Fastn simplifies the process of API integration and orchestration with its intuitive, no-code platform. Leveraging advanced AI technologies, it enables users to easily connect various data sources and automate data workflows. Its visual drag-and-drop interface allows even non-technical users to manage data integration tasks with ease, significantly reducing the time and effort needed for application development. The platform's capabilities extend across numerous applications, making it ideal for businesses looking to improve data accessibility and operational efficiency.

FireAct Agent is an open-source React framework designed for building AI-powered conversational agents. It offers a modular architecture that lets you define custom tools, manage session memory, and render chat UIs with rich message types. With TypeScript typings and server-side rendering support, FireAct Agent streamlines the process of connecting LLMs, invoking external APIs or functions, and maintaining conversational context across interactions. You can customize styling, extend core components, and deploy on any web environment.

FlowOps delivers a visual, no-code environment where users define AI agents as sequential workflows. Through its intuitive drag-and-drop builder, you can assemble modules for LLM interactions, vector store lookups, external API calls, and custom code execution. Advanced features include conditional branching, looping constructs, and error handling to build robust pipelines. It integrates with popular LLM providers (OpenAI, Anthropic), databases (Pinecone, Weaviate), and REST services. Once designed, workflows can be deployed instantly as scalable APIs with built-in monitoring, logging, and version control. Collaboration tools allow teams to share and iterate on agent designs. FlowOps is ideal for creating chatbots, automated document extractors, data analysis workflows, and end-to-end AI-driven business processes without writing a single line of infrastructure code.

FreeAct leverages a modular architecture to streamline the creation of AI agents. Developers define high-level objectives and configure the planning module to generate stepwise plans. The reasoning component evaluates plan feasibility, while the execution engine orchestrates API calls, database queries, and external tool interactions. Memory management tracks conversation context and historical data, allowing agents to make informed decisions. An environment registry simplifies the integration of custom tools and services, enabling dynamic adaptation. FreeAct supports multiple LLM backends and can be deployed on local servers or cloud environments. Its open-source nature and extensible design facilitate rapid prototyping of intelligent agents for research and production use cases.

FoxAcid AI is an advanced platform for creating personalized AI agents. Users can train the AI on their instructions, prompts, and training examples, making it highly customizable for varied needs. FoxAcid AI integrates live data fetching, allowing it to pull data from APIs or databases to give more accurate and dynamic responses. This platform is designed to enhance customer engagement, streamline workflows, and produce effective social media content. With robust security features, your data remains protected while allowing seamless synchronization across multiple devices.

Functionary provides a declarative way to register custom tools — JavaScript functions encapsulating API calls, database queries, or business logic. It wraps an LLM interaction to analyze user prompts, determine which tools to execute, and parse the tool outputs back into conversational responses. The framework supports memory, error handling, and chaining of actions, offering hooks for pre- and post-processing. Developers can quickly spin up agents capable of dynamic function orchestration without boilerplate, enhancing control over AI-driven workflows.

The Gemini Agent Cookbook is a curated open-source toolkit offering a variety of hands-on examples for constructing intelligent agents powered by Google’s Gemini language models. It includes sample code for orchestrating multi-step reasoning chains, dynamically invoking external APIs, integrating toolkits for data retrieval, and managing conversation flows. The cookbook demonstrates best practices for error handling, context management, and prompt engineering, supporting use cases like autonomous chatbots, task automation, and decision support systems. It guides developers through building custom agents that can interpret user requests, fetch real-time data, perform computations, and generate formatted outputs. By following these recipes, engineers can accelerate agent prototyping and deploy robust AI-driven applications in diverse domains.

ggfai provides a unified interface to define goals, manage multi-step reasoning, and maintain conversational context with memory modules. It supports customizable tool integrations for calling external services or APIs, asynchronous execution flows, and abstractions over OpenAI GPT models. The framework’s plugin architecture lets you swap memory backends, knowledge stores, and action templates, simplifying agent orchestration across tasks like customer support, data retrieval, or personal assistants.

Gilio is an innovative platform designed to optimize the extraction of structured information from various document types. Utilizing Generative AI, it allows users to ingest, process, and transform document data rapidly, achieving exceptional accuracy and speed. Businesses can integrate Gilio's powerful API to automate their document management processes, enhancing productivity and minimizing errors in data handling. Ideal for enterprises seeking a robust solution for document processing, Gilio stands out as a reliable choice for developers and organizations committed to digital transformation.

GPT Edit 翻译 is an innovative browser extension that harnesses OpenAI’s API to facilitate efficient translation, content summarization, and text editing. Whether you are reading foreign language articles, writing emails, or coding, this extension enhances your ability to communicate by providing accurate translations and helpful insights. With optimized prompts that make multilingual content easier to digest and edit, GPT Edit is essential for anyone engaged in global communication or content creation.

