Rename RunnableMap to RunnableParallel (#11487)

- keep alias for RunnableMap
- update docs to use RunnableParallel and RunnablePassthrough.assign

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docs/docs_skeleton/docs/expression_language/cookbook/memory.ipynb

@@ -17,9 +17,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "from operator import itemgetter\n",
     "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.memory import ConversationBufferMemory\n",
-    "from langchain.schema.runnable import RunnableMap\n",
+    "from langchain.schema.runnable import RunnablePassthrough\n",
     "from langchain.prompts import ChatPromptTemplate, MessagesPlaceholder\n",
     "\n",
     "model = ChatOpenAI()\n",
@@ -27,7 +28,7 @@
     "    (\"system\", \"You are a helpful chatbot\"),\n",
     "    MessagesPlaceholder(variable_name=\"history\"),\n",
     "    (\"human\", \"{input}\")\n",
-    "])"
+    "])\n"
    ]
   },
   {
@@ -37,7 +38,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "memory = ConversationBufferMemory(return_messages=True)"
+    "memory = ConversationBufferMemory(return_messages=True)\n"
    ]
   },
   {
@@ -58,7 +59,7 @@
     }
    ],
    "source": [
-    "memory.load_memory_variables({})"
+    "memory.load_memory_variables({})\n"
    ]
   },
   {
@@ -68,13 +69,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "chain = RunnableMap({\n",
-    "    \"input\": lambda x: x[\"input\"],\n",
-    "    \"memory\": memory.load_memory_variables\n",
-    "}) | {\n",
-    "    \"input\": lambda x: x[\"input\"],\n",
-    "    \"history\": lambda x: x[\"memory\"][\"history\"]\n",
-    "} | prompt | model"
+    "chain = RunnablePassthrough.assign(\n",
+    "    memory=memory.load_memory_variables | itemgetter(\"history\")\n",
+    ") | prompt | model\n"
    ]
   },
   {
@@ -97,7 +94,7 @@
    "source": [
     "inputs = {\"input\": \"hi im bob\"}\n",
     "response = chain.invoke(inputs)\n",
-    "response"
+    "response\n"
    ]
   },
   {
@@ -107,7 +104,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "memory.save_context(inputs, {\"output\": response.content})"
+    "memory.save_context(inputs, {\"output\": response.content})\n"
    ]
   },
   {
@@ -129,7 +126,7 @@
     }
    ],
    "source": [
-    "memory.load_memory_variables({})"
+    "memory.load_memory_variables({})\n"
    ]
   },
   {
@@ -152,7 +149,7 @@
    "source": [
     "inputs = {\"input\": \"whats my name\"}\n",
     "response = chain.invoke(inputs)\n",
-    "response"
+    "response\n"
    ]
   }
  ],

