return dummy llm api handler which will raise exception if called (#1954)

skyvern/forge/sdk/api/llm/api_handler_factory.py

@@ -18,7 +18,7 @@ from skyvern.forge.sdk.api.llm.exceptions import (
     LLMProviderError,
     LLMProviderErrorRetryableTask,
 )
-from skyvern.forge.sdk.api.llm.models import LLMAPIHandler, LLMConfig, LLMRouterConfig
+from skyvern.forge.sdk.api.llm.models import LLMAPIHandler, LLMConfig, LLMRouterConfig, dummy_llm_api_handler
 from skyvern.forge.sdk.api.llm.utils import llm_messages_builder, parse_api_response
 from skyvern.forge.sdk.artifact.models import ArtifactType
 from skyvern.forge.sdk.core import skyvern_context
@@ -229,7 +229,10 @@ class LLMAPIHandlerFactory:
 
     @staticmethod
     def get_llm_api_handler(llm_key: str, base_parameters: dict[str, Any] | None = None) -> LLMAPIHandler:
-        llm_config = LLMConfigRegistry.get_config(llm_key)
+        try:
+            llm_config = LLMConfigRegistry.get_config(llm_key)
+        except InvalidLLMConfigError:
+            return dummy_llm_api_handler
 
         if LLMConfigRegistry.is_router_config(llm_key):
             return LLMAPIHandlerFactory.get_llm_api_handler_with_router(llm_key)

skyvern/forge/sdk/api/llm/config_registry.py

@@ -55,7 +55,7 @@ if not any(
     ]
 ):
     LOG.warning(
-        "At least one LLM provider must be enabled. Run setup.sh and follow through the LLM provider setup, or "
+        "To run skyvern locally, you need to enable at least one LLM provider. Run setup.sh and follow through the LLM provider setup, or "
         "update the .env file (check out .env.example to see the required environment variables)."
     )
 

skyvern/forge/sdk/api/llm/models.py

@@ -93,3 +93,16 @@ class LLMAPIHandler(Protocol):
         screenshots: list[bytes] | None = None,
         parameters: dict[str, Any] | None = None,
     ) -> Awaitable[dict[str, Any]]: ...
+
+
+async def dummy_llm_api_handler(
+    prompt: str,
+    prompt_name: str,
+    step: Step | None = None,
+    task_v2: TaskV2 | None = None,
+    thought: Thought | None = None,
+    ai_suggestion: AISuggestion | None = None,
+    screenshots: list[bytes] | None = None,
+    parameters: dict[str, Any] | None = None,
+) -> dict[str, Any]:
+    raise NotImplementedError("Your LLM provider is not configured. Please configure it in the .env file.")