Glyph DLP is a data loss prevention API that scans and redacts sensitive information such as emails, Social Security numbers, and credit card details from Base64-encoded strings and documents. By utilizing secure REST API calls, users can easily integrate this tool into their existing workflows. Glyph DLP aims to reduce the risk of data breaches and ensure compliance with data protection regulations, which is vital for organizations handling sensitive customer information. Its functionality is particularly beneficial for businesses in finance, healthcare, and any industry that prioritizes data security.

Go-Pilot leverages advanced language models to understand your Go project context after you connect your repository. It provides real-time code completions, creates new functions or types from high-level descriptions, auto-generates tests, and performs code reviews with style and performance recommendations. Its refactoring suggestions help maintain code quality, while its explanation mode demystifies complex code blocks. Go-Pilot integrates seamlessly into your workflow, minimizing context switches and boosting productivity.

GPT Labs is a comprehensive no-code platform designed to build, train, and deploy GPT-powered AI agents. It offers features such as persistent memory, web browsing capabilities, file upload and processing, and seamless integration with external APIs. Through an intuitive drag-and-drop interface, users design conversational workflows, inject domain-specific knowledge, and test interactions in real time. Once configured, agents can be deployed via REST API or embedded in websites and applications, enabling automated customer support, virtual assistants, and data analysis tasks without writing a single line of code. The platform supports collaboration with team members, offers analytics on agent performance, and provides version control for iterative improvements. Its flexible architecture scales with enterprise needs and includes security features like role-based access and encryption.

GPA-LM is a Python-based framework designed to simplify the creation and orchestration of AI agents powered by large language models. It features a planner that breaks down high-level instructions into sub-tasks, an executor that manages tool calls and interactions, and a memory module that retains context across sessions. The plugin architecture allows developers to add custom tools, APIs, and decision logic. With multi-agent support, GPA-LM can coordinate roles, distribute tasks, and aggregate results. It integrates seamlessly with popular LLMs like OpenAI GPT and supports deployment on various environments. The framework accelerates the development of autonomous agents for research, automation, and application prototyping.

gpt-func-calling is a developer toolkit that showcases OpenAI’s function calling feature, allowing chat-based AI to interact with external services. By defining function signatures in JSON, developers guide GPT-3.5/4 to recognize when to call a function, automatically format arguments, and handle the response in a structured manner. This streamlines integration with weather APIs, database queries, or custom business logic, ensuring consistent, reliable outputs without manual parsing.

GPTZero is a cutting-edge AI detection tool that identifies AI-generated text on sentence, paragraph, and document levels. Trained on a diverse corpus of text, it provides detailed writing reports with statistics and recording capabilities. Users can integrate GPTZero's functionality into their own applications via API. With over 2.5 million users globally and partnerships with over 100 organizations, GPTZero ensures high-quality, transparent information.

HappyML is a versatile platform designed to help businesses create and deploy custom AI chatbots. Using HappyML, users can call 3rd party APIs with no-code setup, automate customer interactions, and enhance business operations. With capabilities for integrating various files, APIs, and websites, HappyML offers a seamless and efficient way to create bots tailored to specific needs.

HexaBot is designed to simplify the development and deployment of intelligent autonomous agents. It provides modular workflow pipelines that break complex tasks into manageable steps, along with persistent memory stores to retain context across sessions. Developers can connect agents to external APIs, databases, and third-party services through a plugin ecosystem. Real-time monitoring and logging ensure visibility into agent behavior, while SDKs for Python and JavaScript enable rapid integration into existing applications. HexaBot’s scalable infrastructure handles high concurrency and supports versioned deployments for reliable production use.

This course equips developers with step-by-step guides to implement various AI Agents using the Hugging Face ecosystem. It covers leveraging Transformers for language understanding, retrieval-augmented generation, integrating external API tools, chaining prompts, and fine-tuning agent behaviors. Learners build agents for document QA, conversational assistants, workflow automation, and multi-step reasoning. Through practical notebooks, users configure agent orchestration, error handling, memory strategies, and deployment patterns to create robust, scalable AI-driven assistants for customer support, data analysis, and content generation.

Our Perception Platform is a cutting-edge solution that integrates active learning and robust APIs, allowing users to automate training, deployment, and ongoing improvement of machine learning models. Designed to be user-friendly without sacrificing performance, this platform serves as a comprehensive tool for organizations to ensure that their AI solutions evolve continuously and efficiently. With its features, companies can handle large-scale data processes, adapt to new information rapidly, and enhance model accuracy while preserving privacy.