Engel Nyst 80fe13f4be rename our completion as a drop-in replacement of litellm completion (#2509) hai 1 ano
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README.md f950e3b48e make CodeAct paper link correct (#1870) hai 1 ano
__init__.py fadcdc117e Migrate to new folder structure in preparation for refactor (#1531) hai 1 ano
action_parser.py f7491bd2fa Refactor response to action in agent step (#2350) hai 1 ano
codeact_agent.py 80fe13f4be rename our completion as a drop-in replacement of litellm completion (#2509) hai 1 ano
prompt.py 823298e0d0 fix: Agentskills enhancements (#2384) hai 1 ano

README.md

CodeAct Agent Framework

This folder implements the CodeAct idea (paper, tweet) that consolidates LLM agents’ actions into a unified code action space for both simplicity and performance (see paper for more details).

The conceptual idea is illustrated below. At each turn, the agent can:

  1. Converse: Communicate with humans in natural language to ask for clarification, confirmation, etc.
  2. CodeAct: Choose to perform the task by executing code
    • Execute any valid Linux bash command
    • Execute any valid Python code with an interactive Python interpreter. This is simulated through bash command, see plugin system below for more details.

image

Plugin System

To make the CodeAct agent more powerful with only access to bash action space, CodeAct agent leverages OpenDevin's plugin system:

Demo

https://github.com/OpenDevin/OpenDevin/assets/38853559/f592a192-e86c-4f48-ad31-d69282d5f6ac

Example of CodeActAgent with gpt-4-turbo-2024-04-09 performing a data science task (linear regression)

Work-in-progress & Next step

[] Support web-browsing [] Complete the workflow for CodeAct agent to submit Github PRs