Best AI tools for< Track Api Changes >

Release AI is an AI tool designed to track and document API changes, enabling users to generate release notes efficiently. The tool automates the process of monitoring and recording modifications made to APIs, streamlining the documentation process. With Release AI, users can stay up-to-date with API changes and easily create comprehensive release notes for their projects.

DocDriven is an AI-powered documentation-driven API development tool that provides a shared workspace for optimizing the API development process. It helps in designing APIs faster and more efficiently, collaborating on API changes in real-time, exploring all APIs in one workspace, generating AI code, maintaining API documentation, and much more. DocDriven aims to streamline communication and coordination among backend developers, frontend developers, UI designers, and product managers, ensuring high-quality API design and development.

Lushair is an AI-powered platform that offers personalized hair and scalp analysis solutions. It aims to create a digital and intelligent ecosystem for dermatology, providing accurate skin and scalp solutions that are accessible and affordable. Lushair offers services such as personal subscriptions, skin & scalp analysis SAAS, and skin & scalp analysis API for hair care specialists and brands. The platform features historical tracking, multi-node analysis, improved management, AI-generated hair care plans, and an easy-to-use interface. Lushair has received positive feedback for its standardization, customization, and intelligent services in the field of dermatology.

PromptLeo is a prompt engineering platform designed to empower organizations in effectively applying Generative AI. It offers a simple interface for prompt engineers to create, test, and change prompts, integrating Generative AI into daily workflows without the need to store prompts in text files. With features like prompt templates, feedback loop & iterations, access to multiple models, and a dedicated prompt engineering library, PromptLeo aims to streamline prompt management and versioning, enhance prompt performance tracking, and facilitate collaboration among team members.

Kolank is an AI tool that provides a unified API for accessing a wide range of Language Model Models (LLMs) and providers. It offers features such as model comparison based on price, latency, output, context, and throughput, OpenAI compatible API integration, transparency in tracking API calls and token expenditure, cost reduction by paying for performance, load balancing with fallbacks, and easy integration with preferred LLMs using Python, Javascript, and Curl.

Monitr is a data visualization and analytics platform that allows users to query, visualize, and share data in one place. It helps in tracking key metrics, making data-driven decisions, and breaking down data silos to provide a unified view of data from various sources. Users can create charts and dashboards, connect to different data sources like Postgresql and MySQL, and collaborate with teammates on SQL queries. Monitr's AI features are powered by Meta AI's Llama 3 LLM, enabling the development of powerful and flexible analytics tools for maximizing data utilization.

Sedo.com is an online platform for buying and selling domain names. It provides a marketplace where users can list their domain names for sale or purchase domains that are already registered. The platform offers a secure and efficient way for domain investors, businesses, and individuals to connect and transact. Sedo.com ensures the security of transactions and provides tools to streamline the domain buying and selling process.

MacWhisper is a native macOS application that utilizes OpenAI's Whisper technology for transcribing audio files into text. It offers a user-friendly interface for recording, transcribing, and editing audio, making it suitable for various use cases such as transcribing meetings, lectures, interviews, and podcasts. The application is designed to protect user privacy by performing all transcriptions locally on the device, ensuring that no data leaves the user's machine.

FareTrack is an AI-driven data intelligence solution tailored for the modern air travel industry. It offers accurate, timely, and actionable insights for airline revenue management, distribution, and network operations teams. By leveraging advanced AI technology, FareTrack empowers clients with competitive fare tracking, ancillary pricing insights, open pricing monitoring, and price rank value optimization. The platform also provides comprehensive travel data solutions beyond airfare, including tax breakdowns, historical fare analysis, and trend analysis. With customizable dashboards and API integration, FareTrack enables users to make informed decisions swiftly and stay ahead in the dynamic world of air travel.

AddisChat is a no-code custom AI chatbot platform that allows businesses to create and integrate AI-powered chatbots directly on their websites. With full control over data and no coding required, AddisChat offers powerful features such as customization options, training data capabilities, user analytics dashboard, and integration capabilities. The platform simplifies chatbot creation and optimization to enhance customer experience and fuel business growth.

