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tej87681088/tejapi*LLM.ipynb

Created October 24, 2023 02:44
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tejapi*LLM.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "11d3d427",
"metadata": {},
"outputs": [],
"source": [
"import tejapi\n",
"api_key = 'your key'\n",
"tejapi.ApiConfig.api_base=\"http://api.tej.com.tw\"\n",
"tejapi.ApiConfig.api_key = api_key\n",
"tejapi.ApiConfig.ignoretz = True\n",
"\n",
"\n",
"def get_stock_price(gte, lte, ticker):\n",
"\n",
" stock = tejapi.get('TWN/APRCD',\n",
" mdate = {'gte':gte, 'lte':lte},\n",
" coid = ticker,\n",
" chinese_column_name = True\n",
" )\n",
" return stock"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "1bf90626",
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"import openai\n",
"os.environ['OPENAI_API_KEY'] = 'your key'\n",
"openai.api_key = os.environ['OPENAI_API_KEY']"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "bc0bdcb5",
"metadata": {},
"outputs": [],
"source": [
"from langchain.chat_models import ChatOpenAI\n",
"from langchain.chains import ConversationChain\n",
"from langchain.memory import ConversationBufferWindowMemory"
]
},
{
"cell_type": "code",
"execution_count": 104,
"id": "0c15aa3f",
"metadata": {},
"outputs": [],
"source": [
"llm_model = 'gpt-3.5-turbo-0301'\n",
"llm = ChatOpenAI(temperature=0.0, model=llm_model)\n",
"memory = ConversationBufferWindowMemory(k=5) # 設定只保留五次對話以前的紀錄\n",
"\n",
"# 建立對話鏈\n",
"conversation = ConversationChain(\n",
" llm=llm, \n",
" memory = memory,\n",
" verbose=False\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 105,
"id": "0da47c1a",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"幫我分析市場波動趨勢，以下為股價資料：\n",
"date: 2023-05-22 open: 532.0 close: 531.0\n",
"date: 2023-05-23 open: 530.0 close: 530.0\n",
"date: 2023-05-24 open: 527.0 close: 525.0\n",
"date: 2023-05-25 open: 542.0 close: 543.0\n",
"date: 2023-05-26 open: 568.0 close: 566.0\n",
"date: 2023-05-29 open: 574.0 close: 568.0\n",
"date: 2023-05-30 open: 566.0 close: 566.0\n",
"date: 2023-05-31 open: 560.0 close: 558.0\n",
"date: 2023-06-01 open: 550.0 close: 551.0\n",
"date: 2023-06-02 open: 559.0 close: 562.0\n",
"date: 2023-06-05 open: 560.0 close: 555.0\n",
"date: 2023-06-06 open: 554.0 close: 560.0\n",
"date: 2023-06-07 open: 561.0 close: 568.0\n",
"date: 2023-06-08 open: 562.0 close: 559.0\n",
"date: 2023-06-09 open: 561.0 close: 565.0\n",
"date: 2023-06-12 open: 574.0 close: 574.0\n",
"date: 2023-06-13 open: 593.0 close: 593.0\n",
"date: 2023-06-14 open: 590.0 close: 590.0\n",
"date: 2023-06-15 open: 590.0 close: 591.0\n",
"date: 2023-06-16 open: 590.0 close: 589.0\n",
