44 lines
1.8 KiB
Python
44 lines
1.8 KiB
Python
from typing import Literal
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from pydantic import Field
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from letta.constants import DEFAULT_EMBEDDING_CHUNK_SIZE, LETTA_MODEL_ENDPOINT
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from letta.schemas.embedding_config import EmbeddingConfig
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from letta.schemas.enums import ProviderCategory, ProviderType
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from letta.schemas.llm_config import LLMConfig
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from letta.schemas.providers.base import Provider
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LETTA_EMBEDDING_ENDPOINT = "https://embeddings.letta.com/"
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class LettaProvider(Provider):
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provider_type: Literal[ProviderType.letta] = Field(ProviderType.letta, description="The type of the provider.")
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provider_category: ProviderCategory = Field(ProviderCategory.base, description="The category of the provider (base or byok)")
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base_url: str = Field(LETTA_EMBEDDING_ENDPOINT, description="Base URL for the Letta API (used for embeddings).")
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async def list_llm_models_async(self) -> list[LLMConfig]:
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return [
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LLMConfig(
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model="letta-free", # NOTE: renamed
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model_endpoint_type="openai",
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model_endpoint=LETTA_MODEL_ENDPOINT,
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context_window=30000,
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handle=self.get_handle("letta-free"),
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max_tokens=self.get_default_max_output_tokens("letta-free"),
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provider_name=self.name,
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provider_category=self.provider_category,
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)
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]
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async def list_embedding_models_async(self):
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return [
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EmbeddingConfig(
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embedding_model="letta-free", # NOTE: renamed
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embedding_endpoint_type="openai",
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embedding_endpoint=self.base_url,
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embedding_dim=1536,
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embedding_chunk_size=DEFAULT_EMBEDDING_CHUNK_SIZE,
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handle=self.get_handle("letta-free", is_embedding=True),
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)
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]
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