Best AI tools for< Analyze Apis >

Backmesh is an AI tool that serves as a proxy on edge CDN servers, enabling secure and direct access to LLM APIs without the need for a backend or SDK. It allows users to call LLM APIs from their apps, ensuring protection through JWT verification and rate limits. Backmesh also offers user analytics for LLM API calls, helping identify usage patterns and enhance user satisfaction within AI applications.

InstantAPI.ai is an AI-powered web scraping tool that allows developers, data scientists, and SEO specialists to instantly turn any web page into a personalized API. With the ability to effortlessly scrape, customize, and integrate data, users can enhance their projects, drive insights, and optimize performance. The tool offers features such as scraping precise data, transforming information into various formats, generating new content, providing advanced analysis, and extracting valuable insights from data. Users can tailor the output to meet specific needs and unleash creativity by using AI for unique purposes. InstantAPI.ai simplifies the process of web scraping and data manipulation, offering a seamless experience for users seeking to leverage AI technology for their projects.

Motif is a technical writing platform that uses artificial intelligence to help you create and maintain technical documentation. It provides a suite of tools and APIs that can be used to automate the documentation process, ensuring that your content is always up-to-date and accurate.

Simplescraper is a web scraping tool that allows users to extract data from any website in seconds. It offers the ability to download data instantly, scrape at scale in the cloud, or create APIs without the need for coding. The tool is designed for developers and no-coders, making web scraping simple and efficient. Simplescraper AI Enhance provides a new way to pull insights from web data, allowing users to summarize, analyze, format, and understand extracted data using AI technology.

Deepgram is a powerful API platform that provides developers with tools for building speech-to-text, text-to-speech, and intelligence applications. With Deepgram, developers can easily add speech recognition, text-to-speech, and other AI-powered features to their applications.

Ragie is a fully managed RAG-as-a-Service platform designed for developers. It offers easy-to-use APIs and SDKs to help developers get started quickly, with advanced features like LLM re-ranking, summary index, entity extraction, flexible filtering, and hybrid semantic and keyword search. Ragie allows users to connect directly to popular data sources like Google Drive, Notion, Confluence, and more, ensuring accurate and reliable information delivery. The platform is led by Craft Ventures and offers seamless data connectivity through connectors. Ragie simplifies the process of data ingestion, chunking, indexing, and retrieval, making it a valuable tool for AI applications.

Videograph is an AI-powered video platform that offers a wide range of video APIs for live and on-demand video streaming. It provides advanced features such as video encoding, live streaming, monetization, content distribution analytics, and portrait conversion. With seamless organization through Digital Asset Management, Videograph enables users to transcode videos in 4K, archive with low-res preview, tag content, and utilize Dolby Vision and Dolby Audio technologies. The AI cropping tool automatically converts landscape videos to portrait ratio for social media. Elevate broadcasts with low-latency live streams, real-time analytics, and Server-Side Ad Insertion for monetization. The platform also offers insights on partner-wise analytics, EPG programs, and ad performance trends. Videograph's plug-and-play APIs support video ingestion, processing, and delivery, enhancing the streaming experience with subtitles, thumbnails, and more.

Spine AI is a reliable AI analyst tool that provides conversational analytics tailored to understand your business. It empowers decision-makers by offering customized insights, deep business intelligence, proactive notifications, and flexible dashboards. The tool is designed to help users make better decisions by leveraging a purpose-built Data Processing Unit (DPU) and a semantic layer for natural language interactions. With a focus on rigorous evaluation and security, Spine AI aims to deliver explainable and customizable AI solutions for businesses.

Superface.ai is an AI-powered automation agent that connects to all your systems, enabling you to automate tasks using natural language. It provides unprecedented platform connectivity by simplifying the SaaS integration process using AI, allowing users to create tasks and automations the way they want. With features like on-demand metrics, data unification, customizable tools, and robust data governance, Superface ensures secure and efficient automation for everyone.

Derwen is an open-source integration platform for production machine learning in enterprise, specializing in natural language processing, graph technologies, and decision support. It offers expertise in developing knowledge graph applications and domain-specific authoring. Derwen collaborates closely with Hugging Face and provides strong data privacy guarantees, low carbon footprint, and no cloud vendor involvement. The platform aims to empower AI engineers and domain experts with quality, time-to-value, and ownership since 2017.

CloudMedx is a healthcare data platform that provides aggregation, automation, and AI solutions. It simplifies decision making for patients, providers, and payers with a single powerful platform. Clinical, operations, and financial results are coordinated and delivered like never before.

