Merge branch 'xtekky:main' into setollamahost

g4f/Provider/Airforce.py

@@ -1,76 +1,199 @@
 from __future__ import annotations
-
-from aiohttp import ClientSession, ClientResponseError
+import random
 import json
+from aiohttp import ClientSession
 from ..typing import AsyncResult, Messages
 from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
 from ..image import ImageResponse
-from .helper import format_prompt
-from ..errors import ResponseStatusError
+
+def split_long_message(message: str, max_length: int = 4000) -> list[str]:
+    return [message[i:i+max_length] for i in range(0, len(message), max_length)]
 
 class Airforce(AsyncGeneratorProvider, ProviderModelMixin):
     url = "https://api.airforce"
-    text_api_endpoint = "https://api.airforce/chat/completions"
     image_api_endpoint = "https://api.airforce/imagine2"
+    text_api_endpoint = "https://api.airforce/chat/completions"
     working = True
+    
+    default_model = 'llama-3-70b-chat'
+    
     supports_gpt_35_turbo = True
     supports_gpt_4 = True
     supports_stream = True
     supports_system_message = True
     supports_message_history = True
-    default_model = 'llama-3-70b-chat'
+    
     text_models = [
-        # Open source models
-        'llama-2-13b-chat',
-        'llama-3-70b-chat',
-        'llama-3-70b-chat-turbo',
-        'llama-3-70b-chat-lite',
-        'llama-3-8b-chat',
-        'llama-3-8b-chat-turbo',
-        'llama-3-8b-chat-lite',
-        'llama-3.1-405b-turbo',
-        'llama-3.1-70b-turbo',
-        'llama-3.1-8b-turbo',
-        'LlamaGuard-2-8b',
-        'Llama-Guard-7b',
-        'Meta-Llama-Guard-3-8B',
-        'Mixtral-8x7B-Instruct-v0.1',
-        'Mixtral-8x22B-Instruct-v0.1',
-        'Mistral-7B-Instruct-v0.1',
-        'Mistral-7B-Instruct-v0.2',
-        'Mistral-7B-Instruct-v0.3',
-        'Qwen1.5-72B-Chat',
-        'Qwen1.5-110B-Chat',
-        'Qwen2-72B-Instruct',
-        'gemma-2b-it',
-        'gemma-2-9b-it',
-        'gemma-2-27b-it',
-        'dbrx-instruct',
-        'deepseek-llm-67b-chat',
-        'Nous-Hermes-2-Mixtral-8x7B-DPO',
-        'Nous-Hermes-2-Yi-34B',
-        'WizardLM-2-8x22B',
-        'SOLAR-10.7B-Instruct-v1.0',
-        'StripedHyena-Nous-7B',      
-        'sparkdesk',
-        
-        # Other models
-        'chatgpt-4o-latest',
-        'gpt-4',
-        'gpt-4-turbo',
-        'gpt-4o-mini-2024-07-18',
-        'gpt-4o-mini',
-        'gpt-4o',
-        'gpt-3.5-turbo',
-        'gpt-3.5-turbo-0125',
-        'gpt-3.5-turbo-1106',
-        'gpt-3.5-turbo-16k',
-        'gpt-3.5-turbo-0613',
-        'gpt-3.5-turbo-16k-0613',
-        'gemini-1.5-flash',
-        'gemini-1.5-pro',
+        # anthorpic
+        'claude-3-haiku-20240307', 
+        'claude-3-sonnet-20240229', 
+        'claude-3-5-sonnet-20240620', 
+        'claude-3-opus-20240229', 
+        
+        # openai
+        'chatgpt-4o-latest', 
+        'gpt-4', 
+        #'gpt-4-0613', 
+        'gpt-4-turbo', 
+        'gpt-4o-mini-2024-07-18', 
+        'gpt-4o-mini', 
+        'gpt-3.5-turbo', 
+        'gpt-3.5-turbo-0125', 
+        'gpt-3.5-turbo-1106', 
+        #'gpt-3.5-turbo-16k', # No response from the API.
+        #'gpt-3.5-turbo-0613', # No response from the API.
+        #'gpt-3.5-turbo-16k-0613', # No response from the API.
+        'gpt-4o', 
+        #'o1-mini', # No response from the API.
+        
+        # meta-llama
+        'llama-3-70b-chat', 
+        'llama-3-70b-chat-turbo', 
+        'llama-3-8b-chat', 
+        'llama-3-8b-chat-turbo', 
+        'llama-3-70b-chat-lite', 
+        'llama-3-8b-chat-lite', 
+        #'llama-2-70b-chat', # Failed to load response after multiple retries.
+        'llama-2-13b-chat', 
+        #'llama-2-7b-chat', # Failed to load response after multiple retries.
+        'llama-3.1-405b-turbo', 
+        'llama-3.1-70b-turbo', 
+        'llama-3.1-8b-turbo', 
+        'LlamaGuard-2-8b', 
+        'Llama-Guard-7b', 
+        'Llama-3.2-90B-Vision-Instruct-Turbo',
+        
+        # codellama
+        #'CodeLlama-7b-Python-hf', # Failed to load response after multiple retries.
+        #'CodeLlama-7b-Python', 
+        #'CodeLlama-13b-Python-hf', # Failed to load response after multiple retries.
+        #'CodeLlama-34b-Python-hf', # Failed to load response after multiple retries.
+        #'CodeLlama-70b-Python-hf', # Failed to load response after multiple retries.
+        
+        # 01-ai
+        #'Yi-34B-Chat', # Failed to load response after multiple retries.
+        #'Yi-34B', # Failed to load response after multiple retries.
+        #'Yi-6B', # Failed to load response after multiple retries.
+        
+        # mistral-ai
+        #'Mixtral-8x7B-v0.1', 
+        #'Mixtral-8x22B', # Failed to load response after multiple retries.
+        'Mixtral-8x7B-Instruct-v0.1', 
+        'Mixtral-8x22B-Instruct-v0.1', 
+        'Mistral-7B-Instruct-v0.1', 
+        'Mistral-7B-Instruct-v0.2', 
+        'Mistral-7B-Instruct-v0.3', 
+        
+        # openchat
+        #'openchat-3.5', # Failed to load response after multiple retries.
+        
+        # wizardlm
+        #'WizardLM-13B-V1.2', # Failed to load response after multiple retries.
+        #'WizardCoder-Python-34B-V1.0', # Failed to load response after multiple retries.
+        
+        # qwen
+        #'Qwen1.5-0.5B-Chat', # Failed to load response after multiple retries.
+        #'Qwen1.5-1.8B-Chat', # Failed to load response after multiple retries.
+        #'Qwen1.5-4B-Chat', # Failed to load response after multiple retries.
+        'Qwen1.5-7B-Chat', 
+        'Qwen1.5-14B-Chat', 
+        'Qwen1.5-72B-Chat', 
+        'Qwen1.5-110B-Chat', 
+        'Qwen2-72B-Instruct', 
+        
+        # google
+        'gemma-2b-it', 
+        #'gemma-7b-it', # Failed to load response after multiple retries.
+        #'gemma-2b', # Failed to load response after multiple retries.
+        #'gemma-7b', # Failed to load response after multiple retries.
+        'gemma-2-9b-it', # fix bug
+        'gemma-2-27b-it', 
+        
+        # gemini
+        'gemini-1.5-flash', 
+        'gemini-1.5-pro', 
+        
+        # databricks
+        'dbrx-instruct', 
+        
+        # lmsys
+        #'vicuna-7b-v1.5', # Failed to load response after multiple retries.
+        #'vicuna-13b-v1.5', # Failed to load response after multiple retries.
+        
+        # cognitivecomputations
+        #'dolphin-2.5-mixtral-8x7b', # Failed to load response after multiple retries.
+        
+        # deepseek-ai
+        #'deepseek-coder-33b-instruct', # No response from the API.
+        #'deepseek-coder-67b-instruct', # Failed to load response after multiple retries.
+        'deepseek-llm-67b-chat', 
+        
+        # NousResearch
+        #'Nous-Capybara-7B-V1p9', # Failed to load response after multiple retries.
+        'Nous-Hermes-2-Mixtral-8x7B-DPO', 
+        #'Nous-Hermes-2-Mixtral-8x7B-SFT', # Failed to load response after multiple retries.
+        #'Nous-Hermes-llama-2-7b', # Failed to load response after multiple retries.
+        #'Nous-Hermes-Llama2-13b', # Failed to load response after multiple retries.
+        'Nous-Hermes-2-Yi-34B', 
+        
+        # Open-Orca
+        #'Mistral-7B-OpenOrca', # Failed to load response after multiple retries.
+        
+        # togethercomputer
+        #'alpaca-7b', # Failed to load response after multiple retries.
+        
+        # teknium
+        #'OpenHermes-2-Mistral-7B', # Failed to load response after multiple retries.
+        #'OpenHermes-2.5-Mistral-7B', # Failed to load response after multiple retries.
+        
+        # microsoft
+        'WizardLM-2-8x22B', 
+        
+        # Nexusflow
+        #'NexusRaven-V2-13B', # Failed to load response after multiple retries.
+        
+        # Phind
+        #'Phind-CodeLlama-34B-v2', # Failed to load response after multiple retries.
+        
+        # Snoflake
+        #'snowflake-arctic-instruct', # No response from the API.
+        
+        # upstage
+        'SOLAR-10.7B-Instruct-v1.0', 
+        
+        # togethercomputer
+        #'StripedHyena-Hessian-7B', # Failed to load response after multiple retries.
+        #'StripedHyena-Nous-7B', # Failed to load response after multiple retries.
+        #'Llama-2-7B-32K-Instruct', # Failed to load response after multiple retries.
+        #'CodeLlama-13b-Instruct', # No response from the API.
+        #'evo-1-131k-base', # Failed to load response after multiple retries.
+        #'OLMo-7B-Instruct', # Failed to load response after multiple retries.
+        
+        # garage-bAInd
+        #'Platypus2-70B-instruct', # Failed to load response after multiple retries.
+        
+        # snorkelai
+        #'Snorkel-Mistral-PairRM-DPO', # Failed to load response after multiple retries.
+        
+        # Undi95
+        #'ReMM-SLERP-L2-13B', # Failed to load response after multiple retries.
+        
+        # Gryphe
+        'MythoMax-L2-13b', 
+        
+        # Autism
+        #'chronos-hermes-13b', # Failed to load response after multiple retries.
+        
+        # Undi95
+        #'Toppy-M-7B', # Failed to load response after multiple retries.
+        
+        # iFlytek
+        #'sparkdesk', # Failed to load response after multiple retries.
+        
+        # pawan
+        'cosmosrp', 
+        
     ]
-    
     image_models = [
         'flux',
         'flux-realism',
@@ -85,158 +208,206 @@ class Airforce(AsyncGeneratorProvider, ProviderModelMixin):
     