Prevess is an AI-powered API tool that provides nutrition and wellness recommendations at scale. It offers businesses in healthcare, fitness, nutrition, and wellness the ability to integrate highly personalized recommendations based on scientific research and user data. Prevess API allows for easy and fast integration into various industries, leveraging a comprehensive knowledge base and data utilization from wearables, lab tests, and user forms. The tool is scalable and customizable, catering to the specific needs of startups and enterprises to enhance user retention and revenue.

AI Spend is an AI application designed to help users monitor their AI costs and prevent surprises. It allows users to keep track of their OpenAI usage and costs, providing fast insights, a beautiful dashboard, cost insights, notifications, usage analytics, and details on models and tokens. The application ensures simple pricing with no additional costs and securely stores API keys. Users can easily remove their data if needed, emphasizing privacy and security.

Wati is a business messaging solution that allows businesses to communicate with their customers through WhatsApp. It offers a range of features such as broadcast messaging, chatbots, and integrations with other business tools. Wati is designed to help businesses improve their customer service, sales, and marketing efforts.

TrainMyAI is a comprehensive solution for creating AI chatbots using retrieval augmented generation (RAG) technology. It allows users to build custom AI chatbots on their servers, enabling interactions over WhatsApp, web, and private APIs. The platform offers deep customization options, fine-grained user management, usage history tracking, content optimization, and linked citations. With TrainMyAI, users can maintain full control over their AI models and data, either on-premise or in the cloud.

Bugasura is an AI-enabled bug management tool designed for fast-moving, modern technology teams. It offers features like issue tracking, bug reporting, performance monitoring, integrations, and API documentation. With intelligent features powered by AI, Bugasura streamlines the bug tracking and resolution process, empowering teams to handle complex challenges efficiently. The tool provides custom workflows, automatic issue assignment, easy exports, and imports, making bug management seamless and productive. Bugasura also includes bug reporters for various use cases, such as website feedback and frontend testing, with features like annotatable screenshots and in-app bug reporting widgets. Additionally, Bugasura offers performance monitoring, advanced filters, and seamless integrations with popular project management tools. The tool is cloud-based with pocket-friendly pricing options for small teams, prioritizing privacy and security with end-to-end encryption and secure authentication protocols.

Clerkie is a powerful debt repayment and optimization platform that offers a full-service automation solution powered by machine learning and human expertise. It helps lenders, both big and small, to manage and optimize their loan portfolios efficiently. With features like smart payment experience, AI-driven repayment strategies, real-time reporting, and easy integration, Clerkie ensures a seamless and secure experience for lenders and borrowers alike.

LiteLLM is an AI tool that offers a Unified API for Azure OpenAI Vertex AI Bedrock. It provides a proxy server for managing authentication, load balancing, and spend tracking across a wide range of LLMs. LiteLLM is designed to simplify the integration and management of various AI services in the OpenAI format. With features like cloud deployment, open-source availability, and extensive provider integrations, LiteLLM aims to streamline AI development workflows and enhance operational efficiency.

Coinfeeds is an AI-powered platform that provides personalized cryptocurrency insights, news, and market data to users. It offers features such as custom portfolio monitoring, AI chatbot, API access, and a database of fundraising events and emerging startups in the crypto industry. Coinfeeds aims to empower investors with the necessary information to make informed decisions in the dynamic landscape of cryptocurrency ventures.

Aim is an open-source experiment tracker that logs your training runs, enables a beautiful UI to compare them, and an API to query them programmatically. It integrates seamlessly with your favorite tools.

Coinfeeds is an AI-powered platform that provides personalized cryptocurrency insights, market data, and news to users. It offers features such as custom portfolio monitoring, AI chatbot, and API integration for real-time updates. The platform caters to cryptocurrency investors, venture capitalists, and enthusiasts by delivering actionable information to make informed decisions in the dynamic crypto landscape.

Sourcegraph is a tool that simplifies reading, writing, and fixing code in large and complex codebases. It offers features such as code search across repositories and hosts, code intelligence for navigation and references, and the ability to roll out large-scale changes and track migrations. Sourcegraph can be used on the cloud or self-hosted, with public code search available on Sourcegraph.com. The tool provides high-level architecture documentation, database setup best practices, Go and documentation style guides, tips for modifying the GraphQL API, and guidelines for contributing.