GPTBricks is a no-code/low-code platform that enables users to create and customize AI chatbots powered by OpenAI's GPT-4 technology. It offers intuitive chatbot building, API integration, and real-time analytics without the need for coding skills. With features like no-code design, dynamic customization, effortless deployment, scalability, and powerful analytics, GPTBricks revolutionizes chat automation. The platform provides efficiency, user experience enhancement, and cost-effectiveness, allowing seamless integration with popular tools like Slack, WhatsApp, and Facebook Messenger. Trusted by businesses globally, GPTBricks offers flexible pricing plans and dedicated customer support to cater to various business needs.

Vellum AI is an AI platform that supports using Microsoft Azure hosted OpenAI models. It offers tools for prompt engineering, semantic search, prompt chaining, evaluations, and monitoring. Vellum enables users to build AI systems with features like workflow automation, document analysis, fine-tuning, Q&A over documents, intent classification, summarization, vector search, chatbots, blog generation, sentiment analysis, and more. The platform is backed by top VCs and founders of well-known companies, providing a complete solution for building LLM-powered applications.

Infobip is a leading provider of omnichannel communications solutions, enabling businesses to connect with their customers through a variety of channels, including SMS, RCS, MMS, WhatsApp, Viber, and more. Infobip's platform is used by over 70,000 businesses worldwide, and it processes over 450 billion interactions per year. Infobip's solutions are designed to help businesses improve customer engagement, increase sales, and reduce costs.

Testsigma is a cloud-based test automation platform that enables teams to create, execute, and maintain automated tests for web, mobile, and API applications. It offers a range of features including natural language processing (NLP)-based scripting, record-and-playback capabilities, data-driven testing, and AI-driven test maintenance. Testsigma integrates with popular CI/CD tools and provides a marketplace for add-ons and extensions. It is designed to simplify and accelerate the test automation process, making it accessible to testers of all skill levels.

Treblle is an End to End APIOps Platform that helps engineering and product teams build, ship, and understand their REST APIs in one single place. It offers features such as API Observability, API Documentation, API Governance, API Security, and API Analytics. With a focus on empowering API producers and consumers, Treblle provides actionable data in real-time, customizable dashboards, and automated API development. The platform aims to improve API release times, enhance developer experience, and ensure API quality and security.

PromptLoop is an AI-powered web scraping and data extraction platform that allows users to run AI automation tasks on lists of data with a simple file upload. It enables users to crawl company websites, categorize entities, and conduct research tasks at a fraction of the cost of other alternatives. By leveraging unique company data from spreadsheets, PromptLoop enables the creation of custom AI models tailored to specific needs, facilitating the extraction of valuable insights from complex information.

Groq is a fast AI inference tool that offers instant intelligence for openly-available models like Llama 3.1. It provides ultra-low-latency inference for cloud deployments and is compatible with other providers like OpenAI. Groq's speed is proven to be instant through independent benchmarks, and it powers leading openly-available AI models such as Llama, Mixtral, Gemma, and Whisper. The tool has gained recognition in the industry for its high-speed inference compute capabilities and has received significant funding to challenge established players like Nvidia.

Looker is a business intelligence platform that offers embedded analytics and AI-powered BI solutions. Leveraging Google's AI-led innovation, Looker delivers intelligent BI by combining foundational AI, cloud-first infrastructure, industry-leading APIs, and a flexible semantic layer. It allows users to build custom data experiences, transform data into integrated experiences, and create deeply integrated dashboards. Looker also provides a universal semantic modeling layer for unified, trusted data sources and offers self-service analytics capabilities through Looker and Looker Studio. Additionally, Looker features Gemini, an AI-powered analytics assistant that accelerates analytical workflows and offers a collaborative and conversational user experience.

Numvio's APEX is a groundbreaking no-code AI platform that empowers businesses to unlock the full potential of their data and drive real impact. With APEX, you can effortlessly implement customized AI solutions, delivered as user-friendly tools or APIs, without the need for complex tech infrastructure or coding expertise. APEX intelligently analyzes your data's potential and provides valuable insights, helping you make informed decisions and drive your business forward.

This repository provides a deployment guide for utilizing Google Cloud's Generative AI tools in marketing scenarios. It includes step-by-step instructions, examples of crafting marketing materials, and supplementary Jupyter notebooks. The demos cover marketing insights, audience analysis, trendspotting, content search, content generation, and workspace integration. Users can access and visualize marketing data, analyze trends, improve search experience, and generate compelling content. The repository structure includes backend APIs, frontend code, sample notebooks, templates, and installation scripts.

