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原型設計

  • Graph-centric AI agent framework orchestrating LLM calls and structured knowledge through customizable language graphs.
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    What is Geers AI Lang Graph?
    Geers AI Lang Graph provides a graph-based abstraction layer for building AI agents that coordinate multiple LLM calls and manage structured knowledge. By defining nodes and edges representing prompts, data, and memory, developers can create dynamic workflows, track context across interactions, and visualize execution flows. The framework supports plugin integrations for various LLM providers, custom prompt templating, and exportable graphs. It simplifies iterative agent design, improves context retention, and accelerates prototyping of conversational assistants, decision-support bots, and research pipelines.
  • ManasAI provides a modular framework to build stateful autonomous AI agents with memory, tools integration, and orchestration.
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    What is ManasAI?
    ManasAI is a Python-based framework that enables the creation of autonomous AI agents with built-in state and modular components. It offers core abstractions for agent reasoning, short-term and long-term memory, external tool and API integrations, message-driven event handling, and multi-agent orchestration. Agents can be configured to manage context, execute tasks, handle retries, and gather feedback. Its pluggable architecture allows developers to tailor memory backends, tools, and orchestrators to specific workflows, making it ideal for prototyping chatbots, digital workers, and automated pipelines that require persistent context and complex interactions.
  • A set of AWS code demos illustrating LLM Model Context Protocol, tool invocation, context management, and streaming responses.
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    What is AWS Sample Model Context Protocol Demos?
    The AWS Sample Model Context Protocol Demos is an open-source repository showcasing standardized patterns for Large Language Model (LLM) context management and tool invocation. It features two complete demos—one in JavaScript/TypeScript and one in Python—that implement the Model Context Protocol, enabling developers to build AI agents that call AWS Lambda functions, preserve conversation history, and stream responses. Sample code demonstrates message formatting, function argument serialization, error handling, and customizable tool integrations, accelerating prototyping of generative AI applications.
  • SketchPro is your AI copilot for architecture and design.
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    What is SketchPro AI?
    SketchPro is a revolutionary AI-powered design tool tailored for architects and designers. It allows users to effortlessly create high-quality renderings and iterate on early design concepts. By leveraging generative design, SketchPro helps professionals explore countless design variations and refine their ideas seamlessly. This platform aims to enhance creativity and streamline the design process, making it faster and more efficient. Whether you are conceptualizing a new project or refining existing plans, SketchPro offers the tools needed to transform your vision into reality.
  • AI TUBO: Free AI Image & Video Generator for creativity.
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    What is aitubo.ai?
    AI TUBO provides advanced AI tools for creating images and videos. It supports various artistic and professional needs like game asset creation, prototype design, and character development. With no requirement for credit card details, it enables users to leverage AI for generating high-quality content seamlessly. Trusted by over 2 million users and having generated over 300 million works, AI TUBO stands as a reliable and efficient solution for creative projects.
  • A Python framework using LLMs to autonomously evaluate, propose, and finalize negotiations in customizable domains.
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    What is negotiation_agent?
    negotiation_agent provides a modular toolkit for building autonomous negotiation bots powered by GPT-like models. Developers can specify negotiation scenarios by defining items, preferences, and utility functions to model agent objectives. The framework includes pre-defined agent templates and allows integration of custom strategies, enabling offer generation, counteroffer evaluation, acceptance decisions, and deal closure. It manages dialogue flows using standardized protocols, supports batch simulations for tournament-style experiments, and calculates performance metrics such as agreement rate, utility gains, and fairness scores. The open architecture facilitates swapping underlying LLM backends and extending agent logic through plugins. With negotiation_agent, teams can quickly prototype and evaluate automated bargaining solutions in e-commerce, research, and educational settings.
  • Production-ready FastAPI template using LangGraph for building scalable LLM agents with customizable pipelines and memory integration.
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    What is FastAPI LangGraph Agent Template?
    FastAPI LangGraph Agent Template offers a comprehensive foundation for developing LLM-driven agents within a FastAPI application. It includes predefined LangGraph nodes for common tasks like text completion, embedding, and vector similarity search while allowing developers to create custom nodes and pipelines. The template manages conversation history via memory modules that persist context across sessions and supports environment-based configuration for different deployment stages. Built-in Docker files and CI/CD-friendly structure ensure seamless containerization and deployment. Logging and error-handling middleware enhance observability, while the modular codebase simplifies extending functionality. By combining FastAPI's high-performance web framework with LangGraph's orchestration capabilities, this template streamlines the agent development lifecycle from prototyping to production.
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