Update g4f

README.md

@@ -161,19 +161,19 @@ For Naga AI, Get this by messaging run the /key get command in th bot channel in
 To use GPT4free API_BASE = 'http://g4f_server:1337' (Only working in docker)
 You can use any provider. I have included Naga AI api base. Use the key for the same.
 
--`MAX_HISTORY`
+- `MAX_HISTORY`
 Number of conversation history to be sent with each request. Default value 10. Don't put more than 20.      
 
--`ENABLED_PLUGINS`
+- `ENABLED_PLUGINS`
 List of enabled plugins. Only wolfram is disabled by default. Add Worlframalpha api key before adding wolfram to this list.     
 
--`WOLFRAM_APP_ID`
+- `WOLFRAM_APP_ID`
 Wolframalpha api key
 
--`DUCKDUCKGO_SAFESEARCH`
+- `DUCKDUCKGO_SAFESEARCH`
 Valid values are 'safe', 'moderate', 'off'
 
--`WORLDTIME_DEFAULT_TIMEZONE`
+- `WORLDTIME_DEFAULT_TIMEZONE`
 Timezone should be in the format Asia/Dubai or Europe/Rome
 
 

interference/app.py

@@ -72,15 +72,15 @@ def chat_completions():
     #AItianhu,
     #Acytoo,
     #Aichat,
-    #Ails,
-    Aivvm,
+    Ails,
+    #Aivvm,
     #Bard,
     #Bing,
     ChatBase,
-    #ChatgptAi,
-    ChatgptLogin,
-    CodeLinkAva,
-    #DeepAi,
+    ChatgptAi,
+    #ChatgptLogin,
+    #CodeLinkAva,
+    DeepAi,
     #H2o,
     #HuggingChat,
     #Opchatgpts,
@@ -91,9 +91,10 @@ def chat_completions():
     #Vercel,
     Vitalentum,
     Wewordle,
-    Ylokh,
+    #Ylokh,
     #You,
-    Yqcloud,]
+    Yqcloud
+    ]
 
     for provider in providers:
         try:

interference/g4f/Provider/AItianhu.py

@@ -1,61 +1,38 @@
 from __future__ import annotations
 
 import json
-from aiohttp import ClientSession, http
+from curl_cffi.requests import AsyncSession
 
-from ..typing import AsyncGenerator
-from .base_provider import AsyncGeneratorProvider, format_prompt
+from .base_provider import AsyncProvider, format_prompt
 
 
-class AItianhu(AsyncGeneratorProvider):
+class AItianhu(AsyncProvider):
     url = "https://www.aitianhu.com"
     working = True
     supports_gpt_35_turbo = True
 
     @classmethod
-    async def create_async_generator(
+    async def create_async(
         cls,
         model: str,
         messages: list[dict[str, str]],
         proxy: str = None,
         **kwargs
-    ) -> AsyncGenerator:
-        headers = {
-            "User-Agent": "Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:109.0) Gecko/20100101 Firefox/116.0",
-            "Accept": "application/json, text/plain, */*",
-            "Accept-Language": "de,en-US;q=0.7,en;q=0.3",
-            "Content-Type": "application/json",
-            "Origin": cls.url,
-            "Connection": "keep-alive",
-            "Referer": cls.url + "/",
-            "Sec-Fetch-Dest": "empty",
-            "Sec-Fetch-Mode": "cors",
-            "Sec-Fetch-Site": "same-origin",
+    ) -> str:
+        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 ClientSession(
-            headers=headers,
-            version=http.HttpVersion10
-        ) 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 session.post(
-                cls.url + "/api/chat-process",
-                proxy=proxy,
-                json=data,
-                ssl=False,
-            ) as response:
-                response.raise_for_status()
-                async for line in response.content:
-                    line = json.loads(line.decode('utf-8'))
-                    token = line["detail"]["choices"][0]["delta"].get("content")
-                    if token:
-                        yield token
+        async with AsyncSession(proxies={"https": proxy}, impersonate="chrome107", verify=False) as session:
+            response = await session.post(cls.url + "/api/chat-process", json=data)
+            response.raise_for_status()
+            line = response.text.splitlines()[-1]
+            line = json.loads(line)
+            return line["text"]
 
 
     @classmethod

interference/g4f/Provider/GptGo.py

@@ -0,0 +1,78 @@
+from __future__ import annotations
+
+from aiohttp import ClientSession
+import json
+
+from ..typing       import AsyncGenerator
+from .base_provider import AsyncGeneratorProvider, format_prompt
+
+
+class GptGo(AsyncGeneratorProvider):
+    url                   = "https://gptgo.ai"
+    supports_gpt_35_turbo = True
+    working               = True
+
+    @classmethod
+    async def create_async_generator(
+        cls,
+        model: str,
+        messages: list[dict[str, str]],
+        proxy: str = None,
+        **kwargs
+    ) -> AsyncGenerator:
+        headers = {
+            "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",
+            "Accept"             : "*/*",
+            "Accept-language"    : "en,fr-FR;q=0.9,fr;q=0.8,es-ES;q=0.7,es;q=0.6,en-US;q=0.5,am;q=0.4,de;q=0.3",
+            "Origin"             : cls.url,
+            "Referer"            : cls.url + "/",
+            "Sec-Fetch-Dest"     : "empty",
+            "Sec-Fetch-Mode"     : "cors",
+            "Sec-Fetch-Site"     : "same-origin",
+        }
+        async with ClientSession(
+            headers=headers
+        ) as session:
+            async with session.get(
+                "https://gptgo.ai/action_get_token.php",
+                params={
+                    "q": format_prompt(messages),
+                    "hlgpt": "default",
+                    "hl": "en"
+                },
+                proxy=proxy
+            ) as response:
+                response.raise_for_status()
+                token = (await response.json(content_type=None))["token"]
+
+            async with session.get(
+                "https://gptgo.ai/action_ai_gpt.php",
+                params={
+                    "token": token,
+                },
+                proxy=proxy
+            ) as response:
+                response.raise_for_status()
+                start = "data: "
+                async for line in response.content:
+                    line = line.decode()
+                    if line.startswith("data: "):
+                        if line.startswith("data: [DONE]"):
+                            break
+                        line = json.loads(line[len(start):-1])
+                        content = line["choices"][0]["delta"].get("content")
+                        if content:
+                            yield content
+
+
+    @classmethod
+    @property
+    def params(cls):
+        params = [
+            ("model", "str"),
+            ("messages", "list[dict[str, str]]"),
+            ("stream", "bool"),
+            ("temperature", "float"),
+        ]
+        param = ", ".join([": ".join(p) for p in params])
+        return f"g4f.provider.{cls.__name__} supports: ({param})"