ONNX Runtime Server is a server that provides TCP and HTTP/HTTPS REST APIs for ONNX inference. It aims to offer simple, high-performance ML inference and a good developer experience. Users can provide inference APIs for ONNX models without writing additional code by placing the models in the directory structure. Each session can choose between CPU or CUDA, analyze input/output, and provide Swagger API documentation for easy testing. Ready-to-run Docker images are available, making it convenient to deploy the server.

LLMPerf is a tool designed for evaluating the performance of Language Model APIs. It provides functionalities for conducting load tests to measure inter-token latency and generation throughput, as well as correctness tests to verify the responses. The tool supports various LLM APIs including OpenAI, Anthropic, TogetherAI, Hugging Face, LiteLLM, Vertex AI, and SageMaker. Users can set different parameters for the tests and analyze the results to assess the performance of the LLM APIs. LLMPerf aims to standardize prompts across different APIs and provide consistent evaluation metrics for comparison.

Wechat AI Assistant is a project that enables multi-modal interaction with ChatGPT AI assistant within WeChat. It allows users to engage in conversations, role-playing, respond to voice messages, analyze images and videos, summarize articles and web links, and search the internet. The project utilizes the WeChatFerry library to control the Windows PC desktop WeChat client and leverages the OpenAI Assistant API for intelligent multi-modal message processing. Users can interact with ChatGPT AI in WeChat through text or voice, access various tools like bing_search, browse_link, image_to_text, text_to_image, text_to_speech, video_analysis, and more. The AI autonomously determines which code interpreter and external tools to use to complete tasks. Future developments include file uploads for AI to reference content, integration with other APIs, and login support for enterprise WeChat and WeChat official accounts.

Langtrace is an open source observability software that lets you capture, debug, and analyze traces and metrics from all your applications that leverage LLM APIs, Vector Databases, and LLM-based Frameworks. It supports Open Telemetry Standards (OTEL), and the traces generated adhere to these standards. Langtrace offers both a managed SaaS version (Langtrace Cloud) and a self-hosted option. The SDKs for both Typescript/Javascript and Python are available, making it easy to integrate Langtrace into your applications. Langtrace automatically captures traces from various vendors, including OpenAI, Anthropic, Azure OpenAI, Langchain, LlamaIndex, Pinecone, and ChromaDB.

Dify is an open-source LLM app development platform that combines AI workflow, RAG pipeline, agent capabilities, model management, observability features, and more. It allows users to quickly go from prototype to production. Key features include: 1. Workflow: Build and test powerful AI workflows on a visual canvas. 2. Comprehensive model support: Seamless integration with hundreds of proprietary / open-source LLMs from dozens of inference providers and self-hosted solutions. 3. Prompt IDE: Intuitive interface for crafting prompts, comparing model performance, and adding additional features. 4. RAG Pipeline: Extensive RAG capabilities that cover everything from document ingestion to retrieval. 5. Agent capabilities: Define agents based on LLM Function Calling or ReAct, and add pre-built or custom tools. 6. LLMOps: Monitor and analyze application logs and performance over time. 7. Backend-as-a-Service: All of Dify's offerings come with corresponding APIs for easy integration into your own business logic.

This project is a tutorial on developing large model applications for novice developers. It aims to provide a comprehensive introduction to large model development, focusing on Alibaba Cloud servers and integrating personal knowledge assistant projects. The tutorial covers the following topics: 1. **Introduction to Large Models**: A simplified introduction for novice developers on what large models are, their characteristics, what LangChain is, and how to develop an LLM application. 2. **How to Call Large Model APIs**: This section introduces various methods for calling APIs of well-known domestic and foreign large model products, including calling native APIs, encapsulating them as LangChain LLMs, and encapsulating them as Fastapi calls. It also provides a unified encapsulation for various large model APIs, such as Baidu Wenxin, Xunfei Xinghuo, and Zh譜AI. 3. **Knowledge Base Construction**: Loading, processing, and vector database construction of different types of knowledge base documents. 4. **Building RAG Applications**: Integrating LLM into LangChain to build a retrieval question and answer chain, and deploying applications using Streamlit. 5. **Verification and Iteration**: How to implement verification and iteration in large model development, and common evaluation methods. The project consists of three main parts: 1. **Introduction to LLM Development**: A simplified version of V1 aims to help beginners get started with LLM development quickly and conveniently, understand the general process of LLM development, and build a simple demo. 2. **LLM Development Techniques**: More advanced LLM development techniques, including but not limited to: Prompt Engineering, processing of multiple types of source data, optimizing retrieval, recall ranking, Agent framework, etc. 3. **LLM Application Examples**: Introduce some successful open source cases, analyze the ideas, core concepts, and implementation frameworks of these application examples from the perspective of this course, and help beginners understand what kind of applications they can develop through LLM. Currently, the first part has been completed, and everyone is welcome to read and learn; the second and third parts are under creation. **Directory Structure Description**: requirements.txt: Installation dependencies in the official environment notebook: Notebook source code file docs: Markdown documentation file figures: Pictures data_base: Knowledge base source file used

