docs: Refine RunnablePassthrough docstring (#19812)

Description: This update refines the documentation for
`RunnablePassthrough` by removing an unnecessary import and correcting a
minor syntactical error in the example provided. This change enhances
the clarity and correctness of the documentation, ensuring that users
have a more accurate guide to follow.

Issue: N/A

Dependencies: None

This PR focuses solely on documentation improvements, specifically
targeting the `RunnablePassthrough` class within the `langchain_core`
module. By clarifying the example provided in the docstring, users are
offered a more straightforward and error-free guide to utilizing the
`RunnablePassthrough` class effectively.

As this is a documentation update, it does not include changes that
require new integrations, tests, or modifications to dependencies. It
adheres to the guidelines of minimal package interference and backward
compatibility, ensuring that the overall integrity and functionality of
the LangChain package remain unaffected.

Thank you for considering this documentation refinement for inclusion in
the LangChain project.

libs/core/langchain_core/runnables/passthrough.py

@@ -107,7 +107,7 @@ class RunnablePassthrough(RunnableSerializable[Other, Other]):
 
         .. code-block:: python
 
-            from langchain_core.runnables import RunnablePassthrough, RunnableParallel
+            from langchain_core.runnables import RunnablePassthrough
 
             def fake_llm(prompt: str) -> str: # Fake LLM for the example
                 return "completion"
@@ -115,10 +115,9 @@ class RunnablePassthrough(RunnableSerializable[Other, Other]):
             runnable = {
                 'llm1':  fake_llm,
                 'llm2':  fake_llm,
-            }
-            | RunnablePassthrough.assign(
+            } | RunnablePassthrough.assign(
                 total_chars=lambda inputs: len(inputs['llm1'] + inputs['llm2'])
-              )
+            )
 
             runnable.invoke('hello')
             # {'llm1': 'completion', 'llm2': 'completion', 'total_chars': 20}