https://github.com/sujata-adhikari/large-language-model

Tool to extract financial news from articles can be approached using Langchain and OpenAI techniques. Enter the URL's in the tools and asked the question.
https://github.com/sujata-adhikari/large-language-model

jyputer-notebook llm openai pickel pycharm-ide streamlit

Last synced: about 1 month ago
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Tool to extract financial news from articles can be approached using Langchain and OpenAI techniques. Enter the URL's in the tools and asked the question.

• Host: GitHub
• URL: https://github.com/sujata-adhikari/large-language-model
• Owner: sujata-adhikari
• Created: 2023-12-13T02:50:49.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2024-01-04T09:35:21.000Z (about 1 year ago)
• Last Synced: 2024-10-31T17:44:42.794Z (3 months ago)
• Topics: jyputer-notebook, llm, openai, pickel, pycharm-ide, streamlit
• Language: Python
• Homepage:
• Size: 310 KB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Financial Insights

A user-friendly news research tool designed for effortless information retrieval. Users can input article URLs and ask questions to receive relevant insights from the stock market and financial domain.

## Features

- Load URLs or upload text files containing URLs to fetch article content.

- Process article content through LangChain's UnstructuredURL Loader

- Construct an embedding vector using OpenAI's embeddings and leverage FAISS, a powerful similarity search library, to enable swift and effective retrieval of relevant information

- Interact with the LLM's (Chatgpt) by inputting queries and receiving answers along with source URLs.

## Installation

1.Clone this repository to your local machine using:

```bash

  git clone https://github.com/

```

2.Navigate to the project directory:

3. Install the required dependencies using pip:

```bash

  pip install -r requirements.txt

```

4.Set up your OpenAI API key by creating a .env file in the project root and adding your API

```bash

  OPENAI_API_KEY=your_api_key_here

```

## Usage/Examples

1. Run the Streamlit app by executing:

```bash

streamlit run main.py

```

## Project Structure

- main.py: The main Streamlit application script.

- requirements.txt: A list of required Python packages for the project.

- faiss_store_openai.pkl: A pickle file to store the FAISS index.

- .env: Configuration file for storing your OpenAI API key.