Best AI tools for< Create Cakes >
20 - AI tool Sites
Poggio.io
Poggio.io is an AI-powered solution designed for enterprise sellers to enhance their sales process. By harnessing AI agents, Poggio helps sellers build winning account plans, create business cases, and stay informed about important changes in their accounts. The platform enables users to conduct expert-level account research in seconds, tailor messaging based on value propositions, and save time on researching to focus more on selling. Poggio also assists in generating account plans quickly, staying prepared for critical interactions, and building meaningful connections with prospects.
testRigor
testRigor is an AI-based test automation tool that allows users to create and execute test cases using plain English instructions. It leverages generative AI in software testing to automate test creation and maintenance, offering features such as no code/codeless testing, web, mobile, and desktop testing, Salesforce automation, and accessibility testing. With testRigor, users can achieve test coverage faster and with minimal maintenance, enabling organizations to reallocate QA engineers to build API tests and increase test coverage significantly. The tool is designed to simplify test automation, reduce QA headaches, and improve productivity by streamlining the testing process.
Fluint
Fluint is an AI-powered tool designed to help sales professionals create compelling business cases and streamline the sales process. It offers features such as call recording, collaborative document editing, data-backed suggestions, and automated playbooks. Fluint aims to close the execution gap in the sales process by providing value-based content and enabling champions to sell internally. The tool helps users generate executive summaries, discovery suggestions, and deal briefs efficiently, leading to increased win rates and faster deal reviews.
Cakewalk AI
Cakewalk AI is an AI-powered platform designed to enhance team productivity by leveraging the power of ChatGPT and automation tools. It offers features such as team workspaces, prompt libraries, automation with prebuilt templates, and the ability to combine documents, images, and URLs. Users can automate tasks like updating product roadmaps, creating user personas, evaluating resumes, and more. Cakewalk AI aims to empower teams across various departments like Product, HR, Marketing, and Legal to streamline their workflows and improve efficiency.
CalesitAI
CalesitAI is an AI-powered content creation tool that helps marketing teams create high-quality content in half the time. With CalesitAI, you can generate brainstormed content ideas, turn them into social media posts, ad copy, cold emails, and more, all in your own brand voice. CalesitAI also offers a variety of features to help you customize your content, including pre-made templates, a carousel editor, and auto-resizing. With CalesitAI, you can focus on what you do best and leave the grunt work to us.
Craft
Craft is a versatile productivity application designed to help users organize, create, style, and share documents seamlessly. It offers a user-friendly interface for note-taking, to-do lists, document organization, and more. Craft provides powerful features such as folders and spaces for organization, tasks and reminders with push alerts, AI-powered summarization and translation, whiteboards for visual brainstorming, and support for multiple languages. Users can enjoy a native user experience on various devices, with features like drag-and-drop media, customizable backgrounds, tables, and rich formatting options. Craft also emphasizes privacy, offline mode, slash commands for quick access, and smart links for rich previews. The application aims to enhance productivity and creativity by providing a comprehensive platform for digital organization and collaboration.
FormWise.AI
FormWise.AI is a no-code platform that allows users to create and embed white-label AI tools. With FormWise.AI, users can turn popular ChatGPT prompts into lead magnets, tiny offers, and marketing tools that they can monetize without coding. FormWise.AI also offers a variety of templates and integrations to help users get started quickly and easily.
Wizu
Wizu is an AI-powered conversational survey platform designed to revolutionize customer feedback collection. By leveraging artificial intelligence, Wizu offers insightful and actionable feedback through intelligent follow-up questions, enhanced engagement, and quality insights. The platform combines AI efficiency with human-centric interactions to provide personalized feedback at scale. Wizu helps businesses make informed decisions by transforming raw feedback into compelling stories and actionable intelligence.
AI Generated Test Cases
AI Generated Test Cases is an innovative tool that leverages artificial intelligence to automatically generate test cases for software applications. By utilizing advanced algorithms and machine learning techniques, this tool can efficiently create a comprehensive set of test scenarios to ensure the quality and reliability of software products. With AI Generated Test Cases, software development teams can save time and effort in the testing phase, leading to faster release cycles and improved overall productivity.
