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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Policy Compare\n",
"This Jupyter Notebook aims to compare how well your policy document aligns with that of the RAI Gold-Standard"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Import Packages"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"from llama_index.node_parser import SimpleNodeParser\n",
"from llama_index import (\n",
" ServiceContext,\n",
" SimpleDirectoryReader)\n",
"from llama_index import VectorStoreIndex\n",
"import openai"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## OpenAI API Key"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"openai.api_key = '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'"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Chunk Information"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"chunk_size = 128\n",
"similarity_top_k = 6"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Load document as query engine"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"documents = SimpleDirectoryReader(input_files=['data/usenix.pdf']).load_data()\n",
"service_context = ServiceContext.from_defaults(chunk_size=chunk_size)\n",
"index = VectorStoreIndex.from_documents(documents, service_context=service_context)\n",
"\n",
"query_engine = index.as_query_engine(similarity_top_k=similarity_top_k)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Form query and get response"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"This privacy policy collects personal information such as name, email address, job title, company, mailing address, phone number, industry, job function, and student status.\n"
]
}
],
"source": [
"query = \"Which specific personal information does this privacy policy collect?\"\n",
"response = query_engine.query(query)\n",
"print(response)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Get Sources Used"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"page_label: 3\n",
"file_name: usenix.pdf\n",
"\n",
"We will ask for your consent before using information for a purpose other than those that are set out in this Privacy Policy .Website Cookies and Logs\n",
"Like many websites, we use cookies and similar tracking technology (collectively \"Cookies\") to collect and use personal\n",
"information about you.For further information about the types of Cookies we use, please see our Cookie Statement\n",
"(https://www .usenix.org/cookies) .Log Data\n",
"We collect the information that your browser sends whenever you visit our website.\n",
"\n",
"-----\n",
"\n",
"page_label: 4\n",
"file_name: usenix.pdf\n",
"\n",
"If you have questions about or need further information concerning the legal basis on which we collect and use your\n",
"personal information, please contact us at privacy@usenix.org (mailto:privacy@usenix.org) .Data Retention\n",
"We retain your personal information and a record of membership, purchases, event attendance, volunteer service, and\n",
"related data.\n",
"\n",
"-----\n",
"\n",
"page_label: 4\n",
"file_name: usenix.pdf\n",
"\n",
"Legal Basis for Processing Your Personal\n",
"Information\n",
"We collect personal information from you where the processing is in our legitimate interests.As described above, the\n",
"data is collected to provide services to our members, conference attendees, those who wish to publish papers or present\n",
"at our conferences, and other interested parties.We send communications announcing upcoming events, submission deadlines, and other issues of interest to our\n",
"membership and constituents.Y ou may opt out of these communications at any time.\n",
"\n",
"-----\n",
"\n",
"page_label: 4\n",
"file_name: usenix.pdf\n",
"\n",
"Where required by law or regulation, court order , or other judicial authorization; in response to lawful requests by\n",
"public authorities, including for the purposes of meeting national security and law enforcement requirements; to\n",
"protect or defend our rights, interests, or property , or that of third parties; to investigate any wrongdoing in\n",
"connection with our products and services; and to protect the vital interests of an individual.To any other person with your consent.We may disclose aggregate, non-identifying information about our members and constituents based on anonymized\n",
"data.\n",
"\n",
"-----\n",
"\n",
"page_label: 1\n",
"file_name: usenix.pdf\n",
"\n",
"Personal Information You Provide to Us\n",
"and Our Data Processors\n",
"USENIX Membership and Account Creation\n",
"When you create an account on the usenix.org website, you provide your name, email address, job title, company ,\n",
"mailing address, phone number , industry , job function, and student status.\n",
"\n",
"-----\n",
"\n",
"page_label: 3\n",
"file_name: usenix.pdf\n",
"\n",
"These providers have limited access to your information to perform these tasks on our behalf and are\n",
"contractually bound to protect and to use it only for the purposes for which it was disclosed and consistent with\n",
"this Privacy Policy .\n",
"\n",
"-----\n",
"\n"
]
}
],
"source": [
"for i in range(similarity_top_k):\n",
" print(response.source_nodes[i].node.get_content(metadata_mode=\"all\") + \"\\n\\n-----\\n\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Write all to text file"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"with open(\"Results/Sources\" + \"_\" + \"_\".join(query.split()[:3]) + \".txt\", \"w\") as fp:\n",
" fp.write(\"---------- Query ----------\\n\" + query + \"\\n\\n\")\n",
" fp.write(\"-------- Response ---------\\n\" + str(response) + \"\\n\\n\")\n",
" fp.write(\"------ Sources used -------\\n\")\n",
" for i in range(similarity_top_k):\n",
" fp.write(response.source_nodes[i].node.get_content(metadata_mode=\"all\") + \"\\n\\n-----\\n\")"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "TW",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.5"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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