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docs: Add FalkorDB Chat Message History and Update Package Registry #28914

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73 changes: 73 additions & 0 deletions docs/docs/integrations/memory/falkordb_chat_message_history.ipynb
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@@ -0,0 +1,73 @@
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# FalkorDB\n",
"\n",
"<a href='https://docs.falkordb.com/' target='_blank'>FalkorDB</a> is an open-source graph database management system, renowned for its efficient management of highly connected data. Unlike traditional databases that store data in tables, FalkorDB uses a graph structure with nodes, edges, and properties to represent and store data. This design allows for high-performance queries on complex data relationships.\n",
"\n",
"This notebook goes over how to use `FalkorDB` to store chat message history\n",
"\n",
"**NOTE**: You can use FalkorDB locally or use FalkorDB Cloud. <a href='https://docs.falkordb.com/' target='blank'>See installation instructions</a>"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"# For this example notebook we will be using FalkorDB locally\n",
"host = \"localhost\"\n",
"port = 6379"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"from langchain_falkordb.message_history import (\n",
" FalkorDBChatMessageHistory,\n",
")\n",
"\n",
"history = FalkorDBChatMessageHistory(host=host, port=port, session_id=\"session_id_1\")\n",
"\n",
"history.add_user_message(\"hi!\")\n",
"\n",
"history.add_ai_message(\"whats up?\")"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[HumanMessage(content='hi!', additional_kwargs={}, response_metadata={}),\n",
" AIMessage(content='whats up?', additional_kwargs={}, response_metadata={})]"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"history.messages"
]
}
],
"metadata": {
"language_info": {
"name": "python"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
72 changes: 72 additions & 0 deletions docs/docs/integrations/providers/falkordb.ipynb
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# FalkorDB\n",
"\n",
">What is `FalkorDB`?\n",
"\n",
">- FalkorDB is an `open-source database management system` that specializes in graph database technology.\n",
">- FalkorDB allows you to represent and store data in nodes and edges, making it ideal for handling connected data and relationships.\n",
">- FalkorDB Supports OpenCypher query language with proprietary extensions, making it easy to interact with and query your graph data.\n",
">- With FalkorDB, you can achieve high-performance `graph traversals and queries`, suitable for production-level systems.\n",
"\n",
">Get started with FalkorDB by visiting [their website](https://docs.falkordb.com/)."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Installation and Setup\n",
"\n",
"- Install the Python SDK with `pip install falkordb langchain-falkordb`"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## VectorStore\n",
"\n",
"The FalkorDB vector index is used as a vectorstore,\n",
"whether for semantic search or example selection.\n",
"\n",
"```python\n",
"from langchain_community.vectorstores.falkordb_vector import FalkorDBVector\n",
"```\n",
"or \n",
"\n",
"```python\n",
"from langchain_falkordb.vectorstore import FalkorDBVector\n",
"```\n",
"\n",
"See a [usage example](/docs/integrations/vectorstores/falkordbvector.ipynb)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Memory\n",
"\n",
"See a [usage example](/docs/integrations/memory/falkordb_chat_message_history.ipynb).\n",
"\n",
"```python\n",
"from langchain_falkordb.message_history import (\n",
" FalkorDBChatMessageHistory,\n",
")\n",
"```"
]
}
],
"metadata": {
"language_info": {
"name": "python"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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