"date: 2023-06-19 open: 583.0 close: 583.0\n",
"date: 2023-06-20 open: 579.0 close: 583.0\n",
"date: 2023-06-21 open: 582.0 close: 581.0\n",
"date: 2023-06-26 open: 576.0 close: 574.0\n",
"date: 2023-06-27 open: 570.0 close: 572.0\n",
"date: 2023-06-28 open: 579.0 close: 574.0\n",
"date: 2023-06-29 open: 578.0 close: 573.0\n",
"date: 2023-06-30 open: 570.0 close: 576.0\n",
"幫我用繁體中文分析\n"
]
}
],
"source": [
"gte = '2023-05-20'\n",
"lte = '2023-06-30'\n",
"stock = get_stock_price(gte, lte, '2330')\n",
"\n",
"# 時間 開收盤價格\n",
"date_price = ''\n",
"for i in range(len(stock)):\n",
" date = stock['年月日'][i].strftime('%Y-%m-%d')\n",
"# opens = stock['開盤價(元)'][i]\n",
" closes = stock['收盤價(元)'][i]\n",
" open_price = stock['開盤價(元)'][i]\n",
" date_price += f'date: {date} '\n",
"# date_price += f'開盤價: {opens} '\n",
" date_price += (f'open: {open_price} ' + f'close: {closes}\\n')\n",
" \n",
"\n",
"prompt = f'幫我分析市場波動趨勢，以下為股價資料：\\n'+ date_price + '幫我用繁體中文分析'\n",
"print(prompt)"
]
},
{
"cell_type": "code",
"execution_count": 106,
"id": "88ba7421",
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"根據這些股價資料，市場波動趨勢似乎是不穩定的。從5月22日到5月25日，股價有所上漲，但在5月29日之後，股價開始下跌。然後在6月12日，股價再次上漲，但在6月16日之後，股價再次下跌。從這些數據來看，市場波動趨勢似乎是不穩定的，並且可能會繼續波動。\n"
]
}
],
"source": [
"print(conversation.predict(input=prompt))"
]
},
{
"cell_type": "code",
"execution_count": 107,
"id": "918ac2c5",
"metadata": {
"scrolled": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"好的，以下是從6月開始每次收盤當天的乖離率表格：\n",
"\n",
"日期 | 收盤價 | 三天移動平均 | 乖離率\n",
"--- | --- | --- | ---\n",
"2023-06-01 | 551.0 | 547.33 | 0.66%\n",
"2023-06-02 | 562.0 | 547.67 | 2.68%\n",
"2023-06-05 | 555.0 | 559.0 | -0.72%\n",
"2023-06-06 | 560.0 | 559.0 | 0.18%\n",
"2023-06-07 | 568.0 | 561.0 | 1.25%\n",
"2023-06-08 | 559.0 | 562.67 | -0.65%\n",
"2023-06-09 | 565.0 | 564.33 | 0.12%\n",
"2023-06-12 | 574.0 | 566.0 | 1.41%\n",
"2023-06-13 | 593.0 | 577.33 | 2.71%\n",
"2023-06-14 | 590.0 | 579.0 | 1.91%\n",
"2023-06-15 | 591.0 | 591.33 | -0.56%\n",
"2023-06-16 | 589.0 | 590.0 | -0.17%\n",
"2023-06-19 | 583.0 | 587.67 | -0.80%\n",
"2023-06-20 | 583.0 | 585.0 | -0.34%\n",
"2023-06-21 | 581.0 | 582.33 | -0.23%\n",
"2023-06-26 | 574.0 | 579.33 | -0.93%\n",
"2023-06-27 | 572.0 | 575.67 | -0.64%\n",
"2023-06-28 | 574.0 | 573.33 | 0.11%\n",
"2023-06-29 | 573.0 | 573.0 | 0.00%\n",
"2023-06-30 | 576.0 | 574.33 | 0.29%\n"
]
}
],
"source": [
"print(conversation.predict(input='用三天的移動平均，幫我計算全部的收盤當天乖離率但只顯示從六月開始每次收盤當天的乖離率，產出表格'))"
]
},
{
"cell_type": "code",
"execution_count": 108,
"id": "9be76723",
"metadata": {
"scrolled": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"好的，以下是根據您提供的規則，從6月1日開始的進出場表格：\n",
"\n",
"日期 | 進出場 | 本金 | 獲利 | 總資產\n",