LangGraph Expense tracker is a small project that explores the possibilities of LangGraph. It allows users to send pictures of invoices, which are then structured and categorized into expenses and stored in a database. The project includes functionalities for invoice extraction, database setup, and API configuration. It consists of various modules for categorizing expenses, creating database tables, and running the API. The database schema includes tables for categories, payment methods, and expenses, each with specific columns to track transaction details. The API documentation is available for reference, and the project utilizes LangChain for processing expense data.

PyTorch Lightning is a framework for training and deploying AI models. It provides a high-level API that abstracts away the low-level details of PyTorch, making it easier to write and maintain complex models. Lightning also includes a number of features that make it easy to train and deploy models on multiple GPUs or TPUs, and to track and visualize training progress. PyTorch Lightning is used by a wide range of organizations, including Google, Facebook, and Microsoft. It is also used by researchers at top universities around the world. Here are some of the benefits of using PyTorch Lightning: * **Increased productivity:** Lightning's high-level API makes it easy to write and maintain complex models. This can save you time and effort, and allow you to focus on the research or business problem you're trying to solve. * **Improved performance:** Lightning's optimized training loops and data loading pipelines can help you train models faster and with better performance. * **Easier deployment:** Lightning makes it easy to deploy models to a variety of platforms, including the cloud, on-premises servers, and mobile devices. * **Better reproducibility:** Lightning's logging and visualization tools make it easy to track and reproduce training results.

AmbuFlow is a mobile application developed using HTML, CSS, JavaScript, and Google API to notify patients of nearby hospitals and provide estimated ambulance arrival times. It offers critical details like patient's location and enhances GPS route management with real-time traffic data for efficient navigation. The app helps users find nearby hospitals, track ambulances in real-time, and manage ambulance routes based on traffic and distance. It ensures quick emergency response, real-time tracking, enhanced communication, resource management, and a user-friendly interface for seamless navigation in high-stress situations.

lmstudio.js is a pre-release alpha client SDK for LM Studio, allowing users to use local LLMs in JS/TS/Node. It is currently undergoing rapid development with breaking changes expected. Users can follow LM Studio's announcements on Twitter and Discord. The SDK provides API usage for loading models, predicting text, setting up the local LLM server, and more. It supports features like custom loading progress tracking, model unloading, structured output prediction, and cancellation of predictions. Users can interact with LM Studio through the CLI tool 'lms' and perform tasks like text completion, conversation, and getting prediction statistics.

Skyvern automates browser-based workflows using LLMs and computer vision. It provides a simple API endpoint to fully automate manual workflows, replacing brittle or unreliable automation solutions. Traditional approaches to browser automations required writing custom scripts for websites, often relying on DOM parsing and XPath-based interactions which would break whenever the website layouts changed. Instead of only relying on code-defined XPath interactions, Skyvern adds computer vision and LLMs to the mix to parse items in the viewport in real-time, create a plan for interaction and interact with them. This approach gives us a few advantages: 1. Skyvern can operate on websites it’s never seen before, as it’s able to map visual elements to actions necessary to complete a workflow, without any customized code 2. Skyvern is resistant to website layout changes, as there are no pre-determined XPaths or other selectors our system is looking for while trying to navigate 3. Skyvern leverages LLMs to reason through interactions to ensure we can cover complex situations. Examples include: 1. If you wanted to get an auto insurance quote from Geico, the answer to a common question “Were you eligible to drive at 18?” could be inferred from the driver receiving their license at age 16 2. If you were doing competitor analysis, it’s understanding that an Arnold Palmer 22 oz can at 7/11 is almost definitely the same product as a 23 oz can at Gopuff (even though the sizes are slightly different, which could be a rounding error!) Want to see examples of Skyvern in action? Jump to #real-world-examples-of- skyvern

