_provider = 'openai',
|
||||
best_provider = Vercel)
|
||||
|
||||
text_ada_001 = Model(
|
||||
name="openai:text-ada-001",
|
||||
base_provider="openai",
|
||||
best_provider=Vercel,
|
||||
)
|
||||
name = 'openai:text-ada-001',
|
||||
base_provider = 'openai',
|
||||
best_provider = Vercel)
|
||||
|
||||
text_babbage_001 = Model(
|
||||
name="openai:text-babbage-001",
|
||||
base_provider="openai",
|
||||
best_provider=Vercel,
|
||||
)
|
||||
name = 'openai:text-babbage-001',
|
||||
base_provider = 'openai',
|
||||
best_provider = Vercel)
|
||||
|
||||
text_curie_001 = Model(
|
||||
name="openai:text-curie-001",
|
||||
base_provider="openai",
|
||||
best_provider=Vercel,
|
||||
)
|
||||
name = 'openai:text-curie-001',
|
||||
base_provider = 'openai',
|
||||
best_provider = Vercel)
|
||||
|
||||
text_davinci_002 = Model(
|
||||
name="openai:text-davinci-002",
|
||||
base_provider="openai",
|
||||
best_provider=Vercel,
|
||||
)
|
||||
name = 'openai:text-davinci-002',
|
||||
base_provider = 'openai',
|
||||
best_provider = Vercel)
|
||||
|
||||
text_davinci_003 = Model(
|
||||
name="openai:text-davinci-003",
|
||||
base_provider="openai",
|
||||
best_provider=Vercel,
|
||||
)
|
||||
name = 'openai:text-davinci-003',
|
||||
base_provider = 'openai',
|
||||
best_provider = Vercel)
|
||||
|
||||
llama13b_v2_chat = Model(
|
||||
name="replicate:a16z-infra/llama13b-v2-chat",
|
||||
base_provider="replicate",
|
||||
best_provider=Vercel,
|
||||
)
|
||||
name = 'replicate:a16z-infra/llama13b-v2-chat',
|
||||
base_provider = 'replicate',
|
||||
best_provider = Vercel)
|
||||
|
||||
llama7b_v2_chat = Model(
|
||||
name="replicate:a16z-infra/llama7b-v2-chat",
|
||||
base_provider="replicate",
|
||||
best_provider=Vercel,
|
||||
)
|
||||
name = 'replicate:a16z-infra/llama7b-v2-chat',
|
||||
base_provider = 'replicate',
|
||||
best_provider = Vercel)
|
||||
|
||||
|
||||
class ModelUtils:
|
||||
convert: dict[str, Model] = {
|
||||
# GPT-3.5 / GPT-4
|
||||
"gpt-3.5-turbo": gpt_35_turbo,
|
||||
"gpt-4": gpt_4,
|
||||
'gpt-3.5-turbo' : gpt_35_turbo,
|
||||
'gpt-4' : gpt_4,
|
||||
|
||||
# Bard
|
||||
"palm2": palm,
|
||||
"palm": palm,
|
||||
"google": palm,
|
||||
"google-bard": palm,
|
||||
"google-palm": palm,
|
||||
"bard": palm,
|
||||
'palm2' : palm,
|
||||
'palm' : palm,
|
||||
'google' : palm,
|
||||
'google-bard' : palm,
|
||||
'google-palm' : palm,
|
||||
'bard' : palm,
|
||||
|
||||
# H2o
|
||||
"falcon-40b": falcon_40b,
|
||||
"falcon-7b": falcon_7b,
|
||||
"llama-13b": llama_13b,
|
||||
'falcon-40b' : falcon_40b,
|
||||
'falcon-7b' : falcon_7b,
|
||||
'llama-13b' : llama_13b,
|
||||
|
||||
# Vercel
|
||||
"claude-instant-v1": claude_instant_v1,
|
||||
"claude-v1": claude_v1,
|
||||
"claude-v2": claude_v2,
|
||||
"command-light-nightly": command_light_nightly,
|
||||
"command-nightly": command_nightly,
|
||||
"gpt-neox-20b": gpt_neox_20b,
|
||||
