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docs[patch]: update chatbot tutorial and migration guide (#26780)
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ccurme
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@ -9,13 +9,13 @@
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"\n",
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"[`ConversationChain`](https://python.langchain.com/api_reference/langchain/chains/langchain.chains.conversation.base.ConversationChain.html) incorporated a memory of previous messages to sustain a stateful conversation.\n",
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"\n",
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"Some advantages of switching to the LCEL implementation are:\n",
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"Some advantages of switching to the Langgraph implementation are:\n",
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"\n",
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"- Innate support for threads/separate sessions. To make this work with `ConversationChain`, you'd need to instantiate a separate memory class outside the chain.\n",
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"- More explicit parameters. `ConversationChain` contains a hidden default prompt, which can cause confusion.\n",
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"- Streaming support. `ConversationChain` only supports streaming via callbacks.\n",
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"\n",
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"`RunnableWithMessageHistory` implements sessions via configuration parameters. It should be instantiated with a callable that returns a [chat message history](https://python.langchain.com/api_reference/core/chat_history/langchain_core.chat_history.BaseChatMessageHistory.html). By default, it expects this function to take a single argument `session_id`."
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"Langgraph's [checkpointing](https://langchain-ai.github.io/langgraph/how-tos/persistence/) system supports multiple threads or sessions, which can be specified via the `\"thread_id\"` key in its configuration parameters."
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]
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},
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{
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@ -61,9 +61,9 @@
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{
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"data": {
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"text/plain": [
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"{'input': 'how are you?',\n",
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"{'input': \"I'm Bob, how are you?\",\n",
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" 'history': '',\n",
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" 'response': \"Arr matey, I be doin' well on the high seas, plunderin' and pillagin' as usual. How be ye?\"}"
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" 'response': \"Arrr matey, I be a pirate sailin' the high seas. What be yer business with me?\"}"
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]
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},
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"execution_count": 2,
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@ -93,7 +93,30 @@
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" prompt=prompt,\n",
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")\n",
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"\n",
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"chain({\"input\": \"how are you?\"})"
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"chain({\"input\": \"I'm Bob, how are you?\"})"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "53f2c723-178f-470a-8147-54e7cb982211",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{'input': 'What is my name?',\n",
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" 'history': \"Human: I'm Bob, how are you?\\nAI: Arrr matey, I be a pirate sailin' the high seas. What be yer business with me?\",\n",
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" 'response': 'Your name be Bob, matey.'}"
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]
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},
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"execution_count": 3,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"chain({\"input\": \"What is my name?\"})"
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]
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},
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{
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@ -103,111 +126,110 @@
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"source": [
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"</details>\n",
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"\n",
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"## LCEL\n",
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"## Langgraph\n",
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"\n",
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"<details open>"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "666c92a0-b555-4418-a465-6490c1b92570",
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"execution_count": 4,
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"id": "a59b910c-0d02-41aa-bc99-441f11989cf8",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"\"Arr, me matey! I be doin' well, sailin' the high seas and searchin' for treasure. How be ye?\""
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]
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},
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"execution_count": 3,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"outputs": [],
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"source": [
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"from langchain_core.chat_history import InMemoryChatMessageHistory\n",
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"from langchain_core.output_parsers import StrOutputParser\n",
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"from langchain_core.prompts import ChatPromptTemplate\n",
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"from langchain_core.runnables.history import RunnableWithMessageHistory\n",
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"import uuid\n",
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"\n",
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"from langchain_openai import ChatOpenAI\n",
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"from langgraph.checkpoint.memory import MemorySaver\n",
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"from langgraph.graph import START, MessagesState, StateGraph\n",
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"\n",
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"prompt = ChatPromptTemplate.from_messages(\n",
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" [\n",
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" (\"system\", \"You are a pirate. Answer the following questions as best you can.\"),\n",
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" (\"placeholder\", \"{chat_history}\"),\n",
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" (\"human\", \"{input}\"),\n",
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" ]\n",
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")\n",
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"model = ChatOpenAI(model=\"gpt-4o-mini\")\n",
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"\n",
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"history = InMemoryChatMessageHistory()\n",
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"# Define a new graph\n",
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"workflow = StateGraph(state_schema=MessagesState)\n",
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"\n",
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"\n",
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"def get_history():\n",
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" return history\n",
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"# Define the function that calls the model\n",
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"def call_model(state: MessagesState):\n",
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" response = model.invoke(state[\"messages\"])\n",
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" return {\"messages\": response}\n",
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"\n",
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"\n",
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"chain = prompt | ChatOpenAI() | StrOutputParser()\n",
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"# Define the two nodes we will cycle between\n",
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"workflow.add_edge(START, \"model\")\n",
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"workflow.add_node(\"model\", call_model)\n",
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"\n",
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"wrapped_chain = RunnableWithMessageHistory(\n",
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" chain,\n",
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" get_history,\n",
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" history_messages_key=\"chat_history\",\n",
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")\n",
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"# Add memory\n",
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"memory = MemorySaver()\n",
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"app = workflow.compile(checkpointer=memory)\n",
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"\n",
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"wrapped_chain.invoke({\"input\": \"how are you?\"})"
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]
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},
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{
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"cell_type": "markdown",
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"id": "6b386ce6-895e-442c-88f3-7bec0ab9f401",
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"metadata": {},
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"source": [
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"The above example uses the same `history` for all sessions. The example below shows how to use a different chat history for each session."