Cognita is an open-source framework to organize your RAG codebase along with a frontend to play around with different RAG customizations. It provides a simple way to organize your codebase so that it becomes easy to test it locally while also being able to deploy it in a production ready environment. The key issues that arise while productionizing RAG system from a Jupyter Notebook are: 1. **Chunking and Embedding Job** : The chunking and embedding code usually needs to be abstracted out and deployed as a job. Sometimes the job will need to run on a schedule or be trigerred via an event to keep the data updated. 2. **Query Service** : The code that generates the answer from the query needs to be wrapped up in a api server like FastAPI and should be deployed as a service. This service should be able to handle multiple queries at the same time and also autoscale with higher traffic. 3. **LLM / Embedding Model Deployment** : Often times, if we are using open-source models, we load the model in the Jupyter notebook. This will need to be hosted as a separate service in production and model will need to be called as an API. 4. **Vector DB deployment** : Most testing happens on vector DBs in memory or on disk. However, in production, the DBs need to be deployed in a more scalable and reliable way. Cognita makes it really easy to customize and experiment everything about a RAG system and still be able to deploy it in a good way. It also ships with a UI that makes it easier to try out different RAG configurations and see the results in real time. You can use it locally or with/without using any Truefoundry components. However, using Truefoundry components makes it easier to test different models and deploy the system in a scalable way. Cognita allows you to host multiple RAG systems using one app. ### Advantages of using Cognita are: 1. A central reusable repository of parsers, loaders, embedders and retrievers. 2. Ability for non-technical users to play with UI - Upload documents and perform QnA using modules built by the development team. 3. Fully API driven - which allows integration with other systems. > If you use Cognita with Truefoundry AI Gateway, you can get logging, metrics and feedback mechanism for your user queries. ### Features: 1. Support for multiple document retrievers that use `Similarity Search`, `Query Decompostion`, `Document Reranking`, etc 2. Support for SOTA OpenSource embeddings and reranking from `mixedbread-ai` 3. Support for using LLMs using `Ollama` 4. Support for incremental indexing that ingests entire documents in batches (reduces compute burden), keeps track of already indexed documents and prevents re-indexing of those docs.

LaVague is an open-source Large Action Model framework that uses advanced AI techniques to compile natural language instructions into browser automation code. It leverages Selenium or Playwright for browser actions. Users can interact with LaVague through an interactive Gradio interface to automate web interactions. The tool requires an OpenAI API key for default examples and offers a Playwright integration guide. Contributors can help by working on outlined tasks, submitting PRs, and engaging with the community on Discord. The project roadmap is available to track progress, but users should exercise caution when executing LLM-generated code using 'exec'.

APIPark is an open-source AI Gateway and Developer Portal that enables users to easily manage, integrate, and deploy AI and API services. It provides robust API management features, including creation, monitoring, and access control, to help developers efficiently and securely develop and manage their APIs. The platform aims to solve challenges such as connecting to powerful AI models, managing complex AI & API call relationships, overseeing API creation and security, simplifying fault detection and troubleshooting, and enhancing the visibility and valuation of data assets.

Ain is a terminal HTTP API client designed for scripting input and processing output via pipes. It allows flexible organization of APIs using files and folders, supports shell-scripts and executables for common tasks, handles url-encoding, and enables sharing the resulting curl, wget, or httpie command-line. Users can put things that change in environment variables or .env-files, and pipe the API output for further processing. Ain targets users who work with many APIs using a simple file format and uses curl, wget, or httpie to make the actual calls.

Glide is a cloud-native LLM gateway that provides a unified REST API for accessing various large language models (LLMs) from different providers. It handles LLMOps tasks such as model failover, caching, key management, and more, making it easy to integrate LLMs into applications. Glide supports popular LLM providers like OpenAI, Anthropic, Azure OpenAI, AWS Bedrock (Titan), Cohere, Google Gemini, OctoML, and Ollama. It offers high availability, performance, and observability, and provides SDKs for Python and NodeJS to simplify integration.

Sourcegraph is a tool that simplifies reading, writing, and fixing code in large and complex codebases. It offers features such as code search across repositories, code intelligence for code navigation and history tracing, and the ability to roll out large-scale changes to multiple repositories simultaneously. Sourcegraph can be used on the cloud or self-hosted, and provides public code search on Sourcegraph.com. The tool is designed to enhance code understanding and collaboration within development teams.

Tonic Validate is a framework for the evaluation of LLM outputs, such as Retrieval Augmented Generation (RAG) pipelines. Validate makes it easy to evaluate, track, and monitor your LLM and RAG applications. Validate allows you to evaluate your LLM outputs through the use of our provided metrics which measure everything from answer correctness to LLM hallucination. Additionally, Validate has an optional UI to visualize your evaluation results for easy tracking and monitoring.

