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AIWaves Agents

AIWaves Agents AI Agent
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Overview

Open‑source adaptive LLM framework for building, training & deploying autonomous language agents.

AIWaves Agents (repo name “agents”) is an open‑source framework for autonomous language agents that supports planning, memory (short‑ and long‑term), tool usage, web navigation, multi‑agent communication, human‑agent interaction, symbolic control via SOPs, and symbolic learning with backprop‑style updates.

Product overview

Capabilities, pricing and fit

AIWaves Agents is best understood as an agent-development framework. An Open-source Framework for Data-centric, Self-evolving Autonomous Language Agents.

Information as of July 30, 2026

What it can do

  • Agent application development

    An Open-source Framework for Data-centric, Self-evolving Autonomous Language Agents.[1]

Where it fits best

  • Building autonomous LLM agents with memory, tools, and web navigation.[1]

Pricing and availability

Access: Source repository[1]

Sources (1)
  1. GitHub - aiwaves-cn/agents: An Open-source Framework for Data-centric, Self-evolving Autonomous Language Agents · GitHubGitHub · checked 2026-07-30

Autonomy level

85/100

Our subjective rating of how independently the product carries out its documented tasks, considering the human setup, input, approval and review it needs. This is not a measured success rate.

Reasoning: The AIWaves Agents framework provides a comprehensive set of features for building autonomous language agents, including planning, memory, tool usage, and multi-agent communication. These features enable the creation of agents that can operate with minimal human intervention. However, the actual autonomy level of a specific agent depends on how it ...

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Some of the use cases of AIWaves Agents:

  • Building autonomous LLM agents with memory, tools, and web navigation.
  • Designing multi‑agent systems with dynamic scheduling and agent communication.
  • Implementing human‑in‑the‑loop workflows via SOPs.
  • Training agents with symbolic learning and language‑gradient optimization.
  • Deploying agents easily with config files and optional UI demos.

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Popularity level: 74%

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