StableCode 24-hours Hackathon Summary

System will be based on image processing techniques. Recognition of facial expressions is targeted in order to improve the autism patient’s emotional understanding. To build software which involves image processing mechanism where training is performed on various facial expressions and then they are tested to recognize desired expression. Our Goal of this project to judge the expressions of autism patients in easiest way who can’t express his feelings. We will make this project to detect the feeling of all these and to help them. • First, the app will start and ask user to capture or browse image. • Then app will convert an RGB image to greyscale/Bitmap and apply noise reduction techniques. • After that, app will detect image and extract required features to create facial expressions. • Then using mood classifiers, it will generate a model. • After that generated model will be matched to trained data using cognitive analysis. • If model matches then app will generate an alert about mood detection. • At last, detected mood will be tested. High-level system components: • Capturing & Browsing of Image • Noise Reduction • Grey Scale Conversion • Image processing & Edge Detection • Analyzing Image matching • Mood Detection

ELGC

"StableReverse" is an app that empowers users to explore, comprehend, and analyze Python code repositories hosted on GitHub. This innovative project simplifies the challenging task of reverse engineering code by offering a comprehensive suite of features and an intuitive interface, making it accessible to a broad spectrum of users, from experienced developers to data scientists and curious learners. StableReverse leverage GPT3 for analyzing the repo filse system and StableCode for writing the code. Use Cases: Code Debugging: Developers can use "StableReverse" to understand and debug unfamiliar code segments, identifying issues and improving software quality. Algorithm Exploration: Data scientists and researchers can explore complex algorithms and data processing techniques implemented in open-source projects. Learning Tool: Students and learners can gain insights into coding practices by studying and reverse engineering real-world code. Open-Source Contribution: Contributors to open-source projects can quickly grasp project structures and coding conventions. Code Auditing: Security experts can use "StableReverse" to identify potential vulnerabilities and security issues in codebases. Innovation Exploration: Innovators and entrepreneurs can explore existing codebases for inspiration and to understand emerging technologies.

StableReverse

**Code Helper Application - StableCode** The **Code Helper** application, powered by **StableCode**, offers a comprehensive solution for developers seeking assistance with their coding tasks. It combines the capabilities of an advanced chatbot and a code completion engine to provide accurate and efficient responses to user inquiries. The application employs a **Flask** backend and a **Streamlit** frontend, offering a seamless and user-friendly experience. **Functionality:** Users of the Code Helper application can submit instructions or code completion queries through a user-friendly interface. These queries cover a wide range of programming-related questions, from seeking explanations about specific coding concepts to requesting code suggestions for a particular task. **Components:** 1. **StableCode AI Engine (stablecode-completion-alpha-3b-4k):** The heart of the application, this AI engine is responsible for processing and understanding user queries. It has been fine-tuned to cater specifically to coding-related questions, ensuring accurate and relevant responses. 2. **Flask Backend:** The backend of the application is built using Flask, a versatile and lightweight web framework. It handles incoming user requests, communicates with the StableCode AI Engine, and returns the generated responses to the frontend. 3. **Streamlit Frontend:** The frontend of the application is developed using Streamlit, a popular Python library for building interactive web applications. Streamlit's user-friendly interface makes it easy for users to input their queries and receive prompt answers from the chatbot.

Xenon

Using StableCode-Completion model, we have built a LaTeX Copilot that can help scientists and engineers around the world write their LaTeX documents (papers, articles, documentation) more easily, faster, and with more enjoyment. We plan on replicating the success GitHub Copilot had with programmers community. After extensive research, we know what we want to make and how. The technology is tested, the plan is laid down, resources are acquired and waiting. Our solution is not only a viable business product, we also care about broader impact. We believe that our product can expedite the process of scientific research on various important topics changing the world for the better. If you want to help us in changing the world, then please contact us!

