ProdForecast-QAChatbot

🗒️ ProdForecast-QAChatbot

This is a Production Forecasting and QA Chatbot project that combines advanced time series forecasting with interactive question-answering capabilities. The application is designed to predict oil production rates and provide insights through a chatbot interface.

🚀 Features

• Production Forecasting:

  • Utilizes multiple forecasting models including Neural Networks, LSTM, Prophet, and RNN.
  • Allows users to select a time period and visualize predictions from different models on a single graph.
  • Capable of handling time series data specific to oil production.

• QA Chatbot:

  • Interactive chatbot designed to answer queries related to the forecasting process, models, and predictions.
  • Provides detailed explanations and insights into the production data and forecast results.
  • Built with a focus on user experience and complete responses.

🛠️ Technology Stack

• Programming Language: Python
• Libraries/Frameworks:
  • Streamlit for building the web interface
  • TensorFlow and Keras for Neural Networks and LSTM
  • Facebook Prophet for time series forecasting
  • LangChain for QA chatbot implementation
• Tools:
  • Git for version control
  • Conda for environment management

📊 Forecasting Models

The project includes the following forecasting models:

• Neural Network: A simple feedforward neural network for basic forecasting.
• LSTM: A Long Short-Term Memory model for handling time series data.
• Prophet: A forecasting model designed for time series data with daily observations.
• RNN: A Recurrent Neural Network model for capturing temporal dependencies.

🗨️ Chatbot Capabilities

The chatbot is capable of:

• Answering user questions related to oil production data.
• Providing insights and explanations for forecasts.
• Guiding users through the process of using the forecasting models.

🖥️ Setup & Installation

1. Clone the repository:

   git clone https://github.com/yourusername/ProdForecast-QAChatbot.git