inclusionAI/AWorld

inclusionAI/AWorld

Description: Search, understand, reproduce, and improve an idea with ease

Language: Python

License: MIT

Stars: 1202

Forks: 123

Open issues: 50

Created: 2025-03-14T08:30:52Z

Pushed: 2026-06-11T02:51:28Z

Default branch: main

Fork: no

Archived: no

README:

*"The Next Frontier for AI is Your Expertise"*

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[中文版](./README_zh.md) | [Automation](#your-journey-with-aworld-cli) | [Evolution](#evolution) | [Contributing](#contributing) |

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General AI often hits a "wall of context"—the nuanced data, workflows, and intuition that define your world. An agent's true power lies not in the model alone, but in its Agent Harness: the framework orchestrating its tools, memory, context, and execution.

This is the AWorld Thesis: A powerful harness is not enough. True AI scaling is unlocked only when experts like you embed the invaluable knowledge, effectively building the gate in that wall.

AWorld is the platform designed for this singular purpose. We provide a complete, battle-tested Harness as the recipe for you, the expert, to forge your knowledge into a fleet of autonomous agents. Together, we move beyond AI's generic promise to create robust, precise applications that master your specific domain.

From Expertise to Product

See what happens when expert knowledge is encoded into reusable Skills. The creations below are orchestrated by the AWorld Agent, demonstrating our core scaling law: as the community contributes more expertise, the entire ecosystem becomes more powerful.

From one-prompt video generation to deep-search workflows, each example turns specialized know-how into repeatable production capability.

This is what's possible today. Imagine what we'll build with *your* expertise.

Capability Expertise See it in Action Recipe

Create App • Auto-creation by base model • Auto-evaluation by UI Evaluation Skill

View Recipe

Deep Search • Auto-search by Agent Browser Skill

View Recipe

One-Prompt Video: Trig-Identity • Auto-creation by Remotion Skill • See full video on Youtube

View Recipe

One-Prompt Video: Corporate Training • Auto-creation by Remotion Skill • See full video on Youtube

View Recipe

One-Prompt Video: Brand Marketing • Auto-creation by Video Diffusion & Audios Insert Skill • See full video on Youtube

View Recipe

One-Prompt Video: Social Media • Auto-creation by Video Diffusion & Audios Insert Skill • See full video on Youtube

View Recipe

One-Prompt Video: Vtuber • Auto-creation by Video Diffusion & Audio Generator & Video Embedded Skill • See full video on Youtube

View Recipe

Your Journey with AWorld-CLI

The journey from an idea to an evolved, autonomous agent begins at your fingertips.

Install and Activate

Install once, configure globally, and run anywhere.

Install AWorld-CLI

git clone https://github.com/inclusionAI/AWorld && cd AWorld

conda create -n aworld_env python=3.11 -y && conda activate aworld_env

pip install -e . && cd aworld-cli && pip install -e .

Config & Launch

cd your working directory

aworld-cli --config

Once configured, simply type aworld-cli in your terminal to start your journey.

Alternatively, you can configure by creating a .env file in your working directory with your model and API settings. See [AWorld CLI Configuration](docs/AWorld%20CLI/Configuration.md) for the core variables.

Automate Creation with AWorld-CLI

AWorld-CLI goes beyond simple scaffolding. It acts as a central brain, the AWorld Agent, which orchestrates a team of specialized sub-agents to build, evaluate, and even evolve other agents autonomously.

This multi-agent system works in concert to turn your ideas into reality:

Agent NameRole & Core Function

👑 AWorld AgentThe Orchestrator: The central brain that interprets user goals, creates a plan, and delegates tasks to the appropriate sub-agents. It manages the entire workflow from start to finish. 🧑‍💻 DeveloperThe Builder: The master craftsman responsible for writing, debugging, and refactoring code. 🧐 EvaluatorThe Judge: The quality assurance expert. It assesses the Developer's output against objective criteria, providing the critical feedback required for the evolution loop. 🎬 Video DiffusionThe Video Creator: A diffusion-model-based sub-agent (e.g., Kling-V3) that generates videos from text or text+image inputs. 🎤 Audio GeneratorThe Voice Creator: A TTS-model-based sub-agent that converts text input into speech audio. 🖼️ Image GeneratorThe Image Creator: A sub-agent that generates images from text or text+image inputs.

The Evolution Loop: Build -> Evaluate -> Evolve

Imagine you ask: *"Help me create an English word learning mini-app with a UI quality score above 0.9."*

• The Developer Builds: The Developer analyzes requirements and writes code (e.g., HTML) using [CAST](#cast-conquering-code-complexity).
• The Evaluator Judges: The Evaluator inspects the output using [our verified Skill](aworld-skills/app_evaluator/SKILL.md).
• The Loop Refines: If the score is below target (e.g., 0.9), AWorld instructs the Developer to fix specific issues identified by the Evaluator. This loop continues until your criteria are met.

*📹 See the Self-Evolution Loop in Action*

No Evaluation, No Evolution

For an agent to improve, it must first understand what "good" looks like. This evaluation is the core of our autonomous evolution loop, but it's a complex challenge. It ranges from objective tasks with clear metrics (e.g., solving a math problem) to subjective ones requiring human preference. Real-world evolution is further complicated by massive codebases, limited context windows, and the need for precise iteration.

AWorld provides the complete infrastructure to master both evaluation scenarios, turning your expertise into the definitive driving force that steers an agent through the entire evolution loop.

CAST: Conquering Code Complexity

Agents often fail because of overwhelming code complexity. We built CAST (Code Abstract Syntax Tree) to solve this. Instead of seeing a flat text file, CAST gives the agent an architectural blueprint of the code. This enables:

• Hierarchical Navigation:…