diff --git a/docs/docs_skeleton/docs/expression_language/cookbook/memory.ipynb b/docs/docs_skeleton/docs/expression_language/cookbook/memory.ipynb index bef7e5ed01..779aa00a88 100644 --- a/docs/docs_skeleton/docs/expression_language/cookbook/memory.ipynb +++ b/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" ] } ], diff --git a/docs/docs_skeleton/docs/expression_language/cookbook/prompt_llm_parser.ipynb b/docs/docs_skeleton/docs/expression_language/cookbook/prompt_llm_parser.ipynb index 1b670904d5..5af7875e7f 100644 --- a/docs/docs_skeleton/docs/expression_language/cookbook/prompt_llm_parser.ipynb +++ b/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" ] } ], diff --git a/docs/docs_skeleton/docs/expression_language/cookbook/retrieval.ipynb b/docs/docs_skeleton/docs/expression_language/cookbook/retrieval.ipynb index c9c9807e48..431b4e84c6 100644 --- a/docs/docs_skeleton/docs/expression_language/cookbook/retrieval.ipynb +++ b/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" ] } ], diff --git a/docs/docs_skeleton/docs/expression_language/cookbook/sql_db.ipynb b/docs/docs_skeleton/docs/expression_language/cookbook/sql_db.ipynb index 0cf0748009..2c9a792438 100644 --- a/docs/docs_skeleton/docs/expression_language/cookbook/sql_db.ipynb +++ b/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" ] }, { diff --git a/docs/docs_skeleton/docs/expression_language/how_to/map.ipynb b/docs/docs_skeleton/docs/expression_language/how_to/map.ipynb index 0d04ad25d0..428a1fa6ac 100644 --- a/docs/docs_skeleton/docs/expression_language/how_to/map.ipynb +++ b/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" ] } ], diff --git a/docs/docs_skeleton/docs/expression_language/interface.ipynb b/docs/docs_skeleton/docs/expression_language/interface.ipynb index 418bc86f60..da52fcb77f 100644 --- a/docs/docs_skeleton/docs/expression_language/interface.ipynb +++ b/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" ] }, { diff --git a/docs/docs_skeleton/docs/integrations/chat/fireworks.ipynb b/docs/docs_skeleton/docs/integrations/chat/fireworks.ipynb index bbb2a48839..38326eb354 100644 --- a/docs/docs_skeleton/docs/integrations/chat/fireworks.ipynb +++ b/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" ] } ], diff --git a/docs/docs_skeleton/docs/integrations/llms/opaqueprompts.ipynb b/docs/docs_skeleton/docs/integrations/llms/opaqueprompts.ipynb index c2ec73fe41..0ce5ea987a 100644 --- a/docs/docs_skeleton/docs/integrations/llms/opaqueprompts.ipynb +++ b/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'] = \"\"\n", - "os.environ['OPENAI_API_KEY'] = \"\"" + "os.environ['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" ] } ], diff --git a/libs/langchain/langchain/chains/sql_database/query.py b/libs/langchain/langchain/chains/sql_database/query.py index e874555e0e..e868c2242a 100644 --- a/libs/langchain/langchain/chains/sql_database/query.py +++ b/libs/langchain/langchain/chains/sql_database/query.py @@ -4,7 +4,7 @@ from langchain.chains.sql_database.prompt import PROMPT, SQL_PROMPTS from langchain.schema.language_model import BaseLanguageModel from langchain.schema.output_parser import NoOpOutputParser from langchain.schema.prompt_template import BasePromptTemplate -from langchain.schema.runnable import RunnableMap, RunnableSequence +from langchain.schema.runnable import RunnableParallel, RunnableSequence from langchain.utilities.sql_database import SQLDatabase @@ -60,7 +60,7 @@ def create_sql_query_chain( if "dialect" in prompt_to_use.input_variables: inputs["dialect"] = lambda _: (db.dialect, prompt_to_use) return ( - RunnableMap(inputs) + RunnableParallel(inputs) | prompt_to_use | llm.bind(stop=["\nSQLResult:"]) | NoOpOutputParser() diff --git a/libs/langchain/langchain/schema/runnable/__init__.py b/libs/langchain/langchain/schema/runnable/__init__.py index 430b1b16b6..2fc7e57b14 100644 --- a/libs/langchain/langchain/schema/runnable/__init__.py +++ b/libs/langchain/langchain/schema/runnable/__init__.py @@ -5,6 +5,7 @@ from langchain.schema.runnable.base import ( RunnableGenerator, RunnableLambda, RunnableMap, + RunnableParallel, RunnableSequence, RunnableSerializable, ) @@ -30,6 +31,7 @@ __all__ = [ "RunnableGenerator", "RunnableLambda", "RunnableMap", + "RunnableParallel", "RunnablePassthrough", "RunnableSequence", "RunnableWithFallbacks", diff --git a/libs/langchain/langchain/schema/runnable/base.py b/libs/langchain/langchain/schema/runnable/base.py index 5cecbadbdf..30ca2d816c 100644 --- a/libs/langchain/langchain/schema/runnable/base.py +++ b/libs/langchain/langchain/schema/runnable/base.py @@ -1490,7 +1490,7 @@ class RunnableSequence(RunnableSerializable[Input, Output]): yield chunk -class RunnableMap(RunnableSerializable[Input, Dict[str, Any]]): +class RunnableParallel(RunnableSerializable[Input, Dict[str, Any]]): """ A runnable that runs a mapping of runnables in parallel, and returns a mapping of their outputs. @@ -1500,16 +1500,27 @@ class RunnableMap(RunnableSerializable[Input, Dict[str, Any]]): def __init__( self, - steps: Mapping[ - str, - Union[ - Runnable[Input, Any], - Callable[[Input], Any], - Mapping[str, Union[Runnable[Input, Any], Callable[[Input], Any]]], - ], + __steps: Optional[ + Mapping[ + str, + Union[ + Runnable[Input, Any], + Callable[[Input], Any], + Mapping[str, Union[Runnable[Input, Any], Callable[[Input], Any]]], + ], + ] + ] = None, + **kwargs: Union[ + Runnable[Input, Any], + Callable[[Input], Any], + Mapping[str, Union[Runnable[Input, Any], Callable[[Input], Any]]], ], ) -> None: - super().__init__(steps={key: coerce_to_runnable(r) for key, r in steps.items()}) + merged = {**__steps} if __steps is not None else {} + merged.update(kwargs) + super().__init__( + steps={key: coerce_to_runnable(r) for key, r in merged.items()} + ) @classmethod def is_lc_serializable(cls) -> bool: @@ -1538,7 +1549,7 @@ class RunnableMap(RunnableSerializable[Input, Dict[str, Any]]): ): # This is correct, but pydantic typings/mypy don't think so. return create_model( # type: ignore[call-overload] - "RunnableMapInput", + "RunnableParallelInput", **{ k: (v.annotation, v.default) for step in self.steps.values() @@ -1553,7 +1564,7 @@ class RunnableMap(RunnableSerializable[Input, Dict[str, Any]]): def output_schema(self) -> Type[BaseModel]: # This is correct, but pydantic typings/mypy don't think so. return create_model( # type: ignore[call-overload] - "RunnableMapOutput", + "RunnableParallelOutput", **{k: (v.OutputType, None) for k, v in self.steps.items()}, ) @@ -1797,6 +1808,10 @@ class RunnableMap(RunnableSerializable[Input, Dict[str, Any]]): yield chunk +# We support both names +RunnableMap = RunnableParallel + + class RunnableGenerator(Runnable[Input, Output]): """ A runnable that runs a generator function. @@ -2435,10 +2450,7 @@ def coerce_to_runnable(thing: RunnableLike) -> Runnable[Input, Output]: elif callable(thing): return RunnableLambda(cast(Callable[[Input], Output], thing)) elif isinstance(thing, dict): - runnables: Mapping[str, Runnable[Any, Any]] = { - key: coerce_to_runnable(r) for key, r in thing.items() - } - return cast(Runnable[Input, Output], RunnableMap(steps=runnables)) + return cast(Runnable[Input, Output], RunnableParallel(thing)) else: raise TypeError( f"Expected a Runnable, callable or dict." diff --git