1 files changed, 32 insertions, 218 deletions

diff --git a/g4f/Provider/Airforce.py b/g4f/Provider/Airforce.py
index 015766f4..b7819f9a 100644
--- a/g4f/Provider/Airforce.py
+++ b/g4f/Provider/Airforce.py
@@ -1,105 +1,30 @@
 from __future__ import annotations
-import random
-import json
-import re
+from typing import Any, Dict
+import inspect
+
 from aiohttp import ClientSession
+
 from ..typing import AsyncResult, Messages
 from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
-from ..image import ImageResponse
-
-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)]
+from .helper import format_prompt
+from .airforce.AirforceChat import AirforceChat
+from .airforce.AirforceImage import AirforceImage
 
 class Airforce(AsyncGeneratorProvider, ProviderModelMixin):
     url = "https://api.airforce"
-    image_api_endpoint = "https://api.airforce/imagine2"
-    text_api_endpoint = "https://api.airforce/chat/completions"
+    api_endpoint_completions = AirforceChat.api_endpoint_completions
+    api_endpoint_imagine2 = AirforceImage.api_endpoint_imagine2
     working = True
+    supports_stream = AirforceChat.supports_stream
+    supports_system_message = AirforceChat.supports_system_message
+    supports_message_history = AirforceChat.supports_message_history 
     
-    default_model = 'llama-3-70b-chat'
-
-    supports_stream = True
-    supports_system_message = True
-    supports_message_history = True
-    
-    text_models = [
-        'claude-3-haiku-20240307', 
-        'claude-3-sonnet-20240229', 
-        'claude-3-5-sonnet-20240620', 
-        'claude-3-opus-20240229', 
-        'chatgpt-4o-latest', 
-        'gpt-4', 
-        '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', 
-        default_model,
-        '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-2-13b-chat', 
-        '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',
-        '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', 
-        'Qwen1.5-7B-Chat', 
-        'Qwen1.5-14B-Chat', 
-        'Qwen1.5-72B-Chat', 
-        'Qwen1.5-110B-Chat', 
-        'Qwen2-72B-Instruct', 
-        'gemma-2b-it', 
-        'gemma-2-9b-it', 
-        'gemma-2-27b-it', 
-        'gemini-1.5-flash', 
-        'gemini-1.5-pro', 
-        'deepseek-llm-67b-chat', 
-        'Nous-Hermes-2-Mixtral-8x7B-DPO', 
-        'Nous-Hermes-2-Yi-34B', 
-        'WizardLM-2-8x22B', 
-        'SOLAR-10.7B-Instruct-v1.0', 
-        'MythoMax-L2-13b', 
-        'cosmosrp', 
-    ]
-    
-    image_models = [
-        'flux',
-        'flux-realism',
-        'flux-anime',
-        'flux-3d',
-        'flux-disney',
-        'flux-pixel',
-        'flux-4o',
-        'any-dark',
-    ]
-    
-    models = [
-        *text_models,
-        *image_models,
-    ]
+    default_model = AirforceChat.default_model
+    models = [*AirforceChat.text_models, *AirforceImage.image_models]
     
     model_aliases = {
-        "claude-3-haiku": "claude-3-haiku-20240307",
-        "claude-3-sonnet": "claude-3-sonnet-20240229",
-        "gpt-4o": "chatgpt-4o-latest",
-        "llama-3-70b": "llama-3-70b-chat",
-        "llama-3-8b": "llama-3-8b-chat",
-        "mixtral-8x7b": "Mixtral-8x7B-Instruct-v0.1",
-        "qwen-1.5-7b": "Qwen1.5-7B-Chat",
-        "gemma-2b": "gemma-2b-it",
-        "gemini-flash": "gemini-1.5-flash",
-        "mythomax-l2-13b": "MythoMax-L2-13b",
-        "solar-10.7b": "SOLAR-10.7B-Instruct-v1.0",
+        **AirforceChat.model_aliases,
+        **AirforceImage.model_aliases
     }
 
     @classmethod
@@ -107,139 +32,28 @@ class Airforce(AsyncGeneratorProvider, ProviderModelMixin):
         if model in cls.models:
             return model
         elif model in cls.model_aliases:
-            return cls.model_aliases.get(model, cls.default_model)
+            return cls.model_aliases[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:
+    async def create_async_generator(cls, model: str, messages: Messages, **kwargs) -> AsyncResult:
         model = cls.get_model(model)
+        
+        provider = AirforceChat if model in AirforceChat.text_models else AirforceImage
 
-        if model in cls.image_models:
-            async for result in cls._generate_image(model, messages, proxy, seed, size):
-                yield result
-        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",
-            "cache-control": "no-cache",
-            "origin": "https://llmplayground.net",
-            "user-agent": "Mozilla/5.0"
-        }
-
-        if seed is None:
-            seed = random.randint(0, 100000)
-
-        prompt = messages[-1]['content']
-
-        async with ClientSession(headers=headers) as session:
-            params = {
-                "model": model,
-                "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()
+        if model not in provider.models:
+            raise ValueError(f"Unsupported model: {model}")
 
-                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_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"
-        }
+        # Get the signature of the provider's create_async_generator method
+        sig = inspect.signature(provider.create_async_generator)
+        
+        # Filter kwargs to only include parameters that the provider's method accepts
+        filtered_kwargs = {k: v for k, v in kwargs.items() if k in sig.parameters}
 
-        async with ClientSession(headers=headers) as session:
-            formatted_prompt = cls._format_messages(messages)
-            prompt_parts = split_long_message(formatted_prompt)
-            full_response = ""
+        # Add model and messages to filtered_kwargs
+        filtered_kwargs['model'] = model
+        filtered_kwargs['messages'] = messages
 
-            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()
-                    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:
-                        json_data = await response.json()
-                        content = json_data['choices'][0]['message']['content']
-                        part_response = content
-
-                    part_response = re.sub(
-                        r"One message exceeds the \d+chars per message limit\..+https:\/\/discord\.com\/invite\/\S+",
-                        '',
-                        part_response
-                    )
-                    
-                    part_response = re.sub(
-                        r"Rate limit \(\d+\/minute\) exceeded\. Join our discord for more: .+https:\/\/discord\.com\/invite\/\S+",
-                        '',
-                        part_response
-                    )
-
-                    full_response += part_response
-            yield full_response
-
-    @classmethod
-    def _format_messages(cls, messages: Messages) -> str:
-        return " ".join([msg['content'] for msg in messages])
+        async for result in provider.create_async_generator(**filtered_kwargs):
+            yield result