📈 FinGuru: News Research Tool

FinGuru is a news research tool that processes and analyzes news articles from given URLs and PDF. It leverages LangChain, Google embeddings, and Streamlit to provide insights and answers based on the content of the articles.

🎯 Features

• Fetch and parse news articles from URLs Or parse data from given pdf
• Split articles into manageable chunks
• Create embeddings for the text using GoogleEmbedding Model
• Store embeddings in a FAISS index for efficient retrieval
• Query the processed data to get answers and sources

🏗️ How It's Built

• Python 3.7+
• Streamlit
• LangChain
• Google API Key
• GOOGLE_CSE_ID

Used LLM

google gemini-pro

AWS Architecture

Equity Research Analysis

Tech Architecture

- Issue 1 : Copy pasting article in ChatGPt is tedious
- Issue 2 : We need an aggregate knowledge base

Revenue of apple

calories in apple

Semantic search

Vector Database

Agents

Used Agents

Wikipedia Google Search Google Finance duckduckGo search

🚀 Getting Started

Installation

1. Clone the repository:

git clone https://github.com/mihirh19/news_research_tool_Equity-Research-Analysis-.git
cd news_research_tool_Equity-Research-Analysis-

2. Create and activate a virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows use `venv\Scripts\activate`

3. Install the required packages:

   pip install -r requirements.txt

Setup

1. First, you need to set up the proper API keys and environment variables. To set it up, create the GOOGLE_API_KEY in the Google Cloud credential console (https://console.cloud.google.com/apis/credentials) and a GOOGLE_CSE_ID using the Programmable Search Engine (https://programmablesearchengine.google.com/controlpanel/create). Next, it is good to follow the instructions found here.

2. create api key on https://serpapi.com/

3. Create a file named secrets.toml in the .streamlit directory with the following content:

GOOGLE_API_KEY = "your-google-api-key"
GOOGLE_CSE_ID = "your-cse-id"
SERP_API_KEY ="your-"

Running the Application

streamlit run app.py

Usage

1. Open the Streamlit application in your browser.
2. Select options From dropdown Menu in the sidebar
3. For URL :
   • Enter the number of URLs you want to process in the sidebar.
   • Provide the URLs for the news articles.
   • Click on "Process URLs" to fetch and analyze the articles.
4. For pdf
   • Upload a PDF.
   • Click on "process Pdf" to analyze the PDF.
5. Enter a query in the text input box and click "Submit" to get answers based on the processed data.

You can also use the advance google search for financial questions.

Example 1 URL :

1. enter 3 as number of urls
2. provide following urls:
   1. https://www.moneycontrol.com/news/business/tata-motors-to-use-new-1-billion-plant-to-make-jaguar-land-rover-cars-report-12666941.html
   2. https://www.moneycontrol.com/news/business/stocks/tata-motors-stock-jumps-x-after-robust-jlr-sales-brokerages-bullish-12603201.html
   3. https://www.moneycontrol.com/news/business/stocks/buy-tata-motors-target-of-rs-1188-sharekhan-12411611.html
3. Click "Process URLs" to start processing.
4. Enter a query like what is the target price of tata motors ? and click Submit to get the answer.

Example 2 PDF :

1. AnnualReport202223.pdf Upload the Given PDF

2. Click "Process PDF" to start processing.

3. Enter a query like what is the yoy change of revenue of tata motors ? and click Submit to get answer.

Author

👤 Mihir Hadavani

• Twitter: @mihirh21
• Github: @mihirh19
• LinkedIn: @mihir-hadavani-996263232

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