Merge pull request #656 from shiv-konar/feature/learning-llm-engineering

adding new day 1 exercise

week1/community-contributions/day1-financial-analyst.ipynb

@@ -0,0 +1,106 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "4a9842d0-2465-4c0a-9f08-3c23f4202c3a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "from dotenv import load_dotenv\n",
+    "from IPython.display import Markdown, display\n",
+    "from openai import OpenAI"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7fcfe08c-d074-41f5-befe-24358c967e1b",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "89fd124d-5e7b-4e61-af85-2fe978c688f2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "system_prompt = \"You are an analyst that analyzes the financial transactions data and provides summary of where the money has been spent, where money can be cut back so savings be increased\"\n",
+    "user_prompt = \"\"\"\n",
+    "    data = [\n",
+    "    {\"transaction_id\": 1, \"date\": \"2025-01-05\", \"merchant\": \"Amazon\", \"category\": \"Shopping\", \"amount\": -120.50, \"currency\": \"GBP\"},\n",
+    "    {\"transaction_id\": 2, \"date\": \"2025-01-07\", \"merchant\": \"Starbucks\", \"category\": \"Food & Drink\", \"amount\": -4.75, \"currency\": \"GBP\"},\n",
+    "    {\"transaction_id\": 3, \"date\": \"2025-01-09\", \"merchant\": \"Tesco\", \"category\": \"Groceries\", \"amount\": -56.20, \"currency\": \"GBP\"},\n",
+    "    {\"transaction_id\": 4, \"date\": \"2025-01-10\", \"merchant\": \"Uber\", \"category\": \"Transport\", \"amount\": -15.80, \"currency\": \"GBP\"},\n",
+    "    {\"transaction_id\": 5, \"date\": \"2025-01-15\", \"merchant\": \"Apple\", \"category\": \"Electronics\", \"amount\": -899.00, \"currency\": \"GBP\"},\n",
+    "    {\"transaction_id\": 6, \"date\": \"2025-01-18\", \"merchant\": \"Netflix\", \"category\": \"Subscription\", \"amount\": -9.99, \"currency\": \"GBP\"},\n",
+    "    {\"transaction_id\": 7, \"date\": \"2025-01-20\", \"merchant\": \"Salary\", \"category\": \"Income\", \"amount\": 2500.00, \"currency\": \"GBP\"},\n",
+    "    {\"transaction_id\": 8, \"date\": \"2025-01-22\", \"merchant\": \"British Airways\", \"category\": \"Travel\", \"amount\": -450.00, \"currency\": \"GBP\"},\n",
+    "    {\"transaction_id\": 9, \"date\": \"2025-01-25\", \"merchant\": \"Marks & Spencer\", \"category\": \"Shopping\", \"amount\": -75.30, \"currency\": \"GBP\"},\n",
+    "    {\"transaction_id\": 10, \"date\": \"2025-01-30\", \"merchant\": \"HMRC\", \"category\": \"Tax\", \"amount\": -320.00, \"currency\": \"GBP\"},\n",
+    "]\n",
+    "\n",
+    "\n",
+    "\"\"\"\n",
+    "\n",
+    "# Step 2: Make the messages list\n",
+    "\n",
+    "messages = [\n",
+    "    {\"role\": \"system\", \"content\": system_prompt},\n",
+    "    {\"role\": \"user\", \"content\": user_prompt}\n",
+    "] # fill this in\n",
+    "\n",
+    "# Step 3: Call OpenAI\n",
+    "\n",
+    "response = openai.chat.completions.create(\n",
+    "        model = \"gpt-4o-mini\",\n",
+    "        messages = messages\n",
+    "    )\n",
+    "\n",
+    "# Step 4: print the result\n",
+    "\n",
+    "display(Markdown(response.choices[0].message.content))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "12d6642e-a4d4-49c7-a14b-8c8200dd210c",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d5fccacf-ddb4-4076-87cc-0ffe6a4d64a4",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.11.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}