~ | Merge pull request #941 from hlohaus/myshell

AItianhuSpace Provider with GPT 4 added

g4f/Provider/AItianhuSpace.py

@@ -0,0 +1,73 @@
+from __future__ import annotations
+
+import random, json
+
+from g4f.requests import AsyncSession, StreamRequest
+from .base_provider import AsyncGeneratorProvider, format_prompt
+
+domains = {
+    "gpt-3.5-turbo": ".aitianhu.space",
+    "gpt-4": ".aitianhu.website",
+}
+
+class AItianhuSpace(AsyncGeneratorProvider):
+    url = "https://chat3.aiyunos.top/"
+    working = True
+    supports_gpt_35_turbo = True
+
+    @classmethod
+    async def create_async_generator(
+        cls,
+        model: str,
+        messages: list[dict[str, str]],
+        stream: bool = True,
+        **kwargs
+    ) -> str:
+        if not model:
+            model = "gpt-3.5-turbo"
+        elif not model in domains:
+            raise ValueError(f"Model are not supported: {model}")
+        
+        chars = 'abcdefghijklmnopqrstuvwxyz0123456789'
+        rand = ''.join(random.choice(chars) for _ in range(6))
+        domain = domains[model]
+        url = f'https://{rand}{domain}/api/chat-process'
+
+        headers = {
+            "User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/113.0.0.0 Safari/537.36",
+        }
+        async with AsyncSession(headers=headers, impersonate="chrome107", verify=False) as session:
+            data = {
+                "prompt": format_prompt(messages),
+                "options": {},
+                "systemMessage": "You are ChatGPT, a large language model trained by OpenAI. Follow the user's instructions carefully.",
+                "temperature": 0.8,
+                "top_p": 1,
+                **kwargs
+            }
+            async with StreamRequest(session, "POST", url, json=data) as response:
+                response.raise_for_status()
+                async for line in response.content:
+                    line = json.loads(line.rstrip())
+                    if "detail" in line:
+                        content = line["detail"]["choices"][0]["delta"].get("content")
+                        if content:
+                            yield content
+                    elif "message" in line and "AI-4接口非常昂贵" in line["message"]:
+                        raise RuntimeError("Rate limit for GPT 4 reached")
+                    else:
+                        raise RuntimeError("Response: {line}")
+        
+
+    @classmethod
+    @property
+    def params(cls):
+        params = [
+            ("model", "str"),
+            ("messages", "list[dict[str, str]]"),
+            ("stream", "bool"),
+            ("temperature", "float"),
+            ("top_p", "int"),
+        ]
+        param = ", ".join([": ".join(p) for p in params])
+        return f"g4f.provider.{cls.__name__} supports: ({param})"

g4f/Provider/Aivvm.py

@@ -60,9 +60,10 @@ class Aivvm(BaseProvider):
 
         response = requests.post(
             "https://chat.aivvm.com/api/chat", headers=headers, json=json_data, stream=True)
+        response.raise_for_status()
 
-        for line in response.iter_content(chunk_size=1048):
-            yield line.decode('utf-8')
+        for chunk in response.iter_content(chunk_size=None):
+            yield chunk.decode('utf-8')
 
     @classmethod
     @property

g4f/Provider/Vercel.py

@@ -18,7 +18,13 @@ class Vercel(BaseProvider):
     def create_completion(
         model: str,
         messages: list[dict[str, str]],
-        stream: bool, **kwargs ) -> CreateResult:
+        stream: bool,
+        **kwargs
+    ) -> CreateResult:
+        if not model:
+            model = "gpt-3.5-turbo"
+        elif model not in model_info:
+            raise ValueError(f"Model are not supported: {model}")
 
         headers = {
             'authority'         : 'sdk.vercel.ai',
@@ -26,7 +32,7 @@ class Vercel(BaseProvider):
             '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',
-            'custom-encoding'   : AntiBotToken(),
+            'custom-encoding'   : get_anti_bot_token(),
             'origin'            : 'https://sdk.vercel.ai',
             'pragma'            : 'no-cache',
             'referer'           : 'https://sdk.vercel.ai/',
@@ -48,22 +54,20 @@ class Vercel(BaseProvider):
             'playgroundId': str(uuid.uuid4()),
             'chatIndex'   : 0} | model_info[model]['default_params']
 
-        server_error = True
-        retries      = 0
         max_retries  = kwargs.get('max_retries', 20)
-        
-        while server_error and not retries > max_retries:
+        for i in range(max_retries):
             response = requests.post('https://sdk.vercel.ai/api/generate', 
                                     headers=headers, json=json_data, stream=True)
+            try:
+                response.raise_for_status()
+            except:
+                continue
+            for token in response.iter_content(chunk_size=8):
+                yield token.decode()
+            break
 
-            for token in response.iter_content(chunk_size=2046):
-                if token != b'Internal Server Error':
-                    server_error = False
-                    yield (token.decode())
-                    
-            retries += 1
 
