Files
letta-server/letta/schemas/providers/deepseek.py
2025-07-22 16:09:50 -07:00

64 lines
2.6 KiB
Python

from typing import Literal
from pydantic import Field
from letta.schemas.enums import ProviderCategory, ProviderType
from letta.schemas.llm_config import LLMConfig
from letta.schemas.providers.openai import OpenAIProvider
class DeepSeekProvider(OpenAIProvider):
"""
DeepSeek ChatCompletions API is similar to OpenAI's reasoning API,
but with slight differences:
* For example, DeepSeek's API requires perfect interleaving of user/assistant
* It also does not support native function calling
"""
provider_type: Literal[ProviderType.deepseek] = Field(ProviderType.deepseek, description="The type of the provider.")
provider_category: ProviderCategory = Field(ProviderCategory.base, description="The category of the provider (base or byok)")
base_url: str = Field("https://api.deepseek.com/v1", description="Base URL for the DeepSeek API.")
api_key: str = Field(..., description="API key for the DeepSeek API.")
# TODO (cliandy): this may need to be updated to reflect current models
def get_model_context_window_size(self, model_name: str) -> int | None:
# DeepSeek doesn't return context window in the model listing,
# so these are hardcoded from their website
if model_name == "deepseek-reasoner":
return 64000
elif model_name == "deepseek-chat":
return 64000
else:
return None
async def list_llm_models_async(self) -> list[LLMConfig]:
from letta.llm_api.openai import openai_get_model_list_async
response = await openai_get_model_list_async(self.base_url, api_key=self.api_key)
data = response.get("data", response)
configs = []
for model in data:
check = self._do_model_checks_for_name_and_context_size(model)
if check is None:
continue
model_name, context_window_size = check
# Not used for deepseek-reasoner, but otherwise is true
put_inner_thoughts_in_kwargs = False if model_name == "deepseek-reasoner" else True
configs.append(
LLMConfig(
model=model_name,
model_endpoint_type="deepseek",
model_endpoint=self.base_url,
context_window=context_window_size,
handle=self.get_handle(model_name),
put_inner_thoughts_in_kwargs=put_inner_thoughts_in_kwargs,
provider_name=self.name,
provider_category=self.provider_category,
)
)
return configs