{ "cells": [ { "cell_type": "markdown", "id": "263f914c-9d67-4316-8b3d-03c3b99ba9d8", "metadata": {}, "source": [ "SEC filings data\n", "=\n", "\n", "SEC filings data powered by [Kay.ai](https://kay.ai) and [Cybersyn](https://www.cybersyn.com/) via [Snowflake Marketplace](https://app.snowflake.com/marketplace/providers/GZTSZAS2KCS/Cybersyn%2C%20Inc).\n", "\n", ">The SEC filing is a financial statement or other formal document submitted to the U.S. Securities and Exchange Commission (SEC). Public companies, certain insiders, and broker-dealers are required to make regular SEC filings. Investors and financial professionals rely on these filings for information about companies they are evaluating for investment purposes." ] }, { "cell_type": "markdown", "id": "fc507b8e-ea51-417c-93da-42bf998a1195", "metadata": {}, "source": [ "Setup\n", "=\n", "\n", "First you will need to install the `kay` package. You will also need an API key: you can get one for free at [https://kay.ai](https://kay.ai/). Once you have an API key, you must set it as an environment variable `KAY_API_KEY`.\n", "\n", "In this example we're going to use the `KayAiRetriever`. Take a look at the [kay notebook](/docs/integrations/retrievers/kay) for more detailed information for the parmeters that it accepts.`" ] }, { "cell_type": "markdown", "id": "c923bea0-585a-4f62-8662-efc167e8d793", "metadata": {}, "source": [ "Examples\n", "=\n", "\n" ] }, { "cell_type": "code", "execution_count": 2, "id": "f7b8c99c-0341-4f3c-912f-a11e98f7de71", "metadata": {}, "outputs": [ { "name": "stdin", "output_type": "stream", "text": [ " ········\n", " ········\n" ] } ], "source": [ "# Setup API keys for Kay and OpenAI\n", "from getpass import getpass\n", "KAY_API_KEY = getpass()\n", "OPENAI_API_KEY = getpass()" ] }, { "cell_type": "code", "execution_count": 3, "id": "04ee2d6b-c2ab-4e15-8a8b-afaf6ef8c0f6", "metadata": {}, "outputs": [], "source": [ "import os\n", "os.environ[\"KAY_API_KEY\"] = KAY_API_KEY\n", "os.environ[\"OPENAI_API_KEY\"] = OPENAI_API_KEY" ] }, { "cell_type": "code", "execution_count": 7, "id": "0c504bcd-f6e0-4028-a797-b31fb4b6d027", "metadata": {}, "outputs": [], "source": [ "from langchain.chains import ConversationalRetrievalChain\n", "from langchain.chat_models import ChatOpenAI\n", "from langchain.retrievers import KayAiRetriever\n", "\n", "model = ChatOpenAI(model_name=\"gpt-3.5-turbo\")\n", "retriever = KayAiRetriever.create(dataset_id=\"company\", data_types=[\"10-K\", \"10-Q\"], num_contexts=6)\n", "qa = ConversationalRetrievalChain.from_llm(model, retriever=retriever)" ] }, { "cell_type": "code", "execution_count": 11, "id": "977f158b-38d3-4b5f-9379-7cdd09436327", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "-> **Question**: What are patterns in Nvidia's spend over the past three quarters? \n", "\n", "**Answer**: Based on the provided information, here are the patterns in NVIDIA's spend over the past three quarters:\n", "\n", "1. Research and Development Expenses:\n", " - Q3 2022: Increased by 34% compared to Q3 2021.\n", " - Q1 2023: Increased by 40% compared to Q1 2022.\n", " - Q2 2022: Increased by 25% compared to Q2 2021.\n", " \n", " Overall, research and development expenses have been consistently increasing over the past three quarters.\n", "\n", "2. Sales, General and Administrative Expenses:\n", " - Q3 2022: Increased by 8% compared to Q3 2021.\n", " - Q1 2023: Increased by 14% compared to Q1 2022.\n", " - Q2 2022: Decreased by 16% compared to Q2 2021.\n", " \n", " The pattern for sales, general and administrative expenses is not as consistent, with some quarters showing an increase and others showing a decrease.\n", "\n", "3. Total Operating Expenses:\n", " - Q3 2022: Increased by 25% compared to Q3 2021.\n", " - Q1 2023: Increased by 113% compared to Q1 2022.\n", " - Q2 2022: Increased by 9% compared to Q2 2021.\n", " \n", " Total operating expenses have generally been increasing over the past three quarters, with a significant increase in Q1 2023.\n", "\n", "Overall, the pattern indicates a consistent increase in research and development expenses and total operating expenses, while sales, general and administrative expenses show some fluctuations. \n", "\n" ] } ], "source": [ "questions = [\n", " \"What are patterns in Nvidia's spend over the past three quarters?\",\n", " #\"What are some recent challenges faced by the renewable energy sector?\",\n", "]\n", "chat_history = []\n", "\n", "for question in questions:\n", " result = qa({\"question\": question, \"chat_history\": chat_history})\n", " chat_history.append((question, result[\"answer\"]))\n", " print(f\"-> **Question**: {question} \\n\")\n", " print(f\"**Answer**: {result['answer']} \\n\")" ] } ], "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": "3.9.1" } }, "nbformat": 4, "nbformat_minor": 5 }