Command-line chatbot on Python

Завдання:

Створити чатбот на завтра , який дає можливість спілкуватись з базою даних (csv). CLI. 

Опис:

Objective:

Build a command-line chatbot that allows users to interact with and analyze the GDP dataset from the World Bank using Python. The chatbot should handle natural language queries related to the dataset and optionally provide predictions on future GDP values.

Dataset:

The dataset to use is the World Bank GDP dataset, available here. The dataset contains GDP data for various countries over multiple years.

Requirements:

 1 Data Ingestion:

 ◦ Load and preprocess the GDP dataset.

 ◦ Handle any necessary data cleaning, such as dealing with missing values and formatting issues.

 2 Chatbot Interface:

 ◦ Implement a command-line interface (CLI) where users can interact with the chatbot. This can be rather simple.

 ◦ The chatbot should accept predefined natural language queries and provide responses based on the GDP dataset.

 ◦ You may use tools like LlamaIndex to parse and handle queries.

 3 Example Core Functionalities:

 ◦ Basic Queries:

 ▪ Retrieve GDP data for a specific country and year. Example query: "What was the GDP of the USA in 2020?"

 ▪ Show the top N countries by GDP for a specific year. Example query: "Show the top 5 countries by GDP in 2019."

 ▪ Compare GDP between two or more countries over a specified period. Example query: "Compare the GDP of China and India from 2000 to 2020."

 ◦ Time Series Analysis:

 ▪ Calculate the average GDP growth rate for a country over a period. Example query: "What was the average GDP growth rate of Brazil from 2000 to 2010?"

 ◦ Aggregated Analysis:

 ▪ Show global GDP growth over time. Example query: "What is the global GDP growth trend?"

 ▪ Identify the region or continent with the highest/lowest GDP for a given year. Example query: "Which continent had the highest GDP in 2015?"

 ▪ Analyze GDP distribution across countries in a particular year. Example query: "What is the GDP distribution for all countries in 2018?"

 ◦ Custom Analysis:

 ▪ Allow users to ask custom queries. Example query: "What is the GDP difference between the USA and Japan in 2010?"

Instructions:

 1 Setup:

 ◦ Use Python to build the chatbot.

 ◦ For the predictive model (if implemented), consider using libraries like scikit-learn, statsmodels, or any other suitable tool.

 ◦ You may use LlamaIndex or any other query-handling tool for predefined natural language queries.