Upload pleasantnoisehf.ipynb

Python Code of our Model in a Jupyter Notebook.
Doesn´t include API-Code and the csv-files.

pleasantnoisehf.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain import OpenAI\n",
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain.prompts import PromptTemplate\n",
+    "from langchain.chains import LLMChain\n",
+    "from langchain.document_loaders import TextLoader\n",
+    "\n",
+    "\n",
+    "from pathlib import Path\n",
+    "import os\n",
+    "\n",
+    "os.environ[\"OPENAI_API_KEY\"] = \"\"\n",
+    "\n",
+    "path = Path().home() / \"Documents\" / \"csv1.csv\"\n",
+    "loader = TextLoader(path)\n",
+    "document = loader.load()\n",
+    "\n",
+    "\n",
+    "path2 = Path().home() / \"Documents\" / \"csv2.csv\"\n",
+    "loader2 = TextLoader(path2)\n",
+    "document2 = loader2.load()\n",
+    "\n",
+    "prompt_template = \"\"\"Following are two lists of Event Titles, Dates and Descriptions in the format <Title>;<Date>:\n",
+    "<Description>\n",
+    "{csv1}\n",
+    "\n",
+    "{csv2}\n",
+    "\n",
+    "TASKS: \n",
+    "1. Show matching string values of the two lists\n",
+    "2. Based on these matches, provide a natural sounding conversation starter \n",
+    "\n",
+    "\"\"\"\n",
+    "prompt = PromptTemplate.from_template(prompt_template)\n",
+    "\n",
+    "llm = OpenAI (temperature=0)\n",
+    "chain = LLMChain(llm=llm, prompt=prompt)\n",
+    "response = chain({\"csv1\": document[0].page_content, \"csv2\": document2[0].page_content})\n",
+    "\n",
+    "\n",
+    "print(response['text'])"
+   ]
+  }
+ ],
+ "metadata": {
+  "language_info": {
+   "name": "python"
+  },
+  "orig_nbformat": 4
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}