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synced 2024-11-26 09:57:24 +03:00
Fix typo in model list
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6e064adb09
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@ -9,13 +9,14 @@ class DeepInfra(Openai):
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label = "DeepInfra"
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url = "https://deepinfra.com"
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working = True
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needs_auth = False
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has_auth = True
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supports_stream = True
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supports_message_history = True
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default_model = "meta-llama/Meta-Llama-3-70b-instruct"
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default_vision_model = "llava-hf/llava-1.5-7b-hf"
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model_aliases = {
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'mixtral-8x22b': 'HuggingFaceH4/zephyr-orpo-141b-A35b-v0.1'
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'dbrx-instruct': 'databricks/dbrx-instruct',
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}
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@classmethod
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@ -6,12 +6,14 @@ from aiohttp import ClientSession, BaseConnector
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from ..typing import AsyncResult, Messages
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from ..requests.raise_for_status import raise_for_status
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from ..providers.conversation import BaseConversation
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from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
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from .helper import format_prompt, get_connector
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from .helper import format_prompt, get_connector, get_cookies
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class HuggingChat(AsyncGeneratorProvider, ProviderModelMixin):
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url = "https://huggingface.co/chat"
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working = True
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needs_auth = True
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default_model = "mistralai/Mixtral-8x7B-Instruct-v0.1"
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models = [
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"HuggingFaceH4/zephyr-orpo-141b-A35b-v0.1",
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@ -22,9 +24,6 @@ class HuggingChat(AsyncGeneratorProvider, ProviderModelMixin):
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'mistralai/Mistral-7B-Instruct-v0.2',
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'meta-llama/Meta-Llama-3-70B-Instruct'
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]
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model_aliases = {
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"openchat/openchat_3.5": "openchat/openchat-3.5-0106",
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}
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@classmethod
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def get_models(cls):
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@ -45,9 +44,16 @@ class HuggingChat(AsyncGeneratorProvider, ProviderModelMixin):
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connector: BaseConnector = None,
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web_search: bool = False,
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cookies: dict = None,
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conversation: Conversation = None,
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return_conversation: bool = False,
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delete_conversation: bool = True,
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**kwargs
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) -> AsyncResult:
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options = {"model": cls.get_model(model)}
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if cookies is None:
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cookies = get_cookies("huggingface.co", False)
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if return_conversation:
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delete_conversation = False
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system_prompt = "\n".join([message["content"] for message in messages if message["role"] == "system"])
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if system_prompt:
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@ -61,9 +67,14 @@ class HuggingChat(AsyncGeneratorProvider, ProviderModelMixin):
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headers=headers,
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connector=get_connector(connector, proxy)
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) as session:
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if conversation is None:
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async with session.post(f"{cls.url}/conversation", json=options) as response:
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await raise_for_status(response)
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conversation_id = (await response.json())["conversationId"]
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if return_conversation:
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yield Conversation(conversation_id)
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else:
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conversation_id = conversation.conversation_id
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async with session.get(f"{cls.url}/conversation/{conversation_id}/__data.json") as response:
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await raise_for_status(response)
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data: list = (await response.json())["nodes"][1]["data"]
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@ -72,7 +83,7 @@ class HuggingChat(AsyncGeneratorProvider, ProviderModelMixin):
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message_id: str = data[message_keys["id"]]
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options = {
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"id": message_id,
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"inputs": format_prompt(messages),
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"inputs": format_prompt(messages) if conversation is None else messages[-1]["content"],
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"is_continue": False,
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"is_retry": False,
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"web_search": web_search
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@ -92,5 +103,10 @@ class HuggingChat(AsyncGeneratorProvider, ProviderModelMixin):
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yield token
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elif line["type"] == "finalAnswer":
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break
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if delete_conversation:
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async with session.delete(f"{cls.url}/conversation/{conversation_id}") as response:
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await raise_for_status(response)
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class Conversation(BaseConversation):
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def __init__(self, conversation_id: str) -> None:
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self.conversation_id = conversation_id
