Financial Intelligence Hub

🔥 Overview

The Financial Intelligence Hub is a comprehensive RAG & LLM based application designed to enhance financial knowledge accessibility.

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🌟 Features

🔥 1. Financial Glossary Augmentation Module (RAG)

• Stores and retrieves financial terms with definitions, simplified explanations, and contextual examples.
• Uses a hybrid RAG architecture combining PostgreSQL (structured metadata) and Pinecone (vector search).
• Efficient retrieval with SQL filtering + vector store similarity search.
• Reranking logic to prioritize relevant results.

📰 2. Financial Market News Summarizer & Sentiment Analyzer Module

• Aggregates financial news articles from multiple sources (Google News RSS).
• Extracts and summarizes articles using LLM-based summarization.
• Stores articles in PostgreSQL with title, content, source, and summary.
• Analyzes the sentiment of financial news summaries.
• Labels each article as positive, negative, or neutral.
• Robust error handling with retries and content extraction.

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🛠️ Tech Stack

• Backend: Python (FastAPI)
• Database: PostgreSQL (structured data storage)
• Vector Store: Pinecone (vector embedding retrieval)
• Embedding Model: OpenAI Ada-002
• LLM: OpenAI GPT (summarization)
• Web Scraping: BeautifulSoup4
• Sentiment Model: VADER

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💡 How It Works

Glossary Augmentation Module Flow Diagram:

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🔧 How to Run

1️⃣ Clone the repository:

git clone https://github.com/your-username/financial-intelligence-hub.git
cd financial-intelligence-hub
python -m venv venv
source venv/bin/activate  # Linux/Mac
venv\Scripts\activate    # Windows

2️⃣ Set up environment variables: Create a .env file with the following details:

PINECONE_API_KEY=<YOUR_PINECONE_KEY>  
PINECONE_INDEX_NAME=<YOUR_INDEX_NAME> 
PINCONE_ENV=<YOUR_PINECONE_REGION>

PG_USER=""
PG_PASSWORD=""
PG_HOST=""
PG_PORT=5432
GLOSSARY_DB=glossary

OPENAI_API_KEY=<YOUR_OPENAI_KEY>

3️⃣ Install dependencies:

pip install -r requirements.txt

4️⃣ Run the PostgreSQL query:

CREATE TABLE glossary (
	id uuid DEFAULT gen_random_uuid() NOT NULL,
	term text NOT NULL,
	definition text NOT NULL,
	simplified_explanation text NULL,
	contextual_examples jsonb NULL,
	created_at timestamp DEFAULT CURRENT_TIMESTAMP NOT NULL,
	updated_at timestamp DEFAULT CURRENT_TIMESTAMP NOT NULL,
	deleted_at timestamp NULL,
	embedded bool NULL
);

CREATE EXTENSION IF NOT EXISTS "uuid-ossp";

CREATE TABLE news_articles (
    id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),
    title TEXT NOT NULL,
    source TEXT NOT NULL,
    url TEXT NOT NULL,
    published_at TIMESTAMP NOT NULL,
    summary TEXT,
	sentiment varchar(10) DEFAULT 'neutral'::character varying NOT NULL,
    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP NOT NULL,
    updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP NOT NULL,
    deleted_at TIMESTAMP NULL
);

5️⃣ Run:

python main.py