cleanup

letta/settings.py

@@ -54,116 +54,6 @@ class Settings(BaseSettings):
     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: