Q&A Project with Language Model and OpenAI API 🤖📚

Overview

This project aims to enhance the question and answer (Q&A) experience by integrating a Language Model (LLM) through the OpenAI API. The combination of advanced language understanding and dynamic responses enables the system to generate meaningful answers to user queries based on a provided passage.

Key Features

1. Language Model (LLM):

The project leverages a sophisticated Language Model capable of comprehending and processing textual information. This model forms the backbone of the Q&A system, enabling it to understand context and generate relevant responses. 🧠

2. OpenAI API Integration:

Integration with the OpenAI API allows seamless communication with the language model. This dynamic interaction enables real-time generation of responses, enhancing the adaptability and intelligence of the Q&A system. 🌐

3. Question and Answer System:

Users can input a passage containing information relevant to a particular domain or topic. The system then processes user queries and extracts information from the provided passage to generate accurate and contextually appropriate responses. ❓💬

Getting Started

1. Clone the Repository:

Clone the project repository from your GitHub account to your local machine. This provides you with the source code and necessary files. 📥

2. Install Dependencies:

Ensure you have the required dependencies installed by running the provided commands. This typically includes any Python packages specified in the requirements.txt file. 🛠️

3. Obtain OpenAI API Key:

To enable communication with the OpenAI API, sign up on the OpenAI platform and obtain an API key. Set this key as an environment variable to facilitate secure access. 🔑

4. Run the Application:

Execute the application to start the Q&A system. Access the system through a web browser at the specified local host address (e.g., http://localhost:5000). ▶️

Usage

1. Input Passage:

Provide a text passage containing information relevant to the questions users might ask. This serves as the knowledge base from which the system draws answers. 📝

2. Ask Questions:

Users can input questions related to the provided passage. The system processes these questions using the language model and generates responses by extracting information from the passage. ❓🤔

3. View Responses:

The system displays the generated responses, allowing users to quickly and accurately obtain information based on their queries. 👁️‍🗨️

Acknowledgments

The project acknowledges and utilizes the OpenAI API. For in-depth information on the API's capabilities and usage, consult the OpenAI documentation.

output of this project

llm.project.recording.1.mp4