OpenAI Custom GPTs AI technology Top Builders

Explore the top contributors showcasing the highest number of OpenAI Custom GPTs AI technology app submissions within our community.

Custom GPTs: Redefining AI Customization

Custom GPTs redefine your ChatGPT experience, enabling the creation of personalized AI models tailored to specific tasks. Whether you strive to optimize your project management workflows, simplify complex legal jargon, or generate captivating marketing copy, Custom GPTs offer a versatile solution to meet your needs.

General
Release date	November 6, 2023
Author	OpenAI
Type	Customizable AI model

Custom GPTs redefine ChatGPT's capabilities, enabling tailored AI models that seamlessly integrate external data sources, catering to personal, corporate, or public requirements without coding skills.

Key Features

Tailored Solutions: Customize AI models for various needs.
Real-World Integration: Seamlessly incorporate external data sources.
Simplified Creation: Build AI models without coding knowledge.

For more details and updates, refer to the OpenAI Blog - Introducing GPTs and explore diverse Use Cases demonstrating the potential of Custom GPTs.

GPTs Tutorials

👉 Discover more Custom GPTs Tutorials on lablab.ai

Edit on Github

OpenAI Custom GPTs AI technology Hackathon projects

Discover innovative solutions crafted with OpenAI Custom GPTs AI technology, developed by our community members during our engaging hackathons.

EOS Advisor

Just input the name of your business and the "EOS Advisor," a specialized GPT, will create a tailored Entrepreneurial Operating System (EOS) plan you can tailor to meet your business needs and align towards achieving your company's vision. The specialized GPT creates a holistic business model designed to harness human energy and align it towards achieving a company's vision. This digital advisor focuses exclusively on guiding teams through the core components of the EOS framework: Vision, People, Data, Issues, Process, and Traction. Each element is crucial for cultivating a well-rounded and effective organizational structure. The tool's conversational and friendly tone demystifies complex concepts related to EOS, making them easier to understand and implement. By fostering a supportive and user-friendly environment, EOS Advisor empowers teams to confidently navigate their business operations and growth through the structured EOS approach. This digital coach essentially acts as a facilitator for enhancing alignment and clarity within businesses, driving them towards their strategic goals with precision and effective team synergy.

MARKETLYTICS-Intelligence Marketing Analytics

MARKETKYTICS is an advanced and innovative marketing analytics application designed to transform businesses' marketing efforts. With its intelligent features and cutting-edge technologies, MARKETKYTICS offers faster and data-driven solutions, empowering businesses to stay ahead in today's competitive landscape. Gain valuable insights, optimize marketing strategies, and drive exceptional results with MARKETKYTICS. MARKETKYTICS is an empowering marketing analytics application, providing businesses with the tools and insights to achieve marketing excellence. Leveraging advanced technologies, MARKETKYTICS enables data-driven decisions, impactful campaigns, and a competitive edge in the ever-evolving marketing landscape. Elevate your marketing strategies with MARKETKYTICS.

End To End Multi Code Assistant App Using LLM

The project you've described aims to search for YouTube videos related to a specific query using the YouTube Data API. Here's a longer description: Description: The project leverages the YouTube Data API to search for videos based on a user-provided query string. This is particularly useful for individuals or applications looking to find relevant video content on YouTube programmatically. How It Works: Input Query: Users provide a query string representing the topic they're interested in finding videos about. For example, the query string could be "factorial of a number". API Key Setup: The project requires a valid Google Cloud API key with access to the YouTube Data API. This key is used to authenticate requests made to the API. API Request: The search_youtube_videos function constructs a request to the YouTube Data API's search.list method. The request includes parameters such as the query string (q), the part of the resource to include in the API response (part), the type of resource (type), and the maximum number of results to return (maxResults). API Response: The request is executed, and the API returns a response containing a list of videos matching the search criteria. Processing Response: The function parses the response to extract relevant information about each video, such as its unique video ID. Generating Video Links: For each video in the response, the function constructs a YouTube video link using the video ID and appends it to a list of video links. Output: Finally, the function returns the list of video links, which can be used by the caller to display or further process the search results.

