70 lines
3.0 KiB
Plaintext
70 lines
3.0 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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"id": "89fd124d-5e7b-4e61-af85-2fe978c688f2",
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"metadata": {},
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"outputs": [],
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"source": [
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"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",
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"user_prompt = \"\"\"\n",
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" data = [\n",
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" {\"transaction_id\": 1, \"date\": \"2025-01-05\", \"merchant\": \"Amazon\", \"category\": \"Shopping\", \"amount\": -120.50, \"currency\": \"GBP\"},\n",
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" {\"transaction_id\": 2, \"date\": \"2025-01-07\", \"merchant\": \"Starbucks\", \"category\": \"Food & Drink\", \"amount\": -4.75, \"currency\": \"GBP\"},\n",
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" {\"transaction_id\": 3, \"date\": \"2025-01-09\", \"merchant\": \"Tesco\", \"category\": \"Groceries\", \"amount\": -56.20, \"currency\": \"GBP\"},\n",
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" {\"transaction_id\": 4, \"date\": \"2025-01-10\", \"merchant\": \"Uber\", \"category\": \"Transport\", \"amount\": -15.80, \"currency\": \"GBP\"},\n",
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" {\"transaction_id\": 5, \"date\": \"2025-01-15\", \"merchant\": \"Apple\", \"category\": \"Electronics\", \"amount\": -899.00, \"currency\": \"GBP\"},\n",
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" {\"transaction_id\": 6, \"date\": \"2025-01-18\", \"merchant\": \"Netflix\", \"category\": \"Subscription\", \"amount\": -9.99, \"currency\": \"GBP\"},\n",
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" {\"transaction_id\": 7, \"date\": \"2025-01-20\", \"merchant\": \"Salary\", \"category\": \"Income\", \"amount\": 2500.00, \"currency\": \"GBP\"},\n",
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" {\"transaction_id\": 8, \"date\": \"2025-01-22\", \"merchant\": \"British Airways\", \"category\": \"Travel\", \"amount\": -450.00, \"currency\": \"GBP\"},\n",
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" {\"transaction_id\": 9, \"date\": \"2025-01-25\", \"merchant\": \"Marks & Spencer\", \"category\": \"Shopping\", \"amount\": -75.30, \"currency\": \"GBP\"},\n",
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" {\"transaction_id\": 10, \"date\": \"2025-01-30\", \"merchant\": \"HMRC\", \"category\": \"Tax\", \"amount\": -320.00, \"currency\": \"GBP\"},\n",
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"]\n",
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"\n",
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"\n",
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"\"\"\"\n",
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"\n",
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"# Step 2: Make the messages list\n",
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"\n",
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"messages = [\n",
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" {\"role\": \"system\", \"content\": system_prompt},\n",
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" {\"role\": \"user\", \"content\": user_prompt}\n",
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"] # fill this in\n",
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"\n",
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"# Step 3: Call OpenAI\n",
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"\n",
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"response = openai.chat.completions.create(\n",
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" model = \"gpt-4o-mini\",\n",
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" messages = messages\n",
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" )\n",
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"\n",
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"# Step 4: print the result\n",
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"\n",
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"display(Markdown(response.choices[0].message.content))"
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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 (ipykernel)",
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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": "3.11.13"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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