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This project demonstrates the application of Natural Language Processing (NLP) and Retrieval-Augmented Generation (RAG) for financial sentiment analysis. It includes scripts for data preprocessing, sentiment analysis of financial news, and a RAG pipeline for question-answering.

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KrishBende/Financial-Sentiment-Analysis-RAG

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AI Financial Sentiment Analysis

This project demonstrates how to use AI for financial sentiment analysis, financial modeling, and question answering using a RAG pipeline.

Features

  • Sentiment Analysis: Analyze the sentiment of financial news headlines using a pre-trained NLP model.
  • Financial Modeling: Correlate sentiment with stock market data to build predictive models.
  • RAG Pipeline: Use a Retrieval-Augmented Generation (RAG) pipeline to answer questions about financial news.

How to Run

  1. Install the dependencies:
pip install -r requirements.txt
  1. Run the main script:
python main.py

About

This project demonstrates the application of Natural Language Processing (NLP) and Retrieval-Augmented Generation (RAG) for financial sentiment analysis. It includes scripts for data preprocessing, sentiment analysis of financial news, and a RAG pipeline for question-answering.

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