Search Results for "reasoning" - Page 2
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Showing 54 open source projects for "reasoning"
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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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KnowNote
A local-first AI knowledge base & NotebookLM alternative
...It lets users build an intelligent, searchable knowledge base from uploaded documents such as PDFs, Word files, PowerPoints, and web pages, and then interact with that content using LLM-powered chat, summarization, and reasoning tools. Unlike many NotebookLM alternatives that rely on Docker or cloud deployments, KnowNote runs natively on desktop platforms without complex setup, meaning all data stays local unless the user opts to integrate with self-managed or private LLM APIs. Its retrieval-augmented generation (RAG) system offers semantic search and traceable source references, and it supports multiple LLM providers through a flexible plugin-style provider architecture. -
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deepsec
Deepsec is a security harness for finding vulnerabilities
...For large repositories, it supports parallel work across worker machines and can resume interrupted scans without repeating completed work. It is aimed at serious security reviews where deeper model reasoning may be worth the higher compute and model cost. The project is especially relevant for teams that need to uncover long-standing vulnerabilities hidden inside complex application code. -
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Substrate
An Open-source Framework for Human Understanding, Meaning, Progress
Substrate is an open-source framework focused on human understanding, meaning, and progress. It aims to surface and structure conceptual objects—ideas, problems, beliefs, models, frames, goals, arguments, sources—to make them more transparent, discussable and actionable. The goal is to enable communities to collectively build and maintain a repository of these objects so that complex systems of meaning and progress can be mapped, analyzed and improved. It is relatively ambitious in... -
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NOFX
Open source AI trading OS for autonomous multi-model trading systems
NOFX is an open source AI-powered trading operating system designed to automate financial trading workflows using autonomous AI agents. It acts as an infrastructure layer that transforms market data into AI-driven trade decisions and execution. Instead of requiring users to manually configure machine learning models, data sources, and API integrations, the system allows AI components to perceive market conditions, select models, and perform trading actions automatically. It supports running... -
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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BuildingAI
Build your own AI application system for free
...The platform aims to bridge the gap between natural language interfaces and building design tools by allowing AI systems to interpret user instructions and convert them into structured architectural operations. By combining generative AI capabilities with building data models, the system can assist with tasks such as design generation, spatial reasoning, and building component creation. The project is intended for architects, engineers, and developers exploring how AI can automate or augment design workflows in the architecture, engineering, and construction industries. It supports interactions where users describe building features, layouts, or modifications in natural language and the AI translates those instructions into actionable design operations. -
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FastbuildAI
An open-source AI framework for developers and entrepreneurs
...The project leans into reproducibility with run records, seed control, and structured traces so you can compare behaviors across versions and inputs. Prompt and memory management are treated as first-class concerns, enabling short-lived scratchpads for reasoning as well as long-horizon state when an agent operates over multiple sessions. The codebase favors small, composable pieces—executors, routers, guards—so teams can adopt just what they need instead of buying into a monolith. It is equally comfortable running locally for development or behind a simple API for production bots and automation workflows. -
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Gemma Chat
Local AI chat + coding agent for Apple Silicon, powered by Gemma 4
...It leverages Google’s Gemma family of lightweight language models, which are built on the same underlying technology as Gemini and designed for efficient local inference and reasoning tasks. The project enables users to interact with AI through a chat interface while also supporting code generation and editing workflows. It emphasizes privacy and independence by avoiding cloud dependencies, allowing all interactions and data to remain local. The system integrates model selection and execution directly into the app, giving users control over performance and behavior. ... -
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OpenClaw Opik Observability Plugin
Official plugin for OpenClaw that exports agent traces to Opik
...This allows developers to inspect inputs, outputs, token usage, latency, and execution flow across complex multi-step agent workflows. The goal of the project is to provide transparency into the internal reasoning and operational pipeline of agent systems so developers can diagnose failures, control costs, and improve reliability. -
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Dexter
An autonomous agent for deep financial research
Dexter is an autonomous agent tailored for deep financial research: you pose complex financial questions (for example, about a company’s revenue growth or financial ratios) and Dexter breaks them down into structured research tasks, fetches relevant real-time data (e.g. income statements, cash flows), performs analysis, and returns data-backed answers. It uses a multi-agent architecture with components such as a planning agent (to decompose queries), an action agent (to run tasks & fetch... -
Cut Data Warehouse Costs by 54%BigQuery delivers 54% lower TCO with exabyte scale and flexible pricing. Free migration tools handle the SQL translation automatically.
