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Replace basic DuckDuckGo-only search with a modern tiered system: 1. Tavily (primary) - AI-optimized results with content extraction - AI-generated answer summaries - Relevance scoring - Full page content extraction via search_and_extract command 2. Serper (secondary) - Fast, cheap Google SERP results - $0.30-1.00 per 1K queries - Real Google results without scraping 3. DDGS multi-engine (fallback) - Free, no API key required - Automatic fallback chain: DuckDuckGo → Bing → Brave → Google → etc. - 8 search backends supported Key changes: - Upgrade duckduckgo-search to ddgs v9.10 (renamed successor package) - Add Tavily and Serper API integrations - Implement automatic provider selection and fallback chain - Add search_and_extract command for research with content extraction - Add TAVILY_API_KEY and SERPER_API_KEY to env templates - Update benchmark httpx constraint for ddgs compatibility - 23 comprehensive tests for all providers and fallback scenarios 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.