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Financial Data Downloader and AI Query System for Enhanced Analysis

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# 📈 Financial Data Downloader & AI Query System

In the ever-evolving world of finance, having access to accurate and timely data is crucial. The **Financial Data Downloader & AI Query System** is an innovative project that enables users to download financial data for stocks and interact with it using an AI-powered natural language interface. This blog post will walk you through the project's features, setup, and potential use cases.

## 🚀 Description

This project is inspired by the article [Grok is Overrated. Do This To Transform ANY LLM to a Super-Intelligent Financial Analyst](https://medium.com/p/40f697092399). It allows users to download quarterly and annual financial data for stocks from EOD Historical Data and store it in both MongoDB and Google BigQuery. Additionally, it provides a natural language interface for querying this financial data, making it accessible even for those who may not be familiar with SQL.

For a more comprehensive solution that includes features like algorithmic trading, check out [NexusTrade](https://nexustrade.io/).

## 🔧 How to Use It

### Prerequisites

Before diving into the setup, ensure you have the following:

- **Node.js** (version 18 or higher) and **npm** installed.
- A running **MongoDB** instance.
- A **Google Cloud Platform (GCP)** account with BigQuery enabled.
- An API key from **Requesty** and **EOD Historical Data**.
- (Optional) **Ollama** installed for local LLM capabilities.

### Setup Steps

1. **Clone the repository:**
   ```bash
   git clone https://github.com/austin-starks/FinAnGPT-Pro
   cd FinAnGPT-Pro
   ```

  1. Install dependencies:

    npm install

  2. Create a .env file in the root directory and populate it with the necessary environment variables, including your MongoDB connection string and API keys.

Running the Script

You can run the script in two ways:

  • Using node directly: Compile the TypeScript code and run the compiled script.
  • Using ts-node: For easier execution during development.

Querying Financial Data

Once the setup is complete, you can download financial data and query it using natural language. Simply run the chat script:

ts-node chat.ts

You can ask questions like, "What stocks have the highest revenue?" and receive insightful responses.

🌟 Benefits and Use Cases

The Financial Data Downloader & AI Query System offers several benefits:

  • Accessibility: Users can query complex financial data using plain English, making it easier for beginners to engage with financial analysis.
  • Data Storage: By utilizing MongoDB and Google BigQuery, users can manage large datasets efficiently.
  • Real-Time Insights: The AI-powered interface allows for real-time data querying, providing up-to-date insights into financial performance.

Potential use cases include:

  • Financial analysts looking to streamline their data analysis process.
  • Students and educators in finance who need a practical tool for learning.
  • Investors seeking to make informed decisions based on comprehensive data analysis.

🔮 Future Directions

As the project evolves, there are several potential enhancements:

  • Integration with additional data sources to provide a more comprehensive financial analysis.
  • Enhanced error handling and logging for improved reliability in production environments.
  • User interface improvements to make the system even more user-friendly.

🏁 Conclusion

The Financial Data Downloader & AI Query System is a powerful tool for anyone interested in financial data analysis. With its ability to download, store, and query financial data using natural language, it opens up new possibilities for both beginners and experienced analysts alike.

To get started, visit the GitHub repository and explore the potential of this innovative project!