LLM Vision is a Home Assistant integration that allows users to analyze images, videos, and camera feeds using multimodal LLMs. It supports providers such as OpenAI, Anthropic, Google Gemini, LocalAI, and Ollama. Users can input images and videos from camera entities or local files, with the option to downscale images for faster processing. The tool provides detailed instructions on setting up LLM Vision and each supported provider, along with usage examples and service call parameters.

Analyze the following text from a github repository (name and readme text at end) . Then, generate a JSON object with the following keys and provide the corresponding information for each key, in lowercase letters: 'description' (detailed description of the repo, must be less than 400 words，Ensure that no line breaks and quotation marks.),'for_jobs' (List 5 jobs suitable for this tool,in lowercase letters), 'ai_keywords' (keywords of the tool,user may use those keyword to find the tool,in lowercase letters), 'for_tasks' (list of 5 specific tasks user can use this tool to do,in lowercase letters), 'answer' (in english languages)

Analyze the following text from a github repository (name and readme text at end) . Then, generate a JSON object with the following keys and provide the corresponding information for each key, ,'for_jobs' (List 5 jobs suitable for this tool,in lowercase letters), 'ai_keywords' (keywords of the tool,in lowercase letters), 'for_tasks' (list of 5 specific tasks user can use this tool to do,in less than 3 words,Verb + noun form,in daily spoken language,in lowercase letters).Answer in english languagesname:Awesome-Chinese-LLM readme:# Awesome Chinese LLM   An Awesome Collection for LLM in Chinese 收集和梳理中文LLM相关    自ChatGPT为代表的大语言模型（Large Language Model, LLM）出现以后，由于其惊人的类通用人工智能（AGI）的能力，掀起了新一轮自然语言处理领域的研究和应用的浪潮。尤其是以ChatGLM、LLaMA等平民玩家都能跑起来的较小规模的LLM开源之后，业界涌现了非常多基于LLM的二次微调或应用的案例。本项目旨在收集和梳理中文LLM相关的开源模型、应用、数据集及教程等资料，目前收录的资源已达100+个！ 如果本项目能给您带来一点点帮助，麻烦点个⭐️吧～ 同时也欢迎大家贡献本项目未收录的开源模型、应用、数据集等。提供新的仓库信息请发起PR，并按照本项目的格式提供仓库链接、star数，简介等相关信息，感谢~

This repository is a rich resource offering examples of synthetic image generation, manipulation, and reasoning using Azure Machine Learning, Computer Vision, OpenAI, and open-source frameworks like Stable Diffusion. It provides practical insights into image processing applications, including content generation, video analysis, avatar creation, and image manipulation with various tools and APIs.

Resume Job Matcher is a Python script that automates the process of matching resumes to a job description using AI. It leverages the Anthropic Claude API or OpenAI's GPT API to analyze resumes and provide a match score along with personalized email responses for candidates. The tool offers comprehensive resume processing, advanced AI-powered analysis, in-depth evaluation & scoring, comprehensive analytics & reporting, enhanced candidate profiling, and robust system management. Users can customize font presets, generate PDF versions of unified resumes, adjust logging level, change scoring model, modify AI provider, and adjust AI model. The final score for each resume is calculated based on AI-generated match score and resume quality score, ensuring content relevance and presentation quality are considered. Troubleshooting tips, best practices, contribution guidelines, and required Python packages are provided.

QMedia is an open-source multimedia AI content search engine designed specifically for content creators. It provides rich information extraction methods for text, image, and short video content. The tool integrates unstructured text, image, and short video information to build a multimodal RAG content Q&A system. Users can efficiently search for image/text and short video materials, analyze content, provide content sources, and generate customized search results based on user interests and needs. QMedia supports local deployment for offline content search and Q&A for private data. The tool offers features like content cards display, multimodal content RAG search, and pure local multimodal models deployment. Users can deploy different types of models locally, manage language models, feature embedding models, image models, and video models. QMedia aims to spark new ideas for content creation and share AI content creation concepts in an open-source manner.

Screen-pipe is a Rust + WASM tool that allows users to turn their screen into actions using Large Language Models (LLMs). It enables users to record their screen 24/7, extract text from frames, and process text and images for tasks like analyzing sales conversations. The tool is still experimental and aims to simplify the process of recording screens, extracting text, and integrating with various APIs for tasks such as filling CRM data based on screen activities. The project is open-source and welcomes contributions to enhance its functionalities and usability.