docs/docs_skeleton/docs/expression_language/cookbook/prompt_llm_parser.ipynb

@@ -8,7 +8,7 @@
     "---\n",
     "sidebar_position: 0\n",
     "title: Prompt + LLM\n",
-    "---"
+    "---\n"
    ]
   },
   {
@@ -47,7 +47,7 @@
     "\n",
     "prompt = ChatPromptTemplate.from_template(\"tell me a joke about {foo}\")\n",
     "model = ChatOpenAI()\n",
-    "chain = prompt | model"
+    "chain = prompt | model\n"
    ]
   },
   {
@@ -68,7 +68,7 @@
     }
    ],
    "source": [
-    "chain.invoke({\"foo\": \"bears\"})"
+    "chain.invoke({\"foo\": \"bears\"})\n"
    ]
   },
   {
@@ -94,7 +94,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "chain = prompt | model.bind(stop=[\"\\n\"])"
+    "chain = prompt | model.bind(stop=[\"\\n\"])\n"
    ]
   },
   {
@@ -115,7 +115,7 @@
     }
    ],
    "source": [
-    "chain.invoke({\"foo\": \"bears\"})"
+    "chain.invoke({\"foo\": \"bears\"})\n"
    ]
   },
   {
@@ -153,7 +153,7 @@
     "      }\n",
     "    }\n",
     "  ]\n",
-    "chain = prompt | model.bind(function_call= {\"name\": \"joke\"}, functions= functions)"
+    "chain = prompt | model.bind(function_call= {\"name\": \"joke\"}, functions= functions)\n"
    ]
   },
   {
@@ -174,7 +174,7 @@
     }
    ],
    "source": [
-    "chain.invoke({\"foo\": \"bears\"}, config={})"
+    "chain.invoke({\"foo\": \"bears\"}, config={})\n"
    ]
   },
   {
@@ -196,7 +196,7 @@
    "source": [
     "from langchain.schema.output_parser import StrOutputParser\n",
     "\n",
-    "chain = prompt | model | StrOutputParser()"
+    "chain = prompt | model | StrOutputParser()\n"
    ]
   },
   {
@@ -225,7 +225,7 @@
     }
    ],
    "source": [
-    "chain.invoke({\"foo\": \"bears\"})"
+    "chain.invoke({\"foo\": \"bears\"})\n"
    ]
   },
   {
@@ -251,7 +251,7 @@
     "    prompt \n",
     "    | model.bind(function_call= {\"name\": \"joke\"}, functions= functions) \n",
     "    | JsonOutputFunctionsParser()\n",
-    ")"
+    ")\n"
    ]
   },
   {
@@ -273,7 +273,7 @@
     }
    ],
    "source": [
-    "chain.invoke({\"foo\": \"bears\"})"
+    "chain.invoke({\"foo\": \"bears\"})\n"
    ]
   },
   {
@@ -289,7 +289,7 @@
     "    prompt \n",
     "    | model.bind(function_call= {\"name\": \"joke\"}, functions= functions) \n",
     "    | JsonKeyOutputFunctionsParser(key_name=\"setup\")\n",
-    ")"
+    ")\n"
    ]
   },
   {
@@ -310,7 +310,7 @@
     }
    ],
    "source": [
-    "chain.invoke({\"foo\": \"bears\"})"
+    "chain.invoke({\"foo\": \"bears\"})\n"
    ]
   },
   {
@@ -332,13 +332,13 @@
    "source": [
     "from langchain.schema.runnable import RunnableMap, RunnablePassthrough\n",
     "\n",
-    "map_ = RunnableMap({\"foo\": RunnablePassthrough()})\n",
+    "map_ = RunnableMap(foo=RunnablePassthrough())\n",
     "chain = (\n",
     "    map_ \n",
     "    | prompt\n",
     "    | model.bind(function_call= {\"name\": \"joke\"}, functions= functions) \n",
     "    | JsonKeyOutputFunctionsParser(key_name=\"setup\")\n",
-    ")"
+    ")\n"
    ]
   },
   {
@@ -359,7 +359,7 @@
     }
    ],
    "source": [
-    "chain.invoke(\"bears\")"
+    "chain.invoke(\"bears\")\n"
    ]
   },
   {
@@ -382,7 +382,7 @@
     "    | prompt\n",
     "    | model.bind(function_call= {\"name\": \"joke\"}, functions= functions) \n",
     "    | JsonKeyOutputFunctionsParser(key_name=\"setup\")\n",
-    ")"
+    ")\n"
    ]
   },
   {
@@ -403,7 +403,7 @@
     }
    ],
    "source": [
-    "chain.invoke(\"bears\")"
+    "chain.invoke(\"bears\")\n"
    ]
   }
  ],

