cr

langchain/chains/llm_math/prompt.py

@@ -35,6 +35,7 @@ class LLMMathExample(BaseExample):
     question: str
     answer: str
 
+    @property
     def formatted(self) -> str:
         return f"Question: {self.question}\n\n{self.answer}"
 

langchain/chains/react/prompt.py

@@ -12,6 +12,7 @@ class ReActExample(BaseExample):
     question: str
     answer: str
 
+    @property
     def formatted(self) -> str:
         return f"Question: {self.question}\n{self.answer}"
 

langchain/chains/self_ask_with_search/prompt.py

@@ -12,6 +12,7 @@ class SelfAskWithSearchExample(BaseExample):
     question: str
     answer: str
 
+    @property
     def formatted(self) -> str:
         return f"Question: {self.question}\n{self.answer}"
 

langchain/prompts/data.py

@@ -6,8 +6,8 @@ from pydantic import BaseModel
 class BaseExample(BaseModel, ABC):
     """Base class for examples."""
 
-    @abstractmethod
     @property
+    @abstractmethod
     def formatted(self) -> str:
         """Returns a formatted example as a string."""
 
@@ -16,6 +16,7 @@ class SimpleExample(BaseExample):
 
     text: str
 
+    @property
     def formatted(self) -> str:
         return self.text
 

langchain/prompts/dynamic.py

@@ -116,7 +116,8 @@ class DynamicPrompt(BaseModel, BasePrompt):
             )
         return values
 
-    @root_validator()
+    # Needs to be pre=True to convert to the right type.
+    @root_validator(pre=True)
     def convert_examples(cls, values: Dict) -> Dict:
         values["examples"] = convert_to_examples(values["examples"])
         return values

tests/unit_tests/test_prompt.py

@@ -51,8 +51,8 @@ Question: {question}
 Answer:"""
     input_variables = ["question"]
     example_separator = "\n\n"
-    prefix = """Test Prompt:\n\n"""
-    suffix = """\n\nQuestion: {question}\nAnswer:"""
+    prefix = """Test Prompt:"""
+    suffix = """Question: {question}\nAnswer:"""
     examples = [
         """Question: who are you?\nAnswer: foo""",
         """Question: what are you?\nAnswer: bar""",