Agentic framework for executing requests via search, code, and testing
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EVAL is an AI agent designed to execute user requests by autonomously searching, coding, running, and testing on the internet. It targets users who need to automate complex tasks, from generating web applications to performing multimodal data analysis, by leveraging a flexible, self-evolving toolset.
How It Works
EVAL integrates LangChain, LlamaIndex, and Visual ChatGPT to create a versatile agent. It employs a modular architecture allowing it to dynamically create, modify, and execute code to build new tools as needed. This approach enables it to handle multimodal inputs (text, image, dataframe, with audio/video planned) and serve blocking processes like web applications.
Quick Start & Requirements
docker-compose up --build eval
(CPU) or docker-compose up --build eval.gpu
(GPU).OPENAI_API_KEY
). GPU version has significant dependencies and is noted as unstable.http://localhost:8000
. API documentation via POST /api/execute
.Highlighted Details
Maintenance & Community
The project references LangChain, LlamaIndex, and Visual ChatGPT. No specific community channels or roadmap are detailed in the README.
Licensing & Compatibility
The README does not explicitly state a license. It references other projects with various licenses, implying potential compatibility considerations for commercial use.
Limitations & Caveats
The GPU version is described as "much heavier and unstable for now." Several features are marked as TODO, including GUI, memory saving, session management, and expanded multimodal support (audio, video).
2 years ago
1 day