tex-savvy

"Empowering Your Coding Journey: CodeHelp" CodeHelp is your dedicated platform for advancing your coding skills. Whether you're a beginner embarking on your coding adventure or an experienced programmer seeking to enhance your capabilities, our platform is tailored to assist you in achieving your coding goals. By integrating cutting-edge AI technology, CodeHelp offers a dynamic and supportive environment for your coding journey. **Tailored to Your Needs** In the rapidly evolving digital landscape, coding has become an indispensable skill. CodeHelp recognizes that coding can be both thrilling and challenging, and we are committed to providing the resources and tools necessary to cater to a diverse range of coding enthusiasts. **AI-Powered Assistance** CodeHelp's core strength lies in its utilization of advanced AI technology. Imagine you're working on a coding project, such as creating a calculator application. You've successfully initiated your code, but as you dive deeper into its complexities, you may encounter obstacles or uncertainties. This is where CodeHelp comes into play. **Seamless Guidance** As you code, CodeHelp actively monitors your progress. When it senses that you might require assistance, it offers a "need help" option. This isn't just any form of assistance; it's AI-driven guidance tailored to your specific needs. **1. Code Suggestions:** When you need assistance with the next lines of code, CodeHelp can suggest code snippets or provide partial code blocks relevant to your ongoing project. Whether you're dealing with intricate algorithms or simple functions, our AI is prepared to lend a helping hand. Regardless of where you stand in your coding voyage, CodeHelp is your trusted companion. It assists you in navigating the dynamic and ever-evolving realm of programming. Join us today and embark on an unparalleled coding adventure. Your coding success story begins here.

BisraAI

AutoStableCode is a VSCode Extension that magically produces code in just about any language well. Coding can be frustrating and time-consuming, with errors adding hours of debugging to a project. Errors in code can result in security risks, broken software, and dissatisfied clients. AutoStableCode produces error-free, usable code for easy and efficient coding without the frustration and risk. Over 19 million developers globally, with the market size expected to grow at a CAGR of 8.9% by 2027. StableCode AI offers a subscription-based service with tiered pricing for individual and enterprise use. Watch StableCode AI in action and see for yourself how it produces fixed, immediately-useable code with zero errors.

Team Tonic

For high school students and those outside of computer science, understanding the syntax being machine leaning can be a steep learning curve. This project aims to help bridge that gap by providing a learning platform, giving everyone access to the world of AI. Design your own AI using our interface and obtain a code with explanation on how to bring your custom AI to life ! We use your design options to build a promo that can be fed into stablecode from Stability AI. The code will generated by stable code will also contain comments, which serve as an explanation, hence allowing you to learn the syntax of implementing your own AI.

ACCESS AI

Research Codey is a one place app where you can get insights of modern researcher papers and Code generation facility. You can upload research papers and can get insights about it by asking question answers. It can be helpful for software engineers as well, they can utilize this facility and get insights of SRS documents. This can help them code as well and to get summary of it. Another interesting feature is Code generation. Our researchers and software engineers can generate code with a help of simple prompts. Our Future functionality is to extract the relevant information and then give the best prompt the the API to get the desired functions.

ICode Guru

The Human Emulation System (Coding Edition), developed during the StableCode Hackathon, represents a cutting-edge convergence of artificial intelligence, software engineering, and cognitive science. This system is rooted in the dual-hemisphere approach, seeking to emulate the human brain's ability to process both logical reasoning and creative expression. Dual-Hemisphere Approach: The core philosophy of the HES is the integration of two distinct cognitive paradigms - the "left hemisphere" focusing on analytic logic and best coding practices, and the "right hemisphere" embracing creative, symbolic, and expressive code structures. By synthesizing these dual aspects, the system achieves a harmonious balance that resonates with diverse cognitive faculties. Technology and Models: Utilizing StabilityAI's StableCode Instruct Alpha model and the Hugging Face Transformers library, the system leverages transformer-based models fine-tuned for code generation. Deployed on CUDA-enabled devices, it ensures optimal performance and real-time responsiveness. Interactive Interface: An interactive interface, built using Gradio, allows users to engage with the system, inputting prompts and viewing generated code. The interface is designed to reflect the dual-hemisphere approach, providing separate sections for logical and creative code generation. Multi-Perspective Code Patterns: The system's goal is to create code patterns that blend logical precision and creative nuance. This involves interpreting user prompts, generating code through StableCode, and then formatting and integrating the output to match the intended style and function. The process is iteratively refined, ensuring that the generated code not only functions optimally but also aligns with human-like thinking and expression. The Human Emulation System stands as a testament to what can be achieved when human intuition and machine intelligence are melded into a unified, coherent system.

