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Build a Chatbot with Gemini Pro Using Flask

PROJECT

Build a Chatbot with Gemini Pro Using Flask

In this project, we’ll build a responsive AI chatbot using Gemini Pro and Flask. The chatbot will provide dynamic, session-aware responses, showcasing real-time language capabilities in a web interface.

You will learn to:

Create a functional chatbot.

Set up a Flask web application.

Integrate the Gemini Pro model into a Python application.

Handle API interactions in a Flask application.

Skills

API Integration

Web Frameworks

Conversational Assistant

Prerequisites

Intermediate knowledge of Python

Intermediate knowledge of Flask

Gemini Pro API Key

Basic understanding of API integration

Technologies

Flask

Gemini

Python

Project Description

In this project, we will build a responsive AI chatbot using Flask and Gemini Pro that delivers smart, real-time responses based on user input.

The chatbot will maintain session context, enabling more natural, conversation-like interactions across multiple messages. We will explore key web development concepts such as form handling, dynamic UI updates, and session management using Flask.

With Gemini Pro’s language generation capabilities, the chatbot will understand various questions and respond intelligently. This project demonstrates how AI can create interactive and personalized web experiences.

Project Tasks

Initial Setup

Task 0: Get Started

Task 1: Get Gemini API

Create a Flask Application

Task 2: Create the Basic Template Layout

Task 3: Set Up Basic Routing and Render the Frontend

Integrate the Gemini API

Task 4: Create the Query Input Form

Task 5: Send the User Query

Task 6: Handle the User Query

Task 7: Render the Response from the API

Task 8: Implement Loading Spinner on Query Submission

Task 9: Add Question History View

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Relevant Courses

Use the following content to review prerequisites or explore specific concepts in detail.