docs/docs_skeleton/docs/expression_language/cookbook/retrieval.ipynb

@@ -8,7 +8,7 @@
     "---\n",
     "sidebar_position: 1\n",
     "title: RAG\n",
-    "---"
+    "---\n"
    ]
   },
   {
@@ -26,7 +26,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "!pip install langchain openai faiss-cpu tiktoken"
+    "!pip install langchain openai faiss-cpu tiktoken\n"
    ]
   },
   {
@@ -43,7 +43,7 @@
     "from langchain.embeddings import OpenAIEmbeddings\n",
     "from langchain.schema.output_parser import StrOutputParser\n",
     "from langchain.schema.runnable import RunnablePassthrough\n",
-    "from langchain.vectorstores import FAISS"
+    "from langchain.vectorstores import FAISS\n"
    ]
   },
   {
@@ -63,7 +63,7 @@
     "\"\"\"\n",
     "prompt = ChatPromptTemplate.from_template(template)\n",
     "\n",
-    "model = ChatOpenAI()"
+    "model = ChatOpenAI()\n"
    ]
   },
   {
@@ -78,7 +78,7 @@
     "    | prompt \n",
     "    | model \n",
     "    | StrOutputParser()\n",
-    ")"
+    ")\n"
    ]
   },
   {
@@ -99,7 +99,7 @@
     }
    ],
    "source": [
-    "chain.invoke(\"where did harrison work?\")"
+    "chain.invoke(\"where did harrison work?\")\n"
    ]
   },
   {
@@ -122,7 +122,7 @@
     "    \"context\": itemgetter(\"question\") | retriever, \n",
     "    \"question\": itemgetter(\"question\"), \n",
     "    \"language\": itemgetter(\"language\")\n",
-    "} | prompt | model | StrOutputParser()"
+    "} | prompt | model | StrOutputParser()\n"
    ]
   },
   {
@@ -143,7 +143,7 @@
     }
    ],
    "source": [
-    "chain.invoke({\"question\": \"where did harrison work\", \"language\": \"italian\"})"
+    "chain.invoke({\"question\": \"where did harrison work\", \"language\": \"italian\"})\n"
    ]
   },
   {
@@ -164,7 +164,7 @@
    "outputs": [],
    "source": [
     "from langchain.schema.runnable import RunnableMap\n",
-    "from langchain.schema import format_document"
+    "from langchain.schema import format_document\n"
    ]
   },
   {
@@ -182,7 +182,7 @@
     "{chat_history}\n",
     "Follow Up Input: {question}\n",
     "Standalone question:\"\"\"\n",
-    "CONDENSE_QUESTION_PROMPT = PromptTemplate.from_template(_template)"
+    "CONDENSE_QUESTION_PROMPT = PromptTemplate.from_template(_template)\n"
    ]
   },
   {
@@ -197,7 +197,7 @@
     "\n",
     "Question: {question}\n",
     "\"\"\"\n",
-    "ANSWER_PROMPT = ChatPromptTemplate.from_template(template)"
+    "ANSWER_PROMPT = ChatPromptTemplate.from_template(template)\n"
    ]
   },
   {
@@ -210,7 +210,7 @@
     "DEFAULT_DOCUMENT_PROMPT = PromptTemplate.from_template(template=\"{page_content}\")\n",
     "def _combine_documents(docs, document_prompt = DEFAULT_DOCUMENT_PROMPT, document_separator=\"\\n\\n\"):\n",
     "    doc_strings = [format_document(doc, document_prompt) for doc in docs]\n",
-    "    return document_separator.join(doc_strings)"
+    "    return document_separator.join(doc_strings)\n"
    ]
   },
   {
@@ -227,7 +227,7 @@
     "        human = \"Human: \" + dialogue_turn[0]\n",
     "        ai = \"Assistant: \" + dialogue_turn[1]\n",
     "        buffer += \"\\n\" + \"\\n\".join([human, ai])\n",
-    "    return buffer"
+    "    return buffer\n"
    ]
   },
   {
@@ -238,18 +238,15 @@
    "outputs": [],
    "source": [
     "_inputs = RunnableMap(\n",
-    "    {\n",
-    "        \"standalone_question\": {\n",
-    "            \"question\": lambda x: x[\"question\"],\n",
-    "            \"chat_history\": lambda x: _format_chat_history(x['chat_history'])\n",
-    "        } | CONDENSE_QUESTION_PROMPT | ChatOpenAI(temperature=0) | StrOutputParser(),\n",