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Phantom
An AI co-worker with its own computer
...Phantom appears to emphasize adaptability, allowing agents to respond dynamically to changing conditions or inputs. It may also incorporate mechanisms for handling external tools, APIs, or system-level operations, expanding its capabilities beyond simple reasoning tasks. The project is particularly suited for experimentation with agent autonomy and workflow abstraction. Overall, phantom represents a flexible foundation for building and testing autonomous AI systems. -
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RuoYi AI
Enterprise AI platform for building, deploying, and managing apps
...RuoYi AI includes built-in support for retrieval-augmented generation, enabling organizations to create secure, private knowledge bases with high-accuracy search and reasoning capabilities. It also offers visual workflow orchestration tools that allow users to design complex AI pipelines, automate tasks, and coordinate multi-agent systems for advanced decision-making scenarios. In addition to backend capabilities, RuoYi AI includes frontend components and administrative dashboards built with modern web technologies, making it a complete end-to-end solution. -
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Zypher Agent
A minimal yet powerful framework for creating AI agents
...It includes mechanisms like checkpointing to version agent decision states, concurrency protections, error handling, and operational interceptors to customize behavior after each reasoning step. Its API is built with TypeScript and is suitable for production contexts where agents must handle real tasks with configurability, logging, and observability. -
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Rig
Rust framework for building modular and scalable LLM-powered apps
...Its architecture emphasizes modularity, enabling developers to integrate only the components and integrations they need for a specific application. Rig includes built-in support for agent workflows, allowing systems to perform multi-turn reasoning, tool calling, and retrieval-based tasks within structured pipelines. It also supports capabilities such as text generation, embeddings, transcription, image generation, and audio generation depending on the provider used. Developers can integrate language models into their software with minimal boilerplate while maintaining flexibility for complex AI workflows. -
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DenchClaw
Fully Managed OpenClaw Framework for all knowledge work ever
...Unlike traditional cloud-based CRMs or AI tools, it runs entirely on the user’s machine and exposes a web interface locally, allowing full control over data, workflows, and automation without relying on external servers. The system combines database management, browser automation, and AI reasoning into a unified interface where users can interact with their data and tools using natural language commands. It can ingest data from sources such as Google Drive, Notion, Gmail, and CRM platforms, consolidating everything into a centralized workspace for analysis and action. One of its most distinctive capabilities is its ability to use the user’s existing browser session, enabling it to log into services, scrape data, and perform actions like outreach or research as if it were the user. -
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Grounded Docs
Open-Source Alternative to Context7, Nia, and Ref.Tools
Grounded Docs is an open-source implementation of a Model Context Protocol server designed to expose documentation and structured information as tools that AI agents can query. The project allows language models and agent frameworks to retrieve and interact with documentation through standardized MCP interfaces. By acting as an intermediary layer between documentation sources and AI tools, the server enables models to access structured documentation in a consistent and machine-readable... -
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TypedAI
TypeScript AI platform with AI chat, Autonomous agents
...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. The platform also includes specialized software engineering agents that can assist with tasks such as code reviews or repository analysis. Developers can integrate multiple model providers and tools into the platform to create flexible agent pipelines. -
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AgentDock
Build Anything with AI Agents
...Built primarily with TypeScript and modern web technologies, the framework emphasizes extensibility and predictable behavior through configurable determinism. AgentDock also supports integration with multiple large language model providers, enabling developers to combine reasoning models, APIs, and external tools within a unified automation pipeline. -
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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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Microsoft Agent Skills
Skills, MCP servers, Custom Agents, Agents.md for SDKs
...The project bundles over a hundred domain-specific skills that teach AI agents how to perform tasks like Azure resource provisioning, SDK usage patterns, infrastructure setup, and common DevOps workflows, bridging the gap between agent reasoning and real-world Microsoft platform needs. In addition to the skills themselves, the repo includes templates for agent configuration (e.g., Agents.md), marketplace setup files, and command utilities to install skills into directories like .github/skills or .claude/skills. It also offers preconfigured MCP servers and custom agent roles covering backend, frontend, infrastructure, planner, and other use cases, helping teams create richer, role-aware AI assistants. -
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Vane
Vane is an AI-powered answering engine
Vane is a privacy-focused AI-powered answering engine that combines web search, AI reasoning, and multiple language model providers into a locally controlled search experience. The platform supports both local LLMs through Ollama and cloud providers such as OpenAI, Claude, Gemini, and Groq, giving users flexibility in how queries are processed. It integrates web search through SearxNG while also supporting discussions, academic sources, image search, and video search to generate citation-backed responses. ... -
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OpenClaw-RL
Train any agents simply by 'talking'
OpenClaw-RL is an open-source reinforcement learning framework designed to train and personalize AI agents built on the OpenClaw ecosystem. The project focuses on enabling agents to improve their behavior through interactive learning rather than relying solely on static prompts or predefined skills. One of its key ideas is allowing users to train an AI agent simply by interacting with it conversationally, using natural language feedback to guide the learning process. The system incorporates... -
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SearChat
Search + Chat = SearChat(AI Chat with Search)
SearChat is an open-source conversational search platform that combines traditional web search engines with large language model reasoning to create an interactive research environment. The project is designed to transform the process of web searching into a multi-turn conversational experience where users can refine queries and explore results through dialogue. Built using a modern monorepo architecture, the system includes a Node.js and Koa backend alongside a Vue 3 and TypeScript frontend that delivers a responsive chat interface. ... -
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Mastra
The TypeScript AI agent framework
...Model routing lets you connect to dozens of providers (OpenAI, Anthropic, Gemini, and others) through a single standardized interface, while agents orchestrate LLM calls and tools to solve open-ended tasks with internal reasoning loops. When explicit control is needed, Mastra’s workflow engine uses a graph-style API (.then(), .branch(), .parallel()) to orchestrate multi-step processes. -
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Inferable
Inferable is a developer-first AI automation platform
Create your first AI automation in 60 seconds. Inferable seamlessly integrates with your existing codebase and infrastructure, allowing you to create powerful AI automation without compromising on control or security. Works with your existing codebase. Integrates with your existing services via opt-in. Enforce determinism through source code. Create and manage automation programmatically. You own the computer, in your own infrastructure. Inferable comes out of the box with delightful DX to... -
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OpenAI Realtime Agents
This is a simple demonstration of more advanced, agentic patterns
...The demo includes a Next.js frontend for browser interaction and likely a backend component to orchestrate realtime sessions and agent logic. It also supports a “Chat-Supervisor” pattern where a lightweight realtime chat agent handles user interactions and delegates more complex reasoning or tool usage to a stronger textual model (e.g. GPT-4). Because realtime agents are still a beta feature, the code and API surface are subject to changes and may evolve.