     models = [
         *text_models,
-        *image_models
+        *image_models,
     ]
     model_aliases = {
-        # Open source models
-        "llama-2-13b": "llama-2-13b-chat",
+        # anthorpic
+        "claude-3-haiku": "claude-3-haiku-20240307",
+        "claude-3-sonnet": "claude-3-sonnet-20240229",
+        "claude-3-5-sonnet": "claude-3-5-sonnet-20240620",
+        "claude-3-opus": "claude-3-opus-20240229",
+        
+        # openai
+        "gpt-4o": "chatgpt-4o-latest",
+        "gpt-4o-mini": "gpt-4o-mini-2024-07-18",
+        "gpt-3.5-turbo": "gpt-3.5-turbo-0125",
+        "gpt-3.5-turbo": "gpt-3.5-turbo-1106",
+        
+        # meta-llama
         "llama-3-70b": "llama-3-70b-chat",
         "llama-3-70b": "llama-3-70b-chat-turbo",
-        "llama-3-70b": "llama-3-70b-chat-lite",
         "llama-3-8b": "llama-3-8b-chat",
         "llama-3-8b": "llama-3-8b-chat-turbo",
+        "llama-3-70b": "llama-3-70b-chat-lite",
         "llama-3-8b": "llama-3-8b-chat-lite",
+        "llama-2-13b": "llama-2-13b-chat",
         "llama-3.1-405b": "llama-3.1-405b-turbo",
         "llama-3.1-70b": "llama-3.1-70b-turbo",
         "llama-3.1-8b": "llama-3.1-8b-turbo",
+        "llamaguard-2-8b": "LlamaGuard-2-8b",
+        "llamaguard-7b": "Llama-Guard-7b",
+        "llama-3.2-90b": "Llama-3.2-90B-Vision-Instruct-Turbo",
+        
+        # mistral-ai
         "mixtral-8x7b": "Mixtral-8x7B-Instruct-v0.1",
         "mixtral-8x22b": "Mixtral-8x22B-Instruct-v0.1",
         "mistral-7b": "Mistral-7B-Instruct-v0.1",
         "mistral-7b": "Mistral-7B-Instruct-v0.2",
         "mistral-7b": "Mistral-7B-Instruct-v0.3",
-        "mixtral-8x7b-dpo": "Nous-Hermes-2-Mixtral-8x7B-DPO",
+        
+        # qwen
+        "qwen-1.5-7b": "Qwen1.5-7B-Chat",
+        "qwen-1.5-14b": "Qwen1.5-14B-Chat",
         "qwen-1.5-72b": "Qwen1.5-72B-Chat",
         "qwen-1.5-110b": "Qwen1.5-110B-Chat",
         "qwen-2-72b": "Qwen2-72B-Instruct",
+        
+        # google
         "gemma-2b": "gemma-2b-it",
-        "gemma-2b-9b": "gemma-2-9b-it",
-        "gemma-2b-27b": "gemma-2-27b-it",
+        "gemma-2-9b": "gemma-2-9b-it",
+        "gemma-2-27b": "gemma-2-27b-it",
+        
+        # gemini
+        "gemini-flash": "gemini-1.5-flash",
+        "gemini-pro": "gemini-1.5-pro",
+        
+        # deepseek-ai
         "deepseek": "deepseek-llm-67b-chat",
+        
+        # NousResearch
+        "mixtral-8x7b-dpo": "Nous-Hermes-2-Mixtral-8x7B-DPO",
         "yi-34b": "Nous-Hermes-2-Yi-34B",
+        
+        # microsoft
         "wizardlm-2-8x22b": "WizardLM-2-8x22B",
-        "solar-10-7b": "SOLAR-10.7B-Instruct-v1.0",
-        "sh-n-7b": "StripedHyena-Nous-7B",
-        "sparkdesk-v1.1": "sparkdesk",
         
