AgentScope

0
AgentScope provides a comprehensive toolkit for building, orchestrating, and deploying AI agents. It offers dynamic planning strategies, context-aware memory systems, and seamless integration with external APIs and tools. With multi-model support and modular components, developers can quickly prototype conversational assistants, automation workflows, and specialized digital workers.
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May 08 2025
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AgentScope

AgentScope

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42.3K
AgentScope
AgentScope provides a comprehensive toolkit for building, orchestrating, and deploying AI agents. It offers dynamic planning strategies, context-aware memory systems, and seamless integration with external APIs and tools. With multi-model support and modular components, developers can quickly prototype conversational assistants, automation workflows, and specialized digital workers.
Added on:
Social & Email:
Platform:
May 08 2025
Featured

What is AgentScope?

AgentScope is a developer-focused framework designed to simplify the creation of intelligent agents by providing modular components for dynamic planning, contextual memory storage, and tool/API integration. It supports multiple LLM backends (OpenAI, Anthropic, Hugging Face) and offers customizable pipelines for task execution, answer synthesis, and data retrieval. AgentScope’s architecture enables rapid prototyping of conversational bots, workflow automation agents, and research assistants, all while maintaining extensibility and scalability.

Who will use AgentScope?

  • AI developers
  • Machine learning engineers
  • Data scientists
  • Product managers
  • Research teams

How to use the AgentScope?

  • Step1: Install AgentScope via pip: `pip install agentscope`
  • Step2: Import AgentScope and initialize an Agent class in your Python script
  • Step3: Configure planning strategy, memory module, and tool integrations
  • Step4: Provide prompts or tasks to the agent and call `agent.run()`
  • Step5: Process the agent’s output or integrate with your application workflow

Platform

  • web
  • mac
  • windows
  • linux

AgentScope's Core Features & Benefits

The Core Features

  • Customizable planning strategies
  • Contextual memory management
  • External tool and API integration
  • Multi-model LLM support
  • Agent orchestration pipelines

The Benefits

  • Accelerates agent development
  • Modular and extensible architecture
  • Seamless integration with popular LLM providers
  • Scalable for production workloads

AgentScope's Main Use Cases & Applications

  • Building conversational AI assistants
  • Automating customer support workflows
  • Data retrieval and summarization
  • Task automation via external tool integration
  • Research assistants for document analysis

AgentScope's Pros & Cons

The Pros

Comprehensive documentation covering various aspects of AI agent development
Supports advanced features like multimodality and retrieval-augmented generation
Includes tools for prompt optimization and system monitoring
Facilitates low-code development for easier integration

The Cons

No clear information on pricing models
Lack of visible open-source community or GitHub repository
No direct links to app stores or integration marketplaces

FAQs of AgentScope

AgentScope Company Information

Analytic of AgentScope

Visit Over Time

Monthly Visits
42.3k
Avg Visit Duration
00:06:27
Page Per Visit
3.14
Bounce Rate
48.07%
Sep 2025 - Nov 2025 All Traffic

Geography

Top 5 Regions
China
83.58%
Hong Kong
8.4%
Singapore
4.52%
United States
1.95%
Taiwan
1.5%
Sep 2025 - Nov 2025 Worldwide Desktop Only

Traffic Sources

Direct
75.87%
Search
11.70%
Referrals
9.85%
Social
2.04%
Paid Referrals
0.44%
Mail
0.10%
Sep 2025 - Nov 2025 Desktop Only

AgentScope Reviews

5/5
Do You Recommend AgentScope? Leave a Comment Below!

AgentScope's Main Competitors and alternatives?

  • LangChain
  • Microsoft Semantic Kernel
  • AutoGen
  • Haystack

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