In this article, we are going to do something really cool: we will build a chatbot using Python and the Gemini API. This will be a web-based assistant and could be the beginning of your own AI project. It's beginner-friendly, and I will guide you through it step-by-step. By the end, you'll have your own AI assistant! What You'll Need IDE (I recommend Visual Studio Code)
Gemini API key
Python
Python libraries Download IDE - VS code You can use any IDE you like, but if you don’t have one, please download VS Code. It’s really powerful and easy to use. Here's the link:  https://code.visualstudio.com/download Gemini API Create a Google Cloud Project Before we obtain an API key, we need to create a project in Google Cloud. To create a project, please follow this link: https://console.cloud.google.com/cloud-resource-manager After the project is created, we are ready to request an API key. How to Get Gemini API Key To get the API key, visit <https://aistudio.google.com/app/apikey](https://aistudio.google.com/app/apikey) and click on the "Create API key" button. Then, select the project that you created in the previous step from the drop-down menu and click "Generate API key”. Copy the key; we’ll need it in the next steps. Install Python Windows: Download the installer from https://www.python.org/downloads/windows/ Linux (Ubuntu/Debian): Use this command in your terminal window: sudo apt-get install python3 Install Python Libraries For the next steps, you need to use the terminal. If you are on Windows, you can use https://apps.microsoft.com/detail/9n0dx20hk701?rtc=1&hl=en-us Install PIP After we set up Python, we need to set up the pip package installer for Python. sudo apt install python3-pip Set Up a Virtual Environment The next step is to set up virtual environments for our project to manage dependencies separately. Use this command: sudo apt install python3-venv The command python3 -m venv myprojectenv is used to create a virtual environment for a Python project: python3 -m venv myprojectenv The command source myprojectenv/bin/activate is used to activate the virtual environment: source myprojectenv/bin/activate Install LangChain LangChain is a framework designed to simplify the creation of applications using large language models. Use this command: pip install langchain-core Install LangChain-Google-GenAI Use this command: pip install langchain-google-genai This package contains the LangChain integrations for Gemini through their generative-ai SDK. Once you’ve done that, we are ready to go to the next steps. Install Flask Once the virtual environment is activated, we can use pip to set up Flask. Use this command: pip install Flask Create a ChatBot with the Python Flask Framework First, let’s create a directory for our app. Use these commands: mkdir myflaskapp cd myflaskapp Inside the directory, create a file for our app and call it "app.py". Then add the following content: from flask import Flask app = Flask(name) @app.route('/') def home(): return "Hello, Flask!" if name == 'main': app.run(debug=True) To make sure that our app is working fine, let’s run it. Use this command: python3 app.py If everything is okay, you will be able to access your Flask app at http://127.0.0.1:5000. Create an HTML Page for the Flask App You can create your own HTML or use the example provided. You can download it from here: <https://github.com/proflead/gemini-flask-app/blob/master/web/index.html](https://github.com/proflead/gemini-flask-app/blob/master/web/index.html) You will need 2 JavaScript files: To communicate with the Gemini API: <https://github.com/proflead/gemini-flask-app/blob/master/web/gemini-api.js](https://github.com/proflead/gemini-flask-app/blob/master/web/gemini-api.js)
And <https://github.com/proflead/gemini-flask-app/blob/master/web/main.js](https://github.com/proflead/gemini-flask-app/blob/master/web/main.js) To format the output result on the page without reloading the page. Change app.py Let’s modify our app.py file with the following code: You can copy the code from here: https://github.com/proflead/gemini-flask-app/blob/master/app.py Once you are ready, run this command in the project folder: python3 app.py If you did everything correctly, you will be able to see your ChatBot. Video Tutorial: AI Chatbot using Python and Gemini API https://youtu.be/CqfKk_JjuEo?si=prok6R_NfkUQRhtC&embedable=true Visit my YouTube Channel Conclusion As you can see, building a chatbot with Python and the Gemini API is not that difficult. You can further improve it by adding styles, extra functions, or even vision recognition. If you run into any issues, feel free to leave a comment explaining your problem, and I'll try to help you. Cheers! :) In this article, we are going to do something really cool: we will build a chatbot using Python and the Gemini API. This will be a web-based assistant and could be the beginning of your own AI project. It's beginner-friendly, and I will guide you through it step-by-step. By the end, you'll have your own AI assistant! Python What You'll Need IDE (I recommend Visual Studio Code) Gemini API key Python Python libraries IDE (I recommend Visual Studio Code) Gemini API key Python Python libraries Download IDE - VS code You can use any IDE you like, but if you don’t have one, please download VS Code. It’s really powerful and easy to use. Here's the link: https://code.visualstudio.com/download https://code.visualstudio.com/download https://code.visualstudio.com/download Gemini API Create a Google Cloud Project Before we obtain an API key, we need to create a project in Google Cloud. To create a project, please follow this link: https://console.cloud.google.com/cloud-resource-manager https://console.cloud.google.com/cloud-resource-manager https://console.cloud.google.com/cloud-resource-manager After the project is created, we are ready to request an API key. How to Get Gemini API Key To get the API key, visit <https://aistudio.google.com/app/apikey](https://aistudio.google.com/app/apikey) and click on the "Create API key" button. <https://aistudio.google.com/app/apikey](https://aistudio.google.com/app/apikey) Then, select the project that you created in the previous step from the drop-down menu and click "Generate API key”. Copy the key; we’ll need it in the next steps. Copy the key; we’ll need it in the next steps. Install Python Windows: Download the installer from https://www.python.org/downloads/windows/ Windows: https://www.python.org/downloads/windows/ https://www.python.org/downloads/windows/ Linux (Ubuntu/Debian): Use this command in your terminal window: Linux (Ubuntu/Debian): sudo apt-get install python3 sudo apt-get install python3 Install Python Libraries For the next steps, you need to use the terminal. If you are on Windows, you can use https://apps.microsoft.com/detail/9n0dx20hk701?rtc=1&hl=en-us https://apps.microsoft.com/detail/9n0dx20hk701?rtc=1&hl=en-us https://apps.microsoft.com/detail/9n0dx20hk701?rtc=1&hl=en-us Install PIP After we set up Python, we need to set up the pip package installer for Python. sudo apt install python3-pip sudo apt install python3-pip Set Up a Virtual Environment The next step is to set up virtual environments for our project to manage dependencies separately. Use this command: sudo apt install python3-venv sudo apt install python3-venv The command python3 -m venv myprojectenv is used to create a virtual environment for a Python project: python3 -m venv myprojectenv python3 -m venv myprojectenv The command source myprojectenv/bin/activate is used to activate the virtual environment: source myprojectenv/bin/activate source myprojectenv/bin/activate Install LangChain LangChain is a framework designed to simplify the creation of applications using large language models. Use this command: pip install langchain-core pip install langchain-core Install LangChain-Google-GenAI Use this command: pip install langchain-google-genai pip install langchain-google-genai This package contains the LangChain integrations for Gemini through their generative-ai SDK. Once you’ve done that, we are ready to go to the next steps. Install Flask Once the virtual environment is activated, we can use pip to set up Flask. Use this command: pip install Flask pip install Flask Create a ChatBot with the Python Flask Framework First, let’s create a directory for our app. Use these commands: mkdir myflaskapp mkdir myflaskapp cd myflaskapp cd myflaskapp Inside the directory, create a file for our app and call it "app.py". Then add the following content: from flask import Flask from flask import Flask app = Flask(name) app = Flask(name) @app.route('/') @app.route('/') def home(): def home(): return "Hello, Flask!" return "Hello, Flask!" if name == 'main': if name == 'main': app.run(debug=True) app.run(debug=True) To make sure that our app is working fine, let’s run it. Use this command: python3 app.py python3 app.py If everything is okay, you will be able to access your Flask app at http:// 127.0.0.1:5000 . 127.0.0.1:5000 Create an HTML Page for the Flask App You can create your own HTML or use the example provided. You can download it from here: <https://github.com/proflead/gemini-flask-app/blob/master/web/index.html](https://github.com/proflead/gemini-flask-app/blob/master/web/index.html) <https://github.com/proflead/gemini-flask-app/blob/master/web/index.html](https://github.com/proflead/gemini-flask-app/blob/master/web/index.html) <https://github.com/proflead/gemini-flask-app/blob/master/web/index.html](https://github.com/proflead/gemini-flask-app/blob/master/web/index.html) You will need 2 JavaScript files: You will need 2 JavaScript files: To communicate with the Gemini API: <https://github.com/proflead/gemini-flask-app/blob/master/web/gemini-api.js](https://github.com/proflead/gemini-flask-app/blob/master/web/gemini-api.js) And <https://github.com/proflead/gemini-flask-app/blob/master/web/main.js](https://github.com/proflead/gemini-flask-app/blob/master/web/main.js) To format the output result on the page without reloading the page. To communicate with the Gemini API: <https://github.com/proflead/gemini-flask-app/blob/master/web/gemini-api.js](https://github.com/proflead/gemini-flask-app/blob/master/web/gemini-api.js) <https://github.com/proflead/gemini-flask-app/blob/master/web/gemini-api.js](https://github.com/proflead/gemini-flask-app/blob/master/web/gemini-api.js) And <https://github.com/proflead/gemini-flask-app/blob/master/web/main.js](https://github.com/proflead/gemini-flask-app/blob/master/web/main.js) To format the output result on the page without reloading the page. <https://github.com/proflead/gemini-flask-app/blob/master/web/main.js](https://github.com/proflead/gemini-flask-app/blob/master/web/main.js) Change app.py Let’s modify our app.py file with the following code: You can copy the code from here: https://github.com/proflead/gemini-flask-app/blob/master/app.py https://github.com/proflead/gemini-flask-app/blob/master/app.py https://github.com/proflead/gemini-flask-app/blob/master/app.py Once you are ready, run this command in the project folder: python3 app.py python3 app.py If you did everything correctly, you will be able to see your ChatBot. Video Tutorial: AI Chatbot using Python and Gemini API https://youtu.be/CqfKk_JjuEo?si=prok6R_NfkUQRhtC&embedable=true https://youtu.be/CqfKk_JjuEo?si=prok6R_NfkUQRhtC&embedable=true Visit my YouTube Channel Visit my YouTube Channel Conclusion As you can see, building a chatbot with Python and the Gemini API is not that difficult. You can further improve it by adding styles, extra functions, or even vision recognition. If you run into any issues, feel free to leave a comment explaining your problem, and I'll try to help you. Cheers! :)

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How to Build an AI Chatbot with Python and Gemini API

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