✨ feat(base.py): add input validation for PromptTemplate to ensure that the template and input variables are valid

The commented out code was removed to improve code readability. Input validation was added to ensure that the template and input variables are valid before creating a PromptTemplate object. This helps to prevent errors that may occur when the object is created with invalid input.
🔒 chore(base.py): remove commented out code and add input validation for PromptTemplate

src/backend/langflow/api/v1/base.py

@@ -1,6 +1,7 @@
 from pydantic import BaseModel, validator
 
 from langflow.interface.utils import extract_input_variables_from_prompt
+from langchain.prompts import PromptTemplate
 
 
 class CacheResponse(BaseModel):
@@ -57,6 +58,13 @@ def validate_prompt(template: str):
 
     # Check if there are invalid characters in the input_variables
     input_variables = check_input_variables(input_variables)
+    try:
+        PromptTemplate(template=template, input_variables=input_variables)
+    except Exception as exc:
+        raise ValueError(str(exc)) from exc
+
+    # if len(input_variables) > 1:
+    #     # If there's more than one input variable
 
     return PromptValidationResponse(input_variables=input_variables)