Jar3d is a meta-agent orchestration framework designed for complex, research-intensive tasks. It empowers users to delegate multi-step projects to a team of specialized AI agents, streamlining workflows for research, content creation, and data analysis.

How It Works

Jar3d utilizes LangGraph to manage a team of agents, including a Meta Agent for coordination, Tool Agents for specific functions (like web scraping or RAG), and a Reporter Agent for user communication. It employs meta-prompting and chain-of-reasoning techniques to enhance agent performance and coherence, with a workflow that begins with requirements gathering and progresses through agent execution to final reporting.

Quick Start & Requirements

• Install via git clone and docker-compose up --build.
• Requires Docker, Git, and API keys for LLM providers (OpenAI recommended, Serper, Anthropic, Gemini, Groq supported).
• Access the web interface at http://localhost:8105.
• Official documentation: GitHub repository.

Highlighted Details

• Orchestrates a team of specialized agents (Google Search, Shopping, Web Scraper, RAG).
• Integrates with LangSmith for observability and debugging agent flows.
• Supports advanced prompting techniques like meta-prompting and chain-of-reasoning.
• Future roadmap includes Ollama, vLLM, Gemini, Groq, and enhanced memory management.

Maintenance & Community

• Active development with a clear roadmap.
• Integrations with LangSmith suggest a focus on observability.

Licensing & Compatibility

• The repository does not explicitly state a license in the provided README.

Limitations & Caveats

• Neo4j integration is temporarily removed.
• Anthropic, Gemini, and Groq support are noted as not recommended or not yet supported, respectively.
• Requires careful management of API keys for various LLM providers.