-        # Other models
-        "gpt-4o": "chatgpt-4o-latest",
-        "gpt-4o-mini": "gpt-4o-mini-2024-07-18",
-        "gpt-3.5-turbo": "gpt-3.5-turbo-0125",
-        "gpt-3.5-turbo": "gpt-3.5-turbo-1106",
-        "gpt-3.5-turbo": "gpt-3.5-turbo-16k",
-        "gpt-3.5-turbo": "gpt-3.5-turbo-0613",
-        "gpt-3.5-turbo": "gpt-3.5-turbo-16k-0613",
-        "gemini-flash": "gemini-1.5-flash",
-        "gemini-pro": "gemini-1.5-pro",
+        # upstage
+        "solar-10.7b": "SOLAR-10.7B-Instruct-v1.0",
         
-        # Image models
-        "dalle-3": "dall-e-3",
+        # Gryphe
+        "mythomax-l2-13b": "MythoMax-L2-13b",
     }
 
+    @classmethod
+    def get_model(cls, model: str) -> str:
+        if model in cls.models:
+            return model
+        elif model in cls.model_aliases:
+            return cls.model_aliases.get(model, cls.default_model)
+        else:
+            return cls.default_model
+
     @classmethod
     async def create_async_generator(
         cls,
         model: str,
         messages: Messages,
         proxy: str = None,
+        seed: int = None,
+        size: str = "1:1",
+        stream: bool = False,
         **kwargs
     ) -> AsyncResult:
         model = cls.get_model(model)
-        
+
+        # If the model is an image model, use the image API
+        if model in cls.image_models:
+            async for result in cls._generate_image(model, messages, proxy, seed, size):
+                yield result
+        # If the model is a text model, use the text API
+        elif model in cls.text_models:
+            async for result in cls._generate_text(model, messages, proxy, stream):
+                yield result
+    
+    @classmethod
+    async def _generate_image(
+        cls,
+        model: str,
+        messages: Messages,
+        proxy: str = None,
+        seed: int = None,
+        size: str = "1:1",
+        **kwargs
+    ) -> AsyncResult:
         headers = {
             "accept": "*/*",
             "accept-language": "en-US,en;q=0.9",
-            "content-type": "application/json",
-            "origin": "https://api.airforce",
-            "user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/128.0.0.0 Safari/537.36",
-            "authorization": "Bearer null",
             "cache-control": "no-cache",
-            "pragma": "no-cache",
-            "priority": "u=1, i",
-            "referer": "https://llmplayground.net/",
-            "sec-ch-ua": '"Not;A=Brand";v="24", "Chromium";v="128"',
-            "sec-ch-ua-mobile": "?0",
-            "sec-ch-ua-platform": '"Linux"',
-            "sec-fetch-dest": "empty",
-            "sec-fetch-mode": "cors",
-            "sec-fetch-site": "cross-site",
+            "origin": "https://llmplayground.net",
+            "user-agent": "Mozilla/5.0"
         }
 
-        if model in cls.image_models:
-            async for item in cls.generate_image(model, messages, headers, proxy, **kwargs):
-                yield item
-        else:
-            async for item in cls.generate_text(model, messages, headers, proxy, **kwargs):
-                yield item
+        if seed is None:
+            seed = random.randint(0, 100000)
 
-    @classmethod
-    async def generate_text(cls, model: str, messages: Messages, headers: dict, proxy: str, **kwargs) -> AsyncResult:
-        async with ClientSession() as session:
-            data = {
-                "messages": [{"role": "user", "content": message['content']} for message in messages],
+        # Assume the first message is the prompt for the image
+        prompt = messages[0]['content']
+
+        async with ClientSession(headers=headers) as session:
+            params = {
                 "model": model,
-                "max_tokens": kwargs.get('max_tokens', 4096),
-                "temperature": kwargs.get('temperature', 1),
-                "top_p": kwargs.get('top_p', 1),
-                "stream": True
+                "prompt": prompt,
+                "size": size,
+                "seed": seed
             }
+            async with session.get(f"{cls.image_api_endpoint}", params=params, proxy=proxy) as response:
+                response.raise_for_status()
+                content_type = response.headers.get('Content-Type', '').lower()
 
-            try:
-                async with session.post(cls.text_api_endpoint, json=data, headers=headers, proxy=proxy) as response:
-                    response.raise_for_status()
-                    async for line in response.content:
-                        if line:
-                            line = line.decode('utf-8').strip()
-                            if line.startswith("data: "):
-                                if line == "data: [DONE]":
-                                    break
-                                try:
-                                    data = json.loads(line[6:])
-                                    if 'choices' in data and len(data['choices']) > 0:
-                                        delta = data['choices'][0].get('delta', {})
-                                        if 'content' in delta:
-                                            content = delta['content']
-                                            if "One message exceeds the 1000chars per message limit" in content:
-                                                raise ResponseStatusError(
-                                                    "Message too long",
-                                                    400,
-                                                    "Please try a shorter message."
-                                                )
-                                            yield content
-                                except json.JSONDecodeError:
-                                    continue
-            except ResponseStatusError as e:
-                raise e
-            except Exception as e:
-                raise ResponseStatusError(str(e), 500, "An unexpected error occurred")
+                if 'application/json' in content_type:
+                    async for chunk in response.content.iter_chunked(1024):
+                        if chunk:
+                            yield chunk.decode('utf-8')
+                elif 'image' in content_type:
+                    image_data = b""
+                    async for chunk in response.content.iter_chunked(1024):
+                        if chunk:
+                            image_data += chunk
+                    image_url = f"{cls.image_api_endpoint}?model={model}&prompt={prompt}&size={size}&seed={seed}"
+                    alt_text = f"Generated image for prompt: {prompt}"
+                    yield ImageResponse(images=image_url, alt=alt_text)
 
     @classmethod
-    async def generate_image(cls, model: str, messages: Messages, headers: dict, proxy: str, **kwargs) -> AsyncResult:
-        prompt = messages[-1]['content'] if messages else ""
-        params = {
-            "prompt": prompt,
-            "size": kwargs.get("size", "1:1"),
-            "seed": kwargs.get("seed"),
-            "model": model
+    async def _generate_text(
+        cls,
+        model: str,
+        messages: Messages,
+        proxy: str = None,
+        stream: bool = False,
+        **kwargs
+    ) -> AsyncResult:
+        headers = {
+            "accept": "*/*",
+            "accept-language": "en-US,en;q=0.9",
+            "authorization": "Bearer missing api key",
+            "content-type": "application/json",
+            "user-agent": "Mozilla/5.0"
         }
-        params = {k: v for k, v in params.items() if v is not None}
 
