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COGENTS

COGENTS: Towards COGnitive aGENTic System

A comprehensive, modular ecosystem for building intelligent, cognitive agent systems. COGENTS provides foundational abstractions, specialized toolkits, intelligent agents, and powerful search & automation capabilities—all designed to work together seamlessly.


🎯 Vision

COGENTS is an initiative to develop a cognitive, computation-driven agentic system that combines theoretical foundations with practical implementations. The project emphasizes:

  • Modular Architecture: Build systems with composable, reusable components
  • Cognitive Design: Agent systems grounded in multi-agent system (MAS) philosophy
  • Production-Ready: Battle-tested tools and agents for real-world applications
  • Extensible Framework: Easy integration and customization for diverse use cases

🏗️ Architecture

COGENTS is organized into five interconnected subprojects, each addressing a specific aspect of cognitive agent development:

COGENTS
├── cogents-core          # Foundational abstractions & core modules (BASE)
├── cogents-smith         # Toolkits ecosystem & production agents
├── cogents-browser-use   # AI-powered browser automation
├── wizsearch             # Multi-engine search orchestration
└── wizagent              # Web automation & research framework

📦 Subprojects

1. cogents-core 🧠 (BASE)

PyPI version Ask DeepWiki

The foundational layer providing core abstractions and essential modules for all COGENTS projects.

Core Abstractions

  • Agent: Base classes for building custom agents (BaseAgent, BaseGraphicAgent, BaseConversationAgent, BaseResearcher)
  • Goal Management: Goal decomposition, conflict detection, and dynamic replanning (Goalith)
  • Tool Management: Centralized tool registry, execution engine, and repository system (Toolify)
  • Memory Management: Persistent memory capabilities (under development)
  • Orchestration: Global orchestration system (under development)

Key Features

  • Multi-Model LLM Support: OpenAI, Google GenAI, Ollama, LlamaCPP with dynamic routing
  • Advanced Routing: Complexity-based and self-assessment routing strategies
  • Observability: Built-in token tracking and Opik tracing integration
  • Message Bus: Inter-agent communication system
  • Extensible Design: Easy to add new providers and capabilities
pip install -U cogents-core

Use Cases: Building custom agents, goal-oriented planning, tool integration, LLM management


PyPI version Ask DeepWiki

Extensive toolkit ecosystem and production-ready agents built on cogents-core.

Toolkit Ecosystem (18 Specialized Toolkits in 10 Semantic Groups)

  • Academic Research: arXiv integration for paper discovery and analysis
  • Development Tools: Bash, file editing, GitHub, Python execution
  • Media Processing: Image analysis, video processing, audio transcription
  • Information Retrieval: Wikipedia, web search, knowledge extraction
  • Data Management: Tabular data, memory systems, document handling
  • Communication: Gmail integration
  • Human Interaction: User communication and feedback collection

Production-Ready Agents

  • Askura Agent: Dynamic conversational agent for structured information collection
  • Seekra Agent: Deep research agent for comprehensive topic investigation and report generation

Architecture Features

  • Semantic Organization: Intuitive grouping for easy discovery
  • Lazy Loading: Load only what you need
  • Async-First Design: High-performance concurrent operations
  • Error Resilience: Graceful handling of missing dependencies
pip install -U cogents-smith

Use Cases: Rapid agent development, conversational data collection, deep research, multi-modal processing


PyPI version

AI-powered browser automation adapted from browser-use on the COGENTS stack.

Features

  • Natural language browser control
  • Intelligent web navigation
  • Automated interaction with web elements
  • Built on COGENTS core abstractions
  • Support for headless and headed modes
pip install -U cogents-browser-use

Use Cases: Web scraping, automated testing, data extraction, web interaction automation


4. wizsearch 🔍

PyPI version

Unified Python library for searching across multiple search engines with a consistent interface.

Features

  • Multiple Search Engines: Baidu, Bing, Brave, DuckDuckGo, Google, Google AI, SearxNG, Tavily, WeChat
  • Unified Interface: Single API with consistent SearchResult format
  • Multi-Engine Aggregation: Concurrent searches with round-robin result merging
  • Page Crawling: Built-in web page content extraction using Crawl4AI
  • Semantic Search: Optional vector-based semantic search with local storage
  • Full Async/Await Support: High-performance asynchronous operations
pip install -U wizsearch

Use Cases: Multi-source search, web content aggregation, semantic search, research automation


5. wizagent 🧙

PyPI version

Powerful web automation and research framework combining multi-engine search, deep research, browser automation, and structured data extraction.

Core Capabilities

  • Multi-Engine Web Search: Simultaneous search across multiple engines (Tavily, DuckDuckGo, Google AI, SearXNG, Brave, Baidu, WeChat)
  • Deep Research Agent: Autonomous research with iterative query refinement and source aggregation
  • Browser Automation: Intelligent browser control with natural language instructions (via cogents-browser-use)
  • Structured Data Extraction: Extract data from websites using Pydantic models
  • YAML-Based Schema Parser: Define data models declaratively with the Gem Parser
  • LangGraph Workflows: Advanced agent orchestration with state management

Architecture Stack

Built on cogents-core, cogents-browser-use, wizsearch, LangGraph, and Pydantic for a complete web intelligence solution.

pip install -U wizagent

Use Cases: Market research, competitive analysis, web data extraction, automated web intelligence gathering


Additional Resources


🤝 Contributing

We welcome contributions to any of the COGENTS subprojects! Each subproject follows its own contribution guidelines:

  1. Fork the specific subproject repository
  2. Create your feature branch
  3. Follow the project's code style and testing requirements
  4. Submit a pull request

For major changes, please open an issue first to discuss what you would like to change.


📄 License

All COGENTS subprojects are released under the MIT License. See the LICENSE file in each subproject repository for details.


🌟 Acknowledgments

COGENTS builds upon and integrates with several excellent projects:

  • Tencent Youtu-agent for toolkit integration
  • browser-use for browser automation foundations
  • LangGraph for workflow orchestration
  • The open-source community for continuous inspiration and support

Built with ❤️ by the COGENTS Community

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