Bugbug is a tool developed by Mozilla that leverages machine learning techniques to assist with bug and quality management, as well as other software engineering tasks like test selection and defect prediction. It provides various classifiers to suggest assignees, detect patches likely to be backed-out, classify bugs, assign product/components, distinguish between bugs and feature requests, detect bugs needing documentation, identify invalid issues, verify bugs needing QA, detect regressions, select relevant tests, track bugs, and more. Bugbug can be trained and tested using Python scripts, and it offers the ability to run model training tasks on Taskcluster. The project structure includes modules for data mining, bug/commit feature extraction, model implementations, NLP utilities, label handling, bug history playback, and GitHub issue retrieval.

ByteChef is an open-source, low-code, extendable API integration and workflow automation platform. It provides an intuitive UI Workflow Editor, event-driven & scheduled workflows, multiple flow controls, built-in code editor supporting Java, JavaScript, Python, and Ruby, rich component ecosystem, extendable with custom connectors, AI-ready with built-in AI components, developer-ready to expose workflows as APIs, version control friendly, self-hosted, scalable, and resilient. It allows users to build and visualize workflows, automate tasks across SaaS apps, internal APIs, and databases, and handle millions of workflows with high availability and fault tolerance.

x-crawl is a flexible Node.js AI-assisted crawler library that offers powerful AI assistance functions to make crawler work more efficient, intelligent, and convenient. It consists of a crawler API and various functions that can work normally even without relying on AI. The AI component is currently based on a large AI model provided by OpenAI, simplifying many tedious operations. The library supports crawling dynamic pages, static pages, interface data, and file data, with features like control page operations, device fingerprinting, asynchronous sync, interval crawling, failed retry handling, rotation proxy, priority queue, crawl information control, and TypeScript support.

doc2plan is a browser-based application that helps users create personalized learning plans by extracting content from documents. It features a Creator for manual or AI-assisted plan construction and a Viewer for interactive plan navigation. Users can extract chapters, key topics, generate quizzes, and track progress. The application includes AI-driven content extraction, quiz generation, progress tracking, plan import/export, assistant management, customizable settings, viewer chat with text-to-speech and speech-to-text support, and integration with various Retrieval-Augmented Generation (RAG) models. It aims to simplify the creation of comprehensive learning modules tailored to individual needs.

WilmerAI is a middleware system designed to process prompts before sending them to Large Language Models (LLMs). It categorizes prompts, routes them to appropriate workflows, and generates manageable prompts for local models. It acts as an intermediary between the user interface and LLM APIs, supporting multiple backend LLMs simultaneously. WilmerAI provides API endpoints compatible with OpenAI API, supports prompt templates, and offers flexible connections to various LLM APIs. The project is under heavy development and may contain bugs or incomplete code.

Open Interface is a self-driving software that automates computer tasks by sending user requests to a language model backend (e.g., GPT-4V) and simulating keyboard and mouse inputs to execute the steps. It course-corrects by sending current screenshots to the language models. The tool supports MacOS, Linux, and Windows, and requires setting up the OpenAI API key for access to GPT-4V. It can automate tasks like creating meal plans, setting up custom language model backends, and more. Open Interface is currently not efficient in accurate spatial reasoning, tracking itself in tabular contexts, and navigating complex GUI-rich applications. Future improvements aim to enhance the tool's capabilities with better models trained on video walkthroughs. The tool is cost-effective, with user requests priced between $0.05 - $0.20, and offers features like interrupting the app and primary display visibility in multi-monitor setups.

Synmetrix (prev. MLCraft) is an open source data engineering platform and semantic layer for centralized metrics management. It provides a complete framework for modeling, integrating, transforming, aggregating, and distributing metrics data at scale. Key features include data modeling and transformations, semantic layer for unified data model, scheduled reports and alerts, versioning, role-based access control, data exploration, caching, and collaboration on metrics modeling. Synmetrix leverages Cube (Cube.js) for flexible data models that consolidate metrics from various sources, enabling downstream distribution via a SQL API for integration into BI tools, reporting, dashboards, and data science. Use cases include data democratization, business intelligence, embedded analytics, and enhancing accuracy in data handling and queries. The tool speeds up data-driven workflows from metrics definition to consumption by combining data engineering best practices with self-service analytics capabilities.

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