-        try:
-            async with ClientSession(headers=headers) as session:
-                async with session.get(cls.image_api_endpoint, params=params, proxy=proxy) as response:
+        async with ClientSession(headers=headers) as session:
+            formatted_prompt = cls._format_messages(messages)
+            prompt_parts = split_long_message(formatted_prompt)
+            full_response = ""
+
+            for part in prompt_parts:
+                data = {
+                    "messages": [{"role": "user", "content": part}],
+                    "model": model,
+                    "max_tokens": 4096,
+                    "temperature": 1,
+                    "top_p": 1,
+                    "stream": stream
+                }
+                async with session.post(cls.text_api_endpoint, json=data, proxy=proxy) as response:
                     response.raise_for_status()
-                    content = await response.read()
-                    
-                    if response.content_type.startswith('image/'):
-                        image_url = str(response.url)
-                        yield ImageResponse(image_url, prompt)
+                    part_response = ""
+                    if stream:
+                        async for line in response.content:
+                            if line:
+                                line = line.decode('utf-8').strip()
+                                if line.startswith("data: ") and line != "data: [DONE]":
+                                    json_data = json.loads(line[6:])
+                                    content = json_data['choices'][0]['delta'].get('content', '')
+                                    part_response += content
                     else:
-                        try:
-                            text = content.decode('utf-8', errors='ignore')
-                            raise ResponseStatusError("Image generation failed", response.status, text)
-                        except Exception as decode_error:
-                            raise ResponseStatusError("Decoding error", 500, str(decode_error))
-        except ClientResponseError as e:
-            raise ResponseStatusError(f"HTTP {e.status}", e.status, e.message)
-        except Exception as e:
-            raise ResponseStatusError("Unexpected error", 500, str(e))
+                        json_data = await response.json()
+                        content = json_data['choices'][0]['message']['content']
+                        part_response = content
+
+                    full_response += part_response
+            yield full_response
+
+    @classmethod
+    def _format_messages(cls, messages: Messages) -> str:
+        """Formats messages for text generation."""
+        return " ".join([msg['content'] for msg in messages])

g4f/Provider/Allyfy.py

@@ -9,8 +9,8 @@ from .helper import format_prompt
 
 
 class Allyfy(AsyncGeneratorProvider):
-    url = "https://chatbot.allyfy.chat"
-    api_endpoint = "/api/v1/message/stream/super/chat"
+    url = "https://allyfy.chat"
+    api_endpoint = "https://chatbot.allyfy.chat/api/v1/message/stream/super/chat"
     working = True
     supports_gpt_35_turbo = True
 
@@ -53,7 +53,7 @@ class Allyfy(AsyncGeneratorProvider):
                     "packageName": "com.cch.allyfy.webh",
                 }
             }
-            async with session.post(f"{cls.url}{cls.api_endpoint}", json=data, proxy=proxy) as response:
+            async with session.post(f"{cls.api_endpoint}", json=data, proxy=proxy) as response:
                 response.raise_for_status()
                 full_response = []
                 async for line in response.content:

g4f/Provider/Bixin123.py

@@ -1,94 +0,0 @@
-from __future__ import annotations
-
-from aiohttp import ClientSession
-import json
-import random
-from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
-from ..typing import AsyncResult, Messages
-from .helper import format_prompt
-
-class Bixin123(AsyncGeneratorProvider, ProviderModelMixin):
-    url = "https://chat.bixin123.com"
-    api_endpoint = "https://chat.bixin123.com/api/chatgpt/chat-process"
-    working = True
-    supports_gpt_35_turbo = True
-    supports_gpt_4 = True
-
-    default_model = 'gpt-3.5-turbo-0125'
-    models = ['gpt-3.5-turbo', 'gpt-3.5-turbo-0125', 'gpt-3.5-turbo-16k-0613', 'gpt-4-turbo', 'qwen-turbo']
-    
-    model_aliases = {
-        "gpt-3.5-turbo": "gpt-3.5-turbo-0125",
-        "gpt-3.5-turbo": "gpt-3.5-turbo-16k-0613",
-    }
-
-    @classmethod
-    def get_model(cls, model: str) -> str:
-        if model in cls.models:
-            return model
-        elif model in cls.model_aliases:
-            return cls.model_aliases[model]
-        else:
-            return cls.default_model
-
-    @classmethod
-    def generate_fingerprint(cls) -> str:
-        return str(random.randint(100000000, 999999999))
-
-    @classmethod
-    async def create_async_generator(
-        cls,
-        model: str,
-        messages: Messages,
-        proxy: str = None,
-        **kwargs
-    ) -> AsyncResult:
-        model = cls.get_model(model)
-
-        headers = {
-            "accept": "application/json, text/plain, */*",
-            "accept-language": "en-US,en;q=0.9",
-            "cache-control": "no-cache",
-            "content-type": "application/json",
-            "fingerprint": cls.generate_fingerprint(),
-            "origin": cls.url,
-            "pragma": "no-cache",
-            "priority": "u=1, i",
-            "referer": f"{cls.url}/chat",
-            "sec-ch-ua": '"Chromium";v="127", "Not)A;Brand";v="99"',
-            "sec-ch-ua-mobile": "?0",
-            "sec-ch-ua-platform": '"Linux"',
-            "sec-fetch-dest": "empty",
-            "sec-fetch-mode": "cors",
-            "sec-fetch-site": "same-origin",
-            "user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/127.0.0.0 Safari/537.36",
-            "x-website-domain": "chat.bixin123.com",
-        }
-
-        async with ClientSession(headers=headers) as session:
-            prompt = format_prompt(messages)
-            data = {
-                "prompt": prompt,
-                "options": {
-                    "usingNetwork": False,
-                    "file": ""
-                }
-            }
-            async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response:
-                response.raise_for_status()
-                response_text = await response.text()
-                
-                lines = response_text.strip().split("\n")
-                last_json = None
-                for line in reversed(lines):
-                    try:
-                        last_json = json.loads(line)
-                        break
-                    except json.JSONDecodeError:
-                        pass
-                
-                if last_json:
-                    text = last_json.get("text", "")
-                    yield text
-                else:
-                    yield ""

g4f/Provider/Blackbox.py

@@ -25,18 +25,10 @@ class Blackbox(AsyncGeneratorProvider, ProviderModelMixin):
         'llama-3.1-70b',
         'llama-3.1-405b',
         'ImageGenerationLV45LJp',
-        'GPT-4o',
-        'Gemini-PRO',
-        'Claude-Sonnet-3.5',
+        'gpt-4o',
+        'gemini-pro',
+        'claude-sonnet-3.5',
     ]
-    
-    model_aliases = {
-        "gemini-flash": "gemini-1.5-flash",
-        "flux": "ImageGenerationLV45LJp",
-        "gpt-4o": "GPT-4o",
-        "gemini-pro": "Gemini-PRO",
-        "claude-3.5-sonnet": "Claude-Sonnet-3.5",
-    }
 
     agentMode = {
         'ImageGenerationLV45LJp': {'mode': True, 'id': "ImageGenerationLV45LJp", 'name': "Image Generation"},
@@ -51,9 +43,14 @@ class Blackbox(AsyncGeneratorProvider, ProviderModelMixin):
     }
     
     userSelectedModel = {
-        "GPT-4o": "GPT-4o",
-        "Gemini-PRO": "Gemini-PRO",
-        'Claude-Sonnet-3.5': "Claude-Sonnet-3.5",
+        "gpt-4o": "gpt-4o",
+        "gemini-pro": "gemini-pro",
+        'claude-sonnet-3.5': "claude-sonnet-3.5",
+    }
+    
+    model_aliases = {
+        "gemini-flash": "gemini-1.5-flash",
+        "flux": "ImageGenerationLV45LJp",
     }
 
     @classmethod
@@ -119,8 +116,9 @@ class Blackbox(AsyncGeneratorProvider, ProviderModelMixin):
                 "agentMode": {},
                 "trendingAgentMode": {},
                 "userSelectedModel": None,
+                "userSystemPrompt": None,
                 "isMicMode": False,
-                "maxTokens": 99999999,
+                "maxTokens": 1024,
                 "playgroundTopP": 0.9,
                 "playgroundTemperature": 0.5,
                 "isChromeExt": False,

g4f/Provider/ChatGpt.py

@@ -134,11 +134,21 @@ class ChatGpt(AbstractProvider, ProviderModelMixin):
         }
         
         response = session.post('https://chatgpt.com/backend-anon/sentinel/chat-requirements',
-            headers=headers, json={'p': pow_req}).json()
+            headers=headers, json={'p': pow_req})
 
