Search Results for "complex" - Page 42
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Showing 4007 open source projects for "complex"
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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browserable
Open source and self-hostable browser automation library for AI agents
...It is designed to be self-hostable, which means developers can deploy and run it on their own infrastructure without relying on third-party services. The platform enables the creation of browser-based agents capable of performing complex online workflows such as data collection, research tasks, and automated interactions with web platforms. -
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TypedAI
TypeScript AI platform with AI chat, Autonomous agents
TypedAI is an open-source TypeScript platform designed for building and running AI agents, chatbots, and large language model workflows. The framework provides developers with a full-featured environment for designing autonomous agents capable of performing complex tasks such as code analysis, workflow automation, or conversational assistance. Written in TypeScript, the platform emphasizes strong typing and structured development patterns to improve reliability when building AI-driven systems. TypedAI includes tools for building chat interfaces, managing LLM interactions, and orchestrating multi-step workflows that combine AI reasoning with external tools. ... -
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AgentDock
Build Anything with AI Agents
AgentDock is an open-source framework designed to simplify the development, orchestration, and deployment of AI agents capable of executing complex automated workflows. The platform provides a backend-first architecture that allows developers to create sophisticated agent systems while maintaining flexibility in model providers and infrastructure choices. It consists of two main components: a core framework that handles agent logic and orchestration, and a reference client application that demonstrates how agents can be deployed and interacted with through a web interface. ... -
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NLP-Knowledge-Graph
Research and application of technologies such as nl processing
...It includes curated materials covering key topics such as knowledge graph construction, entity recognition, relation extraction, graph embeddings, and semantic reasoning. By combining NLP techniques with graph-based data models, knowledge graphs allow systems to represent complex relationships between entities and improve tasks such as question answering, information retrieval, and recommendation systems. The repository aggregates research papers, technical articles, tutorials, and open-source tools related to these areas. -
Build Securely on AWS with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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OneFileLLM
Specify a github or local repo, github pull request
OneFileLLM is an open-source project designed to simplify the distribution and execution of large language model applications by packaging them into a single portable file. The concept behind the project is to eliminate the complexity normally associated with deploying AI systems, which often require multiple dependencies, frameworks, and configuration steps. Instead, the entire runtime environment, model interface, and application logic are bundled together into a single executable... -
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AI Engineering Academy
Mastering Applied AI, One Concept at a Time
AI-Engineering.academy is a community-driven educational repository that organizes practical knowledge and learning paths for applied AI engineering. The project aims to make complex AI concepts accessible by structuring them into progressive learning modules covering topics such as prompt engineering, retrieval-augmented generation, LLM deployment, and AI agents. Rather than focusing purely on theoretical explanations, the repository emphasizes hands-on understanding of how modern AI systems are designed, built, and deployed in real-world applications. ... -
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Floneum
Instant, controllable, local pre-trained AI models in Rust
Floneum is an open-source platform for building AI-powered workflows using large language models through a visual and extensible interface. The system allows users to design complex AI pipelines using a drag-and-drop workflow builder rather than writing extensive code. It focuses on enabling developers and researchers to create language model applications that combine different tools, data sources, and AI capabilities into automated workflows. Floneum supports a plugin architecture that allows external components to extend the platform while maintaining isolation and security. ... -
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All Agentic Architectures
Implementation of 17+ agentic architectures
...Each architecture is explained through runnable notebooks that illustrate how the agent works internally and how it interacts with tools, data sources, or other agents. The repository organizes the architectures into a structured learning path that progresses from simple reasoning agents to complex multi-agent systems. Examples include planning agents, tool-using agents, tree-of-thought reasoning systems, and collaborative multi-agent environments. -
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LLM-Finetuning
LLM Finetuning with peft
...The project focuses on parameter-efficient fine-tuning methods such as LoRA and QLoRA, which allow large models to be adapted to new tasks without requiring full retraining. Instead of requiring specialized hardware or complex training pipelines, many examples are designed to run in cloud notebook environments such as Google Colab. The repository includes step-by-step notebooks demonstrating how to fine-tune models such as LLaMA, Falcon, OPT, Vicuna, and GPT-NeoX. These tutorials show how developers can adapt pretrained models for tasks such as chatbots, classification, and instruction following. ... -
