mirror of
https://github.com/xtekky/gpt4free.git
synced 2024-11-10 19:11:01 +00:00
Updated g4f/Provider/selenium/__init__.py
This commit is contained in:
kqlio67
parent
a4f75407f6
commit
a53954e777
@ -1,40 +1,32 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import base64
|
||||
from aiohttp import ClientSession
|
||||
from typing import AsyncGenerator
|
||||
|
||||
from ..typing import AsyncResult, Messages
|
||||
from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
|
||||
from ..image import ImageResponse
|
||||
from .helper import format_prompt
|
||||
from ..image import ImageResponse
|
||||
|
||||
class Nexra(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
url = "https://nexra.aryahcr.cc"
|
||||
api_endpoint_text = "https://nexra.aryahcr.cc/api/chat/gpt"
|
||||
api_endpoint_image = "https://nexra.aryahcr.cc/api/image/complements"
|
||||
chat_api_endpoint = "https://nexra.aryahcr.cc/api/chat/gpt"
|
||||
image_api_endpoint = "https://nexra.aryahcr.cc/api/image/complements"
|
||||
working = True
|
||||
supports_gpt_35_turbo = True
|
||||
supports_gpt_4 = True
|
||||
supports_stream = True
|
||||
supports_system_message = True
|
||||
supports_message_history = True
|
||||
|
||||
default_model = 'gpt-3.5-turbo'
|
||||
models = [
|
||||
# Text models
|
||||
text_models = [
|
||||
'gpt-4', 'gpt-4-0613', 'gpt-4-32k', 'gpt-4-0314', 'gpt-4-32k-0314',
|
||||
'gpt-3.5-turbo', 'gpt-3.5-turbo-16k', 'gpt-3.5-turbo-0613', 'gpt-3.5-turbo-16k-0613', 'gpt-3.5-turbo-0301',
|
||||
'gpt-3', 'text-davinci-003', 'text-davinci-002', 'code-davinci-002',
|
||||
'text-curie-001', 'text-babbage-001', 'text-ada-001',
|
||||
'davinci', 'curie', 'babbage', 'ada', 'babbage-002', 'davinci-002',
|
||||
# Image models
|
||||
'dalle', 'dalle-mini', 'emi'
|
||||
]
|
||||
|
||||
image_models = {"dalle", "dalle-mini", "emi"}
|
||||
text_models = set(models) - image_models
|
||||
image_models = ['dalle', 'dalle2', 'dalle-mini', 'emi']
|
||||
models = [*text_models, *image_models]
|
||||
|
||||
model_aliases = {
|
||||
"gpt-4": "gpt-4-0613",
|
||||
@ -60,16 +52,21 @@ class Nexra(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
"gpt-3": "ada",
|
||||
"gpt-3": "babbage-002",
|
||||
"gpt-3": "davinci-002",
|
||||
|
||||
"dalle-2": "dalle2",
|
||||
}
|
||||
|
||||
|
||||
|
||||
@classmethod
|
||||
def get_model(cls, model: str) -> str:
|
||||
if model in cls.models:
|
||||
if model in cls.text_models or model in cls.image_models:
|
||||
return model
|
||||
elif model in cls.model_aliases:
|
||||
return cls.model_aliases[model]
|
||||
elif model in cls.image_models:
|
||||
return cls.default_image_model
|
||||
else:
|
||||
return cls.default_model
|
||||
return cls.default_chat_model
|
||||
|
||||
@classmethod
|
||||
async def create_async_generator(
|
||||
@ -78,104 +75,45 @@ class Nexra(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
messages: Messages,
|
||||
proxy: str = None,
|
||||
**kwargs
|
||||
) -> AsyncGenerator[str | ImageResponse, None]:
|
||||
) -> AsyncResult:
|
||||
model = cls.get_model(model)
|
||||
|
||||
if model in cls.image_models:
|
||||
async for result in cls.create_image_async_generator(model, messages, proxy, **kwargs):
|
||||
yield result
|
||||
else:
|
||||
async for result in cls.create_text_async_generator(model, messages, proxy, **kwargs):
|
||||
yield result
|
||||
|
||||
@classmethod
|
||||
async def create_text_async_generator(
|
||||
cls,
|
||||
model: str,
|
||||
messages: Messages,
|
||||
proxy: str = None,
|
||||
**kwargs
|
||||
) -> AsyncGenerator[str, None]:
|
||||
headers = {
|
||||
"Content-Type": "application/json",
|
||||
}
|
||||
|
||||
async with ClientSession(headers=headers) as session:
|
||||
data = {
|
||||
"messages": messages,
|
||||
"prompt": format_prompt(messages),