-        turnstile          = response.get('turnstile', {})
+        if response.status_code != 200:
+            print(f"Request failed with status: {response.status_code}")
+            print(f"Response content: {response.content}")
+            return
+
+        response_data = response.json()
+        if "detail" in response_data and "Unusual activity" in response_data["detail"]:
+            print(f"Blocked due to unusual activity: {response_data['detail']}")
+            return
+        
+        turnstile          = response_data.get('turnstile', {})
         turnstile_required = turnstile.get('required')
-        pow_conf           = response.get('proofofwork', {})
+        pow_conf           = response_data.get('proofofwork', {})
 
         if turnstile_required:
             turnstile_dx    = turnstile.get('dx')
@@ -146,7 +156,7 @@ class ChatGpt(AbstractProvider, ProviderModelMixin):
         
         headers = headers | {
             'openai-sentinel-turnstile-token'        : turnstile_token,
-            'openai-sentinel-chat-requirements-token': response.get('token'),
+            'openai-sentinel-chat-requirements-token': response_data.get('token'),
             'openai-sentinel-proof-token'            : get_answer_token(
                 pow_conf.get('seed'), pow_conf.get('difficulty'), config
             )
@@ -187,20 +197,29 @@ class ChatGpt(AbstractProvider, ProviderModelMixin):
                 'screen_width': random.randint(1200, 2000),
             },
         }
+
+        time.sleep(2)
         
         response = session.post('https://chatgpt.com/backend-anon/conversation',
             headers=headers, json=json_data, stream=True)
-        
+
         replace = ''
         for line in response.iter_lines():
             if line:
-                if 'DONE' in line.decode():
-                    break
-                
-                data = json.loads(line.decode()[6:])
-                if data.get('message').get('author').get('role') == 'assistant':
-                    tokens = (data.get('message').get('content').get('parts')[0])
-                    
-                    yield tokens.replace(replace, '')
-                    
-                    replace = tokens
+                decoded_line = line.decode()
+                print(f"Received line: {decoded_line}")
+                if decoded_line.startswith('data:'):
+                    json_string = decoded_line[6:]
+                    if json_string.strip():
+                        try:
+                            data = json.loads(json_string)
+                        except json.JSONDecodeError as e:
+                            print(f"Error decoding JSON: {e}, content: {json_string}")
+                            continue
+                        
+                        if data.get('message').get('author').get('role') == 'assistant':
+                            tokens = (data.get('message').get('content').get('parts')[0])
+                            
+                            yield tokens.replace(replace, '')
+                            
+                            replace = tokens

g4f/Provider/HuggingChat.py

@@ -17,6 +17,7 @@ class HuggingChat(AbstractProvider, ProviderModelMixin):
         'meta-llama/Meta-Llama-3.1-70B-Instruct',
         'CohereForAI/c4ai-command-r-plus-08-2024',
         'Qwen/Qwen2.5-72B-Instruct',
+        'meta-llama/Llama-3.2-11B-Vision-Instruct',
         'NousResearch/Hermes-3-Llama-3.1-8B',
         'mistralai/Mistral-Nemo-Instruct-2407',
         'microsoft/Phi-3.5-mini-instruct',
@@ -26,6 +27,7 @@ class HuggingChat(AbstractProvider, ProviderModelMixin):
         "llama-3.1-70b": "meta-llama/Meta-Llama-3.1-70B-Instruct",
         "command-r-plus": "CohereForAI/c4ai-command-r-plus-08-2024",
         "qwen-2-72b": "Qwen/Qwen2.5-72B-Instruct",
+        "llama-3.2-11b": "meta-llama/Llama-3.2-11B-Vision-Instruct",
         "hermes-3": "NousResearch/Hermes-3-Llama-3.1-8B",
         "mistral-nemo": "mistralai/Mistral-Nemo-Instruct-2407",
         "phi-3.5-mini": "microsoft/Phi-3.5-mini-instruct",

g4f/Provider/Liaobots.py

@@ -9,6 +9,15 @@ from .helper import get_connector
 from ..requests import raise_for_status
 
 models = {
+    "gpt-3.5-turbo": {
+        "id": "gpt-3.5-turbo",
+        "name": "GPT-3.5-Turbo",
+        "model": "ChatGPT",
+        "provider": "OpenAI",
+        "maxLength": 48000,
+        "tokenLimit": 14000,
+        "context": "16K",
+    },
     "gpt-4o-mini-free": {
         "id": "gpt-4o-mini-free",
         "name": "GPT-4o-Mini-Free",

g4f/Provider/LiteIcoding.py

@@ -1,12 +1,11 @@
 from __future__ import annotations
-
-from aiohttp import ClientSession, ClientResponseError
+import base64
 import re
+from aiohttp import ClientSession, ClientResponseError
 from ..typing import AsyncResult, Messages
 from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
 from .helper import format_prompt
 
-
 class LiteIcoding(AsyncGeneratorProvider, ProviderModelMixin):
     url = "https://lite.icoding.ink"
     api_endpoint = "/api/v1/gpt/message"
@@ -27,18 +26,20 @@ class LiteIcoding(AsyncGeneratorProvider, ProviderModelMixin):
     }
 
     bearer_tokens = [
-        "aa3020ee873e40cb8b3f515a0708ebc4",
-        "5d69cd271b144226ac1199b3c849a566",
-        "62977f48a95844f8853a953679401850",
-        "d815b091959e42dd8b7871dfaf879485"
+        "NWQ2OWNkMjcxYjE0NDIyNmFjMTE5OWIzYzg0OWE1NjY=",
+        "ZDgxNWIwOTU5NTk0ZTRkZDhiNzg3MWRmYWY4Nzk0ODU=" 
     ]
     current_token_index = 0
 
+    @classmethod
+    def decode_token(cls, encoded_token: str) -> str:
+        return base64.b64decode(encoded_token).decode('utf-8')
+
     @classmethod
     def get_next_bearer_token(cls):
-        token = cls.bearer_tokens[cls.current_token_index]
+        encoded_token = cls.bearer_tokens[cls.current_token_index]
         cls.current_token_index = (cls.current_token_index + 1) % len(cls.bearer_tokens)
-        return token
+        return cls.decode_token(encoded_token)
 
     @classmethod
     async def create_async_generator(
@@ -95,9 +96,11 @@ class LiteIcoding(AsyncGeneratorProvider, ProviderModelMixin):
                     response.raise_for_status()
                     buffer = ""
                     full_response = ""
+
                     def decode_content(data):
                         bytes_array = bytes([int(b, 16) ^ 255 for b in data.split()])
                         return bytes_array.decode('utf-8')
+
                     async for chunk in response.content.iter_any():
                         if chunk:
                             buffer += chunk.decode()

g4f/Provider/MagickPen.py

@@ -24,21 +24,18 @@ class MagickPen(AsyncGeneratorProvider, ProviderModelMixin):
 
     @classmethod
     async def fetch_api_credentials(cls) -> tuple:
-        url = "https://magickpen.com/_nuxt/9e47cd7579e60a9d1f13.js"
+        url = "https://magickpen.com/_nuxt/bf709a9ce19f14e18116.js"
         async with ClientSession() as session:
             async with session.get(url) as response:
                 text = await response.text()
 