interference/g4f/Provider/Vercel.py

@@ -9,7 +9,7 @@
 
 class Vercel(AsyncProvider):
     url                   = "https://sdk.vercel.ai"
-    working               = True
+    working               = False
     supports_gpt_35_turbo = True
     model                 = "replicate:replicate/llama-2-70b-chat"
 
@@ -21,74 +21,12 @@ async def create_async(
         proxy: str = None,
         **kwargs
     ) -> str:
-        if model in ["gpt-3.5-turbo", "gpt-4"]:
-            model = "openai:" + model
-        model = model if model else cls.model
-        proxies = None
-        if proxy:
-            if "://" not in proxy:
-                proxy = "http://" + proxy
-            proxies = {"http": proxy, "https": proxy}
-        headers = {
-            "User-Agent": "Mozilla/5.0 (Windows NT 6.1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/107.0.{rand1}.{rand2} Safari/537.36".format(
-                rand1=random.randint(0,9999),
-                rand2=random.randint(0,9999)
-            ),
-            "Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,*/*;q=0.8",
-            "Accept-Encoding": "gzip, deflate, br",
-            "Accept-Language": "en-US,en;q=0.5",
-            "TE": "trailers",
-        }
-        async with AsyncSession(headers=headers, proxies=proxies, impersonate="chrome107") as session:
-            response = await session.get(cls.url + "/openai.jpeg")
-            response.raise_for_status()
-            custom_encoding = _get_custom_encoding(response.text)
-            headers = {
-                "Content-Type": "application/json",
-                "Custom-Encoding": custom_encoding,
-            }
-            data = _create_payload(model, messages)
-            response = await session.post(cls.url + "/api/generate", json=data, headers=headers)
-            response.raise_for_status()
-            return response.text
-
-
-def _create_payload(model: str, messages: list[dict[str, str]]) -> dict[str, Any]:
-    if model not in model_info:
-        raise ValueError(f'Model are not supported: {model}')
-    default_params = model_info[model]["default_params"]
-    return {
-        "messages": messages,
-        "playgroundId": str(uuid.uuid4()),
-        "chatIndex": 0,
-        "model": model
-    } | default_params
-
-# based on https://github.com/ading2210/vercel-llm-api
-def _get_custom_encoding(text: str) -> str:
-    data = json.loads(base64.b64decode(text, validate=True))
-    script = """
-      String.prototype.fontcolor = function() {{
-        return `<font>${{this}}</font>`
-      }}
-      var globalThis = {{marker: "mark"}};
-      ({script})({key})
-    """.format(
-        script=data["c"], key=data["a"]
-    )
-    context = quickjs.Context()  # type: ignore
-    token_data = json.loads(context.eval(script).json())  # type: ignore
-    token_data[2] = "mark"
-    token = {"r": token_data, "t": data["t"]}
-    token_str = json.dumps(token, separators=(",", ":")).encode("utf-16le")
-    return base64.b64encode(token_str).decode()
-
+        return
 
 class ModelInfo(TypedDict):
     id: str
     default_params: dict[str, Any]
 
-
 model_info: dict[str, ModelInfo] = {
     "anthropic:claude-instant-v1": {
         "id": "anthropic:claude-instant-v1",

interference/g4f/Provider/Ylokh.py

@@ -51,7 +51,9 @@ async def create_async_generator(
                 if stream:
                     async for line in response.content:
                         line = line.decode()
-                        if line.startswith("data: ") and not line.startswith("data: [DONE]"):
+                        if line.startswith("data: "):
+                            if line.startswith("data: [DONE]"):
+                                break
                             line = json.loads(line[6:-1])
                             content = line["choices"][0]["delta"].get("content")
                             if content:
@@ -71,6 +73,7 @@ def params(cls):
             ("stream", "bool"),
             ("proxy", "str"),
             ("temperature", "float"),
+            ("top_p", "float"),
         ]
         param = ", ".join([": ".join(p) for p in params])
         return f"g4f.provider.{cls.__name__} supports: ({param})"

interference/g4f/Provider/__init__.py

@@ -16,6 +16,7 @@
 from .EasyChat      import EasyChat
 from .Forefront     import Forefront
 from .GetGpt        import GetGpt
+from .GptGo         import GptGo
 from .H2o           import H2o
 from .HuggingChat   import HuggingChat
 from .Liaobots      import Liaobots
@@ -57,6 +58,7 @@
     'EasyChat',
     'Forefront',
     'GetGpt',
+    'GptGo',
     'H2o',
     'HuggingChat',
     'Liaobots',