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https://github.com/hwchase17/langchain
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2667ddc686
**Description: a description of the change** Fixed `make docs_build` and related scripts which caused errors. There are several changes. First, I made the build of the documentation and the API Reference into two separate commands. This is because it takes less time to build. The commands for documents are `make docs_build`, `make docs_clean`, and `make docs_linkcheck`. The commands for API Reference are `make api_docs_build`, `api_docs_clean`, and `api_docs_linkcheck`. It looked like `docs/.local_build.sh` could be used to build the documentation, so I used that. Since `.local_build.sh` was also building API Rerefence internally, I removed that process. `.local_build.sh` also added some Bash options to stop in error or so. Futher more added `cd "${SCRIPT_DIR}"` at the beginning so that the script will work no matter which directory it is executed in. `docs/api_reference/api_reference.rst` is removed, because which is generated by `docs/api_reference/create_api_rst.py`, and added it to .gitignore. Finally, the description of CONTRIBUTING.md was modified. **Issue: the issue # it fixes (if applicable)** https://github.com/hwchase17/langchain/issues/6413 **Dependencies: any dependencies required for this change** `nbdoc` was missing in group docs so it was added. I installed it with the `poetry add --group docs nbdoc` command. I am concerned if any modifications are needed to poetry.lock. I would greatly appreciate it if you could pay close attention to this file during the review. **Tag maintainer** - General / Misc / if you don't know who to tag: @baskaryan If this PR needs any additional changes, I'll be happy to make them! --------- Co-authored-by: Bagatur <baskaryan@gmail.com>
375 lines
9.3 KiB
Plaintext
375 lines
9.3 KiB
Plaintext
{
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"cells": [
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# KuzuQAChain\n",
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"\n",
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"This notebook shows how to use LLMs to provide a natural language interface to [Kùzu](https://kuzudb.com) database."
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"[Kùzu](https://kuzudb.com) is an in-process property graph database management system. You can simply install it with `pip`:\n",
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"\n",
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"```bash\n",
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"pip install kuzu\n",
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"```\n",
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"\n",
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"Once installed, you can simply import it and start creating a database on the local machine and connect to it:\n"
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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": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"import kuzu\n",
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"\n",
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"db = kuzu.Database(\"test_db\")\n",
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"conn = kuzu.Connection(db)"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"First, we create the schema for a simple movie database:"
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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": 2,
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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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"<kuzu.query_result.QueryResult at 0x1066ff410>"
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]
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},
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"execution_count": 2,
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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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"conn.execute(\"CREATE NODE TABLE Movie (name STRING, PRIMARY KEY(name))\")\n",
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"conn.execute(\n",
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" \"CREATE NODE TABLE Person (name STRING, birthDate STRING, PRIMARY KEY(name))\"\n",
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")\n",
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"conn.execute(\"CREATE REL TABLE ActedIn (FROM Person TO Movie)\")"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Then we can insert some data."
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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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"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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"<kuzu.query_result.QueryResult at 0x107016210>"
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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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"conn.execute(\"CREATE (:Person {name: 'Al Pacino', birthDate: '1940-04-25'})\")\n",
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"conn.execute(\"CREATE (:Person {name: 'Robert De Niro', birthDate: '1943-08-17'})\")\n",
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"conn.execute(\"CREATE (:Movie {name: 'The Godfather'})\")\n",
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"conn.execute(\"CREATE (:Movie {name: 'The Godfather: Part II'})\")\n",
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"conn.execute(\n",
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" \"CREATE (:Movie {name: 'The Godfather Coda: The Death of Michael Corleone'})\"\n",
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")\n",
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"conn.execute(\n",
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" \"MATCH (p:Person), (m:Movie) WHERE p.name = 'Al Pacino' AND m.name = 'The Godfather' CREATE (p)-[:ActedIn]->(m)\"\n",
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")\n",
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"conn.execute(\n",
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" \"MATCH (p:Person), (m:Movie) WHERE p.name = 'Al Pacino' AND m.name = 'The Godfather: Part II' CREATE (p)-[:ActedIn]->(m)\"\n",
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")\n",
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"conn.execute(\n",
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" \"MATCH (p:Person), (m:Movie) WHERE p.name = 'Al Pacino' AND m.name = 'The Godfather Coda: The Death of Michael Corleone' CREATE (p)-[:ActedIn]->(m)\"\n",
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")\n",
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"conn.execute(\n",
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" \"MATCH (p:Person), (m:Movie) WHERE p.name = 'Robert De Niro' AND m.name = 'The Godfather: Part II' CREATE (p)-[:ActedIn]->(m)\"\n",
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")"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Creating `KuzuQAChain`\n",
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"\n",
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"We can now create the `KuzuGraph` and `KuzuQAChain`. To create the `KuzuGraph` we simply need to pass the database object to the `KuzuGraph` constructor."
