mirror of
https://github.com/hwchase17/langchain.git
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Demonstrate use of get_buffer_string (#13013)
**Description** The docs for creating a RAG chain with Memory [currently use a manual lambda](https://python.langchain.com/docs/expression_language/cookbook/retrieval#with-memory-and-returning-source-documents) to format chat history messages. [There exists a helper method within the codebase](https://github.com/langchain-ai/langchain/blob/master/libs/langchain/langchain/schema/messages.py#L14C15-L14C15) to perform this task so I've updated the documentation to demonstrate its usage Also worth noting that the current documented method of using the included `_format_chat_history ` function actually results in an error: ``` TypeError: 'HumanMessage' object is not subscriptable ``` --------- Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
This commit is contained in:
Matt Wells
GitHub
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"outputs": [
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@ -95,7 +95,7 @@
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"'Harrison worked at Kensho.'"
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]
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},
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"cell_type": "code",
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"outputs": [
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"'Harrison ha lavorato a Kensho.'"
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]
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},
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"execution_count": 7,
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"execution_count": 6,
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{
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"cell_type": "code",
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"execution_count": 8,
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"execution_count": 21,
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"id": "3f30c348",
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"metadata": {},
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"outputs": [],
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"source": [
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"from langchain.schema import format_document\n",
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"from langchain.schema.runnable import RunnableParallel"
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"from langchain.schema.messages import get_buffer_string\n",
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"from langchain.schema.runnable import RunnableParallel\n",
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"from langchain_core.messages import AIMessage, HumanMessage"
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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": 9,
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"id": "64ab1dbf",
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"cell_type": "code",
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"execution_count": 10,
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"execution_count": 9,
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"id": "7d628c97",
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{
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"cell_type": "code",
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"execution_count": 11,
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"execution_count": 10,
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"id": "f60a5d0f",
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"id": "7d007db6",
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"metadata": {},
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"outputs": [],
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"source": [
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"from typing import List, Tuple\n",
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"\n",
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"\n",
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"def _format_chat_history(chat_history: List[Tuple[str, str]]) -> str:\n",
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" # chat history is of format:\n",
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" # [\n",
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" # (human_message_str, ai_message_str),\n",
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" # ...\n",
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" # ]\n",
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" # see below for an example of how it's invoked\n",
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" buffer = \"\"\n",
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" for dialogue_turn in chat_history:\n",
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" human = \"Human: \" + dialogue_turn[0]\n",
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" ai = \"Assistant: \" + dialogue_turn[1]\n",
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" buffer += \"\\n\" + \"\\n\".join([human, ai])\n",
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" return buffer"
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]
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"cell_type": "code",
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"execution_count": 13,
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"execution_count": 11,
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"id": "5c32cc89",
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"metadata": {},
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"outputs": [],
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"source": [
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"_inputs = RunnableParallel(\n",
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" standalone_question=RunnablePassthrough.assign(\n",
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" chat_history=lambda x: _format_chat_history(x[\"chat_history\"])\n",
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" chat_history=lambda x: get_buffer_string(x[\"chat_history\"])\n",
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" )\n",
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" | CONDENSE_QUESTION_PROMPT\n",
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" | ChatOpenAI(temperature=0)\n",
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"execution_count": 12,
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"id": "135c8205",
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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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"AIMessage(content='Harrison was employed at Kensho.', additional_kwargs={}, example=False)"
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"AIMessage(content='Harrison was employed at Kensho.')"
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]
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},
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"execution_count": 14,
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"execution_count": 12,
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"metadata": {},
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"output_type": "execute_result"
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}
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@ -299,17 +276,17 @@
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},
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{
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"cell_type": "code",
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"execution_count": 15,
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"execution_count": 22,
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"id": "424e7e7a",
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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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"AIMessage(content='Harrison worked at Kensho.', additional_kwargs={}, example=False)"
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"AIMessage(content='Harrison worked at Kensho.')"
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]
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},
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"execution_count": 15,
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"metadata": {},
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"output_type": "execute_result"
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}
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@ -318,7 +295,10 @@
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"conversational_qa_chain.invoke(\n",
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" {\n",
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" \"question\": \"where did he work?\",\n",
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" \"chat_history\": [(\"Who wrote this notebook?\", \"Harrison\")],\n",
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" \"chat_history\": [\n",
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" HumanMessage(content=\"Who wrote this notebook?\"),\n",
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" AIMessage(content=\"Harrison\"),\n",
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" ],\n",
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" }\n",
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")"
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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": 16,
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"execution_count": 14,
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"id": "e31dd17c",
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"metadata": {},
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"outputs": [],
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},
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{
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"cell_type": "code",
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"execution_count": 17,
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"id": "d4bffe94",
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"metadata": {},
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"outputs": [],
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},
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{
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"cell_type": "code",
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"id": "733be985",
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"metadata": {},
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"outputs": [],
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@ -373,7 +353,7 @@
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"standalone_question = {\n",
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" \"standalone_question\": {\n",
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" \"question\": lambda x: x[\"question\"],\n",
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" \"chat_history\": lambda x: _format_chat_history(x[\"chat_history\"]),\n",
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" \"chat_history\": lambda x: get_buffer_string(x[\"chat_history\"]),\n",
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" }\n",
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" | CONDENSE_QUESTION_PROMPT\n",
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" | ChatOpenAI(temperature=0)\n",
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},
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{
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"cell_type": "code",
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"execution_count": 19,
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"execution_count": 17,
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"id": "806e390c",
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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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"{'answer': AIMessage(content='Harrison was employed at Kensho.', additional_kwargs={}, example=False),\n",
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" 'docs': [Document(page_content='harrison worked at kensho', metadata={})]}"
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"{'answer': AIMessage(content='Harrison was employed at Kensho.'),\n",
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" 'docs': [Document(page_content='harrison worked at kensho')]}"
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]
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},
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"execution_count": 19,
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"execution_count": 17,
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"metadata": {},
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"output_type": "execute_result"
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}
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@ -424,7 +404,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 20,
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"execution_count": 18,
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"id": "977399fd",
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"metadata": {},
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"outputs": [],
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},
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{
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"cell_type": "code",
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"execution_count": 21,
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"execution_count": 19,
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"id": "f94f7de4",
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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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"{'history': [HumanMessage(content='where did harrison work?', additional_kwargs={}, example=False),\n",
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" AIMessage(content='Harrison was employed at Kensho.', additional_kwargs={}, example=False)]}"
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"{'history': [HumanMessage(content='where did harrison work?'),\n",
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" AIMessage(content='Harrison was employed at Kensho.')]}"
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]
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},
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"execution_count": 21,
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"execution_count": 19,
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"metadata": {},
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"output_type": "execute_result"
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}
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"source": [
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"memory.load_memory_variables({})"
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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": 20,
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"id": "88f2b7cd",
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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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"{'answer': AIMessage(content='Harrison actually worked at Kensho.'),\n",
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" 'docs': [Document(page_content='harrison worked at kensho')]}"
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]
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},
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"execution_count": 20,
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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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"inputs = {\"question\": \"but where did he really work?\"}\n",
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"result = final_chain.invoke(inputs)\n",
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"result"
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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": null,
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"id": "207a2782",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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@ -474,7 +486,7 @@
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.1"
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"version": "3.10.1"
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}
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},
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"nbformat": 4,
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