MIND INTERFACES

The usual flow while debugging and trying to code is to google the stuff online understand the answers over StackOverflow and then try to apply it on your code. But that's no longer the case. If you want to debug the code want to write a function that has the logic defined Ask Stablecode is there for you. You can just ask AskStablecode and it'll generate required code free for you. Ask stable code is powered by stable code instruct alpha 3b parameter models specifically trained on code generation tasks and it's gonna help you write the code in various programming lanague which you'd like to work on.

Code Helper

This app lets the user automatically scrape websites by letting Stablecode generate JavaScript code to parse a part of the HTML and convert it to a CSV. Here is how our app works: The user enters a URL and the app returns the page's HTML. The user can then tell the AI where the data is located, and Stablecode will then write javascript file to parse the HTML and convert the relevant part into a csv. We are taking inputs from the user, that input will be HTML link that user wants to scrape and parse, we have the option given to user to select an element and write a prompt accordingly to scrap and parse that element from the given HTML link. Stablecode will generate JavaScript code to parse part of HTML and convert it into CSV format. This will help users to scrape websites and get JavaScript code for the selected element as well as the Downloadable CSV format code for the selected element.

Visioneers

Welcome to the "StableCode Instruct API," where coding and AI unite. Our mission is clear: empower developers with StableCode Instruct Alpha 3b's brilliance. Seamlessly integrating its power opens the door to advanced coding suggestions for all projects, big or small. Our vision stretches further. Imagine our API embracing hackathon projects and beyond. Envision a VSCode extension that turns Flask/ngrok into an API key, an open-source alternative to Copilot. Ambitious? Yes, and we're poised to realize it. Meta's Codellama collaboration? It's a glimpse into a future of intuitive, innovative, and accessible coding. Join us in reshaping the coding landscape. The "StableCode Instruct API" isn't just code; it's about rewriting accessibility's rules, forging an AI-infused future. Embrace innovation, one API call at a time.

Coffee2code

Building an interactive coding tutor that leverages the StableCode model can be an exciting and educational project. Here's a detailed breakdown of how you could approach this idea: Key Features: User Authentication and Profiles: Allow users to create accounts and log in. Each user should have a personalized profile where their progress, completed exercises, and achievements are tracked. Exercise Library: Create a library of programming exercises covering various difficulty levels and programming concepts. Each exercise should come with a description, a code editor, and an expected output or behavior. Real-time Code Analysis: Integrate a code editor with real-time syntax highlighting and analysis. As users type code, the system should use the StableCode model to analyze the code for errors, suggest improvements, and provide explanations for various coding decisions. Feedback and Suggestions: Based on the analysis, provide immediate feedback and suggestions to users. If the user makes a syntax error, the system should highlight the error and provide guidance on how to correct it. If the user's code could be optimized, the system should suggest more efficient alternatives. Explanation Generation: Use the StableCode model to generate explanations for coding concepts. When a user encounters a new concept, the tutor can provide an explanation that breaks down the concept and provides examples. This could include explanations of data types, control structures, functions, and more. Progress Tracking and Gamification: Track users' progress as they complete exercises. Community Interaction: Allow users to share their code and solutions with the community. They can ask questions, receive feedback from peers, and collaborate on solving challenges. Learning Paths: Offer predefined learning paths that guide users through a series of exercises, gradually increasing in complexity. Learning paths can be tailored to different programming languages and concepts.

