4c264b7ae9
Add a task management component modeled after Claude Code's TodoWrite: - TodoItem with recursive sub_items for hierarchical task structure - todo_write: atomic list replacement with sub-items support - todo_read: retrieve current todos with nested structure - todo_clear: clear all todos - todo_decompose: use smart LLM to break down tasks into sub-steps Features: - Hierarchical task tracking with independent status per sub-item - MessageProvider shows todos in LLM context with proper indentation - DirectiveProvider adds best practices for task management - Graceful fallback when LLM provider not configured Integrates with: - original_autogpt Agent (full LLM decomposition support) - ForgeAgent (basic task tracking, no decomposition) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
AutoGPT Classic
AutoGPT Classic was an experimental project to demonstrate autonomous GPT-4 operation. It was designed to make GPT-4 independently operate and chain together tasks to achieve more complex goals.
Project Status
This project is unsupported, and dependencies will not be updated. It was an experiment that has concluded its initial research phase. If you want to use AutoGPT, you should use the AutoGPT Platform.
For those interested in autonomous AI agents, we recommend exploring more actively maintained alternatives or referring to this codebase for educational purposes only.
Overview
AutoGPT Classic was one of the first implementations of autonomous AI agents - AI systems that can independently:
- Break down complex goals into smaller tasks
- Execute those tasks using available tools and APIs
- Learn from the results and adjust its approach
- Chain multiple actions together to achieve an objective
Structure
/benchmark- Performance testing tools/forge- Core autonomous agent framework/original_autogpt- Original implementation
Getting Started
Prerequisites
- Python 3.10+
- Poetry
Installation
# Clone the repository
git clone https://github.com/Significant-Gravitas/AutoGPT.git
cd classic
# Install forge (core library)
cd forge && poetry install
# Or install original_autogpt (includes forge as dependency)
cd original_autogpt && poetry install
# Install benchmark (optional)
cd benchmark && poetry install
Configuration
Copy the example environment file and add your API keys:
cp .env.example .env
# Edit .env with your OPENAI_API_KEY, etc.
Running
# Run forge agent
cd forge && poetry run python -m forge
# Run original autogpt server
cd original_autogpt && poetry run serve --debug
# Run autogpt CLI
cd original_autogpt && poetry run autogpt
Agents run on http://localhost:8000 by default.
Benchmarking
cd benchmark && poetry run agbenchmark
Testing
cd forge && poetry run pytest
cd original_autogpt && poetry run pytest
Security Notice
This codebase has known vulnerabilities and issues with its dependencies. It will not be updated to new dependencies. Use for educational purposes only.
License
This project segment is licensed under the MIT License - see the LICENSE file for details.
Documentation
Please refer to the documentation for more detailed information about the project's architecture and concepts.