"--- | --- | --- | --- | ---\n",
"2023-06-01 | 進場 | 100000 | 0 | 100000\n",
"2023-06-02 | 出場 | 100000 | 2200 | 102200\n",
"2023-06-05 | 進場 | 102200 | 0 | 102200\n",
"2023-06-06 | 出場 | 102200 | 600 | 102800\n",
"2023-06-07 | 出場 | 102800 | 3200 | 106000\n",
"2023-06-08 | 進場 | 106000 | 0 | 106000\n",
"2023-06-09 | 出場 | 106000 | 1500 | 107500\n",
"2023-06-12 | 出場 | 107500 | 6500 | 114000\n",
"2023-06-13 | 出場 | 114000 | 3900 | 117900\n",
"2023-06-14 | 出場 | 117900 | 0 | 117900\n",
"2023-06-15 | 出場 | 117900 | 100 | 118000\n",
"2023-06-16 | 進場 | 118000 | 0 | 118000\n",
"2023-06-19 | 進場 | 118000 | 0 | 118000\n",
"2023-06-20 | 出場 | 118000 | 0 | 118000\n",
"2023-06-21 | 出場 | 118000 | 0 | 118000\n",
"2023-06-26 | 進場 | 118000 | 0 | 118000\n",
"2023-06-27 | 出場 | 118000 | 0 | 118000\n",
"2023-06-28 | 進場 | 118000 | 0 | 118000\n",
"2023-06-29 | 出場 | 118000 | 0 | 118000\n",
"2023-06-30 | 出場 | 118000 | 2400 | 120400\n",
"\n",
"請注意，進出場僅基於您提供的規則，並不代表任何投資建議。此外，獲利僅為估算值，實際獲利可能因手續費、稅金等因素而有所不同。\n"
]
}
],
"source": [
"print(conversation.predict(input='幫我用本金十萬元遵照以下規則。在六月第一天進場，前一天收盤價大於四天前最高價，且收盤乖離率>=0，則當天開盤價出場。\\\n",
" 在前一天收盤價小於四天前最低價，且收盤乖離率<=0，則當天開盤價進場，生成表格，請記得進出場都是用全部本金加獲利。'))"
]
},
{
"cell_type": "code",
"execution_count": 109,
"id": "f30e1550",
"metadata": {
"scrolled": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"好的，以下是詳細的報表：\n",
"\n",
"日期 | 進出場 | 本金 | 獲利 | 總資產 | 獲利金額\n",
"--- | --- | --- | --- | --- | ---\n",
"2023-06-01 | 進場 | 100000 | 0 | 100000 | 0\n",
"2023-06-02 | 出場 | 100000 | 2200 | 102200 | 2200\n",
"2023-06-05 | 進場 | 102200 | 0 | 102200 | 0\n",
"2023-06-06 | 出場 | 102200 | 600 | 102800 | 600\n",
"2023-06-07 | 出場 | 102800 | 3200 | 106000 | 3200\n",
"2023-06-08 | 進場 | 106000 | 0 | 106000 | 0\n",
"2023-06-09 | 出場 | 106000 | 1500 | 107500 | 1500\n",
"2023-06-12 | 出場 | 107500 | 6500 | 114000 | 6500\n",
"2023-06-13 | 出場 | 114000 | 3900 | 117900 | 3900\n",
"2023-06-14 | 出場 | 117900 | 0 | 117900 | 0\n",
"2023-06-15 | 出場 | 117900 | 100 | 118000 | 100\n",
"2023-06-16 | 進場 | 118000 | 0 | 118000 | 0\n",
"2023-06-19 | 進場 | 118000 | 0 | 118000 | 0\n",
"2023-06-20 | 出場 | 118000 | 0 | 118000 | 0\n",
"2023-06-21 | 出場 | 118000 | 0 | 118000 | 0\n",
"2023-06-26 | 進場 | 118000 | 0 | 118000 | 0\n",
"2023-06-27 | 出場 | 118000 | 0 | 118000 | 0\n",
"2023-06-28 | 進場 | 118000 | 0 | 118000 | 0\n",
"2023-06-29 | 出場 | 118000 | 0 | 118000 | 0\n",
"2023-06-30 | 出場 | 118000 | 2400 | 120400 | 2400\n",
"\n",
"總獲利大小為：17,800元。\n"
]
}
],
"source": [
"print(conversation.predict(input='幫我產出詳細表格報表，包含獲利金額大小、總獲利大小'))"
]
}
],
"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": "3.8.17"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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