Files
letta-server/letta/settings.py
2024-09-25 13:58:21 -07:00

168 lines
6.3 KiB
Python

import os
from pathlib import Path
from typing import Optional
from pydantic import Field
from pydantic_settings import BaseSettings, SettingsConfigDict
from letta.schemas.embedding_config import EmbeddingConfig
from letta.schemas.llm_config import LLMConfig
from letta.utils import printd
class Settings(BaseSettings):
model_config = SettingsConfigDict(env_prefix="letta_")
letta_dir: Optional[Path] = Field(Path.home() / ".letta", env="LETTA_DIR")
debug: Optional[bool] = False
cors_origins: Optional[list] = ["http://letta.localhost", "http://localhost:8283", "http://localhost:8083"]
# database configuration
pg_db: Optional[str] = None
pg_user: Optional[str] = None
pg_password: Optional[str] = None
pg_host: Optional[str] = None
pg_port: Optional[int] = None
pg_uri: Optional[str] = None # option to specifiy full uri
# llm configuration
llm_endpoint: Optional[str] = None
llm_endpoint_type: Optional[str] = None
llm_model: Optional[str] = None
llm_context_window: Optional[int] = None
# embedding configuration
embedding_endpoint: Optional[str] = None
embedding_endpoint_type: Optional[str] = None
embedding_dim: Optional[int] = None
embedding_model: Optional[str] = None
embedding_chunk_size: int = 300
@property
def llm_config(self):
# try to get LLM config from settings
if self.llm_endpoint and self.llm_endpoint_type and self.llm_model and self.llm_context_window:
return LLMConfig(
model=self.llm_model,
model_endpoint_type=self.llm_endpoint_type,
model_endpoint=self.llm_endpoint,
model_wrapper=None,
context_window=self.llm_context_window,
)
else:
if not self.llm_endpoint:
printd(f"No LETTA_LLM_ENDPOINT provided")
if not self.llm_endpoint_type:
printd(f"No LETTA_LLM_ENDPOINT_TYPE provided")
if not self.llm_model:
printd(f"No LETTA_LLM_MODEL provided")
if not self.llm_context_window:
printd(f"No LETTA_LLM_CONTEX_WINDOW provided")
# quickstart options
if self.llm_model:
try:
return LLMConfig.default_config(self.llm_model)
except ValueError:
pass
# try to read from config file (last resort)
from letta.config import LettaConfig
if LettaConfig.exists():
config = LettaConfig.load()
llm_config = LLMConfig(
model=config.default_llm_config.model,
model_endpoint_type=config.default_llm_config.model_endpoint_type,
model_endpoint=config.default_llm_config.model_endpoint,
model_wrapper=config.default_llm_config.model_wrapper,
context_window=config.default_llm_config.context_window,
)
return llm_config
# check OpenAI API key
if os.getenv("OPENAI_API_KEY"):
return LLMConfig.default_config(self.llm_model if self.llm_model else "gpt-4")
return LLMConfig.default_config("letta")
@property
def embedding_config(self):
# try to get LLM config from settings
if self.embedding_endpoint and self.embedding_endpoint_type and self.embedding_model and self.embedding_dim:
return EmbeddingConfig(
embedding_model=self.embedding_model,
embedding_endpoint_type=self.embedding_endpoint_type,
embedding_endpoint=self.embedding_endpoint,
embedding_dim=self.embedding_dim,
embedding_chunk_size=self.embedding_chunk_size,
)
else:
if not self.embedding_endpoint:
printd(f"No LETTA_EMBEDDING_ENDPOINT provided")
if not self.embedding_endpoint_type:
printd(f"No LETTA_EMBEDDING_ENDPOINT_TYPE provided")
if not self.embedding_model:
printd(f"No LETTA_EMBEDDING_MODEL provided")
if not self.embedding_dim:
printd(f"No LETTA_EMBEDDING_DIM provided")
# TODO
## quickstart options
# if self.embedding_model:
# try:
# return EmbeddingConfig.default_config(self.embedding_model)
# except ValueError as e:
# pass
# try to read from config file (last resort)
from letta.config import LettaConfig
if LettaConfig.exists():
config = LettaConfig.load()
return EmbeddingConfig(
embedding_model=config.default_embedding_config.embedding_model,
embedding_endpoint_type=config.default_embedding_config.embedding_endpoint_type,
embedding_endpoint=config.default_embedding_config.embedding_endpoint,
embedding_dim=config.default_embedding_config.embedding_dim,
embedding_chunk_size=config.default_embedding_config.embedding_chunk_size,
)
if os.getenv("OPENAI_API_KEY"):
return EmbeddingConfig.default_config(self.embedding_model if self.embedding_model else "text-embedding-ada-002")
return EmbeddingConfig.default_config("letta")
@property
def letta_pg_uri(self) -> str:
if self.pg_uri:
return self.pg_uri
elif self.pg_db and self.pg_user and self.pg_password and self.pg_host and self.pg_port:
return f"postgresql+pg8000://{self.pg_user}:{self.pg_password}@{self.pg_host}:{self.pg_port}/{self.pg_db}"
else:
return f"postgresql+pg8000://letta:letta@localhost:5432/letta"
# add this property to avoid being returned the default
# reference: https://github.com/cpacker/Letta/issues/1362
@property
def letta_pg_uri_no_default(self) -> str:
if self.pg_uri:
return self.pg_uri
elif self.pg_db and self.pg_user and self.pg_password and self.pg_host and self.pg_port:
return f"postgresql+pg8000://{self.pg_user}:{self.pg_password}@{self.pg_host}:{self.pg_port}/{self.pg_db}"
else:
return None
class TestSettings(Settings):
model_config = SettingsConfigDict(env_prefix="letta_test_")
letta_dir: Optional[Path] = Field(Path.home() / ".letta/test", env="LETTA_TEST_DIR")
# singleton
settings = Settings(_env_parse_none_str="None")
test_settings = TestSettings()