-        # Extract the necessary values from the file
         pattern = r'"X-API-Secret":"(\w+)"'
         match = re.search(pattern, text)
         X_API_SECRET = match.group(1) if match else None
 
-        # Generate timestamp and nonce
-        timestamp = str(int(time.time() * 1000))  # in milliseconds
+        timestamp = str(int(time.time() * 1000))
         nonce = str(random.random())
 
-        # Generate the signature
         s = ["TGDBU9zCgM", timestamp, nonce]
         s.sort()
         signature_string = ''.join(s)

g4f/Provider/__init__.py

@@ -19,7 +19,6 @@ from .Aura             import Aura
 from .Bing             import Bing
 from .BingCreateImages import BingCreateImages
 from .Binjie           import Binjie
-from .Bixin123         import Bixin123
 from .Blackbox         import Blackbox
 from .ChatGot          import ChatGot
 from .ChatGpt          import ChatGpt

g4f/client/async_client.py

@@ -33,6 +33,12 @@ except NameError:
         except StopAsyncIteration:
             raise StopIteration
 
+async def safe_aclose(generator):
+    try:
+        await generator.aclose()
+    except Exception as e:
+        logging.warning(f"Error while closing generator: {e}")
+
 async def iter_response(
     response: AsyncIterator[str],
     stream: bool,
@@ -45,48 +51,56 @@ async def iter_response(
     completion_id = ''.join(random.choices(string.ascii_letters + string.digits, k=28))
     idx = 0
 
-    async for chunk in response:
-        if isinstance(chunk, FinishReason):
-            finish_reason = chunk.reason
-            break
-        elif isinstance(chunk, BaseConversation):
-            yield chunk
-            continue
+    try:
+        async for chunk in response:
+            if isinstance(chunk, FinishReason):
+                finish_reason = chunk.reason
+                break
+            elif isinstance(chunk, BaseConversation):
+                yield chunk
+                continue
 
-        content += str(chunk)
-        idx += 1
+            content += str(chunk)
+            idx += 1
 
-        if max_tokens is not None and idx >= max_tokens:
-            finish_reason = "length"
+            if max_tokens is not None and idx >= max_tokens:
+                finish_reason = "length"
 
-        first, content, chunk = find_stop(stop, content, chunk if stream else None)
+            first, content, chunk = find_stop(stop, content, chunk if stream else None)
 
-        if first != -1:
-            finish_reason = "stop"
+            if first != -1:
+                finish_reason = "stop"
 
-        if stream:
-            yield ChatCompletionChunk(chunk, None, completion_id, int(time.time()))
+            if stream:
+                yield ChatCompletionChunk(chunk, None, completion_id, int(time.time()))
 
-        if finish_reason is not None:
-            break
+            if finish_reason is not None:
+                break
 
-    finish_reason = "stop" if finish_reason is None else finish_reason
+        finish_reason = "stop" if finish_reason is None else finish_reason
 
-    if stream:
-        yield ChatCompletionChunk(None, finish_reason, completion_id, int(time.time()))
-    else:
-        if response_format is not None and "type" in response_format:
-            if response_format["type"] == "json_object":
-                content = filter_json(content)
-        yield ChatCompletion(content, finish_reason, completion_id, int(time.time()))
+        if stream:
+            yield ChatCompletionChunk(None, finish_reason, completion_id, int(time.time()))
+        else:
+            if response_format is not None and "type" in response_format:
+                if response_format["type"] == "json_object":
+                    content = filter_json(content)
+            yield ChatCompletion(content, finish_reason, completion_id, int(time.time()))
+    finally:
+        if hasattr(response, 'aclose'):
+            await safe_aclose(response)
 
 async def iter_append_model_and_provider(response: AsyncIterator) -> AsyncIterator:
     last_provider = None
-    async for chunk in response:
-        last_provider = get_last_provider(True) if last_provider is None else last_provider
-        chunk.model = last_provider.get("model")
-        chunk.provider = last_provider.get("name")
-        yield chunk
+    try:
+        async for chunk in response:
+            last_provider = get_last_provider(True) if last_provider is None else last_provider
+            chunk.model = last_provider.get("model")
+            chunk.provider = last_provider.get("name")
+            yield chunk
+    finally:
+        if hasattr(response, 'aclose'):
+            await safe_aclose(response)
 
 class AsyncClient(BaseClient):
     def __init__(
@@ -158,8 +172,6 @@ class Completions:
             response = iter_append_model_and_provider(response)
             return response if stream else await anext(response)
 
-
-
 class Chat:
     completions: Completions
 
@@ -168,14 +180,18 @@ class Chat:
 
 async def iter_image_response(response: AsyncIterator) -> Union[ImagesResponse, None]:
     logging.info("Starting iter_image_response")
-    async for chunk in response:
-        logging.info(f"Processing chunk: {chunk}")
-        if isinstance(chunk, ImageProviderResponse):
-            logging.info("Found ImageProviderResponse")
-            return ImagesResponse([Image(image) for image in chunk.get_list()])
-    
-    logging.warning("No ImageProviderResponse found in the response")
-    return None
+    try:
+        async for chunk in response:
+            logging.info(f"Processing chunk: {chunk}")
+            if isinstance(chunk, ImageProviderResponse):
+                logging.info("Found ImageProviderResponse")
+                return ImagesResponse([Image(image) for image in chunk.get_list()])
+        
+        logging.warning("No ImageProviderResponse found in the response")
+        return None
+    finally:
+        if hasattr(response, 'aclose'):
+            await safe_aclose(response)
 
 async def create_image(client: AsyncClient, provider: ProviderType, prompt: str, model: str = "", **kwargs) -> AsyncIterator:
     logging.info(f"Creating image with provider: {provider}, model: {model}, prompt: {prompt}")
@@ -220,12 +236,25 @@ class Images:
         if isinstance(provider, type) and issubclass(provider, AsyncGeneratorProvider):
             logging.info("Using AsyncGeneratorProvider")
             messages = [{"role": "user", "content": prompt}]
-            async for response in provider.create_async_generator(model, messages, **kwargs):
-                if isinstance(response, ImageResponse):
-                    return self._process_image_response(response)
-                elif isinstance(response, str):
-                    image_response = ImageResponse([response], prompt)
-                    return self._process_image_response(image_response)
+            generator = None
+            try:
+                generator = provider.create_async_generator(model, messages, **kwargs)
+                async for response in generator:
+                    logging.debug(f"Received response: {type(response)}")
+                    if isinstance(response, ImageResponse):
+                        return self._process_image_response(response)
+                    elif isinstance(response, str):
+                        image_response = ImageResponse([response], prompt)
+                        return self._process_image_response(image_response)
+            except RuntimeError as e:
+                if "async generator ignored GeneratorExit" in str(e):
+                    logging.warning("Generator ignored GeneratorExit, handling gracefully")
+                else:
+                    raise
+            finally:
+                if generator and hasattr(generator, 'aclose'):
+                    await safe_aclose(generator)
+                logging.info("AsyncGeneratorProvider processing completed")
         elif hasattr(provider, 'create'):
             logging.info("Using provider's create method")
             async_create = asyncio.iscoroutinefunction(provider.create)
@@ -241,7 +270,7 @@ class Images:
                 return self._process_image_response(image_response)
         elif hasattr(provider, 'create_completion'):
             logging.info("Using provider's create_completion method")
-            response = await create_image(provider, prompt, model, **kwargs)
+            response = await create_image(self.client, provider, prompt, model, **kwargs)
             async for chunk in response:
                 if isinstance(chunk, ImageProviderResponse):
                     logging.info("Found ImageProviderResponse")
@@ -277,12 +306,24 @@ class Images:
         if isinstance(provider, type) and issubclass(provider, AsyncGeneratorProvider):
             messages = [{"role": "user", "content": "create a variation of this image"}]
             image_data = to_data_uri(image)
-            async for response in provider.create_async_generator(model, messages, image=image_data, **kwargs):
-                if isinstance(response, ImageResponse):
-                    return self._process_image_response(response)
-                elif isinstance(response, str):
-                    image_response = ImageResponse([response], "Image variation")
-                    return self._process_image_response(image_response)
+            generator = None
+            try:
+                generator = provider.create_async_generator(model, messages, image=image_data, **kwargs)
+                async for response in generator:
+                    if isinstance(response, ImageResponse):
+                        return self._process_image_response(response)
+                    elif isinstance(response, str):
+                        image_response = ImageResponse([response], "Image variation")
+                        return self._process_image_response(image_response)
+            except RuntimeError as e:
+                if "async generator ignored GeneratorExit" in str(e):
+                    logging.warning("Generator ignored GeneratorExit in create_variation, handling gracefully")
+                else:
+                    raise
+            finally:
+                if generator and hasattr(generator, 'aclose'):
+                    await safe_aclose(generator)
+                logging.info("AsyncGeneratorProvider processing completed in create_variation")
         elif hasattr(provider, 'create_variation'):
             if asyncio.iscoroutinefunction(provider.create_variation):
                 response = await provider.create_variation(image, **kwargs)
@@ -296,5 +337,3 @@ class Images:
                 return self._process_image_response(image_response)
         else:
             raise ValueError(f"Provider {provider} does not support image variation")
-
-        raise NoImageResponseError("Failed to create image variation")