-    "    }\n",
+    "    standalone_question=RunnablePassthrough.assign(\n",
+    "        chat_history=lambda x: _format_chat_history(x['chat_history'])\n",
+    "    ) | CONDENSE_QUESTION_PROMPT | ChatOpenAI(temperature=0) | StrOutputParser(),\n",
     ")\n",
     "_context = {\n",
     "    \"context\": itemgetter(\"standalone_question\") | retriever | _combine_documents,\n",
     "    \"question\": lambda x: x[\"standalone_question\"]\n",
     "}\n",
-    "conversational_qa_chain = _inputs | _context | ANSWER_PROMPT | ChatOpenAI()"
+    "conversational_qa_chain = _inputs | _context | ANSWER_PROMPT | ChatOpenAI()\n"
    ]
   },
   {
@@ -273,7 +270,7 @@
     "conversational_qa_chain.invoke({\n",
     "    \"question\": \"where did harrison work?\",\n",
     "    \"chat_history\": [],\n",
-    "})"
+    "})\n"
    ]
   },
   {
@@ -297,7 +294,7 @@
     "conversational_qa_chain.invoke({\n",
     "    \"question\": \"where did he work?\",\n",
     "    \"chat_history\": [(\"Who wrote this notebook?\", \"Harrison\")],\n",
-    "})"
+    "})\n"
    ]
   },
   {
@@ -317,7 +314,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain.memory import ConversationBufferMemory"
+    "from operator import itemgetter\n",
+    "from langchain.memory import ConversationBufferMemory\n"
    ]
   },
   {
@@ -327,7 +325,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "memory = ConversationBufferMemory(return_messages=True, output_key=\"answer\", input_key=\"question\")"
+    "memory = ConversationBufferMemory(return_messages=True, output_key=\"answer\", input_key=\"question\")\n"
    ]
   },
   {
@@ -338,19 +336,10 @@
    "outputs": [],
    "source": [
     "# First we add a step to load memory\n",
-    "# This needs to be a RunnableMap because its the first input\n",
-    "loaded_memory = RunnableMap(\n",
-    "    {\n",
-    "        \"question\": itemgetter(\"question\"),\n",
-    "        \"memory\": memory.load_memory_variables,\n",
-    "    }\n",
+    "# This adds a \"memory\" key to the input object\n",
+    "loaded_memory = RunnablePassthrough.assign(\n",
+    "    chat_history=memory.load_memory_variables | itemgetter(\"history\"),\n",
     ")\n",
-    "# Next we add a step to expand memory into the variables\n",
-    "expanded_memory = {\n",
-    "    \"question\": itemgetter(\"question\"),\n",
-    "    \"chat_history\": lambda x: x[\"memory\"][\"history\"]\n",
-    "}\n",
-    "\n",
     "# Now we calculate the standalone question\n",
     "standalone_question = {\n",
     "    \"standalone_question\": {\n",
@@ -374,7 +363,7 @@
     "    \"docs\": itemgetter(\"docs\"),\n",
     "}\n",
     "# And now we put it all together!\n",
-    "final_chain = loaded_memory | expanded_memory | standalone_question | retrieved_documents | answer"
+    "final_chain = loaded_memory | expanded_memory | standalone_question | retrieved_documents | answer\n"
    ]
   },
   {
@@ -398,7 +387,7 @@
    "source": [
     "inputs = {\"question\": \"where did harrison work?\"}\n",
     "result = final_chain.invoke(inputs)\n",
-    "result"
+    "result\n"
    ]
   },
   {
@@ -411,7 +400,7 @@
     "# Note that the memory does not save automatically\n",
     "# This will be improved in the future\n",
     "# For now you need to save it yourself\n",
-    "memory.save_context(inputs, {\"answer\": result[\"answer\"].content})"
+    "memory.save_context(inputs, {\"answer\": result[\"answer\"].content})\n"
    ]
   },
   {
@@ -433,7 +422,7 @@
     }
    ],
    "source": [
-    "memory.load_memory_variables({})"
+    "memory.load_memory_variables({})\n"
    ]
   }
  ],