-def AntiBotToken() -> str:
+def get_anti_bot_token() -> str:
     headers = {
         'authority'         : 'sdk.vercel.ai',
         'accept'            : '*/*',

g4f/Provider/__init__.py

@@ -4,6 +4,7 @@ from .Aichat        import Aichat
 from .Ails          import Ails
 from .AiService     import AiService
 from .AItianhu      import AItianhu
+from .AItianhuSpace import AItianhuSpace
 from .Aivvm         import Aivvm
 from .Bard          import Bard
 from .Bing          import Bing
@@ -52,6 +53,7 @@ __all__ = [
     'Ails',
     'AiService',
     'AItianhu',
+    'AItianhuSpace',
     'Aivvm',
     'Bard',
     'Bing',

g4f/Provider/base_provider.py

@@ -1,7 +1,9 @@
 from __future__ import annotations
 
 import asyncio
-from asyncio import SelectorEventLoop
+import functools
+from asyncio import SelectorEventLoop, AbstractEventLoop
+from concurrent.futures import ThreadPoolExecutor
 from abc import ABC, abstractmethod
 
 import browser_cookie3
@@ -27,6 +29,31 @@ class BaseProvider(ABC):
     ) -> CreateResult:
         raise NotImplementedError()
 
+    @classmethod
+    async def create_async(
+        cls,
+        model: str,
+        messages: list[dict[str, str]],
+        *,
+        loop: AbstractEventLoop = None,
+        executor: ThreadPoolExecutor = None,
+        **kwargs
+    ) -> str:
+        if not loop:
+            loop = asyncio.get_event_loop()
+
+        partial_func = functools.partial(
+            cls.create_completion,
+            model,
+            messages,
+            False,
+            **kwargs
+        )
+        response = await loop.run_in_executor(
+            executor,
+            partial_func
+        )
+        return "".join(response)
 
     @classmethod
     @property
@@ -127,7 +154,7 @@ def create_event_loop() -> SelectorEventLoop:
     except RuntimeError:
         return SelectorEventLoop()
     raise RuntimeError(
-        'Use "create_async" instead of "create" function in a async loop.')
+        'Use "create_async" instead of "create" function in a running event loop.')
 
 
 _cookies = {}

g4f/models.py

@@ -17,6 +17,7 @@ from .Provider   import (
     Wewordle,
     Yqcloud,
     AItianhu,
+    AItianhuSpace,
     Aichat,
     Myshell,
 )
@@ -38,7 +39,7 @@ default = Model(
         Wewordle,     # Responds with markdown
         Yqcloud,      # Answers short questions in chinese
         ChatBase,     # Don't want to answer creatively
-        DeepAi, ChatgptLogin, ChatgptAi, Aivvm, GptGo, AItianhu, Aichat, Myshell,
+        DeepAi, ChatgptLogin, ChatgptAi, Aivvm, GptGo, AItianhu, AItianhuSpace, Aichat, Myshell,
     ])
 )
 
@@ -47,7 +48,7 @@ gpt_35_turbo = Model(
     name          = 'gpt-3.5-turbo',
     base_provider = 'openai',
     best_provider = RetryProvider([
-        DeepAi, ChatgptLogin, ChatgptAi, Aivvm, GptGo, AItianhu, Aichat, Myshell,
+        DeepAi, ChatgptLogin, ChatgptAi, Aivvm, GptGo, AItianhu, Aichat, AItianhuSpace, Myshell,
     ])
 )
 
@@ -55,7 +56,7 @@ gpt_4 = Model(
     name          = 'gpt-4',
     base_provider = 'openai',
     best_provider = RetryProvider([
-        Aivvm, Myshell
+        Aivvm, Myshell, AItianhuSpace,
     ])
 )
 

g4f/requests.py

@@ -0,0 +1,78 @@
+from __future__ import annotations
+
+import json, sys
+from aiohttp import StreamReader
+from aiohttp.base_protocol import BaseProtocol
+
+from curl_cffi.requests import AsyncSession
+from curl_cffi.requests.cookies import Request
+from curl_cffi.requests.cookies import Response
+
+
+class StreamResponse:
+    def __init__(self, inner: Response, content: StreamReader, request: Request):
+        self.inner = inner
+        self.content = content
+        self.request = request
+        self.status_code = inner.status_code
+        self.reason = inner.reason
+        self.ok = inner.ok
+
+    async def text(self) -> str:
+        content = await self.content.read()
+        return content.decode()
+
+    def raise_for_status(self):
+        if not self.ok:
+            raise RuntimeError(f"HTTP Error {self.status_code}: {self.reason}")
+
+    async def json(self, **kwargs):
+        return json.loads(await self.content.read(), **kwargs)
+
+
+class StreamRequest:
+    def __init__(self, session: AsyncSession, method: str, url: str, **kwargs):
+        self.session = session
+        self.loop = session.loop
+        self.content = StreamReader(
+            BaseProtocol(session.loop),
+            sys.maxsize,
+            loop=session.loop
+        )
+        self.method = method
+        self.url = url
+        self.options = kwargs
+
+    def on_content(self, data):
+        if not self.enter.done():
+            self.enter.set_result(None)
+        self.content.feed_data(data)
+
+    def on_done(self, task):
+        self.content.feed_eof()
+
+    async def __aenter__(self) -> StreamResponse:
+        self.curl = await self.session.pop_curl()
+        self.enter = self.session.loop.create_future()
+        request, _, header_buffer = self.session._set_curl_options(
+            self.curl,
+            self.method,
+            self.url,
+            content_callback=self.on_content,
+            **self.options
+        )
+        handle = self.session.acurl.add_handle(self.curl)
+        self.handle = self.session.loop.create_task(handle)
+        self.handle.add_done_callback(self.on_done)
+        await self.enter
+        return StreamResponse(
+            self.session._parse_response(self.curl, request, _, header_buffer),
+            self.content,
+            request
+        )
+            
+    async def __aexit__(self, exc_type, exc, tb):
+        await self.handle
+        self.curl.clean_after_perform()
+        self.curl.reset()
+        self.session.push_curl(self.curl)