a/libs/langchain/langchain/schema/runnable/passthrough.py b/libs/langchain/langchain/schema/runnable/passthrough.py index 79b743c5b4..65730b9f80 100644 --- a/libs/langchain/langchain/schema/runnable/passthrough.py +++ b/libs/langchain/langchain/schema/runnable/passthrough.py @@ -21,7 +21,7 @@ from langchain.pydantic_v1 import BaseModel, create_model from langchain.schema.runnable.base import ( Input, Runnable, - RunnableMap, + RunnableParallel, RunnableSerializable, ) from langchain.schema.runnable.config import RunnableConfig, get_executor_for_config @@ -83,7 +83,7 @@ class RunnablePassthrough(RunnableSerializable[Input, Input]): A runnable that merges the Dict input with the output produced by the mapping argument. """ - return RunnableAssign(RunnableMap(kwargs)) + return RunnableAssign(RunnableParallel(kwargs)) def invoke(self, input: Input, config: Optional[RunnableConfig] = None) -> Input: return self._call_with_config(identity, input, config) @@ -119,9 +119,9 @@ class RunnableAssign(RunnableSerializable[Dict[str, Any], Dict[str, Any]]): A runnable that assigns key-value pairs to Dict[str, Any] inputs. """ - mapper: RunnableMap[Dict[str, Any]] + mapper: RunnableParallel[Dict[str, Any]] - def __init__(self, mapper: RunnableMap[Dict[str, Any]], **kwargs: Any) -> None: + def __init__(self, mapper: RunnableParallel[Dict[str, Any]], **kwargs: Any) -> None: super().__init__(mapper=mapper, **kwargs) @classmethod diff --git a/libs/langchain/tests/integration_tests/llms/test_opaqueprompts.py b/libs/langchain/tests/integration_tests/llms/test_opaqueprompts.py index c9d0b17567..9efde28caf 100644 --- a/libs/langchain/tests/integration_tests/llms/test_opaqueprompts.py +++ b/libs/langchain/tests/integration_tests/llms/test_opaqueprompts.py @@ -5,7 +5,7 @@ from langchain.llms.opaqueprompts import OpaquePrompts from langchain.memory import ConversationBufferWindowMemory from langchain.prompts import PromptTemplate from langchain.schema.output_parser import StrOutputParser -from langchain.schema.runnable import RunnableMap +from langchain.schema.runnable import RunnableParallel prompt_template = """ As an AI assistant, you will answer questions according to given context. @@ -64,14 +64,12 @@ def test_opaqueprompts_functions() -> None: llm = OpenAI() pg_chain = ( op.sanitize - | RunnableMap( - { - "response": (lambda x: x["sanitized_input"]) # type: ignore - | prompt - | llm - | StrOutputParser(), - "secure_context": lambda x: x["secure_context"], - } + | RunnableParallel( + secure_context=lambda x: x["secure_context"], # type: ignore + response=(lambda x: x["sanitized_input"]) # type: ignore + | prompt + | llm + | StrOutputParser(), ) | (lambda x: op.desanitize(x["response"], x["secure_context"])) ) diff --git a/libs/langchain/tests/unit_tests/schema/runnable/__snapshots__/test_runnable.ambr b/libs/langchain/tests/unit_tests/schema/runnable/__snapshots__/test_runnable.ambr index 7fc8ba8c8d..15d2e82970 100644 --- a/libs/langchain/tests/unit_tests/schema/runnable/__snapshots__/test_runnable.ambr +++ b/libs/langchain/tests/unit_tests/schema/runnable/__snapshots__/test_runnable.ambr @@ -629,7 +629,7 @@ "langchain", "schema", "runnable", - "RunnableMap" + "RunnableParallel" ], "kwargs": { "steps": { @@ -643,7 +643,7 @@ "base", "RunnableLambda" ], - "repr": "RunnableLambda(...)" + "repr": "RunnableLambda(lambda x: x['key'])" }, "input": { "lc": 1, @@ -652,7 +652,7 @@ "langchain", "schema", "runnable", - "RunnableMap" + "RunnableParallel" ], "kwargs": { "steps": { @@ -666,7 +666,7 @@ "base", "RunnableLambda" ], - "repr": "RunnableLambda(...)" + "repr": "RunnableLambda(lambda x: x['question'])" } } } @@ -709,7 +709,7 @@ "langchain", "schema", "runnable", - "RunnableMap" + "RunnableParallel" ], "kwargs": { "steps": { @@ -1438,7 +1438,7 @@ "langchain", "schema", "runnable", - "RunnableMap" + "RunnableParallel" ], "kwargs": { "steps": { @@ -1461,7 +1461,7 @@ "langchain", "schema", "runnable", - "RunnableMap" + "RunnableParallel" ], "kwargs": { "steps": { @@ -3455,7 +3455,7 @@ "langchain", "schema", "runnable", - "RunnableMap" + "RunnableParallel" ], "kwargs": { "steps": { @@ -3769,7 +3769,7 @@ "langchain", "schema", "runnable", - "RunnableMap" + "RunnableParallel" ], "kwargs": { "steps": { @@ -3910,7 +3910,7 @@ "langchain", "schema", "runnable", - "RunnableMap" + "RunnableParallel" ], "kwargs": { "steps": { diff --git a/libs/langchain/tests/unit_tests/schema/runnable/test_runnable.py b/libs/langchain/tests/unit_tests/schema/runnable/test_runnable.py index 81da3b0c97..f9ebb98245 100644 --- a/libs/langchain/tests/unit_tests/schema/runnable/test_runnable.py +++ b/libs/langchain/tests/unit_tests/schema/runnable/test_runnable.py @@ -53,7 +53,7 @@ from langchain.schema.runnable import ( RunnableBranch, RunnableConfig, RunnableLambda, - RunnableMap, + RunnableParallel, RunnablePassthrough, RunnableSequence, RunnableWithFallbacks, @@ -491,7 +491,7 @@ def test_schemas(snapshot: SnapshotAssertion) -> None: "properties": {"name": {"title": "Name", "type": "string"}}, } assert seq_w_map.output_schema.schema() == { - "title": "RunnableMapOutput", + "title": "RunnableParallelOutput", "type": "object", "properties": { "original": {"title": "Original", "type": "string"}, @@ -593,7 +593,7 @@ def test_schema_complex_seq() -> None: ) assert chain2.input_schema.schema() == { - "title": "RunnableMapInput", + "title": "RunnableParallelInput", "type": "object", "properties": { "person": {"title": "Person", "type": "string"}, @@ -1656,12 +1656,12 @@ async def test_stream_log_retriever() -> None: RunLogPatch( { "op": "add", - "path": "/logs/RunnableMap", + "path": "/logs/RunnableParallel", "value": { "end_time": None, "final_output": None, "metadata": {}, - "name": "RunnableMap", + "name": "RunnableParallel", "start_time": "2023-01-01T00:00:00.000", "streamed_output_str": [], "tags": ["seq:step:1"], @@ -1733,7 +1733,7 @@ async def test_stream_log_retriever() -> None: RunLogPatch( { "op": "add", - "path": "/logs/RunnableMap/final_output", + "path": "/logs/RunnableParallel/final_output", "value": { "documents": [ Document(page_content="foo"), @@ -1744,7 +1744,7 @@ async def test_stream_log_retriever() -> None: }, { "op": "add", - "path": "/logs/RunnableMap/end_time", + "path": "/logs/RunnableParallel/end_time", "value": "2023-01-01T00:00:00.000", }, ), @@ -1792,8 +1792,8 @@ async def test_stream_log_retriever() -> None: "FakeListLLM:2", "Retriever", "RunnableLambda", - "RunnableMap", - "RunnableMap:2", + "RunnableParallel", + "RunnableParallel:2", ] @@ -1977,7 +1977,7 @@ Question: assert repr(chain) == snapshot assert isinstance(chain, RunnableSequence) - assert isinstance(chain.first, RunnableMap) + assert isinstance(chain.first, RunnableParallel) assert chain.middle == [prompt, chat] assert chain.last == parser assert dumps(chain, pretty=True) == snapshot @@ -2013,7 +2013,7 @@ What is your name?""" parent_run = next(r for r in tracer.runs if r.parent_run_id is None) assert len(parent_run.child_runs) == 4 map_run = parent_run.child_runs[0] - assert map_run.name == "RunnableMap" + assert map_run.name == "RunnableParallel" assert len(map_run.child_runs) == 3 @@ -2043,7 +2043,7 @@ def test_seq_prompt_dict(mocker: MockerFixture, snapshot: SnapshotAssertion) -> assert isinstance(chain, RunnableSequence) assert