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LLM_Engineering_OLD/week1/community-contributions/day1-finviz_stock_analysis.ipynb
2025-06-30 01:21:01 +07:00

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4.7 KiB
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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"id": "922bb144",
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"import requests\n",
"from dotenv import load_dotenv\n",
"from bs4 import BeautifulSoup\n",
"from IPython.display import Markdown, display\n",
"from openai import OpenAI"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "870bdcd9",
"metadata": {},
"outputs": [],
"source": [
"# Load environment variables in a file called .env\n",
"load_dotenv(override=True)\n",
"api_key = os.getenv(\"OPENAI_API_KEY\")\n",
"\n",
"# Check the key\n",
"if not api_key:\n",
" print(\"No API key was found - please head over to the troubleshooting notebook in this folder to identify & fix!\")\n",
"elif not api_key.startswith(\"sk-proj-\"):\n",
" print(\"An API key was found, but it doesn't start sk-proj-; please check you're using the right key - see troubleshooting notebook\")\n",
"elif api_key.strip() != api_key:\n",
" print(\"An API key was found, but it looks like it might have space or tab characters at the start or end - please remove them - see troubleshooting notebook\")\n",
"else:\n",
" print(\"API key found and looks good so far!\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f6146102",
"metadata": {},
"outputs": [],
"source": [
"openai = OpenAI()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "2f75573f",
"metadata": {},
"outputs": [],
"source": [
"class FinvizWebsite():\n",
" \"\"\"\n",
" Create this Website object from the given url using the BeautifulSoup library\n",
" \"\"\"\n",
" \n",
" def __init__(self, ticker):\n",
" self.ticker = ticker.upper()\n",
" self.url = f\"https://finviz.com/quote.ashx?t={self.ticker}&p=d&ty=ea\"\n",
" self.headers = {\n",
" \"User-Agent\": \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/117.0.0.0 Safari/537.36\"\n",
" }\n",
" response = requests.get(self.url, headers=self.headers)\n",
" soup = BeautifulSoup(response.content, \"html.parser\")\n",
" self.title = soup.title.string if soup.title else \"No title found\"\n",
" self.table = soup.find(\"table\", class_=\"snapshot-table2\") "
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "42c7ced6",
"metadata": {},
"outputs": [],
"source": [
"def messages_for(website):\n",
" system_prompt = \"\"\"\n",
" You are a financial analysis assistant that analyzes the contents of HTML formated table.\n",
" and provides a summary of the stock's analysis with clear and professional language appropriate for financial research \n",
" with bulleted important list of **pros** and **cons** , ignoring text that might be navigation related. Repond in markdown.\n",
" \"\"\"\n",
" \n",
" user_prompt = f\"\"\"\n",
" You are looking at a website titled {website.title}.\\n\n",
" The contents of this website is as follows; please provide a summary of the stock's analysis from this website in markdown.\\n\\n\n",
" {website.table}\n",
" \"\"\"\n",
" \n",
" return [\n",
" {\"role\": \"system\", \"content\": system_prompt},\n",
" {\"role\": \"user\", \"content\": user_prompt}\n",
" ]\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7bfaa6da",
"metadata": {},
"outputs": [],
"source": [
"def display_summary(ticker):\n",
" website = FinvizWebsite(ticker)\n",
" response = openai.chat.completions.create(\n",
" model = \"gpt-4o-mini\",\n",
" messages = messages_for(website)\n",
" )\n",
" summary = response.choices[0].message.content\n",
" display(Markdown(summary))"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "eeeff6f7",
"metadata": {},
"outputs": [],
"source": [
"display_summary(\"aapl\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "5aed2001",
"metadata": {},
"outputs": [],
"source": [
"display_summary(\"tsla\")"
]
}
],
"metadata": {
"kernelspec": {
"display_name": ".venv",
"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": "3.12.10"
}
},
"nbformat": 4,
"nbformat_minor": 5
}