How to Build an AI Chatbot with Python and Gemini API

ChatGPT-4o vs Claude 3 5 Sonnet which AI chatbot wins?

There are many existing models out there for the training of chatbots. For me personally, I followed sentdex’s Youtube tutorial series which uses Python and TensorFlow. I used the nmt-chatbot (Github repository here) as the foundation and wrote a few tools to help me do the pre-processing of my WhatsApp chat data (My Github repository of tools here).

After the training of 200 epochs is completed we then save the trained model using Keras model.save(“chatbot_model.h5”) function. Import libraries and load the data- Create a new python file and name it as train_chatbot and then we are going to import all the required modules. After that, we will read the JSON data file in our python program. Today we are going to build an exciting project on Chatbot.

The complete code will look like this:

Once you run these commands, Pip will fetch the required libraries from the Python Package Index (PyPI) and neatly set them up in your Python environment. You’re now just a couple of steps away from creating your own AI chatbot. Once you run the whole python code, you can open your Discord and start talking with you AI Chatbot. It will stay Online as long as you don’t interrupt the running of the python file.

Anthropic launched Claude 3.5 Sonnet out of nowhere this week, providing a significant upgrade on its predecessor and outperforming even its largest Claude 3 model Opus on many common benchmarks. This course was created by Antonio Cangiano, a Software Developer at IBM Developer Skills Network. And Rishabh Kaushick, an active student leader with Toronto’s Google Developer Group and NU Coding Society, presented his work in AI tool development, specifically an AI-driven book recommendation system called Book Verse. Northeastern President Joseph E. Aoun recently delivered the keynote address at the annual conference of the Canadian Association of Graduate Studies. The event highlighted the practical application of AI in Toronto and across the global university system where interdisciplinary collaboration with industry partners is woven into the curriculum. Finally, the problem with Android connections is that you can’t do any Network related operation in the main thread as it would give the NetworkOnMainThreadException.

These, while initially unnecessary, have turned into proper careers. The best part is that to create an AI chatbot, you don’t need to be a programmer. Ask it how to create an AI chatbot using Python, and it will start giving you instructions. Now, open the Telegram app and send a direct message to your bot. You should receive a response back from the bot, generated by the OpenAI API.

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Torestart the AI chatbot server, simply move to the Desktop location again and run the below command. First, open the Terminal and run the below command to move to the Desktop. Conversational AI chatbots are undoubtedly the most advanced chatbots currently available. This type of chatbots use a mixture of Natural Language Processing (NLP) and Artificial Intelligence (AI) to understand the user intention and to provide personalised responses.

You can query further and conceptualize the plan on how to start it, what are the things to keep in mind, etc. You can also start with “Generate a new business idea for…” and then ChatGPT will come up with some amazing results. ChatGPT recently got support for Dall -E 3 and with this addition, it has gotten even more versatile and useful. You can create AI images with ChatGPT and generate logos, illustrations, and sketches.

It is based on the GPT-3.5 architecture and is trained on a massive corpus of text data. Telegram Bot, on the other hand, is a platform for building chatbots on the Telegram messaging app. It allows users to interact with your bot via text messages and provides a range of features for customisation.

That patient and understanding friend you’re looking for might just be a virtual language tutor powered by LLMs! This could be a game-changing way to master a language, all from the comfort of your own space. It is important to understand how to process the user answers. Simply feed the information to the AI to assume that role.

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Once the LLM has processed the data, you will find a local URL. Here, replace Your API Key with the one that you generated above on OpenAI’s website. Next, go to platform.openai.com/account/usage and check if you have enough credit left.

To use the gTTS library, you will need to have an internet connection as the library requires access to the Google’s server to convert the text to speech. For ChromeOS, you can use the excellent Caret app (Download) to edit the code. Now, it’s time to install the OpenAI library, which will allow us to interact with ChatGPT through their API. In the Terminal, run the below command to install the OpenAI library using Pip. Test your bot with different input messages to see how it responds.

Machine Learning time!

And just in case you do not like VS Code, other options worth considering include Notepad++, Sublime Text, PyCharm, and Atom, among others. However, if an update is available, pip will automatically handle the download and installation. Once the process is over, double-check the Pip version with the pip –version command to ensure the update was successful. Pip is Python’s package manager, essential for installing and managing Python libraries and dependencies. Keeping it updated ensures you benefit from the latest features and fixes, which is crucial when setting up libraries for your AI chatbot.

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To start, you’ll want to set up Python on your computer, ideally opting for one of its recent versions. Head to the official Python website’s download section to grab the 32- or 64-bit Windows installer, depending on the Windows version installed on your computer. For those who have never heard about Discord, it is a popular group-chatting app that was originally made to give gamers or geeks a place to build communities and talk [1]. What is interesting about Discord is the fact that it has a developer portal where you can do many fascinating things like deploying your own AI chatbot. Therefore, you need to sign up and join Discord Developer Portal from here. In this article, I am going to share with you my personal experience in creating and building my own AI Chatbot on Discord.

How to Build an AI Chatbot with Python and Gemini API

We can as well inspect the test response and choose best answer or add alternative phrasing for fine tuning. Once we are done with the training it is time to test the QnA maker. There are listings on resale sites for iPhones and Androids with TikTok downloaded for up to $10,000.

We will set value 1 to only those index that contains the word in the patterns. Same way we will create the output by setting 1 to the class input pattern belongs to. We’ve only scratched the surface so far, but this is a great starting point.

For a textual data, there are many preprocessing techniques available. The first technique is Tokenizing in which we break the sentences into words. The on_message() function listens for any message that comes into any channel that the bot is in. Each message that is sent on the Discord side will trigger this function and send a Message object that contains a lot of information about the message that was sent.

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• With the API operational, we will proceed to implement the node system in Java.
• From the output, the agent receives the task as input, and it initiates thought on knowing what is the task about.
• After that, we will read the JSON data file in our python program.
• There are many existing models out there for the training of chatbots.

So if you want to sell the idea of a custom-trained AI chatbot for customer service, technical assistance, database management, etc., you can start by creating an AI chatbot. If you are making an AI chatbot with ChatGPT, start by grabbing an API key from OpenAI’s website. Once you have that, you’ll integrate it into your coding environment to access the GPT-3.5 turbo model. For ease of use, use something like Gradio to create a neat interface. Refer to the guide above for the detailed step-by-step procedure.

To showcase this capability I served the chatbot through a Shiny for Python web application. Shiny is a framework that can be used to create interactive web applications that can run code in the backend. At the same time, it will have to support the client’s requests once it has accessed the interface. In this endpoint, the server uses a previously established Socket channel with the root node in the hierarchy to forward the query, waiting for its response through a synchronization mechanism. Nevertheless, creating and maintaining models to perform this kind of operation, particularly at a large scale, is not an easy job. One of the main reasons is data, as it represents the major contribution to a well-functioning model.

Additionally, I instructed her to keep the conversation engaging by asking questions. Speech recognition for my language tutor acts as the bridge between the user’s spoken input and the AI’s text-based understanding to generate response. It’s a critical component that enables voice-driven interaction, contributing to a more immersive and effective language learning experience.

Just scroll down, and there it is —  you’ll spot both a local and public URL. Grab that local URL, toss it into your browser, and prepare to be amazed. If you want to show off your achievement with your friends, do it by sharing the public URL. Note that these URLs are valid for only a limited period. Besides, you may have to keep your computer (and the command prompt window) up and running for the URLs to remain valid.