AgentForge is a low-code framework for rapid development, testing, and iteration of AI-powered autonomous agents and cognitive architectures. Its core concepts—flexible Agents, declarative Cogs, and integrated Memory—enable both simple agent implementations and sophisticated multi-agent orchestration with minimal code.
Compatible with a range of LLM models—including OpenAI, Google's Gemini, Anthropic's Claude, and local models via Ollama or LMStudio—AgentForge lets you run different models for different agents as needed.
Whether you're new to AI agents or building advanced cognitive systems, AgentForge provides the tools to craft intelligent, model-agnostic, and database-flexible autonomous agents.
Build agents and cognitive architectures (multi-agent systems) with:
- Declarative Cogs: Orchestrate multi-agent workflows, branching logic, and memory using simple YAML files. Cogs are the primary way to compose agents into complex, reusable workflows.
- Customizable Agents: Define agents using YAML prompt templates and configuration.
- Integrated Memory: Add contextual memory to agents and cogs for coherent, context-aware interactions. Memory nodes are declared in Cogs and made available to agents automatically.
- Personas: Configure agent identity, style, and context using persona YAML files.
- Dynamic Prompt Templates: Use flexible prompt templates that adapt to various contexts and memory.
- LLM Agnostic: Run different agents with different LLMs as needed.
- On-The-Fly Prompt Editing: Modify prompts in real-time without restarting the system.
- OpenAI, Google & Anthropic API Support: Integrate with popular LLM APIs.
- Open-Source Model Support: Leverage local models through Ollama and LMStudio.
Note: Actions and tools are deprecated as of this release and will be replaced in a future version with a new system based on the MCP standard.
Comprehensive documentation is available to help you get started and go deeper:
- Installation Guide: Step-by-step instructions to install AgentForge.
- Using AgentForge: Learn how to run agents, create custom agents, and build cognitive architectures with examples.
- Prerequisites Guide: Details all pre-installation requirements and dependencies.
- Troubleshooting Guide: Find solutions to common issues and platform-specific problems.
- Agents: Create and customize individual AI agents for various tasks.
- Cogs: Design multi-agent workflows with branching logic and memory using YAML configuration. Cogs are the main way to build and run multi-agent systems in AgentForge.
- Memory: Add contextual memory to your agents and cogs for more coherent, context-aware interactions. Memory is managed declaratively in Cogs and accessed in agent prompts.
- API Integration: Understand how AgentForge connects with various Large Language Model (LLM) APIs.
- Personas: Use personas to encapsulate agent identity, style, and reusable knowledge.
- Settings: Configure models, storage, and system behavior.
- Storage: AgentForge uses ChromaDB as its vector store implementation for memory.
- Tools & Actions: Deprecated—will be replaced by an MCP-based system in a future release.
- Utilities: Explore utility functions and tools that enhance the system's capabilities.
We welcome issues and pull requests with improvements or bug fixes!
We’re looking for a volunteer UI/UX collaborator—ideally someone who’s genuinely passionate about open-source—to help us develop a front-end for AgentForge. To be clear, this isn’t a paid position or formal job; we’re just a couple of backend folks looking to team up with someone interested in contributing their front-end skills for the love of the project and learning together. If you’re interested in collaborating, see Contact Us below.
- Email: [email protected]
- Discord: Join our Discord Server
This project is licensed under the GNU General Public License v3.0. See LICENSE for more details.