Edulance-AI

Edulance is an open-source project that utilizes advanced technologies such as Unstructured, machine learning models, and APIs to transform text documents and PDFs into interactive educational resources. The software accepts user-uploaded files, applies optical character recognition (OCR) for text documents, or extracts valuable content from PDFs. It then generates lessons, quizzes, and lesson plans based on the content using its Lesson Graph model and agents like LessonGenerator, LessonPlanner, OCRAgent, PdfAgent, QuizAgent, and TogetherLLM. Edulance provides an immersive learning experience, enabling effective teaching and interactive knowledge acquisition. Overall this project incorporates the following: TogetherAI's LLM Models Unstructured Partition pdf for making PDFs LLM Ready Agentic AI with state management. Features Feature Description ⚙️ Architecture Edulance is a Python-based project using FastAPI as the web framework and Uvicorn for runtime serving. The application leverages containers with Docker for deployment, installing required dependencies from requirements.txt. It utilizes libraries like LangChain, PikePDF, PyTesseract for OCR, and TogetherAI's LLM models. 🔩 Code Quality The codebase follows a modular structure with clearly defined agents and graph files, ensuring high cohesion and low coupling. Python style guides are followed consistently, including PEP8 and PEP534. There is adequate usage of comments throughout the codebase.🔌 Integrations Key integrations include Docker for deployment, LangChain libraries, TogetherAI's LLM models, Vectara for Chat. 🧩 Modularity 📦 Dependencies Main dependencies include FastAPI, Docker, Python 3.10, requirements.txt, LangChain package, PikePDF, PyTesseract, and related tools.

The Orcas

The ORCAS AI is an platform for connecting different organization of government bodies during calamities. Our Aim at ORCA is to create an decentralized AI systems controlled by government bodies. The user whenever in danger or runs out of ration due to natural calamities can make SOS emergency call or texts and the automated AI bot takes the call and asks query of the user. After that the automated call sends the information of response to the centralized government where the government officials can assign tasks to specific government bodies to save the user. The central government forwards the assigned tasks to the specific government bodies where the specific government can view them in dashboard. The forward of tasks is done quickly and the specific government bodies can see the user location with number and also the percentage of affected in that area so the government can get the idea about the area and its situation. The Orca AI helps in finding the area's affected percentage and also suggest the best possible way to reach the user with safety. The government can plan accordingly based on the workers there with amount of transport. We help them to organize effectively based on their resources. And inefficiently resource of item at a place will be swapped by nearby government place. The all process in stored in blockchain to make it tamper free and secure and also rescue the person as early as possible with the help of AI and blockchain.

Massar team submission

Masaar is described as a personal companion with the following capabilities: 1. Deep Understanding: It claims to surpass your self-knowledge, implying it can analyze your personality, preferences, and strengths better than you can yourself. This could involve using advanced data analysis or machine learning to process information about you from various sources (e.g., your interactions with the companion, your online activity). 2. Personalized Learning: Based on its deep understanding, Masaar would then tailor its approach to teach you new skills. It would consider your unique learning style, pace, and preferences to create an optimal learning experience. This could involve: - Identifying if you learn best by doing, watching, or reading. - Adjusting the difficulty and pace of learning materials based on your progress. - Recommending learning methods that resonate with you (e.g., gamification, interactive exercises). Think of it this way: Imagine a highly knowledgeable and adaptable tutor who can constantly assess your strengths, weaknesses, and learning style. Masaar strives to be that kind of companion, dynamically adjusting its approach to maximize your learning potential. However, it's important to consider some limitations: - Data Privacy: The level of deep understanding Masaar claims might raise concerns about data privacy and how it collects information about you. - Accuracy of Self-Knowledge: The idea of surpassing self-knowledge is debatable. While Masaar might identify patterns you haven't noticed, true self-awareness is a complex process. - Limited Scope: It's unclear how Masaar would define "new skills." Can it teach complex physical skills or require real-world practice? Overall, Masaar presents an intriguing concept for a future personalized learning companion. However, it's essential to be mindful of potential limitations and ensure it operates with transparency and user control over data.