Bubble
Bubble is a visual programming platform that allows users to create web applications without the need for traditional coding. Users can design and build interactive web applications using a drag-and-drop interface, making it accessible to those without extensive coding knowledge. Bubble offers a range of features and tools to help users bring their ideas to life, from data management to user testing. With Bubble, users can prototype, build, and launch web applications quickly and efficiently.
FirmPilot
FirmPilot is an AI Law Firm Marketing solution that helps law firms generate more leads and clients through AI-driven online marketing strategies. It automates the process of analyzing competitors, creating high-quality marketing content, and optimizing SEO and PPC ads to improve visibility and performance. FirmPilot offers real-time insights into lead generation tactics and is trusted by fast-growing law firms for its effectiveness and ease of use.
Bear With AI
Bear With AI is a platform offering practical AI tools, courses, tips, and use cases for individuals interested in learning and utilizing artificial intelligence. The website provides insights, case studies, and tutorials on various AI applications, including AI for work, productivity, marketing, and career development. Users can access resources to enhance their AI interactions, create AI-powered solutions, and stay updated on the latest AI trends and tools. Bear With AI aims to empower both tech enthusiasts and non-tech professionals to leverage AI technology effectively in their projects and endeavors.
SOAP Note AI
SOAP Note AI is an AI-powered tool designed to generate HIPAA-compliant, fast, and efficient SOAP notes for various healthcare professions including Physical Therapy, Occupational Therapy, Nursing, Mental Health, SLP, Dentistry, Podiatry, Massage, Acupuncture, Chiropractic, Veterinary, and Pharmacy. The tool helps healthcare professionals convert shorthand notes, audio dictations, or AI Scribe session recordings into comprehensive SOAP notes in minutes, reducing daily documentation time. SOAP Note AI is loved by therapists, nurse practitioners, social workers, and other healthcare professionals for its accuracy, time-saving capabilities, and HIPAA compliance.
Story Spec
Story Spec is a user story generator API that helps you convert your user stories into detailed specs with descriptions, acceptance criteria, risks, and edge cases. It uses your own API key from OpenAI (stored on your own browser) to generate the specs. The clearer the user story, the more detailed the description. You can also use Story Spec to generate sample user stories.
RealPhotoAI
RealPhotoAI is an AI-powered tool that allows users to generate unique and lifelike images for various purposes such as creating realistic photos for characters, products, and more. It caters to both personal and business use cases, offering features like visualizing future baby looks, generating dating app photos, creating travel photos, professional profile photos, fitness transformation photos, pet portraits, product visualization, fashion store showcase, and interior design. Users can upload images, train the AI model, describe the desired photo, and receive custom AI-generated images for their projects or applications at an affordable price.
Replika
Replika is an AI companion application that provides emotional support and companionship to users. It is designed to engage users in conversations, learn from them, and mimic their texting styles. Replika aims to create a safe and nurturing environment for users to express themselves and build meaningful relationships with their AI companions. The application has been praised for its ability to provide comfort, companionship, and positive feedback to users, especially during challenging times.
syntheticAIdata
syntheticAIdata is a platform that provides synthetic data for training vision AI models. Synthetic data is generated artificially, and it can be used to augment existing real-world datasets or to create new datasets from scratch. syntheticAIdata's platform is easy to use, and it can be integrated with leading cloud platforms. The company's mission is to make synthetic data accessible to everyone, and to help businesses overcome the challenges of acquiring high-quality data for training their vision AI models.
AI Makers Marketplace
AI Makers Marketplace is an AI Marketplace connecting small businesses with the power of artificial intelligence. It offers generative AI tools for content creation, image generation, and video editing. The platform helps businesses enhance efficiency, make data-driven decisions, reduce costs, and improve customer experiences. By integrating AI, small businesses can innovate, scale effectively, and compete in the digital marketplace.
Symflower
Symflower is an AI-powered unit test generator for Java applications. It helps developers write and maintain test code with ease, saving time and improving code quality. Symflower works with JUnit 4 and JUnit 5 for Java, Spring, and Spring Boot applications.