|
||||
"model": model,
|
||||
"markdown": False,
|
||||
"stream": False,
|
||||
}
|
||||
async with session.post(cls.api_endpoint_text, json=data, proxy=proxy) as response:
|
||||
response.raise_for_status()
|
||||
result = await response.text()
|
||||
json_result = json.loads(result)
|
||||
yield json_result["gpt"]
|
||||
|
||||
@classmethod
|
||||
async def create_image_async_generator(
|
||||
cls,
|
||||
model: str,
|
||||
messages: Messages,
|
||||
proxy: str = None,
|
||||
**kwargs
|
||||
) -> AsyncGenerator[ImageResponse | str, None]:
|
||||
headers = {
|
||||
"Content-Type": "application/json"
|
||||
}
|
||||
|
||||
prompt = messages[-1]['content'] if messages else ""
|
||||
|
||||
data = {
|
||||
"prompt": prompt,
|
||||
"model": model
|
||||
}
|
||||
|
||||
async def process_response(response_text: str) -> ImageResponse | None:
|
||||
json_start = response_text.find('{')
|
||||
if json_start != -1:
|
||||
json_data = response_text[json_start:]
|
||||
try:
|
||||
response_data = json.loads(json_data)
|
||||
image_data = response_data.get('images', [])[0]
|
||||
if model in cls.image_models:
|
||||
# Image generation
|
||||
prompt = messages[-1]['content'] if messages else ""
|
||||
data = {
|
||||
"prompt": prompt,
|
||||
"model": model,
|
||||
"response": "url"
|
||||
}
|
||||
async with session.post(cls.image_api_endpoint, json=data, proxy=proxy) as response:
|
||||
response.raise_for_status()
|
||||
result = await response.text()
|
||||
result_json = json.loads(result.strip('_'))
|
||||
image_url = result_json['images'][0] if result_json['images'] else None
|
||||
|
||||
if image_data.startswith('data:image/'):
|
||||
return ImageResponse([image_data], "Generated image")
|
||||
if image_url:
|
||||
yield ImageResponse(images=image_url, alt=prompt)
|
||||
else:
|
||||
# Text completion
|
||||
data = {
|
||||
"messages": messages,
|
||||
"prompt": format_prompt(messages),
|
||||
"model": model,
|
||||
"markdown": False
|
||||
}
|
||||
async with session.post(cls.chat_api_endpoint, json=data, proxy=proxy) as response:
|
||||
response.raise_for_status()
|
||||
result = await response.text()
|
||||
|
||||
try:
|
||||
base64.b64decode(image_data)
|
||||
data_uri = f"data:image/jpeg;base64,{image_data}"
|
||||
return ImageResponse([data_uri], "Generated image")
|
||||
except:
|
||||
print("Invalid base64 data")
|
||||
return None
|
||||
except json.JSONDecodeError:
|
||||
print("Failed to parse JSON.")
|
||||
else:
|
||||
print("No JSON data found in the response.")
|
||||
return None
|
||||
|
||||
async with ClientSession(headers=headers) as session:
|
||||
async with session.post(cls.api_endpoint_image, json=data, proxy=proxy) as response:
|
||||
response.raise_for_status()
|
||||
response_text = await response.text()
|
||||
|
||||
image_response = await process_response(response_text)
|
||||
if image_response:
|
||||
yield image_response
|
||||
else:
|
||||
yield "Failed to process image data."
|
||||
|
||||
@classmethod
|
||||
async def create_async(
|
||||
cls,
|
||||
model: str,
|
||||
messages: Messages,
|
||||
proxy: str = None,
|
||||
**kwargs
|
||||
) -> str:
|
||||
async for response in cls.create_async_generator(model, messages, proxy, **kwargs):
|
||||
if isinstance(response, ImageResponse):
|
||||
return response.images[0]
|
||||
return response
|
||||
json_response = json.loads(result)
|
||||
gpt_response = json_response.get('gpt', '')
|
||||
yield gpt_response
|
||||
except json.JSONDecodeError:
|
||||
yield result
|
||||
|
||||
@ -1,4 +1,3 @@
|
||||
from .AItianhuSpace import AItianhuSpace
|
||||
from .MyShell import MyShell
|
||||
from .PerplexityAi import PerplexityAi
|
||||
from .Phind import Phind
|
||||
|
||||
Loading…
Reference in New Issue
Block a user