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@ -11,7 +11,7 @@ class Llama(AsyncGeneratorProvider, ProviderModelMixin):
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url = "https://www.llama2.ai"
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working = True
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supports_message_history = True
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default_model = "meta/llama-3-70b-chat"
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default_model = "meta/meta-llama-3-70b-instruct"
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models = [
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"meta/llama-2-7b-chat",
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"meta/llama-2-13b-chat",
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@ -20,8 +20,8 @@ class Llama(AsyncGeneratorProvider, ProviderModelMixin):
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"meta/meta-llama-3-70b-instruct",
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]
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model_aliases = {
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"meta-llama/Meta-Llama-3-8b-instruct": "meta/meta-llama-3-8b-instruct",
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"meta-llama/Meta-Llama-3-70b-instruct": "meta/meta-llama-3-70b-instruct",
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"meta-llama/Meta-Llama-3-8B-Instruct": "meta/meta-llama-3-8b-instruct",
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"meta-llama/Meta-Llama-3-70B-Instruct": "meta/meta-llama-3-70b-instruct",
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"meta-llama/Llama-2-7b-chat-hf": "meta/llama-2-7b-chat",
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"meta-llama/Llama-2-13b-chat-hf": "meta/llama-2-13b-chat",
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"meta-llama/Llama-2-70b-chat-hf": "meta/llama-2-70b-chat",
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@ -11,6 +11,9 @@ class Replicate(AsyncGeneratorProvider, ProviderModelMixin):
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url = "https://replicate.com"
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working = True
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default_model = "meta/meta-llama-3-70b-instruct"
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model_aliases = {
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"meta-llama/Meta-Llama-3-70B-Instruct": default_model
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}
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@classmethod
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async def create_async_generator(
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@ -29,7 +29,9 @@ _cookies: Dict[str, Cookies] = {}
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DOMAINS = [
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".bing.com",
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".meta.ai",
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".google.com"
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".google.com",
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"www.whiterabbitneo.com",
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"huggingface.co"
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]
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if has_browser_cookie3 and os.environ.get('DBUS_SESSION_BUS_ADDRESS') == "/dev/null":
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@ -25,6 +25,7 @@ from .Provider import (
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Llama,
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OpenaiChat,
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PerplexityLabs,
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Replicate,
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Pi,
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Vercel,
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You,
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@ -137,19 +138,19 @@ llama2_13b = Model(
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llama2_70b = Model(
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name = "meta-llama/Llama-2-70b-chat-hf",
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base_provider = "meta",
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best_provider = RetryProvider([Llama, DeepInfra, HuggingChat])
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best_provider = RetryProvider([Llama, DeepInfra])
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)
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llama3_8b_instruct = Model(
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name = "meta-llama/Meta-Llama-3-8b-instruct",
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name = "meta-llama/Meta-Llama-3-8B-Instruct",
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base_provider = "meta",
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best_provider = RetryProvider([Llama])
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best_provider = RetryProvider([Llama, DeepInfra, Replicate])
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)
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llama3_70b_instruct = Model(
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name = "meta-llama/Meta-Llama-3-70b-instruct",
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name = "meta-llama/Meta-Llama-3-70B-Instruct",
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base_provider = "meta",
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best_provider = RetryProvider([Llama, HuggingChat])
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best_provider = RetryProvider([Llama, DeepInfra])
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)
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codellama_34b_instruct = Model(
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@ -168,7 +169,7 @@ codellama_70b_instruct = Model(
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mixtral_8x7b = Model(
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name = "mistralai/Mixtral-8x7B-Instruct-v0.1",
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base_provider = "huggingface",
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best_provider = RetryProvider([DeepInfra, HuggingChat, HuggingFace, PerplexityLabs])
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best_provider = RetryProvider([DeepInfra, HuggingFace, PerplexityLabs])
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)
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mistral_7b = Model(
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@ -186,7 +187,7 @@ mistral_7b_v02 = Model(
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mixtral_8x22b = Model(
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name = "HuggingFaceH4/zephyr-orpo-141b-A35b-v0.1",
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base_provider = "huggingface",
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best_provider = RetryProvider([HuggingChat, DeepInfra])
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best_provider = DeepInfra
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)
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# Misc models
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@ -211,7 +212,7 @@ airoboros_70b = Model(
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openchat_35 = Model(
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name = "openchat/openchat_3.5",
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base_provider = "huggingface",
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best_provider = RetryProvider([DeepInfra, HuggingChat])
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best_provider = DeepInfra
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)
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# Bard
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