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"\n",
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"# The thread id is a unique key that identifies\n",
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"# this particular conversation.\n",
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"# We'll just generate a random uuid here.\n",
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"thread_id = uuid.uuid4()\n",
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"config = {\"configurable\": {\"thread_id\": thread_id}}"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"id": "96152263-98d7-4e06-8c73-d0c0abf3e8e9",
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"execution_count": 5,
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"id": "3a9df4bb-e804-4373-9a15-a29dc0371595",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"'Ahoy there, me hearty! What can this old pirate do for ye today?'"
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]
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},
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"================================\u001b[1m Human Message \u001b[0m=================================\n",
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"\n",
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"I'm Bob, how are you?\n",
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"==================================\u001b[1m Ai Message \u001b[0m==================================\n",
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"\n",
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"Ahoy, Bob! I be feelin' as lively as a ship in full sail! How be ye on this fine day?\n"
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]
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}
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],
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"source": [
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"from langchain_core.chat_history import BaseChatMessageHistory\n",
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"from langchain_core.runnables.history import RunnableWithMessageHistory\n",
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"query = \"I'm Bob, how are you?\"\n",
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"\n",
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"store = {}\n",
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"input_messages = [\n",
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" {\n",
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" \"role\": \"system\",\n",
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" \"content\": \"You are a pirate. Answer the following questions as best you can.\",\n",
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" },\n",
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" {\"role\": \"user\", \"content\": query},\n",
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"]\n",
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"for event in app.stream({\"messages\": input_messages}, config, stream_mode=\"values\"):\n",
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" event[\"messages\"][-1].pretty_print()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"id": "d3f77e69-fa3d-496c-968c-86371e1e8cf1",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"================================\u001b[1m Human Message \u001b[0m=================================\n",
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"\n",
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"What is my name?\n",
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"==================================\u001b[1m Ai Message \u001b[0m==================================\n",
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"\n",
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"Ye be callin' yerself Bob, I reckon! A fine name for a swashbuckler like yerself!\n"
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]
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}
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],
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"source": [
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"query = \"What is my name?\"\n",
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"\n",
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"\n",
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"def get_session_history(session_id: str) -> BaseChatMessageHistory:\n",
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" if session_id not in store:\n",
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" store[session_id] = InMemoryChatMessageHistory()\n",
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" return store[session_id]\n",
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"\n",
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"\n",
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"chain = prompt | ChatOpenAI() | StrOutputParser()\n",
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"\n",
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"wrapped_chain = RunnableWithMessageHistory(\n",
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" chain,\n",
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" get_session_history,\n",
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" history_messages_key=\"chat_history\",\n",
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")\n",
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"\n",
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"wrapped_chain.invoke(\n",
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" {\"input\": \"Hello!\"},\n",
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" config={\"configurable\": {\"session_id\": \"abc123\"}},\n",
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")"
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"input_messages = [{\"role\": \"user\", \"content\": query}]\n",
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"for event in app.stream({\"messages\": input_messages}, config, stream_mode=\"values\"):\n",
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" event[\"messages\"][-1].pretty_print()"
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]
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},
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{
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