gpt4free/g4f/Provider/nexra/NexraGeminiPro.py

69 lines
2.2 KiB
Python

from __future__ import annotations
from aiohttp import ClientSession
import json
from ..base_provider import AsyncGeneratorProvider, ProviderModelMixin
from ..helper import format_prompt
from ...typing import AsyncResult, Messages
class NexraGeminiPro(AsyncGeneratorProvider, ProviderModelMixin):
label = "Nexra Gemini PRO"
url = "https://nexra.aryahcr.cc/documentation/gemini-pro/en"
api_endpoint = "https://nexra.aryahcr.cc/api/chat/complements"
working = False
supports_stream = True
default_model = 'gemini-pro'
models = [default_model]
@classmethod
def get_model(cls, model: str) -> str:
return cls.default_model
@classmethod
async def create_async_generator(
cls,
model: str,
messages: Messages,
proxy: str = None,
stream: bool = False,
markdown: bool = False,
**kwargs
) -> AsyncResult:
model = cls.get_model(model)
headers = {
"Content-Type": "application/json"
}
data = {
"messages": [
{
"role": "user",
"content": format_prompt(messages)
}
],
"markdown": markdown,
"stream": stream,
"model": model
}
async with ClientSession(headers=headers) as session:
async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response:
response.raise_for_status()
buffer = ""
async for chunk in response.content.iter_any():
if chunk.strip(): # Check if chunk is not empty
buffer += chunk.decode()
while '\x1e' in buffer:
part, buffer = buffer.split('\x1e', 1)
if part.strip():
try:
response_json = json.loads(part)
message = response_json.get("message", "")
if message:
yield message
except json.JSONDecodeError as e:
print(f"JSONDecodeError: {e}")