feat: local auth config (#854)

memgpt/cli/cli.py

@@ -162,7 +162,7 @@ def quickstart(
         api_key = os.getenv("OPENAI_API_KEY")
         while api_key is None or len(api_key) == 0:
             # Ask for API key as input
-            api_key = questionary.text("Enter your OpenAI API key (starts with 'sk-', see https://platform.openai.com/api-keys):").ask()
+            api_key = questionary.password("Enter your OpenAI API key (starts with 'sk-', see https://platform.openai.com/api-keys):").ask()
         credentials.openai_key = api_key
         credentials.save()
 

memgpt/cli/cli_config.py

@@ -16,7 +16,7 @@ from memgpt.log import logger
 from memgpt import utils
 
 from memgpt.config import MemGPTConfig
-from memgpt.credentials import MemGPTCredentials
+from memgpt.credentials import MemGPTCredentials, SUPPORTED_AUTH_TYPES
 from memgpt.constants import MEMGPT_DIR
 
 # from memgpt.agent_store.storage import StorageConnector, TableType
@@ -79,7 +79,7 @@ def configure_llm_endpoint(config: MemGPTConfig, credentials: MemGPTCredentials)
             if openai_api_key is None:
                 while openai_api_key is None or len(openai_api_key) == 0:
                     # Ask for API key as input
-                    openai_api_key = questionary.text(
+                    openai_api_key = questionary.password(
                         "Enter your OpenAI API key (starts with 'sk-', see https://platform.openai.com/api-keys):"
                     ).ask()
                     if openai_api_key is None:
@@ -92,7 +92,7 @@ def configure_llm_endpoint(config: MemGPTConfig, credentials: MemGPTCredentials)
             default_input = (
                 shorten_key_middle(credentials.openai_key) if credentials.openai_key.startswith("sk-") else credentials.openai_key
             )
-            openai_api_key = questionary.text(
+            openai_api_key = questionary.password(
                 "Enter your OpenAI API key (starts with 'sk-', see https://platform.openai.com/api-keys):",
                 default=default_input,
             ).ask()
@@ -314,6 +314,31 @@ def configure_model(config: MemGPTConfig, credentials: MemGPTCredentials, model_
         if model_wrapper is None:
             raise KeyboardInterrupt
 
+        # ask about local auth
+        use_local_auth = questionary.confirm(
+            "Is your LLM endpoint authenticated? (default no)",
+            default=False,
+        ).ask()
+        if use_local_auth is None:
+            raise KeyboardInterrupt
+        if use_local_auth:
+            local_auth_type = questionary.select(
+                "What HTTP authentication method does your endpoint require?",
+                choices=SUPPORTED_AUTH_TYPES,
+                default=SUPPORTED_AUTH_TYPES[0],
+            ).ask()
+            if local_auth_type is None:
+                raise KeyboardInterrupt
+            local_auth_key = questionary.password(
+                "Enter your authentication key:",
+            ).ask()
+            if local_auth_key is None:
+                raise KeyboardInterrupt
+            # credentials = MemGPTCredentials.load()
+            credentials.openllm_auth_type = local_auth_type
+            credentials.openllm_key = local_auth_key
+            credentials.save()
+
     # set: context_window
     if str(model) not in LLM_MAX_TOKENS:
         # Ask the user to specify the context length
@@ -373,13 +398,13 @@ def configure_embedding_endpoint(config: MemGPTConfig, credentials: MemGPTCreden
                 # if we still can't find it, ask for it as input
                 while openai_api_key is None or len(openai_api_key) == 0:
                     # Ask for API key as input
-                    openai_api_key = questionary.text(
+                    openai_api_key = questionary.password(
                         "Enter your OpenAI API key (starts with 'sk-', see https://platform.openai.com/api-keys):"
                     ).ask()
                     if openai_api_key is None:
                         raise KeyboardInterrupt
                 credentials.openai_key = openai_api_key
-                config.save()
+                credentials.save()
 
         embedding_endpoint_type = "openai"
         embedding_endpoint = "https://api.openai.com/v1"
@@ -514,7 +539,7 @@ def configure_archival_storage(config: MemGPTConfig, credentials: MemGPTCredenti
     # TODO: allow configuring embedding model
 
 
-def configure_recall_storage(config: MemGPTConfig):
+def configure_recall_storage(config: MemGPTConfig, credentials: MemGPTCredentials):
     # Configure recall storage backend
     recall_storage_options = ["sqlite", "postgres"]
     recall_storage_type = questionary.select(
@@ -602,13 +627,6 @@ def configure():
         persona=default_persona,
         human=default_human,
         agent=default_agent,
-        # credentials
-        openai_key=openai_key,
-        azure_key=azure_creds["azure_key"],
-        azure_endpoint=azure_creds["azure_endpoint"],
-        azure_version=azure_creds["azure_version"],
-        azure_deployment=azure_creds["azure_deployment"],  # OK if None
-        azure_embedding_deployment=azure_creds["azure_embedding_deployment"],  # OK if None
         # storage
         archival_storage_type=archival_storage_type,
         archival_storage_uri=archival_storage_uri,

memgpt/data_types.py

@@ -172,7 +172,7 @@ class Message(Record):
                 if "tool_call_id" in openai_message_dict:
                     assert openai_message_dict["tool_call_id"] is None, openai_message_dict
 
-            if "tool_calls" in openai_message_dict:
+            if "tool_calls" in openai_message_dict and openai_message_dict["tool_calls"] is not None:
                 assert openai_message_dict["role"] == "assistant", openai_message_dict
 
                 tool_calls = [