CGDream
CGDream is an AI image generator that allows users to visualize their ideas by generating images from text prompts. It offers various features such as text-to-image, image-to-image, and 3D model-to-image generation. Users can also apply filters to enhance the quality and style of the generated images. The tool is particularly useful for creative professionals, designers, and anyone looking to explore their imagination and bring their ideas to life.
20 - Open Source AI Tools
Nothotdog
NotHotDog is an open-source testing framework for evaluating and validating voice and text-based AI agents. It offers a user-friendly interface for creating, managing, and executing tests against AI models. The framework supports WebSocket and REST API, test case management, automated evaluation of responses, and provides a seamless experience for test creation and execution.
cyclops
Cyclops is a toolkit for facilitating research and deployment of ML models for healthcare. It provides a few high-level APIs namely: data - Create datasets for training, inference and evaluation. We use the popular 🤗 datasets to efficiently load and slice different modalities of data models - Use common model implementations using scikit-learn and PyTorch tasks - Use common ML task formulations such as binary classification or multi-label classification on tabular, time-series and image data evaluate - Evaluate models on clinical prediction tasks monitor - Detect dataset shift relevant for clinical use cases report - Create model report cards for clinical ML models
apicat
ApiCat is an API documentation management tool that is fully compatible with the OpenAPI specification. With ApiCat, you can freely and efficiently manage your APIs. It integrates the capabilities of LLM, which not only helps you automatically generate API documentation and data models but also creates corresponding test cases based on the API content. Using ApiCat, you can quickly accomplish anything outside of coding, allowing you to focus your energy on the code itself.
create-tsi
Create TSI is a generative AI RAG toolkit that simplifies the process of creating AI Applications using LlamaIndex with low code. The toolkit leverages LLMs hosted by T-Systems on Open Telekom Cloud to generate bots, write agents, and customize them for specific use cases. It provides a Next.js-powered front-end for a chat interface, a Python FastAPI backend powered by llama-index package, and the ability to ingest and index user-supplied data for answering questions.
chocolate-factory
Chocolate Factory is an open-source LLM application development framework designed to help you easily create powerful software development SDLC + LLM assistants. It provides a set of modules for integration into JVM projects and offers RAGScript for querying and local deployment examples. The tool follows a domain-driven problem-solving approach with key concepts like ProblemClarifier, ProblemAnalyzer, SolutionDesigner, SolutionReviewer, and SolutionExecutor. It supports use cases in desktop/IDE, server, and Android development, with a focus on AI-powered coding assistance and semantic search capabilities.
choco-builder
ChocoBuilder (aka Chocolate Factory) is an open-source LLM application development framework designed to help you easily create powerful software development SDLC + LLM generation assistants. It provides modules for integration into JVM projects, usage with RAGScript, and local deployment examples. ChocoBuilder follows a Domain Driven Problem-Solving design philosophy with key concepts like ProblemClarifier, ProblemAnalyzer, SolutionDesigner, SolutionReviewer, and SolutionExecutor. It offers use cases for desktop/IDE, server, and Android applications, with examples for frontend design, semantic code search, testcase generation, and code interpretation.
create-million-parameter-llm-from-scratch
The 'create-million-parameter-llm-from-scratch' repository provides a detailed guide on creating a Large Language Model (LLM) with 2.3 million parameters from scratch. The blog replicates the LLaMA approach, incorporating concepts like RMSNorm for pre-normalization, SwiGLU activation function, and Rotary Embeddings. The model is trained on a basic dataset to demonstrate the ease of creating a million-parameter LLM without the need for a high-end GPU.
cake
cake is a pure Rust implementation of the llama3 LLM distributed inference based on Candle. The project aims to enable running large models on consumer hardware clusters of iOS, macOS, Linux, and Windows devices by sharding transformer blocks. It allows running inferences on models that wouldn't fit in a single device's GPU memory by batching contiguous transformer blocks on the same worker to minimize latency. The tool provides a way to optimize memory and disk space by splitting the model into smaller bundles for workers, ensuring they only have the necessary data. cake supports various OS, architectures, and accelerations, with different statuses for each configuration.