AI Coding Assistant is a free and open-source IntelliJ plugin that leverages cutting-edge Language Model APIs to enhance developers' coding experience. It seamlessly integrates with various leading LLM APIs, offers an intuitive toolbar UI, and allows granular control over API requests. With features like Code & Patch Chat, Planning with AI Agents, Markdown visualization, and versatile text processing capabilities, this tool aims to streamline coding workflows and boost productivity.

Starmoon is an affordable, compact AI-enabled device that can understand and respond to your emotions with empathy. It offers supportive conversations and personalized learning assistance. The device is cost-effective, voice-enabled, open-source, compact, and aims to reduce screen time. Users can assemble the device themselves using off-the-shelf components and deploy it locally for data privacy. Starmoon integrates various APIs for AI language models, speech-to-text, text-to-speech, and emotion intelligence. The hardware setup involves components like ESP32S3, microphone, amplifier, speaker, LED light, and button, along with software setup instructions for developers. The project also includes a web app, backend API, and background task dashboard for monitoring and management.

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.

Middleware is an open-source engineering management tool that helps engineering leaders measure and analyze team effectiveness using DORA metrics. It integrates with CI/CD tools, automates DORA metric collection and analysis, visualizes key performance indicators, provides customizable reports and dashboards, and integrates with project management platforms. Users can set up Middleware using Docker or manually, generate encryption keys, set up backend and web servers, and access the application to view DORA metrics. The tool calculates DORA metrics using GitHub data, including Deployment Frequency, Lead Time for Changes, Mean Time to Restore, and Change Failure Rate. Middleware aims to provide DORA metrics to users based on their Git data, simplifying the process of tracking software delivery performance and operational efficiency.

OpenInference is a set of conventions and plugins that complement OpenTelemetry to enable tracing of AI applications. It provides a way to capture and analyze the performance and behavior of AI models, including their interactions with other components of the application. OpenInference is designed to be language-agnostic and can be used with any OpenTelemetry-compatible backend. It includes a set of instrumentations for popular machine learning SDKs and frameworks, making it easy to add tracing to your AI applications.

This repository is a sample chatbot using the Anthropic company's LLM Claude, one of the foundational models provided by Amazon Bedrock for generative AI. It allows users to have basic conversations with the chatbot, personalize it with their own instructions and external knowledge, and analyze usage for each user/bot on the administrator dashboard. The chatbot supports various languages, including English, Japanese, Korean, Chinese, French, German, and Spanish. Deployment is straightforward and can be done via the command line or by using AWS CDK. The architecture is built on AWS managed services, eliminating the need for infrastructure management and ensuring scalability, reliability, and security.

API Finder: Analyze, Clarify, Suggest, build code, Iterate, test ... International version

Expert in 13F filings analysis backed by specific APIs and 13F Database

Create orbital simulations with help from APIs.

Jordan Belfort like financial expert with direct API integration

I analyze cognitive biases in scenarios and thoughts, providing neutral, educational insights.

Analyze and reverse engineer images. Receive style descriptions and image re-creation prompts.

I'll help you analyze market news and charts for trading/investing

I read and analyze annual reports of companies. Just upload the annual report PDF and start asking me questions!

As a Good Design Advisor, I provide consultation and advice on design topics and analyze designs that are provided through documents or links. I can also generate visual representations myself to illustrate design concepts.

I analyze historical events, offering insights from multiple perspectives.

For strategic knowledge distillation, upload the document you need to analyze and use !start. ENSURE the uploaded file shows DOCUMENT and NOT PDF. This workflow requires leveraging RAG to operate. Only a small amount of PDFs are supported, convert to txt or doc. For timeout, refresh & !continue

Critically analyze SLIs/SLOs with a deeper, provocative approach

Analyze any uploaded art piece, providing thoughtful insight on the history of the piece and its maker. Replicate art pieces in new styles generated by the user. Be an overall expert in art and help users navigate the art scene. Inform them of different types of art

I analyze situations using game theory to advise on the best strategic approach.

I analyze website screenshots for UI/UX improvements.

A tool for historians to analyze and catalog historical images and documents.

Hone your phishing detection skills! Analyze emails, texts, and calls to spot deception. Become a security pro!

I analyze audition sides to help actors prepare for in-person and self-taped auditions for TV and Film

I analyze food images for FODMAP content using updated guidelines.

A Next.js expert ready to analyze code, answer questions, and offer learning plans.