"oasst-sft-1-pythia-12b": oasst_sft_1_pythia_12b,
|
||||
"oasst-sft-4-pythia-12b-epoch-3.5": oasst_sft_4_pythia_12b_epoch_35,
|
||||
"santacoder": santacoder,
|
||||
"bloom": bloom,
|
||||
"flan-t5-xxl": flan_t5_xxl,
|
||||
"code-davinci-002": code_davinci_002,
|
||||
"gpt-3.5-turbo-16k": gpt_35_turbo_16k,
|
||||
"gpt-3.5-turbo-16k-0613": gpt_35_turbo_16k_0613,
|
||||
"gpt-4-0613": gpt_4_0613,
|
||||
"text-ada-001": text_ada_001,
|
||||
"text-babbage-001": text_babbage_001,
|
||||
"text-curie-001": text_curie_001,
|
||||
"text-davinci-002": text_davinci_002,
|
||||
"text-davinci-003": text_davinci_003,
|
||||
"llama13b-v2-chat": llama13b_v2_chat,
|
||||
"llama7b-v2-chat": llama7b_v2_chat,
|
||||
}
|
||||
'claude-instant-v1' : claude_instant_v1,
|
||||
'claude-v1' : claude_v1,
|
||||
'claude-v2' : claude_v2,
|
||||
'command-nightly' : command_nightly,
|
||||
'gpt-neox-20b' : gpt_neox_20b,
|
||||
'santacoder' : santacoder,
|
||||
'bloom' : bloom,
|
||||
'flan-t5-xxl' : flan_t5_xxl,
|
||||
'code-davinci-002' : code_davinci_002,
|
||||
'gpt-3.5-turbo-16k' : gpt_35_turbo_16k,
|
||||
'gpt-4-0613' : gpt_4_0613,
|
||||
'text-ada-001' : text_ada_001,
|
||||
'text-babbage-001' : text_babbage_001,
|
||||
'text-curie-001' : text_curie_001,
|
||||
'text-davinci-002' : text_davinci_002,
|
||||
'text-davinci-003' : text_davinci_003,
|
||||
'llama13b-v2-chat' : llama13b_v2_chat,
|
||||
'llama7b-v2-chat' : llama7b_v2_chat,
|
||||
|
||||
'oasst-sft-1-pythia-12b' : oasst_sft_1_pythia_12b,
|
||||
'oasst-sft-4-pythia-12b-epoch-3.5' : oasst_sft_4_pythia_12b_epoch_35,
|
||||
'command-light-nightly' : command_light_nightly,
|
||||
'gpt-3.5-turbo-16k-0613' : gpt_35_turbo_16k_0613,
|
||||
}
|
||||
@ -1,15 +1,14 @@
|
||||
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]
|
||||
|
||||
|
||||
__all__ = [
|
||||
"Any",
|
||||
"AsyncGenerator",
|
||||
"Generator",
|
||||
"Tuple",
|
||||
"TypedDict",
|
||||
"SHA256",
|
||||
"CreateResult",
|
||||
]
|
||||
'Any',
|
||||
'AsyncGenerator',
|
||||
'Generator',
|
||||
'Tuple',
|
||||
'TypedDict',
|
||||
'SHA256',
|
||||
'CreateResult',
|
||||
]
|
||||
@ -12,6 +12,7 @@ from g4f import ChatCompletion
|
||||
app = Flask(__name__)
|
||||
CORS(app)
|
||||
|
||||
|
||||
@app.route("/chat/completions", methods=["POST"])
|
||||
def chat_completions():
|
||||
model = request.get_json().get("model", "gpt-3.5-turbo")
|
||||
@ -87,5 +88,9 @@ def chat_completions():
|
||||
return app.response_class(streaming(), mimetype="text/event-stream")
|
||||
|
||||
|
||||
def main():
|
||||
app.run(host="0.0.0.0", port=1337, debug=True)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
app.run(host="0.0.0.0", port=1337, debug=True)
|
||||
main()
|
||||
|
||||
@ -8,4 +8,5 @@ websockets
|
||||
js2py
|
||||
quickjs
|
||||
flask
|
||||
flask-cors
|
||||
flask-cors
|
||||
httpx
|
||||
|
||||
16
setup.py
16
setup.py
@ -11,7 +11,10 @@ with codecs.open(os.path.join(here, "README.md"), encoding="utf-8") as fh:
