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61 lines
1.6 KiB
Plaintext
61 lines
1.6 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"from main import chat_with_pdf, print_stream_and_return_full_answer\n",
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"from dotenv import load_dotenv\n",
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"\n",
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"load_dotenv()\n",
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"\n",
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"bert_paper_url = \"https://arxiv.org/pdf/1810.04805.pdf\"\n",
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"questions = [\n",
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" \"what is BERT?\",\n",
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" \"what NLP tasks does it perform well?\",\n",
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" \"is BERT suitable for NER?\",\n",
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" \"is it better than GPT\",\n",
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" \"when was GPT come up?\",\n",
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" \"when was BERT come up?\",\n",
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" \"so about same time?\",\n",
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"]\n",
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"\n",
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"history = []\n",
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"for q in questions:\n",
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" stream, context = chat_with_pdf(q, bert_paper_url, history)\n",
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" print(\"User: \" + q, flush=True)\n",
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" print(\"Bot: \", end=\"\", flush=True)\n",
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" answer = print_stream_and_return_full_answer(stream)\n",
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" history = history + [\n",
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" {\"role\": \"user\", \"content\": q},\n",
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" {\"role\": \"assistant\", \"content\": answer},\n",
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" ]"
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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": "pf",
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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": "3.9.17"
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},
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"stage": "development"
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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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