65 lines
2.2 KiB
Python
65 lines
2.2 KiB
Python
from typing import Optional
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from letta.llm_api.llm_client_base import LLMClientBase
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from letta.schemas.enums import ProviderType
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class LLMClient:
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"""Factory class for creating LLM clients based on the model endpoint type."""
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@staticmethod
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def create(
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provider_type: ProviderType,
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provider_name: Optional[str] = None,
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put_inner_thoughts_first: bool = True,
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actor_id: Optional[str] = None,
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) -> Optional[LLMClientBase]:
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"""
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Create an LLM client based on the model endpoint type.
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Args:
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provider: The model endpoint type
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put_inner_thoughts_first: Whether to put inner thoughts first in the response
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Returns:
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An instance of LLMClientBase subclass
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Raises:
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ValueError: If the model endpoint type is not supported
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"""
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match provider_type:
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case ProviderType.google_ai:
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from letta.llm_api.google_ai_client import GoogleAIClient
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return GoogleAIClient(
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provider_name=provider_name,
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put_inner_thoughts_first=put_inner_thoughts_first,
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actor_id=actor_id,
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)
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case ProviderType.google_vertex:
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from letta.llm_api.google_vertex_client import GoogleVertexClient
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return GoogleVertexClient(
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provider_name=provider_name,
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put_inner_thoughts_first=put_inner_thoughts_first,
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actor_id=actor_id,
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)
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case ProviderType.anthropic:
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from letta.llm_api.anthropic_client import AnthropicClient
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return AnthropicClient(
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provider_name=provider_name,
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put_inner_thoughts_first=put_inner_thoughts_first,
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actor_id=actor_id,
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)
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case ProviderType.openai:
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from letta.llm_api.openai_client import OpenAIClient
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return OpenAIClient(
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provider_name=provider_name,
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put_inner_thoughts_first=put_inner_thoughts_first,
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actor_id=actor_id,
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)
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case _:
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return None
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