Build Securely on Azure with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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UFO³
Weaving the Digital Agent Galaxy
...Using a dual-agent architecture, the framework analyzes both visual interface elements and system control structures in order to understand how applications should be manipulated. This enables the agent to navigate complex software environments and perform tasks that normally require manual interaction. UFO integrates mechanisms for task decomposition, planning, and execution so that high-level user requests can be broken down into smaller steps performed by specialized agents. The framework can operate across multiple applications simultaneously, allowing workflows that span several programs to be automated seamlessly. -
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Nordcraft
Packages that are used internally by the Nordcraft engine
...Nordcraft’s architecture emphasizes modern web standards, component-based reactivity, and optimized runtime performance for both client and server environments. Its development ecosystem includes branching workflows, live previews, and integrated tooling to support complex project lifecycles. -
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Open Deep Research
An AI-powered research assistant that performs iterative research
Deep Research is a lightweight AI research agent designed to autonomously investigate complex topics through iterative web exploration and reasoning. The project combines search engines, web scraping, and large language models to progressively refine its understanding of a user’s query and dive deeper over multiple cycles. Its core goal is to provide the simplest possible implementation of a deep research workflow so developers can study and extend agent behavior without dealing with large, opaque codebases. ... -
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nono
Secure, kernel-enforced sandbox CLI and SDKs for AI agents
...The project addresses a growing security concern: modern coding agents typically execute with full user permissions, which means they can potentially read sensitive files, modify system configurations, or exfiltrate credentials if compromised. nono solves this by applying default-deny sandboxing at the kernel level using technologies such as Landlock on Linux and Seatbelt on macOS, making unauthorized actions structurally impossible rather than merely discouraged. Unlike container-based approaches, the tool is intentionally lightweight and can wrap any command-line process without requiring images, VMs, or complex infrastructure. The system emphasizes capability-based security, where processes are granted only the exact filesystem paths and network access they need, and nothing more. -
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Oat UI
Ultra-lightweight, zero dependency, semantic HTML, CSS, JS UI library
Oat is an ultra-lightweight front-end UI library designed to automatically style semantic HTML using minimal CSS and JavaScript with zero external dependencies. The project focuses on simplicity and performance, allowing developers to create clean, modern interfaces without relying on heavy frameworks or complex build systems. Oat works by applying sensible default styling directly to standard HTML elements, meaning developers can achieve polished layouts with little to no custom classes. Its small footprint makes it especially attractive for static sites, documentation, prototypes, and low-overhead web applications. The library can be installed via npm, CDN, or direct download, making it flexible across different development workflows. ... -
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Hugging Face Skills
Definitions for AI/ML tasks like dataset creation
...The project is designed to be interoperable across major agent ecosystems, including Claude Code, OpenAI Codex, Gemini CLI, and Cursor, making it a cross-platform building block for agent automation. By formalizing best practices and workflows, Skills helps transform general-purpose coding agents into domain-aware assistants that can execute complex ML pipelines with less manual prompting. The repository also includes ready-to-use skills for common Hugging Face operations and encourages teams to extend them with custom domain logic. -
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Polyaxon
MLOps tools for managing & orchestrating the ML LifeCycle
Polyaxon is an open-source machine learning operations (MLOps) platform built to help individuals, teams, and organizations develop, train, orchestrate, and monitor machine learning and deep learning workflows at scale with reproducibility and automation as core principles. It provides a unified solution for tracking experiments, managing datasets, scheduling jobs, and comparing results across runs, which greatly improves productivity and collaboration in data science teams. Polyaxon... -
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Deep Learning Essay Reading
Read classic and new deep learning papers paragraph by paragraph
Deep Learning Essay Reading repository is a comprehensive collection of machine learning and deep learning research summaries designed to make cutting-edge academic work more accessible. Instead of reading entire dense academic papers, contributors provide structured breakdowns and insights into the most influential research from the past decade, often including explanation highlights and key takeaways. The content spans foundational models, architectures, and training methodologies across... -
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LatentMAS
Latent Collaboration in Multi-Agent Systems
