fix: Clean up some legacy code and fix Groq provider (#1950)

.github/workflows/tests.yml

@@ -5,6 +5,7 @@ env:
   COMPOSIO_API_KEY: ${{ secrets.COMPOSIO_API_KEY }}
   ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
   GEMINI_API_KEY: ${{ secrets.GEMINI_API_KEY }}
+  GROQ_API_KEY: ${{ secrets.GROQ_API_KEY }}
 
 on:
   push:

letta/client/client.py

@@ -276,10 +276,10 @@ def get_messages(
     ) -> List[Message]:
         raise NotImplementedError
 
-    def list_models(self) -> List[LLMConfig]:
+    def list_model_configs(self) -> List[LLMConfig]:
         raise NotImplementedError
 
-    def list_embedding_models(self) -> List[EmbeddingConfig]:
+    def list_embedding_configs(self) -> List[EmbeddingConfig]:
         raise NotImplementedError
 
 
@@ -1234,32 +1234,6 @@ def detach_source(self, source_id: str, agent_id: str):
         assert response.status_code == 200, f"Failed to detach source from agent: {response.text}"
         return Source(**response.json())
 
-    # server configuration commands
-
-    def list_models(self):
-        """
-        List available LLM models
-
-        Returns:
-            models (List[LLMConfig]): List of LLM models
-        """
-        response = requests.get(f"{self.base_url}/{self.api_prefix}/models", headers=self.headers)
-        if response.status_code != 200:
-            raise ValueError(f"Failed to list models: {response.text}")
-        return [LLMConfig(**model) for model in response.json()]
-
-    def list_embedding_models(self):
-        """
-        List available embedding models
-
-        Returns:
-            models (List[EmbeddingConfig]): List of embedding models
-        """
-        response = requests.get(f"{self.base_url}/{self.api_prefix}/models/embedding", headers=self.headers)
-        if response.status_code != 200:
-            raise ValueError(f"Failed to list embedding models: {response.text}")
-        return [EmbeddingConfig(**model) for model in response.json()]
-
     # tools
 
     def get_tool_id(self, tool_name: str):
@@ -2572,24 +2546,6 @@ def get_messages(
             return_message_object=True,
         )
 
-    def list_models(self) -> List[LLMConfig]:
-        """
-        List available LLM models
-
-        Returns:
-            models (List[LLMConfig]): List of LLM models
-        """
-        return self.server.list_models()
-
-    def list_embedding_models(self) -> List[EmbeddingConfig]:
-        """
-        List available embedding models
-
-        Returns:
-            models (List[EmbeddingConfig]): List of embedding models
-        """
-        return [self.server.server_embedding_config]
-
     def list_blocks(self, label: Optional[str] = None, templates_only: Optional[bool] = True) -> List[Block]:
         """
         List available blocks

letta/llm_api/llm_api_tools.py

@@ -313,7 +313,6 @@ def create(
             stream_interface.stream_start()
         try:
             # groq uses the openai chat completions API, so this component should be reusable
-            assert model_settings.groq_api_key is not None, "Groq key is missing"
             response = openai_chat_completions_request(
                 url=llm_config.model_endpoint,
                 api_key=model_settings.groq_api_key,

letta/providers.py

@@ -313,7 +313,7 @@ def list_llm_models(self) -> List[LLMConfig]:
                 continue
             configs.append(
                 LLMConfig(
-                    model=model["id"], model_endpoint_type="openai", model_endpoint=self.base_url, context_window=model["context_window"]
+                    model=model["id"], model_endpoint_type="groq", model_endpoint=self.base_url, context_window=model["context_window"]
                 )
             )
         return configs

letta/server/server.py

@@ -43,6 +43,7 @@
     AnthropicProvider,
     AzureProvider,
     GoogleAIProvider,
+    GroqProvider,
     LettaProvider,
     OllamaProvider,
     OpenAIProvider,
@@ -298,6 +299,8 @@ def __init__(
                     api_version=model_settings.azure_api_version,
                 )
             )
+        if model_settings.groq_api_key:
+            self._enabled_providers.append(GroqProvider(api_key=model_settings.groq_api_key))
         if model_settings.vllm_api_base:
             # vLLM exposes both a /chat/completions and a /completions endpoint
             self._enabled_providers.append(

tests/test_client.py

@@ -2,7 +2,7 @@
 import threading
 import time
 import uuid
-from typing import Union
+from typing import List, Union
 
 import pytest
 from dotenv import load_dotenv
@@ -18,6 +18,7 @@
 from letta.schemas.llm_config import LLMConfig
 from letta.schemas.message import Message
 from letta.schemas.usage import LettaUsageStatistics
+from letta.settings import model_settings
 from tests.helpers.client_helper import upload_file_using_client
 
 # from tests.utils import create_config
@@ -262,21 +263,6 @@ def test_humans_personas(client: Union[LocalClient, RESTClient], agent: AgentSta
     assert human.value == "Human text", "Creating human failed"
 
 
-def test_config(client: Union[LocalClient, RESTClient], agent: AgentState):
-    # _reset_config()
-
-    models_response = client.list_models()
-    print("MODELS", models_response)
-
-    embeddings_response = client.list_embedding_models()
-    print("EMBEDDINGS", embeddings_response)
-
-    # TODO: add back
-    # config_response = client.get_config()
-    # TODO: ensure config is the same as the one in the server
-    # print("CONFIG", config_response)
-
-
 def test_list_tools_pagination(client: Union[LocalClient, RESTClient], agent: AgentState):
     tools = client.list_tools()
     visited_ids = {t.id: False for t in tools}
@@ -503,11 +489,20 @@ def test_organization(client: RESTClient):
         pytest.skip("Skipping test_organization because LocalClient does not support organizations")
 
 
-def test_model_configs(client: Union[LocalClient, RESTClient]):
-    # _reset_config()
+def test_list_llm_models(client: RESTClient):
+    """Test that if the user's env has the right api keys set, at least one model appears in the model list"""
 
-    model_configs = client.list_models()
-    print("MODEL CONFIGS", model_configs)
+    def has_model_endpoint_type(models: List["LLMConfig"], target_type: str) -> bool:
+        return any(model.model_endpoint_type == target_type for model in models)
 
-    embedding_configs = client.list_embedding_models()
-    print("EMBEDDING CONFIGS", embedding_configs)
+    models = client.list_llm_configs()
+    if model_settings.groq_api_key:
+        assert has_model_endpoint_type(models, "groq")
+    if model_settings.azure_api_key:
+        assert has_model_endpoint_type(models, "azure")
+    if model_settings.openai_api_key:
+        assert has_model_endpoint_type(models, "openai")
+    if model_settings.gemini_api_key:
+        assert has_model_endpoint_type(models, "google_ai")
+    if model_settings.anthropic_api_key:
+        assert has_model_endpoint_type(models, "anthropic")

tests/test_providers.py

@@ -4,6 +4,7 @@
     AnthropicProvider,
     AzureProvider,
     GoogleAIProvider,
+    GroqProvider,
     MistralProvider,
     OllamaProvider,
     OpenAIProvider,
@@ -27,12 +28,10 @@ def test_anthropic():
     print(models)
 
 
-# def test_groq():
-#    provider = GroqProvider(api_key=os.getenv("GROQ_API_KEY"))
-#    models = provider.list_llm_models()
-#    print(models)
-#
-#
+def test_groq():
+    provider = GroqProvider(api_key=os.getenv("GROQ_API_KEY"))
+    models = provider.list_llm_models()
+    print(models)
 
 
 def test_azure():