0.3.2.6

1 files changed, 133 insertions, 0 deletions

diff --git a/g4f/Provider/Snova.py b/g4f/Provider/Snova.py
new file mode 100644
index 00000000..76dfac40
--- /dev/null
+++ b/g4f/Provider/Snova.py
@@ -0,0 +1,133 @@
+from __future__ import annotations
+
+import json
+from typing import AsyncGenerator
+
+from aiohttp import ClientSession
+
+from ..typing import AsyncResult, Messages
+from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
+from .helper import format_prompt
+
+
+class Snova(AsyncGeneratorProvider, ProviderModelMixin):
+    url = "https://fast.snova.ai"
+    api_endpoint = "https://fast.snova.ai/api/completion"
+    working = True
+    supports_stream = True
+    supports_system_message = True
+    supports_message_history = True
+    
+    default_model = 'Meta-Llama-3.1-8B-Instruct'
+    models = [
+        'Meta-Llama-3.1-8B-Instruct',
+        'Meta-Llama-3.1-70B-Instruct',
+        'Meta-Llama-3.1-405B-Instruct',
+        'Samba-CoE',
+        'ignos/Mistral-T5-7B-v1',
+        'v1olet/v1olet_merged_dpo_7B',
+        'macadeliccc/WestLake-7B-v2-laser-truthy-dpo',
+        'cookinai/DonutLM-v1',
+    ]
+    
+    model_aliases = {
+        "llama-3.1-8b": "Meta-Llama-3.1-8B-Instruct",
+        "llama-3.1-70b": "Meta-Llama-3.1-70B-Instruct",
+        "llama-3.1-405b": "Meta-Llama-3.1-405B-Instruct",
+        
+        "mistral-7b": "ignos/Mistral-T5-7B-v1",
+        
+        "samba-coe-v0.1": "Samba-CoE",
+        "v1olet-merged-7b": "v1olet/v1olet_merged_dpo_7B",
+        "westlake-7b-v2": "macadeliccc/WestLake-7B-v2-laser-truthy-dpo",
+        "donutlm-v1": "cookinai/DonutLM-v1",
+    }
+
+    @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
+    async def create_async_generator(
+        cls,
+        model: str,
+        messages: Messages,
+        proxy: str = None,
+        **kwargs
+    ) -> AsyncGenerator[str, None]:
+        model = cls.get_model(model)
+        
+        headers = {
+            "accept": "text/event-stream",
+            "accept-language": "en-US,en;q=0.9",
+            "cache-control": "no-cache",
+            "content-type": "application/json",
+            "origin": cls.url,
+            "pragma": "no-cache",
+            "priority": "u=1, i",
+            "referer": f"{cls.url}/",
+            "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"
+        }
+        async with ClientSession(headers=headers) as session:
+            data = {
+                "body": {
+                    "messages": [
+                        {
+                            "role": "system",
+                            "content": "You are a helpful assistant."
+                        },
+                        {
+                            "role": "user",
+                            "content": format_prompt(messages),
+                            "id": "1-id",
+                            "ref": "1-ref",
+                            "revision": 1,
+                            "draft": False,
+                            "status": "done",
+                            "enableRealTimeChat": False,
+                            "meta": None
+                        }
+                    ],
+                    "max_tokens": 1000,
+                    "stop": ["<|eot_id|>"],
+                    "stream": True,
+                    "stream_options": {"include_usage": True},
+                    "model": model
+                },
+                "env_type": "tp16"
+            }
+            async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response:
+                response.raise_for_status()
+                full_response = ""
+                async for line in response.content:
+                    line = line.decode().strip()
+                    if line.startswith("data: "):
+                        data = line[6:]
+                        if data == "[DONE]":
+                            break
+                        try:
+                            json_data = json.loads(data)
+                            choices = json_data.get("choices", [])
+                            if choices:
+                                delta = choices[0].get("delta", {})
+                                content = delta.get("content", "")
+                                full_response += content
+                        except json.JSONDecodeError:
+                            continue
+                        except Exception as e:
+                            print(f"Error processing chunk: {e}")
+                            print(f"Problematic data: {data}")
+                            continue
+                
+                yield full_response.strip()