docs/docs_skeleton/docs/expression_language/cookbook/sql_db.ipynb

@@ -8,7 +8,7 @@
     "---\n",
     "sidebar_position: 3\n",
     "title: Querying a SQL DB\n",
-    "---"
+    "---\n"
    ]
   },
   {
@@ -33,7 +33,7 @@
     "\n",
     "Question: {question}\n",
     "SQL Query:\"\"\"\n",
-    "prompt = ChatPromptTemplate.from_template(template)"
+    "prompt = ChatPromptTemplate.from_template(template)\n"
    ]
   },
   {
@@ -43,7 +43,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain.utilities import SQLDatabase"
+    "from langchain.utilities import SQLDatabase\n"
    ]
   },
   {
@@ -61,7 +61,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "db = SQLDatabase.from_uri(\"sqlite:///./Chinook.db\")"
+    "db = SQLDatabase.from_uri(\"sqlite:///./Chinook.db\")\n"
    ]
   },
   {
@@ -72,7 +72,7 @@
    "outputs": [],
    "source": [
     "def get_schema(_):\n",
-    "    return db.get_table_info()"
+    "    return db.get_table_info()\n"
    ]
   },
   {
@@ -83,7 +83,7 @@
    "outputs": [],
    "source": [
     "def run_query(query):\n",
-    "    return db.run(query)"
+    "    return db.run(query)\n"
    ]
   },
   {
@@ -93,24 +93,18 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from operator import itemgetter\n",
-    "\n",
     "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.schema.output_parser import StrOutputParser\n",
-    "from langchain.schema.runnable import RunnableLambda, RunnableMap\n",
+    "from langchain.schema.runnable import RunnablePassthrough\n",
     "\n",
     "model = ChatOpenAI()\n",
     "\n",
-    "inputs = {\n",
-    "    \"schema\": RunnableLambda(get_schema),\n",
-    "    \"question\": itemgetter(\"question\")\n",
-    "}\n",
     "sql_response = (\n",
-    "        RunnableMap(inputs)\n",
+    "        RunnablePassthrough.assign(schema=get_schema)\n",
     "        | prompt\n",
     "        | model.bind(stop=[\"\\nSQLResult:\"])\n",
     "        | StrOutputParser()\n",
-    "    )"
+    "    )\n"
    ]
   },
   {
@@ -131,7 +125,7 @@
     }
    ],
    "source": [
-    "sql_response.invoke({\"question\": \"How many employees are there?\"})"
+    "sql_response.invoke({\"question\": \"How many employees are there?\"})\n"
    ]
   },
   {
@@ -147,7 +141,7 @@
     "Question: {question}\n",
     "SQL Query: {query}\n",
     "SQL Response: {response}\"\"\"\n",
-    "prompt_response = ChatPromptTemplate.from_template(template)"
+    "prompt_response = ChatPromptTemplate.from_template(template)\n"
    ]
   },
   {
@@ -158,19 +152,14 @@
    "outputs": [],
    "source": [
     "full_chain = (\n",
-    "    RunnableMap({\n",
-    "        \"question\": itemgetter(\"question\"),\n",
-    "        \"query\": sql_response,\n",
-    "    }) \n",
-    "    | {\n",
-    "        \"schema\": RunnableLambda(get_schema),\n",
-    "        \"question\": itemgetter(\"question\"),\n",
-    "        \"query\": itemgetter(\"query\"),\n",
-    "        \"response\": lambda x: db.run(x[\"query\"])    \n",
-    "    } \n",
+    "    RunnablePassthrough.assign(query=sql_response) \n",
+    "    | RunnablePassthrough.assign(\n",
+    "        schema=get_schema,\n",
+    "        response=lambda x: db.run(x[\"query\"]),\n",
+    "    )\n",
     "    | prompt_response \n",
     "    | model\n",
-    ")"
+    ")\n"
    ]
   },
   {
@@ -191,7 +180,7 @@
     }
    ],
    "source": [
-    "full_chain.invoke({\"question\": \"How many employees are there?\"})"
+    "full_chain.invoke({\"question\": \"How many employees are there?\"})\n"
    ]
   },
   {

