stocks-insights-ai-agent

What is the Stock Analysis Tool?

The stock analysis tool is a full-stack application that uses LLM (large language models) and LangChain technology combined with LangGraph to retrieve and analyze stock data and news. It utilizes ChromaDB as a vector database, supporting semantic search and data visualization to provide users with deep insights into the stock market. This product is aimed at investors, financial analysts, and data scientists, helping them quickly obtain and analyze stock-related information to assist in decision-making. The product is currently open-source and free, suitable for users who need efficient processing of financial data and news.

Who Can Use This Product?

This product is ideal for investors, financial analysts, and data scientists. Investors can use it to quickly access stock market information, aiding investment decisions. Financial analysts can delve into stock data and news for comprehensive research support. Data scientists can leverage its technical architecture for further data mining and model development.

Example Scenarios:

Investors can use this application to quickly review the historical price trends and related news of specific stocks, aiding investment decisions.

Financial analysts can utilize its data scraping and analysis features to thoroughly examine the financial performance and market dynamics of specific companies.

Data scientists can build custom financial data analysis models based on the open-source code and architecture of this application.

Key Features:

Stock Performance Visualization: Display selected stock historical performance through charts.

Attribute-Specific Data Retrieval: Obtain detailed information about specific stocks.

News Aggregation: Provide news articles related to specific stocks or companies.

Asynchronous Data Scraping: Regularly scrape news and financial data, storing it in the database.

LangGraph Workflow: Implement semantic search and result generation for news and stock data using RAG graphs.

API Interface: Offer various APIs to access stock price statistics, news, and other data.

Testing Framework: Use pytest for automated testing to ensure application stability and reliability.

Observability and Tracing: Integrate LangSmith tracking to monitor LLM calls and debug processes.

How to Use This Product:

1. Visit the GitHub repository page, clone or download the project code.

2. Install project dependencies including Python environment and libraries.

3. Configure database connections including MongoDB and PostgreSQL.

4. Start the data scraping service to regularly update stock and news data.

5. Use LangGraph workflow for data queries and analysis.

6. Access stock price statistics, news, and other data via API interfaces.

7. Use visualization tools to view stock performance charts.

8. Expand the code or integrate into other systems as needed.