Add MetaAI Provider and some small improvments

etc/examples/api.py

@@ -0,0 +1,19 @@
+import requests
+import json
+url = "http://localhost:1337/v1/chat/completions"
+body = {
+    "model": "",
+    "provider": "MetaAI",
+    "stream": True,
+    "messages": [
+        {"role": "assistant", "content": "What can you do? Who are you?"}
+    ]
+}
+lines = requests.post(url, json=body, stream=True).iter_lines()
+for line in lines:
+    if line.startswith(b"data: "):
+        try:
+            print(json.loads(line[6:]).get("choices", [{"delta": {}}])[0]["delta"].get("content", ""), end="")
+        except json.JSONDecodeError:
+            pass
+print()

etc/unittest/integration.py

@@ -19,6 +19,7 @@ def setUp(self):
             self.skipTest("nest_asyncio is not installed")
 
     def test_bing(self):
+        self.skipTest("Not working")
         client = Client(provider=Bing)
         response = client.chat.completions.create(DEFAULT_MESSAGES, "", response_format={"type": "json_object"})
         self.assertIsInstance(response, ChatCompletion)

g4f/Provider/BingCreateImages.py

@@ -15,6 +15,7 @@ class BingCreateImages(AsyncGeneratorProvider, ProviderModelMixin):
     label = "Microsoft Designer"
     url = "https://www.bing.com/images/create"
     working = True
+    needs_auth = True
 
     def __init__(self, cookies: Cookies = None, proxy: str = None) -> None:
         self.cookies: Cookies = cookies

g4f/Provider/Ecosia.py

@@ -15,19 +15,19 @@ class Ecosia(AsyncGeneratorProvider, ProviderModelMixin):
     working = True
     supports_gpt_35_turbo = True
     default_model = "gpt-3.5-turbo-0125"
-    model_aliases = {"gpt-3.5-turbo": "gpt-3.5-turbo-0125"}
+    models = [default_model, "green"]
+    model_aliases = {"gpt-3.5-turbo": default_model}
 
     @classmethod
     async def create_async_generator(
         cls,
         model: str,
         messages: Messages,
         connector: BaseConnector = None,
-        green: bool = False,
         proxy: str = None,
         **kwargs
     ) -> AsyncResult:
-        cls.get_model(model)
+        model = cls.get_model(model)
         headers = {
             "authority": "api.ecosia.org",
             "accept": "*/*",
@@ -39,7 +39,7 @@ async def create_async_generator(
             data = {
                 "messages": base64.b64encode(json.dumps(messages).encode()).decode()
             }
-            api_url = f"https://api.ecosia.org/v2/chat/?sp={'eco' if green else 'productivity'}"
+            api_url = f"https://api.ecosia.org/v2/chat/?sp={'eco' if model == 'green' else 'productivity'}"
             async with session.post(api_url, json=data) as response:
                 await raise_for_status(response)
                 async for chunk in response.content.iter_any():