Tutor with StableCode

Polisplexity is a groundbreaking platform focused on redefining how we understand and manage cities using open generative AI, code simulations, Virtual Reality (VR), and mathematical models. The platform excels at capturing the complexity of modern cities, which includes not only urban infrastructure but also social networks, culture, and human behavior. Our core technology leverages open generative AI to create smart agents that mimic real-world behaviors. These agents populate our code simulations, offering dynamic, insightful models of city environments. Mathematical models add structural integrity to these simulations, increasing their accuracy and predictive power. VR enhances the user experience by offering an immersive journey through these data-driven city models. Financially, Polisplexity is well-positioned in the market. We estimate a Total Addressable Market (TAM) of $4 billion and a near-term Serviceable Obtainable Market (SOM) of $16 million. Our business model includes a multi-tier subscription service catering to different stakeholders, such as planners, policymakers, and researchers, along with customized consultancy services. The societal implications of Polisplexity are significant. As cities continue to grow, so does the stress on infrastructure, social systems, and resources. Polisplexity helps mitigate these challenges by enabling accurate, data-driven policy and planning. This contributes to more sustainable resource allocation and improved quality of life. The platform also fosters social inclusion, effective governance, and cultural integration. In essence, Polisplexity aims not just to optimize cities but to make them better, more humane places to live.

Hadox Human Networks

In today's digital age, online toxicity and harmful content are pressing issues that erode the quality of online interactions. AI Guardian, a revolutionary application leveraging StableCode's real-time content analysis capabilities, is designed to transform the online experience. It acts as a vigilant guardian, constantly scanning digital content for toxic language, hate speech, cyberbullying, and other harmful elements. AI Guardian goes beyond mere detection; it identifies ethical concerns in digital discourse. By analyzing text, comments, and posts in real-time, it offers users valuable ethical insights, helping them become more aware of the ethical implications of their online interactions. What sets AI Guardian apart is its commitment to empowering users. With customizable filters, users can tailor their ethical preferences, deciding what kind of content aligns with their values. Content warnings act as signposts, alerting users to potentially harmful material and providing them with the choice to proceed or avoid such content, thus granting them control over their online experience. But AI Guardian doesn't stop at detection and warning; it's also an educational resource. It offers a wealth of information and tips on responsible online behavior, enabling users to navigate the digital world ethically and safely. It aims to foster not only a safer online environment but also a more responsible and respectful digital culture. In a world where digital wellbeing is increasingly important, AI Guardian steps in as an indispensable tool. It prioritizes user data privacy, ensuring that content analysis is conducted while respecting privacy rights and regulations. It empowers users to make informed and ethical choices, promoting digital wellbeing in an age where it is needed more than ever.

EthicalCode Innovators

One of the challenges of learning to code is understanding the relationship between natural language and code.This can be difficult, especially for beginners.Another challenge of coding is debugging code.When a program doesn't work as expected, it can be difficult to figure out what is wrong.Our code instruction generator uses Stable Code to generate step-by-step instructions for completing a coding task from natural language descriptions.Stable Code is a large language model (LLM) that has been trained on a massive dataset of code. This allows Stable Code to generate instructions that are both correct and readable.Our code instruction generator also provides the source document from which the instructions were generated. This can be helpful for debugging code or understanding the reasoning behind the instructions.Our code instruction generator can be used for a variety of tasks, including: Learning to code Debugging code Generating new code Automating repetitive tasks Creating new features for a software application

PopeyeX

We utilize a multi-agent setting to create a language-to-database interface. Think Code Interpreter but with multiple models that can be hosted locally or on-premise and your data never leaves your laptop. LLMs enable no-code future. Any person or business with data will be able to interact with it without any coding or hiring an engineer. We believe that the multi-agent paradigm will enable that. In our demo first layer of the system is a non-coding LLM that interacts with the user via chat, when code needs to be written, it passes the task down to StableCode, which is then executed. If there are bugs, agents iteratively fix them until the code is working. In the future agents will be able to code systems of arbitrary complexity.

renqon

As earlier mentioned we added the automatic-speech-recognition model by zuu. This significant addition stems from the pipelines integrated within the transformers library. The integration of this audio speech recognition model is poised to yield remarkable improvements in the accessibility and usability of the stablecode module. Furthermore, our commitment to ensuring a comprehensive accessibility experience prompted us to integrate the text-to-speech (TTS) by suno/bark framework. This TTS model introduces an auditory dimension to the module, generating natural and coherent speech outputs based on the textual information present. This feature not only enriches the overall user experience but also serves as an additional layer of accessibility.

Creatting Unstability