wip

letta/llm_api/llm_api_tools.py

@@ -455,7 +455,7 @@ def create(
             chat_completion_request=ChatCompletionRequest(
                 model="command-r-plus",  # TODO
                 messages=[cast_message_to_subtype(m.to_openai_dict()) for m in messages],
-                tools=[{"type": "function", "function": f} for f in functions] if functions else None,
+                tools=tools,
                 tool_choice=function_call,
                 # user=str(user_id),
                 # NOTE: max_tokens is required for Anthropic API
@@ -463,6 +463,10 @@ def create(
             ),
         )
 
+    elif llm_config.model_endpoint_type == "groq":
+        if stream:
+            raise NotImplementedError(f"Streaming not yet implemented for {llm_config.model_endpoint_type}")
+
     # local model
     else:
         if stream:

letta/schemas/llm_config.py

@@ -1,4 +1,4 @@
-from typing import Optional
+from typing import Literal, Optional
 
 from pydantic import BaseModel, ConfigDict, Field
 
@@ -16,7 +16,7 @@ class LLMConfig(BaseModel):
     """
 
     # TODO: 🤮 don't default to a vendor! bug city!
-    model: str = Field(..., description="LLM model name. ")
+    model: Literal["openai", "anthropic", "cohere", "google_ai", "azure", "groq"] = Field(..., description="LLM model name. ")
     model_endpoint_type: str = Field(..., description="The endpoint type for the model.")
     model_endpoint: str = Field(..., description="The endpoint for the model.")
     model_wrapper: Optional[str] = Field(None, description="The wrapper for the model.")