docstrings `langchain` update (#14870)

Added missed docstrings

libs/langchain/langchain/chains/conversational_retrieval/base.py

@@ -55,8 +55,12 @@ def _get_chat_history(chat_history: List[CHAT_TURN_TYPE]) -> str:
 
 
 class InputType(BaseModel):
+    """Input type for ConversationalRetrievalChain."""
+
     question: str
+    """The question to answer."""
     chat_history: List[CHAT_TURN_TYPE] = Field(default_factory=list)
+    """The chat history to use for retrieval."""
 
 
 class BaseConversationalRetrievalChain(Chain):

libs/langchain/langchain/chains/openai_tools/extraction.py

@@ -19,6 +19,16 @@ def create_extraction_chain_pydantic(
     llm: BaseLanguageModel,
     system_message: str = _EXTRACTION_TEMPLATE,
 ) -> Runnable:
+    """Creates a chain that extracts information from a passage.
+
+    Args:
+        pydantic_schemas: The schema of the entities to extract.
+        llm: The language model to use.
+        system_message: The system message to use for extraction.
+
+    Returns:
+        A runnable that extracts information from a passage.
+    """
     if not isinstance(pydantic_schemas, list):
         pydantic_schemas = [pydantic_schemas]
     prompt = ChatPromptTemplate.from_messages(

libs/langchain/langchain/retrievers/self_query/redis.py

@@ -34,7 +34,7 @@ _COMPARATOR_TO_BUILTIN_METHOD = {
 
 
 class RedisTranslator(Visitor):
-    """Translate"""
+    """Visitor for translating structured queries to Redis filter expressions."""
 
     allowed_comparators = (
         Comparator.EQ,

libs/langchain/langchain/smith/evaluation/config.py

@@ -55,6 +55,8 @@ class EvalConfig(BaseModel):
 
 
 class SingleKeyEvalConfig(EvalConfig):
+    """Configuration for a run evaluator that only requires a single key."""
+
     reference_key: Optional[str] = None
     """The key in the dataset run to use as the reference string.
     If not provided, we will attempt to infer automatically."""

libs/langchain/langchain/tools/retriever.py

@@ -5,6 +5,8 @@ from langchain.tools import Tool
 
 
 class RetrieverInput(BaseModel):
+    """Input to the retriever."""
+
     query: str = Field(description="query to look up in retriever")