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.
- 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.
1.Clone this repository to your local machine using:
git clone https://github.com/
2.Navigate to the project directory:
- Install the required dependencies using pip:
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
OPENAI_API_KEY=your_api_key_here
- Run the Streamlit app by executing:
streamlit run main.py
- 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.