|
||||
with open("requirements.txt") as f:
|
||||
required = f.read().splitlines()
|
||||
|
||||
VERSION = '0.0.2.3'
|
||||
with open("interference/requirements.txt") as f:
|
||||
api_required = f.read().splitlines()
|
||||
|
||||
VERSION = "0.0.2.6"
|
||||
DESCRIPTION = (
|
||||
"The official gpt4free repository | various collection of powerful language models"
|
||||
)
|
||||
@ -26,11 +29,16 @@ setup(
|
||||
long_description_content_type="text/markdown",
|
||||
long_description=long_description,
|
||||
packages=find_packages(),
|
||||
data_files=["interference/app.py"],
|
||||
install_requires=required,
|
||||
url='https://github.com/xtekky/gpt4free', # Link to your GitHub repository
|
||||
extras_require={"api": api_required},
|
||||
entry_points={
|
||||
"console_scripts": ["g4f=interference.app:main"],
|
||||
},
|
||||
url="https://github.com/xtekky/gpt4free", # Link to your GitHub repository
|
||||
project_urls={
|
||||
'Source Code': 'https://github.com/xtekky/gpt4free', # GitHub link
|
||||
'Bug Tracker': 'https://github.com/xtekky/gpt4free/issues', # Link to issue tracker
|
||||
"Source Code": "https://github.com/xtekky/gpt4free", # GitHub link
|
||||
"Bug Tracker": "https://github.com/xtekky/gpt4free/issues", # Link to issue tracker
|
||||
},
|
||||
keywords=[
|
||||
"python",
|
||||
|
||||
25
testing/log_time.py
Normal file
25
testing/log_time.py
Normal file
@ -0,0 +1,25 @@
|
||||
from time import time
|
||||
|
||||
|
||||
async def log_time_async(method: callable, **kwargs):
|
||||
start = time()
|
||||
result = await method(**kwargs)
|
||||
secs = f"{round(time() - start, 2)} secs"
|
||||
if result:
|
||||
return " ".join([result, secs])
|
||||
return secs
|
||||
|
||||
|
||||
def log_time_yield(method: callable, **kwargs):
|
||||
start = time()
|
||||
result = yield from method(**kwargs)
|
||||
yield f" {round(time() - start, 2)} secs"
|
||||
|
||||
|
||||
def log_time(method: callable, **kwargs):
|
||||
start = time()
|
||||
result = method(**kwargs)
|
||||
secs = f"{round(time() - start, 2)} secs"
|
||||
if result:
|
||||
return " ".join([result, secs])
|
||||
return secs
|
||||
@ -14,4 +14,4 @@ response = g4f.ChatCompletion.create(
|
||||
active_server=5,
|
||||
)
|
||||
|
||||
print(response)
|
||||
print(response)
|
||||
|
||||
96
testing/test_needs_auth.py
Normal file
96
testing/test_needs_auth.py
Normal file
@ -0,0 +1,96 @@
|
||||
import sys
|
||||
from pathlib import Path
|
||||
import asyncio
|
||||
|
||||
sys.path.append(str(Path(__file__).parent.parent))
|
||||
|
||||
import g4f
|
||||
from testing.log_time import log_time, log_time_async, log_time_yield
|
||||
|
||||
|
||||
_providers = [
|
||||
g4f.Provider.H2o,
|
||||
g4f.Provider.You,
|
||||
g4f.Provider.HuggingChat,
|
||||
g4f.Provider.OpenAssistant,
|
||||
g4f.Provider.Bing,
|
||||
g4f.Provider.Bard
|
||||
]
|
||||
|
||||
_instruct = "Hello, tell about you in one sentence."
