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feat: claude api support (#572)

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This commit is contained in:
John Wang
2023-07-17 00:14:19 +08:00
committed by GitHub
parent 510389909c
commit 7599f79a17
52 changed files with 637 additions and 349 deletions
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70
api/core/llm/llm_builder.py
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@@ -8,9 +8,10 @@ from core.llm.provider.base import BaseProvider
from core.llm.provider.llm_provider_service import LLMProviderService
from core.llm.streamable_azure_chat_open_ai import StreamableAzureChatOpenAI
from core.llm.streamable_azure_open_ai import StreamableAzureOpenAI
from core.llm.streamable_chat_anthropic import StreamableChatAnthropic
from core.llm.streamable_chat_open_ai import StreamableChatOpenAI
from core.llm.streamable_open_ai import StreamableOpenAI
from models.provider import ProviderType
from models.provider import ProviderType, ProviderName
class LLMBuilder:
@@ -32,43 +33,43 @@ class LLMBuilder:
@classmethod
def to_llm(cls, tenant_id: str, model_name: str, **kwargs) -> Union[StreamableOpenAI, StreamableChatOpenAI]:
provider = cls.get_default_provider(tenant_id)
provider = cls.get_default_provider(tenant_id, model_name)
model_credentials = cls.get_model_credentials(tenant_id, provider, model_name)
llm_cls = None
mode = cls.get_mode_by_model(model_name)
if mode == 'chat':
if provider == 'openai':
if provider == ProviderName.OPENAI.value:
llm_cls = StreamableChatOpenAI
else:
elif provider == ProviderName.AZURE_OPENAI.value:
llm_cls = StreamableAzureChatOpenAI
elif provider == ProviderName.ANTHROPIC.value:
llm_cls = StreamableChatAnthropic
elif mode == 'completion':
if provider == 'openai':
if provider == ProviderName.OPENAI.value:
llm_cls = StreamableOpenAI
else:
elif provider == ProviderName.AZURE_OPENAI.value:
llm_cls = StreamableAzureOpenAI
else:
if not llm_cls:
raise ValueError(f"model name {model_name} is not supported.")
model_kwargs = {
'model_name': model_name,
'temperature': kwargs.get('temperature', 0),
'max_tokens': kwargs.get('max_tokens', 256),
'top_p': kwargs.get('top_p', 1),
'frequency_penalty': kwargs.get('frequency_penalty', 0),
'presence_penalty': kwargs.get('presence_penalty', 0),
'callbacks': kwargs.get('callbacks', None),
'streaming': kwargs.get('streaming', False),
}
model_extras_kwargs = model_kwargs if mode == 'completion' else {'model_kwargs': model_kwargs}
model_kwargs.update(model_credentials)
model_kwargs = llm_cls.get_kwargs_from_model_params(model_kwargs)
return llm_cls(
model_name=model_name,
temperature=kwargs.get('temperature', 0),
max_tokens=kwargs.get('max_tokens', 256),
**model_extras_kwargs,
callbacks=kwargs.get('callbacks', None),
streaming=kwargs.get('streaming', False),
# request_timeout=None
**model_credentials
)
return llm_cls(**model_kwargs)
@classmethod
def to_llm_from_model(cls, tenant_id: str, model: dict, streaming: bool = False,
@@ -118,14 +119,29 @@ class LLMBuilder:
return provider_service.get_credentials(model_name)
@classmethod
def get_default_provider(cls, tenant_id: str) -> str:
provider = BaseProvider.get_valid_provider(tenant_id)
if not provider:
raise ProviderTokenNotInitError()
def get_default_provider(cls, tenant_id: str, model_name: str) -> str:
provider_name = llm_constant.models[model_name]
if provider.provider_type == ProviderType.SYSTEM.value:
provider_name = 'openai'
else:
provider_name = provider.provider_name
if provider_name == 'openai':
# get the default provider (openai / azure_openai) for the tenant
openai_provider = BaseProvider.get_valid_provider(tenant_id, ProviderName.OPENAI.value)
azure_openai_provider = BaseProvider.get_valid_provider(tenant_id, ProviderName.AZURE_OPENAI.value)
provider = None
if openai_provider:
provider = openai_provider
elif azure_openai_provider:
provider = azure_openai_provider
if not provider:
raise ProviderTokenNotInitError(
f"No valid {provider_name} model provider credentials found. "
f"Please go to Settings -> Model Provider to complete your provider credentials."
)
if provider.provider_type == ProviderType.SYSTEM.value:
provider_name = 'openai'
else:
provider_name = provider.provider_name
return provider_name