g4f/models.py

@@ -9,10 +9,8 @@ from .Provider import (
     Allyfy,
     Bing,
     Binjie,
-    Bixin123,
     Blackbox,
     ChatGpt,
-    Chatgpt4o,
     Chatgpt4Online,
     ChatGptEs,
     ChatgptFree,
@@ -80,12 +78,16 @@ default = Model(
         ReplicateHome,
         Upstage,
         Blackbox,
-        Bixin123,
         Binjie,
         Free2GPT,
         MagickPen,
         DeepInfraChat,
         LiteIcoding,
+        Airforce, 
+        ChatHub,
+        Nexra,
+        ChatGptEs,
+        ChatHub,
     ])
 )
 
@@ -106,7 +108,7 @@ gpt_35_turbo = Model(
     name          = 'gpt-3.5-turbo',
     base_provider = 'OpenAI',
     best_provider = IterListProvider([
-        Allyfy, Nexra, Bixin123, Airforce,
+        Allyfy, Nexra, Airforce, Liaobots,
     ])
 )
 
@@ -115,7 +117,7 @@ gpt_4o = Model(
     name          = 'gpt-4o',
     base_provider = 'OpenAI',
     best_provider = IterListProvider([
-        Liaobots, Nexra, Airforce, Chatgpt4o, ChatGptEs,
+        Liaobots, Nexra, ChatGptEs, Airforce, 
         OpenaiChat
     ])
 )
@@ -133,7 +135,7 @@ gpt_4_turbo = Model(
     name          = 'gpt-4-turbo',
     base_provider = 'OpenAI',
     best_provider = IterListProvider([
-        Nexra, Bixin123, Liaobots, Airforce, Bing
+        Nexra, Liaobots, Airforce, Bing
     ])
 )
 
@@ -141,9 +143,8 @@ gpt_4 = Model(
     name          = 'gpt-4',
     base_provider = 'OpenAI',
     best_provider = IterListProvider([
-        Nexra, Binjie, Airforce,
-        gpt_4_turbo.best_provider, gpt_4o.best_provider, gpt_4o_mini.best_provider,
-        Chatgpt4Online, Bing, OpenaiChat,
+        Nexra, Binjie, Airforce, Chatgpt4Online, Bing, OpenaiChat,
+        gpt_4_turbo.best_provider, gpt_4o.best_provider, gpt_4o_mini.best_provider
     ])
 )
 
@@ -205,7 +206,7 @@ llama_3_1_70b = Model(
 llama_3_1_405b = Model(
     name          = "llama-3.1-405b",
     base_provider = "Meta Llama",
-    best_provider = IterListProvider([Blackbox, DeepInfraChat, Airforce])
+    best_provider = IterListProvider([DeepInfraChat, Blackbox, Airforce])
 )
 
 llama_3_1 = Model(
@@ -214,12 +215,38 @@ llama_3_1 = Model(
     best_provider = IterListProvider([Nexra, llama_3_1_8b.best_provider, llama_3_1_70b.best_provider, llama_3_1_405b.best_provider,])
 )
 
+# llama 3.2
+llama_3_2_11b = Model(
+    name          = "llama-3.2-11b",
+    base_provider = "Meta Llama",
+    best_provider = IterListProvider([HuggingChat, HuggingFace])
+)
+
+llama_3_2_90b = Model(
+    name          = "llama-3.2-90b",
+    base_provider = "Meta Llama",
+    best_provider = IterListProvider([Airforce])
+)
+
+# llamaguard
+llamaguard_7b = Model(
+    name          = "llamaguard-7b",
+    base_provider = "Meta Llama",
+    best_provider = IterListProvider([Airforce])
+)
+
+llamaguard_2_8b = Model(
+    name          = "llamaguard-2-8b",
+    base_provider = "Meta Llama",
+    best_provider = IterListProvider([Airforce])
+)
+
 
 ### Mistral ###
 mistral_7b = Model(
     name          = "mistral-7b",
     base_provider = "Mistral",
-    best_provider = IterListProvider([HuggingChat, DeepInfraChat, Airforce, HuggingFace, DeepInfra])
+    best_provider = IterListProvider([DeepInfraChat, Airforce, HuggingFace, DeepInfra])
 )
 
 mixtral_8x7b = Model(
@@ -245,7 +272,13 @@ mistral_nemo = Model(
 mixtral_8x7b_dpo = Model(
     name          = "mixtral-8x7b-dpo",
     base_provider = "NousResearch",
-    best_provider = Airforce
+    best_provider = IterListProvider([Airforce])
+)
+
+yi_34b = Model(
+    name          = "yi-34b",
+    base_provider = "NousResearch",
+    best_provider = IterListProvider([Airforce])
 )
 
 hermes_3 = Model(
@@ -310,49 +343,56 @@ gemma_2b = Model(
    ])
 )
 
+# gemma 2
+gemma_2_27b = Model(
+    name          = 'gemma-2-27b',
+    base_provider = 'Google',
+    best_provider = Airforce
+)
+
 gemma_2 = Model(
     name          = 'gemma-2',
     base_provider = 'Google',
-    best_provider = ChatHub
+    best_provider = IterListProvider([
+        ChatHub,
+        gemma_2_27b.best_provider,
+   ])
 )
 
 
 ### Anthropic ###
-claude_2 = Model(
-    name          = 'claude-2',
-    base_provider = 'Anthropic',
-    best_provider = You
-)
-
-claude_2_0 = Model(
-    name          = 'claude-2.0',
+claude_2_1 = Model(
+    name          = 'claude-2.1',
     base_provider = 'Anthropic',
     best_provider = Liaobots
 )
 