|
||||
|
||||
_example = """
|
||||
OpenaiChat: Hello! How can I assist you today? 2.0 secs
|
||||
Bard: Hello! How can I help you today? 3.44 secs
|
||||
Bing: Hello, this is Bing. How can I help? 😊 4.14 secs
|
||||
Async Total: 4.25 secs
|
||||
|
||||
OpenaiChat: Hello! How can I assist you today? 1.85 secs
|
||||
Bard: Hello! How can I help you today? 3.38 secs
|
||||
Bing: Hello, this is Bing. How can I help? 😊 6.14 secs
|
||||
Stream Total: 11.37 secs
|
||||
|
||||
OpenaiChat: Hello! How can I help you today? 3.28 secs
|
||||
Bard: Hello there! How can I help you today? 3.58 secs
|
||||
Bing: Hello! How can I help you today? 3.28 secs
|
||||
No Stream Total: 10.14 secs
|
||||
"""
|
||||
|
||||
print("Bing: ", end="")
|
||||
for response in log_time_yield(
|
||||
g4f.ChatCompletion.create,
|
||||
model=g4f.models.gpt_35_turbo,
|
||||
messages=[{"role": "user", "content": _instruct}],
|
||||
provider=g4f.Provider.Bing,
|
||||
#cookies=g4f.get_cookies(".huggingface.co"),
|
||||
#stream=True,
|
||||
auth=True
|
||||
):
|
||||
print(response, end="")
|
||||
print()
|
||||
print()
|
||||
|
||||
|
||||
async def run_async():
|
||||
responses = [
|
||||
log_time_async(
|
||||
provider.create_async,
|
||||
model=None,
|
||||
messages=[{"role": "user", "content": _instruct}],
|
||||
)
|
||||
for provider in _providers
|
||||
]
|
||||
responses = await asyncio.gather(*responses)
|
||||
for idx, provider in enumerate(_providers):
|
||||
print(f"{provider.__name__}:", responses[idx])
|
||||
print("Async Total:", asyncio.run(log_time_async(run_async)))
|
||||
print()
|
||||
|
||||
|
||||
def run_stream():
|
||||
for provider in _providers:
|
||||
print(f"{provider.__name__}: ", end="")
|
||||
for response in log_time_yield(
|
||||
provider.create_completion,
|
||||
model=None,
|
||||
messages=[{"role": "user", "content": _instruct}],
|
||||
):
|
||||
print(response, end="")
|
||||
print()
|
||||
print("Stream Total:", log_time(run_stream))
|
||||
print()
|
||||
|
||||
|
||||
def create_no_stream():
|
||||
for provider in _providers:
|
||||
print(f"{provider.__name__}:", end=" ")
|
||||
for response in log_time_yield(
|
||||
provider.create_completion,
|
||||
model=None,
|
||||
messages=[{"role": "user", "content": _instruct}],
|
||||
stream=False
|
||||
):
|
||||
print(response, end="")
|
||||
print()
|
||||
print("No Stream Total:", log_time(create_no_stream))
|
||||
print()
|
||||
@ -1,67 +1,76 @@
|
||||
import sys
|
||||
from pathlib import Path
|
||||
from colorama import Fore
|
||||
|
||||
sys.path.append(str(Path(__file__).parent.parent))
|
||||
|
||||
from g4f import BaseProvider, models, provider
|
||||
from g4f import BaseProvider, models, Provider
|
||||
|
||||
logging = False
|
||||
|
||||
def main():
|
||||
providers = get_providers()
|
||||
results: list[list[str | bool]] = []
|
||||
failed_providers = []
|
||||
|
||||
for _provider in providers:
|
||||
print("start", _provider.__name__)
|
||||
actual_working = judge(_provider)
|
||||
expected_working = _provider.working
|
||||
match = actual_working == expected_working
|
||||
if _provider.needs_auth:
|
||||
continue
|
||||
print("Provider:", _provider.__name__)
|
||||
result = test(_provider)
|
||||
print("Result:", result)
|
||||
if _provider.working and not result:
|
||||
failed_providers.append(_provider)