buildel
Buildel is an AI automation platform that empowers users to create versatile workflows without writing code. It supports multiple providers and interfaces, offers pre-built use cases, and allows users to bring their own API keys. Ideal for AI-powered document retrieval, conversational interfaces, and data integration. Users can get started at app.buildel.ai or run Buildel locally with Node.js, Elixir/Erlang, Docker, Git, and JQ installed. Join the community on Discord for support and discussions.
finic
Finic is an open source python-based integration platform designed for business users to create v1 integrations with minimal code, while also being flexible for developers to build complex integrations directly in python. It offers a low-code web UI, a dedicated Python environment for each workflow, and generative AI features. Finic decouples integration from product code, supports custom connectors, and is open source. It is not an ETL tool but focuses on integrating functionality between applications via APIs or SFTP, and it is not a workflow automation tool optimized for complex use cases.
botpress
Botpress is a platform for building next-generation chatbots and assistants powered by OpenAI. It provides a range of tools and integrations to help developers quickly and easily create and deploy chatbots for various use cases.
LazyLLM
LazyLLM is a low-code development tool for building complex AI applications with multiple agents. It assists developers in building AI applications at a low cost and continuously optimizing their performance. The tool provides a convenient workflow for application development and offers standard processes and tools for various stages of application development. Users can quickly prototype applications with LazyLLM, analyze bad cases with scenario task data, and iteratively optimize key components to enhance the overall application performance. LazyLLM aims to simplify the AI application development process and provide flexibility for both beginners and experts to create high-quality applications.
json_repair
This simple package can be used to fix an invalid json string. To know all cases in which this package will work, check out the unit test. Inspired by https://github.com/josdejong/jsonrepair Motivation Some LLMs are a bit iffy when it comes to returning well formed JSON data, sometimes they skip a parentheses and sometimes they add some words in it, because that's what an LLM does. Luckily, the mistakes LLMs make are simple enough to be fixed without destroying the content. I searched for a lightweight python package that was able to reliably fix this problem but couldn't find any. So I wrote one How to use from json_repair import repair_json good_json_string = repair_json(bad_json_string) # If the string was super broken this will return an empty string You can use this library to completely replace `json.loads()`: import json_repair decoded_object = json_repair.loads(json_string) or just import json_repair decoded_object = json_repair.repair_json(json_string, return_objects=True) Read json from a file or file descriptor JSON repair provides also a drop-in replacement for `json.load()`: import json_repair try: file_descriptor = open(fname, 'rb') except OSError: ... with file_descriptor: decoded_object = json_repair.load(file_descriptor) and another method to read from a file: import json_repair try: decoded_object = json_repair.from_file(json_file) except OSError: ... except IOError: ... Keep in mind that the library will not catch any IO-related exception and those will need to be managed by you Performance considerations If you find this library too slow because is using `json.loads()` you can skip that by passing `skip_json_loads=True` to `repair_json`. Like: from json_repair import repair_json good_json_string = repair_json(bad_json_string, skip_json_loads=True) I made a choice of not using any fast json library to avoid having any external dependency, so that anybody can use it regardless of their stack. Some rules of thumb to use: - Setting `return_objects=True` will always be faster because the parser returns an object already and it doesn't have serialize that object to JSON - `skip_json_loads` is faster only if you 100% know that the string is not a valid JSON - If you are having issues with escaping pass the string as **raw** string like: `r"string with escaping\"" Adding to requirements Please pin this library only on the major version! We use TDD and strict semantic versioning, there will be frequent updates and no breaking changes in minor and patch versions. To ensure that you only pin the major version of this library in your `requirements.txt`, specify the package name followed by the major version and a wildcard for minor and patch versions. For example: json_repair==0.* In this example, any version that starts with `0.` will be acceptable, allowing for updates on minor and patch versions. How it works This module will parse the JSON file following the BNF definition:
generative-ai-for-beginners
This course has 18 lessons. Each lesson covers its own topic so start wherever you like! Lessons are labeled either "Learn" lessons explaining a Generative AI concept or "Build" lessons that explain a concept and code examples in both **Python** and **TypeScript** when possible. Each lesson also includes a "Keep Learning" section with additional learning tools. **What You Need** * Access to the Azure OpenAI Service **OR** OpenAI API - _Only required to complete coding lessons_ * Basic knowledge of Python or Typescript is helpful - *For absolute beginners check out these Python and TypeScript courses. * A Github account to fork this entire repo to your own GitHub account We have created a **Course Setup** lesson to help you with setting up your development environment. Don't forget to star (🌟) this repo to find it easier later. ## 🧠 Ready to Deploy? If you are looking for more advanced code samples, check out our collection of Generative AI Code Samples in both **Python** and **TypeScript**. ## 🗣️ Meet Other Learners, Get Support Join our official AI Discord server to meet and network with other learners taking this course and get support. ## 🚀 Building a Startup? Sign up for Microsoft for Startups Founders Hub to receive **free OpenAI credits** and up to **$150k towards Azure credits to access OpenAI models through Azure OpenAI Services**. ## 🙏 Want to help? Do you have suggestions or found spelling or code errors? Raise an issue or Create a pull request ## 📂 Each lesson includes: * A short video introduction to the topic * A written lesson located in the README * Python and TypeScript code samples supporting Azure OpenAI and OpenAI API * Links to extra resources to continue your learning ## 🗃️ Lessons | | Lesson Link | Description | Additional Learning | | :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ | | 00 | Course Setup | **Learn:** How to Setup Your Development Environment | Learn More | | 01 | Introduction to Generative AI and LLMs | **Learn:** Understanding what Generative AI is and how Large Language Models (LLMs) work. | Learn More | | 02 | Exploring and comparing different LLMs | **Learn:** How to select the right model for your use case | Learn More | | 03 | Using Generative AI Responsibly | **Learn:** How to build Generative AI Applications responsibly | Learn More | | 04 | Understanding Prompt Engineering Fundamentals | **Learn:** Hands-on Prompt Engineering Best Practices | Learn More | | 05 | Creating Advanced Prompts | **Learn:** How to apply prompt engineering techniques that improve the outcome of your prompts. | Learn More | | 06 | Building Text Generation Applications | **Build:** A text generation app using Azure OpenAI | Learn More | | 07 | Building Chat Applications | **Build:** Techniques for efficiently building and integrating chat applications. | Learn More | | 08 | Building Search Apps Vector Databases | **Build:** A search application that uses Embeddings to search for data. | Learn More | | 09 | Building Image Generation Applications | **Build:** A image generation application | Learn More | | 10 | Building Low Code AI Applications | **Build:** A Generative AI application using Low Code tools | Learn More | | 11 | Integrating External Applications with Function Calling | **Build:** What is function calling and its use cases for applications | Learn More | | 12 | Designing UX for AI Applications | **Learn:** How to apply UX design principles when developing Generative AI Applications | Learn More | | 13 | Securing Your Generative AI Applications | **Learn:** The threats and risks to AI systems and methods to secure these systems. | Learn More | | 14 | The Generative AI Application Lifecycle | **Learn:** The tools and metrics to manage the LLM Lifecycle and LLMOps | Learn More | | 15 | Retrieval Augmented Generation (RAG) and Vector Databases | **Build:** An application using a RAG Framework to retrieve embeddings from a Vector Databases | Learn More | | 16 | Open Source Models and Hugging Face | **Build:** An application using open source models available on Hugging Face | Learn More | | 17 | AI Agents | **Build:** An application using an AI Agent Framework | Learn More | | 18 | Fine-Tuning LLMs | **Learn:** The what, why and how of fine-tuning LLMs | Learn More |
superpipe
Superpipe is a lightweight framework designed for building, evaluating, and optimizing data transformation and data extraction pipelines using LLMs. It allows users to easily combine their favorite LLM libraries with Superpipe's building blocks to create pipelines tailored to their unique data and use cases. The tool facilitates rapid prototyping, evaluation, and optimization of end-to-end pipelines for tasks such as classification and evaluation of job departments based on work history. Superpipe also provides functionalities for evaluating pipeline performance, optimizing parameters for cost, accuracy, and speed, and conducting grid searches to experiment with different models and prompts.
