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---
title: STOCK_INSPECT
emoji: 📊
colorFrom: gray
colorTo: pink
sdk: streamlit
pinned: false
license: apache-2.0
---
# Stock Inspect
## Introduction
Stock Inspect is a Streamlit web application designed for stock analysis. It uses the Language Model (Gemini-pro from google) to provide insights based on user-provided stock names from NSE.
## Installation
1. Clone the repository:
```bash
git clone [email protected]:kailashsp/Stock_Inspect.git
cd Stock_Inspect
```
2. Install the required dependencies:
```bash
pip install -r requirements.txt
```
3. Setup env file
1. Create a `.env` file in the root directory of the project.
2. Add the following line to your `.env` file, replacing `YOUR_GOOGLE_API_KEY` with your actual Google API key:
```env
GOOGLE_API_KEY=YOUR_GOOGLE_API_KEY
```
## Usage
1. Run the Streamlit app:
```bash
streamlit run app.py
```
2. The web application will open in your default browser.
3. Enter a stock symbol in the search box to analyze the stock.
## Components
### Libraries/Frameworks Used
- Pandas: Data manipulation and analysis.
- JSON: Data interchange format.
- Streamlit: Web application framework.
- Streamlit Searchbox: Extension for a searchable dropdown.
### Files
- `app.py`: Main Streamlit application.
- `document_preprocessor.py`: Module for generating stock fundamentals.
- `llm.py`: Module for the Language Model (LLM).
- `prompt.py`: Module containing the stock analysis prompt.
- `MCAP31122023.xlsx`: Excel file containing stock data.
## Configuration
- `streamlit_config.toml`: Configuration file for Streamlit settings.
## Acknowledgments
- Stock data provided by [Finology](https://finology.in/).
## License
This project is licensed under the [MIT License](LICENSE).
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