The new deadline for submission is July 24 due to community request.
Challenge:
This month’s community challenge is all about envisioning the future of AI-enabled apps. We would like to officially open this initiative to the community and challenge you to build a Dash app that integrates the ChatGPT API into your app.
The winning apps will be judged according to the following categories:
Depth of integration of ChatGPT API into the Dash app
App Design
Data exploration and data analysis routines (e.g. numerical methods, machine learning, prediction, classification, optimization)
Integrate ChatGPT into an app in a safe manner is increasingly important. To keep your app safe, we encourage you to read all about Prompt Hacking.
The winners will be announced in the next Dash Club dispatch and will receive a reward of:
$125 USD
$75 USD
$50 USD
To submit your app, share it by replying to this Forum topic by midnight Monday, July 10 (now July 24). Please include a link to the app, the code on GitHub, and a short description of the app.
For any questions, feel free to reply to the Forum topic or message me (Adam) directly.
An article with code explaining how the app was built is being finalizedhow to finetune ChatGPT for entity extraction has been published. It also links to the GH repo, with full code, as well as the training data.
Thank you for sharing this information about the community challenge.
For this challenge, I have developed a Model Competition app that allows users to compare different LLM models in terms of speed and the quality of their responses. It provides an interactive platform where you can assess multiple models simultaneously and determine which one performs the best.
Thank you @abhinva. I’ve heard people ask which LLM is better. This app should help them make their own judgement
I also saw all the other apps you have on your portfolio. Really nice collection!
I have developed an AI Summarizer app powered by OpenAI GPT-3.5 API, a cutting-edge language model. The app leverages the advanced capabilities of GPT-3.5 to generate accurate and coherent summaries of various types of texts, ranging from articles and blog posts to reports and documents.
Key Features:
Advanced Language Model: The app utilizes OpenAI GPT-3.5, a state-of-the-art language model, to understand the context, extract key information, and generate concise and coherent summaries.
Natural Language Understanding: GPT-3.5 comprehends the nuances of the input text, ensuring that the generated summaries capture the essential details and maintain the overall meaning and coherence.
Customizable Summarization Options: Users have the flexibility to customize the length and style of the summaries, tailoring them to their specific requirements.
User-Friendly Interface: The app features a user-friendly interface that allows users to easily input the text they want to summarize and obtain the summarized output within seconds.
I am excited to have created this AI Summarizer app using OpenAI GPT-3.5 API, which enables users to obtain accurate and concise summaries effortlessly.
My app was actually designed to fetch earthquake information from the records of the Kandilli Observatory and Earthquake Research Institute in Turkey. I retrieved the data by parsing the XML file in the desired format. Later, I visualized this information on various types of maps, including scatter, density, and hexagon layers. I also integrated a search bar with ChatGPT for brief interactions. Now, what I wanted to do was to introduce my dataframe to ChatGPT and have it provide me with the requested code snippets.GitHub - ceyhunsahin/earthquake, Afterwards, I planned to display the results using Python code. Although there are some CSS deficiencies, I shared a video on Twitter which you can review and provide feedback on. https://twitter.com/melkebir1/status/1671934468976787473?s=20
I’ll try to deploy but there were 3 million row in my dataset so I need to get a sample. If you have a docker, you can open it directly from my GitHub explanation that will be more effective😂 but when you’re ask for something you need to insist with explained question😁
For the needs of a circle of friends and me, I’ve built the Dash app for:
An easy communication with GPT-4 or 3.5 (first UI tab), which provides some AI personalities to chat with - or you can describe a custom one. It also supports markdown formatting and Latex for displaying equations
A summarization (second UI tab) of arbitrarily long PDF documents and web pages. There are three summarization options (normal summary, bullet points, focus on a question) and it tries to provide a structure with headings and subheadings.
I can’t provide a link to the working app due to potential costs but I have published it on GitHub so anyone can use it with their API keys:
Find the AI
In Find the AI, you will be presented with two quotes—one from a human and one generated by ChatGPT. Your objective is to identify which quote was written by the AI. You are presented with 10 quotes per day, and are given a score at the end of the game. The deployed app is available down below, and you can also run it locally by including your own OpenAI API key.
Some technical details:
Calls to external API for random quote and ChatGPT for AI quote
Responses from ChatGPT are cached to avoid unnecessary calls
Clientside callbacks are used to update the state of the game
New set of quotes are generated and saved to cache each day by scheduled task
$125 USD
$75 USD
$50 USD