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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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"metadata": {},
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"outputs": [],
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"source": [
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"from langchain.chat_models import ChatOpenAI\n",
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"from langchain.graphs import KuzuGraph\n",
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"from langchain.chains import KuzuQAChain"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"graph = KuzuGraph(db)"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"chain = KuzuQAChain.from_llm(ChatOpenAI(temperature=0), graph=graph, verbose=True)"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Refresh graph schema information\n",
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"\n",
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"If the schema of database changes, you can refresh the schema information needed to generate Cypher statements."
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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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"metadata": {},
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"outputs": [],
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"source": [
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"# graph.refresh_schema()"
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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": 8,
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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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"Node properties: [{'properties': [('name', 'STRING')], 'label': 'Movie'}, {'properties': [('name', 'STRING'), ('birthDate', 'STRING')], 'label': 'Person'}]\n",
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"Relationships properties: [{'properties': [], 'label': 'ActedIn'}]\n",
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"Relationships: ['(:Person)-[:ActedIn]->(:Movie)']\n",
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"\n"
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]
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}
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],
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"source": [
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"print(graph.get_schema)"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Querying the graph\n",
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"\n",
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"We can now use the `KuzuQAChain` to ask question of the graph"
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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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"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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"\n",
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"\n",
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"\u001b[1m> Entering new chain...\u001b[0m\n",
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"Generated Cypher:\n",
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"\u001b[32;1m\u001b[1;3mMATCH (p:Person)-[:ActedIn]->(m:Movie {name: 'The Godfather: Part II'}) RETURN p.name\u001b[0m\n",
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"Full Context:\n",
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"\u001b[32;1m\u001b[1;3m[{'p.name': 'Al Pacino'}, {'p.name': 'Robert De Niro'}]\u001b[0m\n",
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"\n",
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"\u001b[1m> Finished chain.\u001b[0m\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"'Al Pacino and Robert De Niro both played in The Godfather: Part II.'"
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]
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},
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"execution_count": 9,
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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.run(\"Who played in The Godfather: Part II?\")"
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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": 10,
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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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"\n",
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"\n",
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"\u001b[1m> Entering new chain...\u001b[0m\n",
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"Generated Cypher:\n",
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"\u001b[32;1m\u001b[1;3mMATCH (p:Person {name: 'Robert De Niro'})-[:ActedIn]->(m:Movie)\n",
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"RETURN m.name\u001b[0m\n",
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"Full Context:\n",
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"\u001b[32;1m\u001b[1;3m[{'m.name': 'The Godfather: Part II'}]\u001b[0m\n",
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"\n",
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"\u001b[1m> Finished chain.\u001b[0m\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"'Robert De Niro played in The Godfather: Part II.'"
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]
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},
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"execution_count": 10,
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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.run(\"Robert De Niro played in which movies?\")"
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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": 11,
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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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"\n",
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"\n",
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"\u001b[1m> Entering new chain...\u001b[0m\n",
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"Generated Cypher:\n",
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"\u001b[32;1m\u001b[1;3mMATCH (p:Person {name: 'Robert De Niro'})-[:ActedIn]->(m:Movie)\n",
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"RETURN p.birthDate\u001b[0m\n",
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"Full Context:\n",
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"\u001b[32;1m\u001b[1;3m[{'p.birthDate': '1943-08-17'}]\u001b[0m\n",
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"\n",
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"\u001b[1m> Finished chain.\u001b[0m\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"'Robert De Niro was born on August 17, 1943.'"
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]
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},
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"execution_count": 11,
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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.run(\"Robert De Niro is born in which year?\")"
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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": 12,
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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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"\n",
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"\n",
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"\u001b[1m> Entering new chain...\u001b[0m\n",
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"Generated Cypher:\n",
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"\u001b[32;1m\u001b[1;3mMATCH (p:Person)-[:ActedIn]->(m:Movie{name:'The Godfather: Part II'})\n",
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"WITH p, m, p.birthDate AS birthDate\n",
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"ORDER BY birthDate ASC\n",
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"LIMIT 1\n",
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"RETURN p.name\u001b[0m\n",
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"Full Context:\n",
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"\u001b[32;1m\u001b[1;3m[{'p.name': 'Al Pacino'}]\u001b[0m\n",
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"\n",
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"\u001b[1m> Finished chain.\u001b[0m\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"'The oldest actor who played in The Godfather: Part II is Al Pacino.'"
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]
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},
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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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],
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"source": [
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"chain.run(\"Who is the oldest actor who played in The Godfather: Part II?\")"
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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",
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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": "3.11.4"
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},
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"orig_nbformat": 4
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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