QuantGPT is an AI-powered financial report analysis engine designed to efficiently parse and analyze large-scale financial documents, such as 300-page annual reports. By leveraging advanced NLP techniques, Langchain, and ChromaDB, QuantGPT allows for vectorized querying of financial statements, offering users precise, real-time insights into financial data.
This project deploys a Streamlit interface, integrated with the OpenAI API, to provide a seamless, interactive platform for financial report extraction and analysis. It offers real-time financial statement parsing, using GPT-4 to enhance financial data comprehension and decision-making.
- AI Agent: Utilizes Langchain and ChromaDB for vectorized NLP querying of large financial reports.
- Streamlit Interface: Provides an interactive platform for users to query and analyze financial statements in real-time.
- OpenAI API Integration: Integrated with GPT-4 for advanced natural language processing, extracting precise financial insights.
- Financial Statement Analysis: Automated extraction and summarization of key financial metrics and statements from reports.
- Python: The core programming language used for the backend and agent.
- Langchain: Manages the document parsing pipeline, vectorizing and analyzing text.
- ChromaDB: A vector store used for document embeddings and querying.
- Streamlit: Used to build an intuitive user interface for financial statement analysis.
- GPT-4: The language model used for processing financial language and extracting insights.
- PyPDF: Library used to handle PDF extraction and processing.
- CryptoDome: Adds security and cryptographic functionality.
This project is heavily inspired by LangchainDocuments, where similar methods were used to parse documents and apply NLP techniques.
Feel free to fork this repository, create a branch, and submit a pull request with any features, bug fixes, or improvements.
This project is licensed under the MIT License. See the LICENSE file for more details.