chore: fix branch (#1865)

letta/cli/cli.py

@@ -14,7 +14,9 @@ from letta.constants import CLI_WARNING_PREFIX, LETTA_DIR
 from letta.local_llm.constants import ASSISTANT_MESSAGE_CLI_SYMBOL
 from letta.log import get_logger
 from letta.metadata import MetadataStore
+from letta.schemas.embedding_config import EmbeddingConfig
 from letta.schemas.enums import OptionState
+from letta.schemas.llm_config import LLMConfig
 from letta.schemas.memory import ChatMemory, Memory
 from letta.server.server import logger as server_logger
 
@@ -233,25 +235,46 @@ def run(
         # choose from list of llm_configs
         llm_configs = client.list_llm_configs()
         llm_options = [llm_config.model for llm_config in llm_configs]
+
+        # TODO move into LLMConfig as a class method?
+        def prettify_llm_config(llm_config: LLMConfig) -> str:
+            return f"{llm_config.model}" + f" ({llm_config.model_endpoint})" if llm_config.model_endpoint else ""
+
+        llm_choices = [questionary.Choice(title=prettify_llm_config(llm_config), value=llm_config) for llm_config in llm_configs]
+
         # select model
         if len(llm_options) == 0:
             raise ValueError("No LLM models found. Please enable a provider.")
         elif len(llm_options) == 1:
             llm_model_name = llm_options[0]
         else:
-            llm_model_name = questionary.select("Select LLM model:", choices=llm_options).ask()
+            llm_model_name = questionary.select("Select LLM model:", choices=llm_choices).ask().model
         llm_config = [llm_config for llm_config in llm_configs if llm_config.model == llm_model_name][0]
 
         # choose form list of embedding configs
         embedding_configs = client.list_embedding_configs()
         embedding_options = [embedding_config.embedding_model for embedding_config in embedding_configs]
+
+        # TODO move into EmbeddingConfig as a class method?
+        def prettify_embed_config(embedding_config: EmbeddingConfig) -> str:
+            return (
+                f"{embedding_config.embedding_model}" + f" ({embedding_config.embedding_endpoint})"
+                if embedding_config.embedding_endpoint
+                else ""
+            )
+
+        embedding_choices = [
+            questionary.Choice(title=prettify_embed_config(embedding_config), value=embedding_config)
+            for embedding_config in embedding_configs
+        ]
+
         # select model
         if len(embedding_options) == 0:
             raise ValueError("No embedding models found. Please enable a provider.")
         elif len(embedding_options) == 1:
             embedding_model_name = embedding_options[0]
         else:
-            embedding_model_name = questionary.select("Select embedding model:", choices=embedding_options).ask()
+            embedding_model_name = questionary.select("Select embedding model:", choices=embedding_choices).ask().embedding_model
         embedding_config = [
             embedding_config for embedding_config in embedding_configs if embedding_config.embedding_model == embedding_model_name
         ][0]