Change RunnableMap to RunnableParallel for consistency (#14142)

- **Description:** Change instances of RunnableMap to RunnableParallel,
as that should be the one used going forward. This makes it consistent
across the codebase.

templates/anthropic-iterative-search/anthropic_iterative_search/retriever_agent.py

@@ -2,7 +2,7 @@ from langchain.agents import AgentExecutor
 from langchain.chat_models import ChatAnthropic
 from langchain.prompts import ChatPromptTemplate
 from langchain.schema.output_parser import StrOutputParser
-from langchain.schema.runnable import RunnableMap, RunnablePassthrough
+from langchain.schema.runnable import RunnableParallel, RunnablePassthrough
 
 from .agent_scratchpad import format_agent_scratchpad
 from .output_parser import parse_output
@@ -29,7 +29,7 @@ chain = (
 )
 
 agent_chain = (
-    RunnableMap(
+    RunnableParallel(
         {
             "partial_completion": chain,
             "intermediate_steps": lambda x: x["intermediate_steps"],

templates/rag-conversation-zep/rag_conversation_zep/chain.py

@@ -14,7 +14,7 @@ from langchain.schema.runnable import (
     ConfigurableField,
     RunnableBranch,
     RunnableLambda,
-    RunnableMap,
+    RunnableParallel,
     RunnablePassthrough,
 )
 from langchain.schema.runnable.utils import ConfigurableFieldSingleOption
@@ -133,7 +133,7 @@ class ChatHistory(BaseModel):
     question: str
 
 
-_inputs = RunnableMap(
+_inputs = RunnableParallel(
     {
         "question": lambda x: x["question"],
         "chat_history": lambda x: _format_chat_history(x["chat_history"]),

templates/rag-conversation/rag_conversation/chain.py

@@ -11,7 +11,7 @@ from langchain.schema.output_parser import StrOutputParser
 from langchain.schema.runnable import (
     RunnableBranch,
     RunnableLambda,
-    RunnableMap,
+    RunnableParallel,
     RunnablePassthrough,
 )
 from langchain.vectorstores import Pinecone
@@ -108,7 +108,7 @@ _search_query = RunnableBranch(
     RunnableLambda(itemgetter("question")),
 )
 
-_inputs = RunnableMap(
+_inputs = RunnableParallel(
     {
         "question": lambda x: x["question"],
         "chat_history": lambda x: _format_chat_history(x["chat_history"]),

templates/rag-elasticsearch/rag_elasticsearch/chain.py

@@ -5,7 +5,7 @@ from langchain.chat_models import ChatOpenAI
 from langchain.embeddings import HuggingFaceEmbeddings
 from langchain.schema import BaseMessage, format_document
 from langchain.schema.output_parser import StrOutputParser
-from langchain.schema.runnable import RunnableMap, RunnablePassthrough
+from langchain.schema.runnable import RunnableParallel, RunnablePassthrough
 from langchain.vectorstores.elasticsearch import ElasticsearchStore
 from pydantic import BaseModel, Field
 
@@ -49,7 +49,7 @@ class ChainInput(BaseModel):
     question: str = Field(..., description="The question to answer.")
 
 
-_inputs = RunnableMap(
+_inputs = RunnableParallel(
     standalone_question=RunnablePassthrough.assign(
         chat_history=lambda x: _format_chat_history(x["chat_history"])
     )

templates/rag-google-cloud-sensitive-data-protection/rag_google_cloud_sensitive_data_protection/chain.py

@@ -7,7 +7,7 @@ from langchain.prompts import ChatPromptTemplate, MessagesPlaceholder
 from langchain.pydantic_v1 import BaseModel, Field
 from langchain.schema.messages import AIMessage, HumanMessage
 from langchain.schema.output_parser import StrOutputParser
-from langchain.schema.runnable import RunnableLambda, RunnableMap
+from langchain.schema.runnable import RunnableLambda, RunnableParallel
 
 
 # Formatting for chat history
@@ -96,7 +96,7 @@ class ChatHistory(BaseModel):
     chat_history: List[Tuple[str, str]] = Field(..., extra={"widget": {"type": "chat"}})
 
 
-_inputs = RunnableMap(
+_inputs = RunnableParallel(
     {
         "question": RunnableLambda(
             lambda x: _deidentify_with_replace(

templates/rag-timescale-conversation/rag_timescale_conversation/chain.py

@@ -13,7 +13,7 @@ from langchain.schema.output_parser import StrOutputParser
 from langchain.schema.runnable import (
     RunnableBranch,
     RunnableLambda,
-    RunnableMap,
+    RunnableParallel,
     RunnablePassthrough,
 )
 from langchain.vectorstores.timescalevector import TimescaleVector
@@ -136,7 +136,7 @@ def get_retriever_with_metadata(x):
 
 _retriever = RunnableLambda(get_retriever_with_metadata)
 
-_inputs = RunnableMap(
+_inputs = RunnableParallel(
     {
         "question": lambda x: x["question"],
         "chat_history": lambda x: _format_chat_history(x["chat_history"]),