g4f/Provider/MetaAI.py

@@ -0,0 +1,206 @@
+import json
+import uuid
+import random
+import time
+from typing import Dict, List
+
+from aiohttp import ClientSession, BaseConnector
+
+from ..typing import AsyncResult, Messages, Cookies
+from ..requests import raise_for_status, DEFAULT_HEADERS
+from .base_provider import AsyncGeneratorProvider
+from .helper import format_prompt, get_connector
+
+class Sources():
+    def __init__(self, link_list: List[Dict[str, str]]) -> None:
+        self.link = link_list
+
+    def __str__(self) -> str:
+        return "\n\n" + ("\n".join([f"[{link['title']}]({link['link']})" for link in self.list]))
+
+class AbraGeoBlockedError(Exception):
+    pass
+
+class MetaAI(AsyncGeneratorProvider):
+    url = "https://www.meta.ai"
+    working = True
+
+    def __init__(self, proxy: str = None, connector: BaseConnector = None):
+        self.session = ClientSession(connector=get_connector(connector, proxy), headers=DEFAULT_HEADERS)
+        self.cookies: Cookies = None
+        self.access_token: str = None
+
+    @classmethod
+    async def create_async_generator(
+        cls,
+        model: str,
+        messages: Messages,
+        proxy: str = None,
+        **kwargs
+    ) -> AsyncResult:
+        #cookies = get_cookies(".meta.ai", False, True)
+        async for chunk in cls(proxy).prompt(format_prompt(messages)):
+            yield chunk
+
+    async def get_access_token(self, birthday: str = "1999-01-01") -> str:
+        url = "https://www.meta.ai/api/graphql/"
+
+        payload = {
+            "lsd": self.lsd,
+            "fb_api_caller_class": "RelayModern",
+            "fb_api_req_friendly_name": "useAbraAcceptTOSForTempUserMutation",
+            "variables": json.dumps({
+                "dob": birthday,
+                "icebreaker_type": "TEXT",
+                "__relay_internal__pv__WebPixelRatiorelayprovider": 1,
+            }),
+            "doc_id": "7604648749596940",
+        }
+        headers = {
+            "x-fb-friendly-name": "useAbraAcceptTOSForTempUserMutation",
+            "x-fb-lsd": self.lsd,
+            "x-asbd-id": "129477",
+            "alt-used": "www.meta.ai",
+            "sec-fetch-site": "same-origin"
+        }
+        async with self.session.post(url, headers=headers, cookies=self.cookies, data=payload) as response:
+            await raise_for_status(response, "Fetch access_token failed")
+            auth_json = await response.json(content_type=None)
+            access_token = auth_json["data"]["xab_abra_accept_terms_of_service"]["new_temp_user_auth"]["access_token"]
+            return access_token
+
+    async def prompt(self, message: str, cookies: Cookies = None) -> AsyncResult:
+        if cookies is not None:
+            self.cookies = cookies
+            self.access_token = None
+        if self.cookies is None:
+            self.cookies = await self.get_cookies()
+        if self.access_token is None:
+            self.access_token  = await self.get_access_token()
+
+        url = "https://graph.meta.ai/graphql?locale=user"
+        #url = "https://www.meta.ai/api/graphql/"
+        payload = {
+            "access_token": self.access_token,
+            #"lsd": cookies["lsd"],
+            "fb_api_caller_class": "RelayModern",
+            "fb_api_req_friendly_name": "useAbraSendMessageMutation",
+            "variables": json.dumps({
+                "message": {"sensitive_string_value": message},
+                "externalConversationId": str(uuid.uuid4()),
+                "offlineThreadingId": generate_offline_threading_id(),
+                "suggestedPromptIndex": None,
+                "flashVideoRecapInput": {"images": []},
+                "flashPreviewInput": None,
+                "promptPrefix": None,
+                "entrypoint": "ABRA__CHAT__TEXT",
+                "icebreaker_type": "TEXT",
+                "__relay_internal__pv__AbraDebugDevOnlyrelayprovider": False,
+                "__relay_internal__pv__WebPixelRatiorelayprovider": 1,
+            }),
+            "server_timestamps": "true",
+            "doc_id": "7783822248314888",
+        }
+        headers = {
+            "x-asbd-id": "129477",
+            "x-fb-friendly-name": "useAbraSendMessageMutation",
+            #"x-fb-lsd": cookies["lsd"],
+        }
+        async with self.session.post(url, headers=headers, cookies=self.cookies, data=payload) as response:
+            await raise_for_status(response, "Fetch response failed")
+            last_snippet_len = 0
+            fetch_id = None
+            async for line in response.content:
+                try:
+                    json_line = json.loads(line)
+                except json.JSONDecodeError:
+                    continue
+                bot_response_message = json_line.get("data", {}).get("node", {}).get("bot_response_message", {})
+                streaming_state = bot_response_message.get("streaming_state")