chain.first == prompt assert chain.middle == [RunnableLambda(passthrough)] - assert isinstance(chain.last, RunnableMap) + assert isinstance(chain.last, RunnableParallel) assert dumps(chain, pretty=True) == snapshot # Test invoke @@ -2074,7 +2074,7 @@ def test_seq_prompt_dict(mocker: MockerFixture, snapshot: SnapshotAssertion) -> parent_run = next(r for r in tracer.runs if r.parent_run_id is None) assert len(parent_run.child_runs) == 3 map_run = parent_run.child_runs[2] - assert map_run.name == "RunnableMap" + assert map_run.name == "RunnableParallel" assert len(map_run.child_runs) == 2 @@ -2142,11 +2142,9 @@ async def test_higher_order_lambda_runnable( english_chain = ChatPromptTemplate.from_template( "You are an english major. Answer the question: {question}" ) | FakeListLLM(responses=["2"]) - input_map: Runnable = RunnableMap( - { # type: ignore[arg-type] - "key": lambda x: x["key"], - "input": {"question": lambda x: x["question"]}, - } + input_map: Runnable = RunnableParallel( + key=lambda x: x["key"], + input={"question": lambda x: x["question"]}, ) def router(input: Dict[str, Any]) -> Runnable: @@ -2158,7 +2156,8 @@ async def test_higher_order_lambda_runnable( raise ValueError(f"Unknown key: {input['key']}") chain: Runnable = input_map | router - assert dumps(chain, pretty=True) == snapshot + if sys.version_info >= (3, 9): + assert dumps(chain, pretty=True) == snapshot result = chain.invoke({"key": "math", "question": "2 + 2"}) assert result == "4" @@ -2256,7 +2255,7 @@ def test_seq_prompt_map(mocker: MockerFixture, snapshot: SnapshotAssertion) -> N assert isinstance(chain, RunnableSequence) assert chain.first == prompt assert chain.middle == [RunnableLambda(passthrough)] - assert isinstance(chain.last, RunnableMap) + assert isinstance(chain.last, RunnableParallel) assert dumps(chain, pretty=True) == snapshot # Test invoke @@ -2293,7 +2292,7 @@ def test_seq_prompt_map(mocker: MockerFixture, snapshot: SnapshotAssertion) -> N parent_run = next(r for r in tracer.runs if r.parent_run_id is None) assert len(parent_run.child_runs) == 3 map_run = parent_run.child_runs[2] - assert map_run.name == "RunnableMap" + assert map_run.name == "RunnableParallel" assert len(map_run.child_runs) == 3 @@ -2460,12 +2459,12 @@ async def test_map_astream() -> None: assert final_state.state["logs"]["ChatPromptTemplate"][ "final_output" ] == prompt.invoke({"question": "What is your name?"}) - assert final_state.state["logs"]["RunnableMap"]["name"] == "RunnableMap" + assert final_state.state["logs"]["RunnableParallel"]["name"] == "RunnableParallel" assert sorted(final_state.state["logs"]) == [ "ChatPromptTemplate", "FakeListChatModel", "FakeStreamingListLLM", - "RunnableMap", + "RunnableParallel", "RunnablePassthrough", ] @@ -2505,11 +2504,11 @@ async def test_map_astream() -> None: assert final_state.state["logs"]["ChatPromptTemplate"]["final_output"] == ( prompt.invoke({"question": "What is your name?"}) ) - assert final_state.state["logs"]["RunnableMap"]["name"] == "RunnableMap" + assert final_state.state["logs"]["RunnableParallel"]["name"] == "RunnableParallel" assert sorted(final_state.state["logs"]) == [ "ChatPromptTemplate", "FakeStreamingListLLM", - "RunnableMap", + "RunnableParallel", "RunnablePassthrough", ] @@ -2910,7 +2909,7 @@ def llm_chain_with_fallbacks() -> RunnableSequence: pass_llm = FakeListLLM(responses=["bar"]) prompt = PromptTemplate.from_template("what did baz say to {buz}") - return RunnableMap({"buz": lambda x: x}) | (prompt | error_llm).with_fallbacks( + return RunnableParallel({"buz": lambda x: x}) | (prompt | error_llm).with_fallbacks( [prompt | pass_llm] )