160 lines
4.7 KiB
Plaintext
160 lines
4.7 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": "922bb144",
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"metadata": {},
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"outputs": [],
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"source": [
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"import os\n",
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"import requests\n",
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"from dotenv import load_dotenv\n",
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"from bs4 import BeautifulSoup\n",
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"from IPython.display import Markdown, display\n",
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"from openai import OpenAI"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "870bdcd9",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Load environment variables in a file called .env\n",
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"load_dotenv(override=True)\n",
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"api_key = os.getenv(\"OPENAI_API_KEY\")\n",
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"\n",
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"# Check the key\n",
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"if not api_key:\n",
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" print(\"No API key was found - please head over to the troubleshooting notebook in this folder to identify & fix!\")\n",
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"elif not api_key.startswith(\"sk-proj-\"):\n",
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" 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",
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"elif api_key.strip() != api_key:\n",
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" 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",
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"else:\n",
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" print(\"API key found and looks good so far!\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "f6146102",
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"metadata": {},
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"outputs": [],
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"source": [
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"openai = OpenAI()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "2f75573f",
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"metadata": {},
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"outputs": [],
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"source": [
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"class FinvizWebsite():\n",
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" \"\"\"\n",
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" Create this Website object from the given url using the BeautifulSoup library\n",
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" \"\"\"\n",
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" \n",
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" def __init__(self, ticker):\n",
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" self.ticker = ticker.upper()\n",
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" self.url = f\"https://finviz.com/quote.ashx?t={self.ticker}&p=d&ty=ea\"\n",
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" self.headers = {\n",
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" \"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",
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" }\n",
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" response = requests.get(self.url, headers=self.headers)\n",
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" soup = BeautifulSoup(response.content, \"html.parser\")\n",
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" self.title = soup.title.string if soup.title else \"No title found\"\n",
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" self.table = soup.find(\"table\", class_=\"snapshot-table2\") "
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "42c7ced6",
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"metadata": {},
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"outputs": [],
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"source": [
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"def messages_for(website):\n",
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" system_prompt = \"\"\"\n",
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" You are a financial analysis assistant that analyzes the contents of HTML formated table.\n",
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" and provides a summary of the stock's analysis with clear and professional language appropriate for financial research \n",
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" with bulleted important list of **pros** and **cons** , ignoring text that might be navigation related. Repond in markdown.\n",
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" \"\"\"\n",
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" \n",
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" user_prompt = f\"\"\"\n",
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" You are looking at a website titled {website.title}.\\n\n",
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" 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",
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" {website.table}\n",
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" \"\"\"\n",
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" \n",
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" return [\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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" ]\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "7bfaa6da",
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"metadata": {},
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"outputs": [],
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"source": [
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"def display_summary(ticker):\n",
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" website = FinvizWebsite(ticker)\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_for(website)\n",
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" )\n",
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" summary = response.choices[0].message.content\n",
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" display(Markdown(summary))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "eeeff6f7",
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"metadata": {},
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"outputs": [],
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"source": [
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"display_summary(\"aapl\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "5aed2001",
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"metadata": {},
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"outputs": [],
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"source": [
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"display_summary(\"tsla\")"
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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": ".venv",
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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": "3.12.10"
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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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