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https://github.com/hwchase17/langchain.git
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community: add KafkaChatMessageHistory (#22216)
Add chat history store based on Kafka. Files added: `libs/community/langchain_community/chat_message_histories/kafka.py` `docs/docs/integrations/memory/kafka_chat_message_history.ipynb` New issue to be created for future improvement: 1. Async method implementation. 2. Message retrieval based on timestamp. 3. Support for other configs when connecting to cloud hosted Kafka (e.g. add `api_key` field) 4. Improve unit testing & integration testing.
This commit is contained in:
Chang Liu
GitHub
245
docs/docs/integrations/memory/kafka_chat_message_history.ipynb
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245
docs/docs/integrations/memory/kafka_chat_message_history.ipynb
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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "c21deb80-9cf7-4185-8205-a38110152d2c",
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"metadata": {},
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"source": [
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"# Kafka\n",
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"\n",
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"[Kafka](https://github.com/apache/kafka) is a distributed messaging system that is used to publish and subscribe to streams of records. \n",
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"This demo shows how to use `KafkaChatMessageHistory` to store and retrieve chat messages from a Kafka cluster."
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]
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},
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{
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"cell_type": "markdown",
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"id": "c7c4fc02-18ac-4285-b8d6-507357e2aa13",
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"metadata": {},
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"source": [
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"A running Kafka cluster is required to run the demo. You can follow this [instruction](https://developer.confluent.io/get-started/python) to create a Kafka cluster locally."
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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": "f09f3b45-c4ff-4e59-bf79-238cc85d6465",
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"metadata": {},
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"outputs": [],
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"source": [
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"from langchain_community.chat_message_histories import KafkaChatMessageHistory\n",
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"\n",
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"chat_session_id = \"chat-message-history-kafka\"\n",
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"bootstrap_servers = \"localhost:64797\" # host:port. `localhost:Plaintext Ports` if setup Kafka cluster locally\n",
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"history = KafkaChatMessageHistory(\n",
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" chat_session_id,\n",
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" bootstrap_servers,\n",
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")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "109812d2-85c5-4a65-a8a0-2d16eb80347b",
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"metadata": {},
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"source": [
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"Optional parameters to construct `KafkaChatMessageHistory`:\n",
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" - `ttl_ms`: Time to live in milliseconds for the chat messages.\n",
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" - `partition`: Number of partition of the topic to store the chat messages.\n",
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" - `replication_factor`: Replication factor of the topic to store the chat messages."
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]
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},
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{
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"cell_type": "markdown",
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"id": "c8fba39f-650b-4192-94ea-1a2a89f5348d",
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"metadata": {},
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"source": [
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"`KafkaChatMessageHistory` internally uses Kafka consumer to read chat messages, and it has the ability to mark the consumed position persistently. It has following methods to retrieve chat messages:\n",
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"- `messages`: continue consuming chat messages from last one.\n",
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"- `messages_from_beginning`: reset the consumer to the beginning of the history and consume messages. Optional parameters:\n",
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" 1. `max_message_count`: maximum number of messages to read.\n",
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" 2. `max_time_sec`: maximum time in seconds to read messages.\n",
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"- `messages_from_latest`: reset the consumer to the end of the chat history and try consuming messages. Optional parameters same as above.\n",
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"- `messages_from_last_consumed`: return messages continuing from the last consumed message, similar to `messages`, but with optional parameters.\n",
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"\n",
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"`max_message_count` and `max_time_sec` are used to avoid blocking indefinitely when retrieving messages.\n",
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"As a result, `messages` and other methods to retrieve messages may not return all messages in the chat history. You will need to specify `max_message_count` and `max_time_sec` to retrieve all chat history in a single batch.\n"
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]
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},
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{
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"cell_type": "markdown",
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"id": "caf2176b-db7a-451a-a292-3d9fde585ded",
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"metadata": {},
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"source": [
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"Add messages and retrieve."
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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": "7e52a70d-3921-4614-b8cd-53b8d3c2deb4",
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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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"[HumanMessage(content='hi!'), AIMessage(content='whats up?')]"
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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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"history.add_user_message(\"hi!\")\n",
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"history.add_ai_message(\"whats up?\")\n",
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"\n",
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"history.messages"
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]
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},
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{
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"cell_type": "markdown",
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"id": "874ce388-da8f-4796-b9ca-3ac114195b10",
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"metadata": {},
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"source": [
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"Calling `messages` again returns an empty list because the consumer is at the end of the chat history."
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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": "f863618e-7da1-4f46-9182-7a1387b93b16",
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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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"[]"
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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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}
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],
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"source": [
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"history.messages"
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]
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},
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{
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"cell_type": "markdown",
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"id": "e108255b-c240-44f7-9ecc-52bf04cd15b6",
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"metadata": {},
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"source": [
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"Add new messages and continue consuming."
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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": 5,
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"id": "31aa7403-5392-4ad4-ba43-226020a274e3",
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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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"[HumanMessage(content='hi again!'), AIMessage(content='whats up again?')]"
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]
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},
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"execution_count": 5,
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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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"history.add_user_message(\"hi again!\")\n",
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"history.add_ai_message(\"whats up again?\")\n",
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"history.messages"
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]
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},
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{
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"cell_type": "markdown",
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"id": "5062fabc-c605-40dd-933b-c68de2727874",
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"metadata": {},
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"source": [
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"To reset the consumer and read from beginning:"
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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": "005816ae-c8ed-4e41-9ecd-b6432578c8f1",
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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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"[HumanMessage(content='hi again!'),\n",
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" AIMessage(content='whats up again?'),\n",
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" HumanMessage(content='hi!'),\n",
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" AIMessage(content='whats up?')]"
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]
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},
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"execution_count": 6,
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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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"history.messages_from_beginning()"
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]
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},
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{
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"cell_type": "markdown",
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"id": "42cc7bed-5cd7-417f-94fd-fe2e511cc9c6",
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"metadata": {},
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"source": [
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"Set the consumer to the end of the chat history, add a couple of new messages, and consume:"
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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": 7,
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"id": "d8b4f1cd-fa47-461b-b1b6-278ad54e9ac5",
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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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"[HumanMessage(content='HI!'), AIMessage(content='WHATS UP?')]"
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]
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},
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"execution_count": 7,
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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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"history.messages_from_latest()\n",
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"history.add_user_message(\"HI!\")\n",
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"history.add_ai_message(\"WHATS UP?\")\n",
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"history.messages"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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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": "3.8.18"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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