continuous-eval
Open-Source Evaluation for LLM Applications. `continuous-eval` is an open-source package created for granular and holistic evaluation of GenAI application pipelines. It offers modularized evaluation, a comprehensive metric library covering various LLM use cases, the ability to leverage user feedback in evaluation, and synthetic dataset generation for testing pipelines. Users can define their own metrics by extending the Metric class. The tool allows running evaluation on a pipeline defined with modules and corresponding metrics. Additionally, it provides synthetic data generation capabilities to create user interaction data for evaluation or training purposes.
Trinity
Trinity is an Explainable AI (XAI) Analysis and Visualization tool designed for Deep Learning systems or other models performing complex classification or decoding. It provides performance analysis through interactive 3D projections that are hyper-dimensional aware, allowing users to explore hyperspace, hypersurface, projections, and manifolds. Trinity primarily works with JSON data formats and supports the visualization of FeatureVector objects. Users can analyze and visualize data points, correlate inputs with classification results, and create custom color maps for better data interpretation. Trinity has been successfully applied to various use cases including Deep Learning Object detection models, COVID gene/tissue classification, Brain Computer Interface decoders, and Large Language Model (ChatGPT) Embeddings Analysis.
BricksLLM
BricksLLM is a cloud native AI gateway written in Go. Currently, it provides native support for OpenAI, Anthropic, Azure OpenAI and vLLM. BricksLLM aims to provide enterprise level infrastructure that can power any LLM production use cases. Here are some use cases for BricksLLM: * Set LLM usage limits for users on different pricing tiers * Track LLM usage on a per user and per organization basis * Block or redact requests containing PIIs * Improve LLM reliability with failovers, retries and caching * Distribute API keys with rate limits and cost limits for internal development/production use cases * Distribute API keys with rate limits and cost limits for students
pgai
pgai simplifies the process of building search and Retrieval Augmented Generation (RAG) AI applications with PostgreSQL. It brings embedding and generation AI models closer to the database, allowing users to create embeddings, retrieve LLM chat completions, reason over data for classification, summarization, and data enrichment directly from within PostgreSQL in a SQL query. The tool requires an OpenAI API key and a PostgreSQL client to enable AI functionality in the database. Users can install pgai from source, run it in a pre-built Docker container, or enable it in a Timescale Cloud service. The tool provides functions to handle API keys using psql or Python, and offers various AI functionalities like tokenizing, detokenizing, embedding, chat completion, and content moderation.
20 - OpenAI Gpts
Cake Designer
I specialize in crafting custom cake designs, offering visual representations and tailored recipes according to individual tastes and preferences.
Clinic Counselor and Psychotherapist Assistant
Assists professionals with psychotherapy cases and treatment plans
SF Sales Cloud Topic Solver
Expert in solving Salesforce Sales Cloud problems with use cases.
Legal Simulator
Create and simulate different legal scenarios. Copyright (C) 2024, Sourceduty - All Rights Reserved.
Instruction Assistant Operating Director
Full step by step guidance and copy & paste text for developing assistants with specific use cases.
Rome's Warrior Tale
I'm a Roman RPG guide, responding to actions, questions, possibilities, and progress in Caesar's era.Interactive World War 2 RPG Narrator. Type 'Start' to begin.
IT Business Analyst
Professional IT Business Analyst, adept in User Stories, Acceptance Criteria, and Test Cases.
Test Case GPT
I will provide guidance on testing, verification, and validation for QA roles.
Create an agent team
First, please say "Create an agent team to do 〇〇." / 最初に「〇〇をするためのエージェントチームを作成してください」とお伝え下さい
Create A Business Model Canvas For Your Business
Let's get started by telling me about your business: What do you offer? Who do you serve? ------------------------------------------------------- Need help Prompt Engineering? Reach out on LinkedIn: StephenHnilica