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AgentForge

AgentForge is a low-code framework for rapidly developing, testing, and iterating AI-driven autonomous agents and cognitive architectures. Its core concepts include flexible Agents, declarative Cogs, and optional Memory, supporting everything from simple first runs to complex multi-agent orchestration. It is compatible with a variety of LLM models, including OpenAI, Google Gemini, Anthropic Claude, as well as local models running via Ollama or LMStudio, and allows different models to be run for different agents.

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About this tool

Purpose

AgentForge is an extensible AGI framework designed to rapidly develop, test, and iterate AI-driven autonomous agents (Agents) and cognitive architectures (multi-agent systems) in a low-code manner. It supports both simple first runs and complex multi-agent orchestration.

Key Capabilities

  • Declarative Cogs: Use simple YAML files to orchestrate multi-agent workflows, branching logic, and memory. 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 to enable coherent, context-aware interactions. Memory nodes are declared in Cogs and automatically made available to agents.
  • Personas: Configure an agent's identity, style, and context through persona YAML files.
  • Dynamic Prompt Templates: Use flexible prompt templates that adapt to different contexts and memory.
  • LLM Agnostic: Run different LLMs for different agents as needed.
  • Real-Time Prompt Editing: Modify prompts without restarting the system.
  • API Support: Integrate the APIs of OpenAI, Google, and Anthropic.
  • Open-Source Model Support: Leverage local models via Ollama and LMStudio.

Usage

It is officially recommended to start with the public documentation hub (docs hub), which provides a recommended order for the first smoke test, the first real Codex-supported model run, beginner Cog examples, and advanced references.

The quick start process includes: installation, setting up .agentforge/ directory structure, and running a debugging smoke test that requires no credentials. The first real model run can use the default Codex OAuth model path, or choose another provider. Advanced references cover Agents, Cogs, settings, API, memory, storage, utilities, and the legacy Tools/Actions reference.

Applicable Scenarios

Suitable for developers and researchers who need to quickly build and iterate autonomous agents, multi-agent systems, or cognitive architectures, whether using cloud LLMs or local models.

Limitations

Regarding specific fees, pricing, platform limitations, effects, or detailed usage steps, the available information does not currently provide them.

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