docs/docs_skeleton/docs/expression_language/how_to/map.ipynb

@@ -5,9 +5,9 @@
    "id": "b022ab74-794d-4c54-ad47-ff9549ddb9d2",
    "metadata": {},
    "source": [
-    "# Use RunnableMaps\n",
+    "# Use RunnableParallel/RunnableMap\n",
     "\n",
-    "RunnableMaps make it easy to execute multiple Runnables in parallel, and to return the output of these Runnables as a map."
+    "RunnableParallel (aka. RunnableMap) makes it easy to execute multiple Runnables in parallel, and to return the output of these Runnables as a map."
    ]
   },
   {
@@ -31,16 +31,16 @@
    "source": [
     "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.prompts import ChatPromptTemplate\n",
-    "from langchain.schema.runnable import RunnableMap\n",
+    "from langchain.schema.runnable import RunnableParallel\n",
     "\n",
     "\n",
     "model = ChatOpenAI()\n",
     "joke_chain = ChatPromptTemplate.from_template(\"tell me a joke about {topic}\") | model\n",
     "poem_chain = ChatPromptTemplate.from_template(\"write a 2-line poem about {topic}\") | model\n",
     "\n",
-    "map_chain = RunnableMap({\"joke\": joke_chain, \"poem\": poem_chain,})\n",
+    "map_chain = RunnableParallel(joke=joke_chain, poem=poem_chain)\n",
     "\n",
-    "map_chain.invoke({\"topic\": \"bear\"})"
+    "map_chain.invoke({\"topic\": \"bear\"})\n"
    ]
   },
   {
@@ -91,7 +91,7 @@
     "    | StrOutputParser()\n",
     ")\n",
     "\n",
-    "retrieval_chain.invoke(\"where did harrison work?\")"
+    "retrieval_chain.invoke(\"where did harrison work?\")\n"
    ]
   },
   {
@@ -131,7 +131,7 @@
    "source": [
     "%%timeit\n",
     "\n",
-    "joke_chain.invoke({\"topic\": \"bear\"})"
+    "joke_chain.invoke({\"topic\": \"bear\"})\n"
    ]
   },
   {
@@ -151,7 +151,7 @@
    "source": [
     "%%timeit\n",
     "\n",
-    "poem_chain.invoke({\"topic\": \"bear\"})"
+    "poem_chain.invoke({\"topic\": \"bear\"})\n"
    ]
   },
   {
@@ -171,7 +171,7 @@
    "source": [
     "%%timeit\n",
     "\n",
-    "map_chain.invoke({\"topic\": \"bear\"})"
+    "map_chain.invoke({\"topic\": \"bear\"})\n"
    ]
   }
  ],

docs/docs_skeleton/docs/expression_language/interface.ipynb

@@ -131,7 +131,7 @@
    ],
    "source": [
     "# The input schema of the chain is the input schema of its first part, the prompt.\n",
-    "chain.input_schema.schema()"
+    "chain.input_schema.schema()\n"
    ]
   },
   {
@@ -244,7 +244,7 @@
    ],
    "source": [
     "# The output schema of the chain is the output schema of its last part, in this case a ChatModel, which outputs a ChatMessage\n",
-    "chain.output_schema.schema()"
+    "chain.output_schema.schema()\n"
    ]
   },
   {
@@ -783,7 +783,7 @@
    ],
    "source": [
     "async for chunk in retrieval_chain.astream_log(\"where did harrison work?\", include_names=['Docs'], diff=False):\n",
-    "    print(chunk)"
+    "    print(chunk)\n"
    ]
   },
   {
@@ -793,7 +793,7 @@
    "source": [
     "## Parallelism\n",
     "\n",
-    "Let's take a look at how LangChain Expression Language support parallel requests as much as possible. For example, when using a RunnableMap (often written as a dictionary) it executes each element in parallel."
+    "Let's take a look at how LangChain Expression Language support parallel requests as much as possible. For example, when using a RunnableParallel (often written as a dictionary) it executes each element in parallel."
    ]
   },
   {
@@ -803,13 +803,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain.schema.runnable import RunnableMap\n",
+    "from langchain.schema.runnable import RunnableParallel\n",
     "chain1 = ChatPromptTemplate.from_template(\"tell me a joke about {topic}\") | model\n",
     "chain2 = ChatPromptTemplate.from_template(\"write a short (2 line) poem about {topic}\") | model\n",
-    "combined = RunnableMap({\n",
-    "    \"joke\": chain1,\n",
-    "    \"poem\": chain2,\n",
-    "})\n"
+    "combined = RunnableParallel(joke=chain1, poem=chain2)\n"
    ]
   },
   {