|
||||
|
||||
results.append([_provider.__name__, expected_working, actual_working, match])
|
||||
print()
|
||||
|
||||
print("failed provider list")
|
||||
for result in results:
|
||||
if not result[3]:
|
||||
print(result)
|
||||
if failed_providers:
|
||||
print(f"{Fore.RED}Failed providers:\n")
|
||||
for _provider in failed_providers:
|
||||
print(f"{Fore.RED}{_provider.__name__}")
|
||||
else:
|
||||
print(f"{Fore.GREEN}All providers are working")
|
||||
|
||||
|
||||
def get_providers() -> list[type[BaseProvider]]:
|
||||
provider_names = dir(provider)
|
||||
provider_names = dir(Provider)
|
||||
ignore_names = [
|
||||
"base_provider",
|
||||
"BaseProvider",
|
||||
"BaseProvider"
|
||||
]
|
||||
provider_names = [
|
||||
provider_name
|
||||
for provider_name in provider_names
|
||||
if not provider_name.startswith("__") and provider_name not in ignore_names
|
||||
]
|
||||
return [getattr(provider, provider_name) for provider_name in provider_names]
|
||||
return [getattr(Provider, provider_name) for provider_name in sorted(provider_names)]
|
||||
|
||||
|
||||
def create_response(_provider: type[BaseProvider]) -> str:
|
||||
model = (
|
||||
models.gpt_35_turbo.name
|
||||
if _provider is not provider.H2o
|
||||
else models.falcon_7b.name
|
||||
)
|
||||
if _provider.supports_gpt_35_turbo:
|
||||
model = models.gpt_35_turbo.name
|
||||
elif _provider.supports_gpt_4:
|
||||
model = models.gpt_4
|
||||
elif hasattr(_provider, "model"):
|
||||
model = _provider.model
|
||||
else:
|
||||
model = None
|
||||
response = _provider.create_completion(
|
||||
model=model,
|
||||
messages=[{"role": "user", "content": "Hello world!, plz yourself"}],
|
||||
messages=[{"role": "user", "content": "Hello"}],
|
||||
stream=False,
|
||||
)
|
||||
return "".join(response)
|
||||
|
||||
|
||||
def judge(_provider: type[BaseProvider]) -> bool:
|
||||
if _provider.needs_auth:
|
||||
return _provider.working
|
||||
|
||||
|
||||
def test(_provider: type[BaseProvider]) -> bool:
|
||||
try:
|
||||
response = create_response(_provider)
|
||||
assert type(response) is str
|
||||
return len(response) > 1
|
||||
assert len(response) > 0
|
||||
return response
|
||||
except Exception as e:
|
||||
print(e)
|
||||
if logging:
|
||||
print(e)
|
||||
return False
|
||||
|
||||
|
||||
|
||||
@ -30,4 +30,4 @@ def create_content():
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
main()
|
||||
@ -6,14 +6,35 @@ from urllib.parse import urlparse
|
||||
sys.path.append(str(Path(__file__).parent.parent))
|
||||
|
||||
from g4f import models, Provider
|
||||
from g4f.Provider.base_provider import BaseProvider
|
||||
from g4f.Provider.base_provider import BaseProvider, AsyncProvider
|
||||
from testing.test_providers import test
|
||||
|
||||
|
||||
def main():
|
||||
print_providers()
|
||||
print("\n", "-" * 50, "\n")
|
||||
print_models()
|
||||
def print_imports():
|
||||
print("##### Providers:")
|
||||
print("```py")
|
||||
print("from g4f.Provider import (")
|
||||
for _provider in get_providers():
|
||||
if _provider.working:
|
||||
print(f" {_provider.__name__},")
|
||||
print(")")
|
||||
print("# Usage:")
|
||||
print("response = g4f.ChatCompletion.create(..., provider=ProviderName)")
|
||||
print("```")
|
||||
print()
|
||||
print()
|
||||
|
||||
def print_async():
|
||||