-claude_2_1 = Model(
-    name          = 'claude-2.1',
+claude_2 = Model(
+    name          = 'claude-2',
     base_provider = 'Anthropic',
-    best_provider = Liaobots
+    best_provider = IterListProvider([
+        You,
+        claude_2_1.best_provider,
+   ])
 )
 
 # claude 3
 claude_3_opus = Model(
     name          = 'claude-3-opus',
     base_provider = 'Anthropic',
-    best_provider = Liaobots
+    best_provider = IterListProvider([Airforce, Liaobots])
 )
 
 claude_3_sonnet = Model(
     name          = 'claude-3-sonnet',
     base_provider = 'Anthropic',
-    best_provider = Liaobots
+    best_provider = IterListProvider([Airforce, Liaobots])
 )
 
 claude_3_haiku = Model(
     name          = 'claude-3-haiku',
     base_provider = 'Anthropic',
-    best_provider = IterListProvider([DDG, Liaobots])
+    best_provider = IterListProvider([DDG, Airforce, Liaobots])
 )
 
 claude_3 = Model(
@@ -367,7 +407,7 @@ claude_3 = Model(
 claude_3_5_sonnet = Model(
     name          = 'claude-3.5-sonnet',
     base_provider = 'Anthropic',
-    best_provider = IterListProvider([Blackbox, Liaobots])
+    best_provider = IterListProvider([Blackbox, Airforce, Liaobots])
 )
 
 claude_3_5 = Model(
@@ -417,15 +457,22 @@ command_r_plus = Model(
 sparkdesk_v1_1 = Model(
     name = 'sparkdesk-v1.1',
     base_provider = 'iFlytek',
-    best_provider = IterListProvider([FreeChatgpt, Airforce])
+    best_provider = IterListProvider([FreeChatgpt])
 )
 
 
 ### Qwen ###
+# qwen 1
+qwen_1_5_7b = Model(
+    name = 'qwen-1.5-7b',
+    base_provider = 'Qwen',
+    best_provider = Airforce
+)
+
 qwen_1_5_14b = Model(
     name = 'qwen-1.5-14b',
     base_provider = 'Qwen',
-    best_provider = FreeChatgpt
+    best_provider = IterListProvider([FreeChatgpt, Airforce])
 )
 
 qwen_1_5_72b = Model(
@@ -440,22 +487,17 @@ qwen_1_5_110b = Model(
     best_provider = Airforce
 )
 
+# qwen 2
 qwen_2_72b = Model(
     name = 'qwen-2-72b',
     base_provider = 'Qwen',
     best_provider = IterListProvider([DeepInfraChat, HuggingChat, Airforce, HuggingFace])
 )
 
-qwen_turbo = Model(
-    name = 'qwen-turbo',
-    base_provider = 'Qwen',
-    best_provider = Bixin123
-)
-
 qwen = Model(
     name = 'qwen',
     base_provider = 'Qwen',
-    best_provider = IterListProvider([Nexra, qwen_1_5_14b.best_provider, qwen_1_5_72b.best_provider, qwen_1_5_110b.best_provider, qwen_2_72b.best_provider, qwen_turbo.best_provider])
+    best_provider = IterListProvider([Nexra, qwen_1_5_14b.best_provider, qwen_1_5_72b.best_provider, qwen_1_5_110b.best_provider, qwen_2_72b.best_provider])
 )
 
 
@@ -488,13 +530,6 @@ yi_1_5_9b = Model(
     best_provider = FreeChatgpt
 )
 
-yi_34b = Model(
-    name = 'yi-34b',
-    base_provider = '01-ai',
-    best_provider = Airforce
-)
-
-
 ### Upstage ###
 solar_1_mini = Model(
     name = 'solar-1-mini',
@@ -542,14 +577,6 @@ wizardlm_2_8x22b = Model(
     best_provider = IterListProvider([DeepInfraChat, Airforce])
 )
 
-### Together ###
-sh_n_7b = Model(
-    name = 'sh-n-7b',
-    base_provider = 'Together',
-    best_provider = Airforce
-)
-
-
 ### Yorickvp ###
 llava_13b = Model(
     name = 'llava-13b',
@@ -611,7 +638,8 @@ grok_2_mini = Model(
     best_provider = Liaobots
 )
 
-# Perplexity AI
+
+### Perplexity AI ### 
 sonar_online = Model(
     name = 'sonar-online',
     base_provider = 'Perplexity AI',
@@ -625,6 +653,22 @@ sonar_chat = Model(
 )
 
 
+### Gryphe ### 
+mythomax_l2_13b = Model(
+    name = 'mythomax-l2-13b',
+    base_provider = 'Gryphe',
+    best_provider = IterListProvider([Airforce])
+)
+
+
+### Pawan ### 
+cosmosrp = Model(
+    name = 'cosmosrp',
+    base_provider = 'Pawan',
+    best_provider = IterListProvider([Airforce])
+)
+
+
 
 #############
 ### Image ###
@@ -654,6 +698,7 @@ playground_v2_5 = Model(
     
 )
 
+
 ### Flux AI ###
 flux = Model(
     name = 'flux',
@@ -805,6 +850,14 @@ class ModelUtils:
 'llama-3.1-8b': llama_3_1_8b,
 'llama-3.1-70b': llama_3_1_70b,
 'llama-3.1-405b': llama_3_1_405b,
+
+# llama-3.2
+'llama-3.2-11b': llama_3_2_11b,
+'llama-3.2-90b': llama_3_2_90b,
+
+# llamaguard
+'llamaguard-7b': llamaguard_7b,
+'llamaguard-2-8b': llamaguard_2_8b,
       
         
 ### Mistral ###
@@ -835,12 +888,14 @@ class ModelUtils:
 'gemma-2b': gemma_2b,
 'gemma-2b-9b': gemma_2b_9b,
 'gemma-2b-27b': gemma_2b_27b,
+
+# gemma-2
 'gemma-2': gemma_2,
+'gemma-2-27b': gemma_2_27b,
 
 
 ### Anthropic ###
 'claude-2': claude_2,
-'claude-2.0': claude_2_0,
 'claude-2.1': claude_2_1,
 
 # claude 3
@@ -880,11 +935,11 @@ class ModelUtils:
         
 ### Qwen ###
 'qwen': qwen,
+'qwen-1.5-7b': qwen_1_5_7b,
 'qwen-1.5-14b': qwen_1_5_14b,
 'qwen-1.5-72b': qwen_1_5_72b,
 'qwen-1.5-110b': qwen_1_5_110b,
 'qwen-2-72b': qwen_2_72b,
-'qwen-turbo': qwen_turbo,
         
         
 ### Zhipu AI ###
@@ -908,11 +963,7 @@ class ModelUtils:
 
 ### DeepSeek ###
 'deepseek': deepseek,
-
-
-### Together ###
-'sh-n-7b': sh_n_7b,
-      
+     
         
 ### Yorickvp ###
 'llava-13b': llava_13b,
@@ -947,9 +998,18 @@ class ModelUtils:
 'grok-2': grok_2,
 'grok-2-mini': grok_2_mini,
         
+        
 ### Perplexity AI ###
 'sonar-online': sonar_online,
 'sonar-chat': sonar_chat,
+
+
+### Gryphe ###   
+'mythomax-l2-13b': sonar_chat,
+
+   
+### Pawan ###   
+'cosmosrp': cosmosrp,