gpt4free/g4f/Provider/ChatGptEs.py
kqlio67 bb9132bcb4
Updating provider documentation and small fixes in providers (#2469)
* refactor(g4f/Provider/Airforce.py): improve model handling and filtering

- Add hidden_models set to exclude specific models
- Add evil alias for uncensored model handling
- Extend filtering for model-specific response tokens
- Add response buffering for streamed content
- Update model fetching with error handling

* refactor(g4f/Provider/Blackbox.py): improve caching and model handling

- Add caching system for validated values with file-based storage
- Rename 'flux' model to 'ImageGeneration' and update references
- Add temperature, top_p and max_tokens parameters to generator
- Simplify HTTP headers and remove redundant options
- Add model alias mapping for ImageGeneration
- Add file system utilities for cache management

* feat(g4f/Provider/RobocodersAPI.py): add caching and error handling

- Add file-based caching system for access tokens and sessions
- Add robust error handling with specific error messages
- Add automatic dialog continuation on resource limits
- Add HTML parsing with BeautifulSoup for token extraction
- Add debug logging for error tracking
- Add timeout configuration for API requests

* refactor(g4f/Provider/DarkAI.py): update DarkAI default model and aliases

- Change default model from llama-3-405b to llama-3-70b
- Remove llama-3-405b from supported models list
- Remove llama-3.1-405b from model aliases

* feat(g4f/Provider/Blackbox2.py): add image generation support

- Add image model 'flux' with dedicated API endpoint
- Refactor generator to support both text and image outputs
- Extract headers into reusable static method
- Add type hints for AsyncGenerator return type
- Split generation logic into _generate_text and _generate_image methods
- Add ImageResponse handling for image generation results

BREAKING CHANGE: create_async_generator now returns AsyncGenerator instead of AsyncResult

* refactor(g4f/Provider/ChatGptEs.py): update ChatGptEs model configuration

- Update models list to include gpt-3.5-turbo
- Remove chatgpt-4o-latest from supported models
- Remove model_aliases mapping for gpt-4o

* feat(g4f/Provider/DeepInfraChat.py): add Accept-Language header support

- Add Accept-Language header for internationalization
- Maintain existing header configuration
- Improve request compatibility with language preferences

* refactor(g4f/Provider/needs_auth/Gemini.py): add ProviderModelMixin inheritance

- Add ProviderModelMixin to class inheritance
- Import ProviderModelMixin from base_provider
- Move BaseConversation import to base_provider imports

* refactor(g4f/Provider/Liaobots.py): update model details and aliases

- Add version suffix to o1 model IDs
- Update model aliases for o1-preview and o1-mini
- Standardize version format across model definitions

* refactor(g4f/Provider/PollinationsAI.py): enhance model support and generation

- Split generation logic into dedicated image/text methods
- Add additional text models including sur and claude
- Add width/height parameters for image generation
- Add model existence validation
- Add hasattr checks for model lists initialization

* chore(gitignore): add provider cache directory

- Add g4f/Provider/.cache to gitignore patterns

* refactor(g4f/Provider/ReplicateHome.py): update model configuration

- Update default model to gemma-2b-it
- Add default_image_model configuration
- Remove llava-13b from supported models
- Simplify request headers

* feat(g4f/models.py): expand provider and model support

- Add new providers DarkAI and PollinationsAI
- Add new models for Mistral, Flux and image generation
- Update provider lists for existing models
- Add P1 and Evil models with experimental providers

BREAKING CHANGE: Remove llava-13b model support

* refactor(Airforce): Update type hint for split_message return

- Change return type of  from  to  for consistency with import.
- Maintain overall functionality and structure of the  class.
- Ensure compatibility with type hinting standards in Python.

* refactor(g4f/Provider/Airforce.py): Update type hint for split_message return

- Change return type of 'split_message' from 'list[str]' to 'List[str]' for consistency with import.
- Maintain overall functionality and structure of the 'Airforce' class.
- Ensure compatibility with type hinting standards in Python.

* feat(g4f/Provider/RobocodersAPI.py): Add support for optional BeautifulSoup dependency

- Introduce a check for the BeautifulSoup library and handle its absence gracefully.
- Raise a  if BeautifulSoup is not installed, prompting the user to install it.
- Remove direct import of BeautifulSoup to avoid import errors when the library is missing.

* fix: Updating provider documentation and small fixes in providers

* Disabled the provider (RobocodersAPI)

* Fix: Conflicting file g4f/models.py

* Update g4f/models.py g4f/Provider/Airforce.py

* Update docs/providers-and-models.md g4f/models.py g4f/Provider/Airforce.py g4f/Provider/PollinationsAI.py

* Update docs/providers-and-models.md

* Update .gitignore

* Update g4f/models.py

* Update g4f/Provider/PollinationsAI.py

---------

Co-authored-by: kqlio67 <>
2024-12-09 16:52:25 +01:00

84 lines
3.2 KiB
Python

from __future__ import annotations
from aiohttp import ClientSession
import os
import json
import re
from ..typing import AsyncResult, Messages
from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
from .helper import format_prompt
class ChatGptEs(AsyncGeneratorProvider, ProviderModelMixin):
url = "https://chatgpt.es"
api_endpoint = "https://chatgpt.es/wp-admin/admin-ajax.php"
working = True
supports_stream = True
supports_system_message = True
supports_message_history = True
default_model = 'gpt-4o'
models = ['gpt-4', 'gpt-4o', 'gpt-4o-mini']
@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
) -> AsyncResult:
model = cls.get_model(model)
headers = {
"authority": "chatgpt.es",
"accept": "application/json",
"origin": cls.url,
"referer": f"{cls.url}/chat",
"user-agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/129.0.0.0 Safari/537.36",
}
async with ClientSession(headers=headers) as session:
initial_response = await session.get(cls.url)
nonce_ = re.findall(r'data-nonce="(.+?)"', await initial_response.text())[0]
post_id = re.findall(r'data-post-id="(.+?)"', await initial_response.text())[0]
formatted_prompt = format_prompt(messages)
conversation_history = [
"Human: You are a helpful AI assistant. Please respond in the same language that the user uses in their message. Provide accurate, relevant and helpful information while maintaining a friendly and professional tone. If you're not sure about something, please acknowledge that and provide the best information you can while noting any uncertainties. Focus on being helpful while respecting the user's choice of language."
]
for message in messages[:-1]:
if message['role'] == "user":
conversation_history.append(f"Human: {message['content']}")
else:
conversation_history.append(f"AI: {message['content']}")
payload = {
'_wpnonce': nonce_,
'post_id': post_id,
'url': cls.url,
'action': 'wpaicg_chat_shortcode_message',
'message': formatted_prompt,
'bot_id': '0',
'chatbot_identity': 'shortcode',
'wpaicg_chat_client_id': os.urandom(5).hex(),
'wpaicg_chat_history': json.dumps(conversation_history)
}
async with session.post(cls.api_endpoint, headers=headers, data=payload) as response:
response.raise_for_status()
result = await response.json()
yield result['data']