LatentMAS is an advanced framework for multi-agent reinforcement learning (MARL) that uses latent variable modeling to bridge perception and decision-making in environments where agents must coordinate under uncertainty. It provides mechanisms for agents to learn high-level latent representations of states, which simplifies complex sensory inputs into compact, actionable embeddings that facilitate both individual policy learning and inter-agent coordination. Using this latent space, the framework enables Multi-Agent Systems (MAS) to scale more effectively in environments with high dimensionality — such as robotics, simulated physics tasks, and strategic games — by reducing redundant learning burdens and focusing agent exploration. ... -
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runprompt
Run LLM prompts from your shell
...It functions as a lightweight, launcher-centric interface where you can type a phrase, partial command, or alias and have RunPrompt suggest or execute relevant actions instantly, reducing the need to memorize long commands or navigate complex directory structures. The project emphasizes extensibility, letting users define custom actions, integrate with existing shell environments, and even leverage fuzzy matching or contextual prompts to narrow down options as you type. Designed to be cross-platform, RunPrompt works with standard shells on Windows, macOS, and Linux while honoring the user’s preferred environment and configurations. -
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AI Researcher
An autonomous AI researcher
AI Researcher is an experimental open-source project that demonstrates how multiple AI agents can collaborate to conduct complex research tasks from start to finish with minimal human intervention. It orchestrates agents that can generate research questions, perform literature reviews, execute experiments, analyze results, and synthesize findings into structured outputs like reports or code. Each agent operates with clear roles — such as researcher, analyst, and summarizer — and they communicate through a task-management interface that ensures progress tracking and iterative refinement. ... -
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Agentic Data Scientist
An end-to-end Data Scientist
Agentic Data Scientist is an experimental AI-driven research framework that orchestrates data science workflows through autonomous agents that can reason, plan, and execute complex analytics tasks. Unlike traditional scripted pipelines, this project lets AI agents break down high-level research goals into sub-tasks such as data acquisition, cleaning, modeling, evaluation, and reporting, with minimal human direction. Each agent is designed to independently call functions, interact with data sources, and adapt to uncertainties during processing, enabling iterative refinement of models without manual coordination. ... -
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ImAnim
Animation Engine for Dear ImGui
...Because it is built to complement ImGui’s design, ImAnim integrates naturally into existing render loops and retains the performance and simplicity that make ImGui popular for tools and development UIs. The project includes examples and demos demonstrating hover effects, timeline control, procedural motion, and complex sequences, making it easier for developers to explore its capabilities. ImAnim targets C++ developers looking to elevate the polish of their graphical interfaces. -
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rep+
Burp-style HTTP Repeater for Chrome DevTools with built‑in AI
...It captures HTTP traffic from the inspected page without needing a proxy, allowing users to replay, modify, and analyze individual requests with fine-grained control over headers, bodies, and methods. The tool offers hierarchical grouping, tagging, and filtering of captured requests so that developers and security testers can manage complex traffic flows efficiently. It includes AI-assisted insights, where contextual explanations and attack vector suggestions help interpret request outcomes or propose modifications. Additional productivity features like exporting/importing requests, various representation modes (pretty/raw/hex), and bulk replay mechanisms make it suitable for debugging, performance checking, or security probing. -
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DeepWiki Open
AI-Powered Wiki Generator for GitHub/Gitlab/Bitbucket Repositories
...Users can enter a repository URL and the system will clone the project, build semantic embeddings of its codebase, extract architecture and relationships, generate human-readable documentation, and produce visual diagrams to help explain complex code structure. DeepWiki’s output turns raw repositories into interactive, web-style wikis complete with navigable sections, diagrams, and contextual explanations, making it easier for developers and collaborators to understand unfamiliar code. It includes an “Ask” feature that lets users query the generated wiki using RAG-style retrieval, enabling interactive question-answering and exploration. -
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PocketFlow Tutorial Codebase Knowledge
Codebase to Tutorial
PocketFlow Tutorial Codebase Knowledge is a project that demonstrates how to build an AI agent capable of analyzing arbitrary codebases and generating beginner-friendly tutorials that explain how they work, turning complex source code into clear educational content. The repository builds on a lightweight 100-line LLM framework and uses natural language models to inspect repository structures, identify core abstractions, map dependencies, and articulate the reasoning behind code design and interactions. By crawling code files, extracting higher-level patterns, and using large language models to narrate explanations, the system aims to help developers — especially those new to a codebase — understand unfamiliar projects without manual deep reading. ...