print("##### Async support:")
|
||||
print("```py")
|
||||
print("from g4f.Provider import (")
|
||||
for _provider in get_providers():
|
||||
if issubclass(_provider, AsyncProvider):
|
||||
print(f" {_provider.__name__},")
|
||||
print(")")
|
||||
print("```")
|
||||
print()
|
||||
print()
|
||||
|
||||
def print_providers():
|
||||
lines = [
|
||||
@ -21,40 +42,50 @@ def print_providers():
|
||||
"| ------ | ------- | ------- | ----- | --------- | ------ | ---- |",
|
||||
]
|
||||
providers = get_providers()
|
||||
for _provider in providers:
|
||||
netloc = urlparse(_provider.url).netloc
|
||||
website = f"[{netloc}]({_provider.url})"
|
||||
for is_working in (True, False):
|
||||
for _provider in providers:
|
||||
if is_working != _provider.working:
|
||||
continue
|
||||
netloc = urlparse(_provider.url).netloc
|
||||
website = f"[{netloc}]({_provider.url})"
|
||||
|
||||
provider_name = f"g4f.provider.{_provider.__name__}"
|
||||
provider_name = f"g4f.provider.{_provider.__name__}"
|
||||
|
||||
has_gpt_35 = "✔️" if _provider.supports_gpt_35_turbo else "❌"
|
||||
has_gpt_4 = "✔️" if _provider.supports_gpt_4 else "❌"
|
||||
stream = "✔️" if _provider.supports_stream else "❌"
|
||||
status = (
|
||||
""
|
||||
if _provider.working
|
||||
else ""
|
||||
)
|
||||
auth = "✔️" if _provider.needs_auth else "❌"
|
||||
has_gpt_35 = "✔️" if _provider.supports_gpt_35_turbo else "❌"
|
||||
has_gpt_4 = "✔️" if _provider.supports_gpt_4 else "❌"
|
||||
stream = "✔️" if _provider.supports_stream else "❌"
|
||||
if _provider.working:
|
||||
if test(_provider):
|
||||
status = ''
|
||||
else:
|
||||
status = ''
|
||||
else:
|
||||
status = ''
|
||||
auth = "✔️" if _provider.needs_auth else "❌"
|
||||
|
||||
lines.append(
|
||||
f"| {website} | {provider_name} | {has_gpt_35} | {has_gpt_4} | {stream} | {status} | {auth} |"
|
||||
)
|
||||
lines.append(
|
||||
f"| {website} | {provider_name} | {has_gpt_35} | {has_gpt_4} | {stream} | {status} | {auth} |"
|
||||
)
|
||||
print("\n".join(lines))
|
||||
|
||||
|
||||
def get_providers() -> list[type[BaseProvider]]:
|
||||
def get_provider_names() -> list[str]:
|
||||
provider_names = dir(Provider)
|
||||
ignore_names = [
|
||||
"base_provider",
|
||||
"BaseProvider",
|
||||
"AsyncProvider",
|
||||
"AsyncGeneratorProvider"
|
||||
]
|
||||
provider_names = [
|
||||
return [
|
||||
provider_name
|
||||
for provider_name in provider_names
|
||||
if not provider_name.startswith("__") and provider_name not in ignore_names
|
||||
]
|
||||
return [getattr(Provider, provider_name) for provider_name in provider_names]
|
||||
|
||||
|
||||
def get_providers() -> list[type[BaseProvider]]:
|
||||
return [getattr(Provider, provider_name) for provider_name in get_provider_names()]
|
||||
|
||||
|
||||
def print_models():
|
||||
@ -79,6 +110,8 @@ def print_models():
|
||||
|
||||
_models = get_models()
|
||||
for model in _models:
|
||||
if model.best_provider.__name__ not in provider_urls:
|
||||
continue
|
||||
split_name = re.split(r":|/", model.name)
|
||||
name = split_name[-1]
|
||||
|
||||
@ -100,4 +133,8 @@ def get_models():
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
print_imports()
|
||||
print_async()
|
||||
print_providers()
|
||||
print("\n", "-" * 50, "\n")
|
||||
print_models()
|
||||
Loading…
Reference in New Issue
Block a user