docs/docs_skeleton/docs/integrations/chat/fireworks.ipynb

@@ -27,7 +27,7 @@
    "source": [
     "from langchain.chat_models.fireworks import ChatFireworks\n",
     "from langchain.schema import SystemMessage, HumanMessage\n",
-    "import os"
+    "import os\n"
    ]
   },
   {
@@ -56,7 +56,7 @@
     "    os.environ[\"FIREWORKS_API_KEY\"] = getpass.getpass(\"Fireworks API Key:\")\n",
     "\n",
     "# Initialize a Fireworks chat model\n",
-    "chat = ChatFireworks(model=\"accounts/fireworks/models/llama-v2-13b-chat\")"
+    "chat = ChatFireworks(model=\"accounts/fireworks/models/llama-v2-13b-chat\")\n"
    ]
   },
   {
@@ -116,7 +116,7 @@
     "chat = ChatFireworks(model=\"accounts/fireworks/models/llama-v2-13b-chat\", model_kwargs={\"temperature\":1, \"max_tokens\": 20, \"top_p\": 1})\n",
     "system_message = SystemMessage(content=\"You are to chat with the user.\")\n",
     "human_message = HumanMessage(content=\"How's the weather today?\")\n",
-    "chat([system_message, human_message])"
+    "chat([system_message, human_message])\n"
    ]
   },
   {
@@ -144,7 +144,7 @@
    "source": [
     "from langchain.chat_models import ChatFireworks\n",
     "from langchain.memory import ConversationBufferMemory\n",
-    "from langchain.schema.runnable import RunnableMap\n",
+    "from langchain.schema.runnable import RunnablePassthrough\n",
     "from langchain.prompts import ChatPromptTemplate, MessagesPlaceholder\n",
     "\n",
     "llm = ChatFireworks(model=\"accounts/fireworks/models/llama-v2-13b-chat\", model_kwargs={\"temperature\":0, \"max_tokens\":64, \"top_p\":1.0})\n",
@@ -152,7 +152,7 @@
     "    (\"system\", \"You are a helpful chatbot that speaks like a pirate.\"),\n",
     "    MessagesPlaceholder(variable_name=\"history\"),\n",
     "    (\"human\", \"{input}\")\n",
-    "])"
+    "])\n"
    ]
   },
   {
@@ -182,7 +182,7 @@
    ],
    "source": [
     "memory = ConversationBufferMemory(return_messages=True)\n",
-    "memory.load_memory_variables({})"
+    "memory.load_memory_variables({})\n"
    ]
   },
   {
@@ -200,13 +200,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "chain = RunnableMap({\n",
-    "    \"input\": lambda x: x[\"input\"],\n",
-    "    \"memory\": memory.load_memory_variables\n",
-    "}) | {\n",
-    "    \"input\": lambda x: x[\"input\"],\n",
-    "    \"history\": lambda x: x[\"memory\"][\"history\"]\n",
-    "} | prompt | llm.bind(stop=[\"\\n\\n\"])"
+    "chain = RunnablePassthrough.assign(\n",
+    "    history=memory.load_memory_variables | (lambda x: x[\"history\"])\n",
+    ") | prompt | llm.bind(stop=[\"\\n\\n\"])\n"
    ]
   },
   {
@@ -237,7 +233,7 @@
    "source": [
     "inputs = {\"input\": \"hi im bob\"}\n",
     "response = chain.invoke(inputs)\n",
-    "response"
+    "response\n"
    ]
   },
   {
@@ -268,7 +264,7 @@
    ],
    "source": [
     "memory.save_context(inputs, {\"output\": response.content})\n",
-    "memory.load_memory_variables({})"
+    "memory.load_memory_variables({})\n"
    ]
   },
   {
@@ -298,7 +294,7 @@
    ],
    "source": [
     "inputs = {\"input\": \"whats my name\"}\n",
-    "chain.invoke(inputs)"
+    "chain.invoke(inputs)\n"
    ]
   }
  ],