+                fetch_id = bot_response_message.get("fetch_id") or fetch_id
+                if streaming_state in ("STREAMING", "OVERALL_DONE"):
+                    #imagine_card = bot_response_message["imagine_card"]
+                    snippet =  bot_response_message["snippet"]
+                    new_snippet_len = len(snippet)
+                    if new_snippet_len > last_snippet_len:
+                        yield snippet[last_snippet_len:]
+                        last_snippet_len = new_snippet_len
+            #if last_streamed_response is None:
+            #    if attempts > 3:
+            #        raise Exception("MetaAI is having issues and was not able to respond (Server Error)")
+            #    access_token = await self.get_access_token()
+            #    return await self.prompt(message=message, attempts=attempts + 1)
+            if fetch_id is not None:
+                sources = await self.fetch_sources(fetch_id)
+                if sources is not None:
+                    yield sources 
+
+    async def get_cookies(self, cookies: Cookies = None) -> Cookies:
+        async with self.session.get("https://www.meta.ai/", cookies=cookies) as response:
+            await raise_for_status(response, "Fetch home failed")
+            text = await response.text()
+            if "AbraGeoBlockedError" in text:
+                raise AbraGeoBlockedError("Meta AI isn't available yet in your country")
+            if cookies is None:
+                cookies = {
+                    "_js_datr": self.extract_value(text, "_js_datr"),
+                    "abra_csrf": self.extract_value(text, "abra_csrf"),
+                    "datr": self.extract_value(text, "datr"),
+                }
+            self.lsd = self.extract_value(text, start_str='"LSD",[],{"token":"', end_str='"}')
+            return cookies
+
+    async def fetch_sources(self, fetch_id: str) -> Sources:
+        url = "https://graph.meta.ai/graphql?locale=user"
+        payload = {
+            "access_token": self.access_token,
+            "fb_api_caller_class": "RelayModern",
+            "fb_api_req_friendly_name": "AbraSearchPluginDialogQuery",
+            "variables": json.dumps({"abraMessageFetchID": fetch_id}),
+            "server_timestamps": "true",
+            "doc_id": "6946734308765963",
+        }
+        headers = {
+            "authority": "graph.meta.ai",
+            "x-fb-friendly-name": "AbraSearchPluginDialogQuery",
+        }
+        async with self.session.post(url, headers=headers, cookies=self.cookies, data=payload) as response:
+            await raise_for_status(response)
+            response_json = await response.json()
+            try:
+                message = response_json["data"]["message"]
+                if message is not None:
+                    searchResults = message["searchResults"]
+                    if searchResults is not None:
+                        return Sources(searchResults["references"])
+            except (KeyError, TypeError):
+                raise RuntimeError(f"Response: {response_json}")
+
+    @staticmethod
+    def extract_value(text: str, key: str = None, start_str = None, end_str = '",') -> str:
+        if start_str is None:
+            start_str = f'{key}":{{"value":"'
+        start = text.find(start_str)
+        if start >= 0:
+            start+= len(start_str)
+            end = text.find(end_str, start)
+            if end >= 0:
+                return text[start:end]
+
+def generate_offline_threading_id() -> str:
+    """
+    Generates an offline threading ID.
+
+    Returns:
+        str: The generated offline threading ID.
+    """
+    # Generate a random 64-bit integer
+    random_value = random.getrandbits(64)
+
+    # Get the current timestamp in milliseconds
+    timestamp = int(time.time() * 1000)
+
+    # Combine timestamp and random value
+    threading_id = (timestamp << 22) | (random_value & ((1 << 22) - 1))
+
+    return str(threading_id)

g4f/Provider/__init__.py

@@ -42,6 +42,7 @@
 from .Liaobots         import Liaobots
 from .Llama            import Llama
 from .Local            import Local
+from .MetaAI           import MetaAI
 from .PerplexityLabs   import PerplexityLabs
 from .Pi               import Pi
 from .ReplicateImage   import ReplicateImage

g4f/Provider/base_provider.py

@@ -1,3 +1,3 @@
 from ..providers.base_provider import *
-from ..providers.types import FinishReason
+from ..providers.types import FinishReason, Streaming
 from .helper import get_cookies, format_prompt

g4f/Provider/needs_auth/Groq.py

@@ -4,7 +4,7 @@
 from ...typing import AsyncResult, Messages
 
 class Groq(Openai):
-    lebel = "Groq"
+    label = "Groq"
     url = "https://console.groq.com/playground"
     working = True
     default_model = "mixtral-8x7b-32768"

g4f/Provider/needs_auth/OpenaiAccount.py

@@ -3,5 +3,4 @@
 from .OpenaiChat import OpenaiChat
 
 class OpenaiAccount(OpenaiChat):
-    label = "OpenAI ChatGPT with Account"
     needs_auth = True