mirror of
https://github.com/xtekky/gpt4free.git
synced 2025-10-04 16:02:41 +08:00
93986d15f6
- Fixed duplicate model entries in Blackbox provider model_aliases - Added meta-llama- to llama- name cleaning in Cloudflare provider - Enhanced PollinationsAI provider with improved vision model detection - Added reasoning support to PollinationsAI provider - Fixed HuggingChat authentication to include headers and impersonate - Removed unused max_inputs_length parameter from HuggingFaceAPI - Renamed extra_data to extra_body for consistency across providers - Added Puter provider with grouped model support - Enhanced AnyProvider with grouped model display and better model organization - Fixed model cleaning in AnyProvider to handle more model name variations - Added api_key handling for HuggingFace providers in AnyProvider - Added see_stream helper function to parse event streams - Updated GUI server to handle JsonConversation properly - Fixed aspect ratio handling in image generation functions - Added ResponsesConfig and ClientResponse for new API endpoint - Updated requirements to include markitdown
52 lines
1.5 KiB
Python
52 lines
1.5 KiB
Python
from __future__ import annotations
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from ...typing import CreateResult, Messages
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from ..helper import filter_none
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from ..template import OpenaiTemplate
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models = {
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"theb-ai": "TheB.AI",
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"gpt-3.5-turbo": "GPT-3.5",
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"gpt-4-turbo": "GPT-4 Turbo",
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"gpt-4": "GPT-4",
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"claude-3.5-sonnet": "Claude",
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"llama-2-7b-chat": "Llama 2 7B",
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"llama-2-13b-chat": "Llama 2 13B",
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"llama-2-70b-chat": "Llama 2 70B",
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"code-llama-7b": "Code Llama 7B",
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"code-llama-13b": "Code Llama 13B",
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"code-llama-34b": "Code Llama 34B",
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"qwen-2-72b": "Qwen"
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}
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class ThebApi(OpenaiTemplate):
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label = "TheB.AI API"
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url = "https://theb.ai"
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login_url = "https://beta.theb.ai/home"
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api_base = "https://api.theb.ai/v1"
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working = True
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needs_auth = True
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default_model = "theb-ai"
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fallback_models = list(models)
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@classmethod
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def create_async_generator(
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cls,
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model: str,
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messages: Messages,
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temperature: float = None,
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top_p: float = None,
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**kwargs
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) -> CreateResult:
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system_message = "\n".join([message["content"] for message in messages if message["role"] == "system"])
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messages = [message for message in messages if message["role"] != "system"]
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data = {
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"model_params": filter_none(
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system_prompt=system_message,
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temperature=temperature,
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top_p=top_p,
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)
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}
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return super().create_async_generator(model, messages, extra_body=data, **kwargs)
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