docs/docs_skeleton/docs/integrations/llms/opaqueprompts.ipynb

@@ -19,7 +19,7 @@
    "outputs": [],
    "source": [
     "# install the opaqueprompts and langchain packages\n",
-    "! pip install opaqueprompts langchain"
+    "! pip install opaqueprompts langchain\n"
    ]
   },
   {
@@ -40,7 +40,7 @@
     "# Set API keys\n",
     "\n",
     "os.environ['OPAQUEPROMPTS_API_KEY'] = \"<OPAQUEPROMPTS_API_KEY>\"\n",
-    "os.environ['OPENAI_API_KEY'] = \"<OPENAI_API_KEY>\""
+    "os.environ['OPENAI_API_KEY'] = \"<OPENAI_API_KEY>\"\n"
    ]
   },
   {
@@ -59,7 +59,8 @@
    "outputs": [],
    "source": [
     "import langchain\n",
-    "from langchain.chains import LLMChain\nfrom langchain.prompts import PromptTemplate\n",
+    "from langchain.chains import LLMChain\n",
+    "from langchain.prompts import PromptTemplate\n",
     "from langchain.callbacks.stdout import StdOutCallbackHandler\n",
     "from langchain.llms import OpenAI\n",
     "from langchain.memory import ConversationBufferWindowMemory\n",
@@ -117,7 +118,7 @@
     "        {\"question\": \"\"\"Write a message to remind John to do password reset for his website to stay secure.\"\"\"},\n",
     "        callbacks=[StdOutCallbackHandler()],\n",
     "    )\n",
-    ")"
+    ")\n"
    ]
   },
   {
@@ -173,7 +174,7 @@
    "outputs": [],
    "source": [
     "import langchain.utilities.opaqueprompts as op\n",
-    "from langchain.schema.runnable import RunnableMap\n",
+    "from langchain.schema.runnable import RunnablePassthrough\n",
     "from langchain.schema.output_parser import StrOutputParser\n",
     "\n",
     "\n",
@@ -181,19 +182,16 @@
     "llm = OpenAI()\n",
     "pg_chain = (\n",
     "    op.sanitize\n",
-    "    | RunnableMap(\n",
-    "        {\n",
-    "            \"response\": (lambda x: x[\"sanitized_input\"])\n",
+    "    | RunnablePassthrough.assign(\n",
+    "        response=(lambda x: x[\"sanitized_input\"])\n",
     "            | prompt\n",
     "            | llm\n",
     "            | StrOutputParser(),\n",
-    "            \"secure_context\": lambda x: x[\"secure_context\"],\n",
-    "        }\n",
     "    )\n",
     "    | (lambda x: op.desanitize(x[\"response\"], x[\"secure_context\"]))\n",
     ")\n",
     "\n",
-    "pg_chain.invoke({\"question\": \"Write a text message to remind John to do password reset for his website through his email to stay secure.\", \"history\": \"\"})"
+    "pg_chain.invoke({\"question\": \"Write a text message to remind John to do password reset for his website through his email to stay secure.\", \"history\": \"\"})\n"
    ]
   }
  ],