anda
ðĪ An AI agent framework built with Rust, powered by ICP and TEEs.
Stars: 292
Anda is an AI agent framework built with Rust, integrating ICP blockchain and TEE support. It aims to create a network of highly composable, autonomous AI agents across industries to advance artificial intelligence. Key features include composability, simplicity, trustworthiness, autonomy, and perpetual memory. Anda's vision is to build a collaborative network of agents leading to a super AGI system, revolutionizing AI technology applications and creating value for society.
README:
ðĪ An AI agent framework built with Rust, powered by ICP and TEEs.
English readme | äļæčŊīæ | æĨæŽčŠãŪ芎æ
Anda is an AI agent framework built with Rust, featuring ICP blockchain integration and TEE support. It is designed to create a highly composable, autonomous, and perpetually memorizing network of AI agents. By connecting agents across various industries, Anda aims to create a super AGI system, advancing artificial intelligence to higher levels.
-
Composability: Anda agents specialize in solving domain-specific problems and can flexibly combine with other agents to tackle complex tasks. When a single agent cannot solve a problem alone, it collaborates with others to form a robust problem-solving network. This modular design allows Anda to adapt to diverse needs.
-
Simplicity: Anda emphasizes simplicity and ease of use, enabling developers to quickly build powerful and efficient agents. Non-developers can also create their own agents through simple configurations, lowering the technical barrier and inviting broader participation in agent development and application.
-
Trustworthiness: Anda agents operate within a decentralized trusted execution environment (dTEE) based on Trusted Execution Environments (TEEs), ensuring security, privacy, and data integrity. This architecture provides a highly reliable infrastructure for agent operations, safeguarding data and computational processes.
-
Autonomy: Anda agents derive permanent identities and cryptographic capabilities from the ICP blockchain, combined with the reasoning and decision-making abilities of large language models (LLMs). This allows agents to autonomously and efficiently solve problems based on their experiences and knowledge, adapting to dynamic environments and making effective decisions in complex scenarios.
-
Perpetual Memory: The memory states of Anda agents are stored on the ICP blockchain and within the trusted storage network of dTEE, ensuring continuous algorithm upgrades, knowledge accumulation, and evolution. This perpetual memory mechanism enables agents to operate indefinitely, even achieving "immortality", laying the foundation for a super AGI system.
Anda's goal is to create and connect countless agents, building an open, secure, trustworthy, and highly collaborative network of agents, ultimately realizing a super AGI system. We believe Anda will bring revolutionary changes across industries, driving the widespread application of AI technology and creating greater value for human society.
ICPanda DAO is an SNS DAO established on the Internet Computer Protocol (ICP) blockchain, issuing the PANDA token. As the creator of the Anda framework, ICPanda DAO is dedicated to exploring the future of Web3 and AI integration.
- Website: https://panda.fans/
- Permalink: https://dmsg.net/PANDA
- ICP SNS: https://dashboard.internetcomputer.org/sns/d7wvo-iiaaa-aaaaq-aacsq-cai
- Token: PANDA on ICP network, https://www.coingecko.com/en/coins/icpanda-dao
Documents:
anda/
âââ anda_cli/ # The command line interface for Anda engine server
âââ anda_core/ # Core library containing base types and interfaces
âââ anda_engine/ # Engine implementation for agent runtime and management
âââ anda_engine_server/ # A http server to serve multiple Anda engines
âââ anda_lancedb/ # LanceDB integration for vector storage and retrieval
âââ anda_web3_client/ # The Rust SDK for Web3 integration in non-TEE environments
âââ agents/ # Various AI agent implementations
â âââ anda_bot/ # Example agent: Anda ICP
â âââ .../ # More agents in future releases
âââ tools/ # Tool libraries
â âââ anda_icp/ # Anda agent tools offers integration with the Internet Computer (ICP).
â âââ .../ # More tools in future releases
âââ characters/ # characters examples
âââ examples/ # AI agents examplesYou can follow the agents in the agents directory. For example, anda_bot.
The deployment process is currently complex, but we plan to launch a cloud service for one-click deployment in the future.
- Add more integration tools with external services in
tools; - Create more agent applications in
agents; - Or enhance the core engines
anda_coreandanda_engine.
- IC-TEE: ð Make Trusted Execution Environments (TEEs) work with the Internet Computer.
- IC-COSE: âïļ A decentralized COnfiguration service with Signing and Encryption on the Internet Computer.
Copyright ÂĐ 2025 LDC Labs.
ldclabs/anda is licensed under the MIT License. See LICENSE for the full license text.
For Tasks:
Click tags to check more tools for each tasksFor Jobs:
Alternative AI tools for anda
Similar Open Source Tools
anda
Anda is an AI agent framework built with Rust, integrating ICP blockchain and TEE support. It aims to create a network of highly composable, autonomous AI agents across industries to advance artificial intelligence. Key features include composability, simplicity, trustworthiness, autonomy, and perpetual memory. Anda's vision is to build a collaborative network of agents leading to a super AGI system, revolutionizing AI technology applications and creating value for society.
dapr-agents
Dapr Agents is a developer framework for building production-grade resilient AI agent systems that operate at scale. It enables software developers to create AI agents that reason, act, and collaborate using Large Language Models (LLMs), while providing built-in observability and stateful workflow execution to ensure agentic workflows complete successfully. The framework is scalable, efficient, Kubernetes-native, data-driven, secure, observable, vendor-neutral, and open source. It offers features like scalable workflows, cost-effective AI adoption, data-centric AI agents, accelerated development, integrated security and reliability, built-in messaging and state infrastructure, and vendor-neutral and open source support. Dapr Agents is designed to simplify the development of AI applications and workflows by providing a comprehensive API surface and seamless integration with various data sources and services.
magic
Magic is an open-source all-in-one AI productivity platform designed to help enterprises quickly build and deploy AI applications, aiming for a 100x increase in productivity. It consists of various AI products and infrastructure tools, such as Super Magic, Magic IM, Magic Flow, and more. Super Magic is a general-purpose AI Agent for complex task scenarios, while Magic Flow is a visual AI workflow orchestration system. Magic IM is an enterprise-grade AI Agent conversation system for internal knowledge management. Teamshare OS is a collaborative office platform integrating AI capabilities. The platform provides cloud services, enterprise solutions, and a self-hosted community edition for users to leverage its features.
agentUniverse
agentUniverse is a framework for developing applications powered by multi-agent based on large language model. It provides essential components for building single agent and multi-agent collaboration mechanism for customizing collaboration patterns. Developers can easily construct multi-agent applications and share pattern practices from different fields. The framework includes pre-installed collaboration patterns like PEER and DOE for complex task breakdown and data-intensive tasks.
akeru
Akeru.ai is an open-source AI platform leveraging the power of decentralization. It offers transparent, safe, and highly available AI capabilities. The platform aims to give developers access to open-source and transparent AI resources through its decentralized nature hosted on an edge network. Akeru API introduces features like retrieval, function calling, conversation management, custom instructions, data input optimization, user privacy, testing and iteration, and comprehensive documentation. It is ideal for creating AI agents and enhancing web and mobile applications with advanced AI capabilities. The platform runs on a Bittensor Subnet design that aims to democratize AI technology and promote an equitable AI future. Akeru.ai embraces decentralization challenges to ensure a decentralized and equitable AI ecosystem with security features like watermarking and network pings. The API architecture integrates with technologies like Bun, Redis, and Elysia for a robust, scalable solution.
synthora
Synthora is a lightweight and extensible framework for LLM-driven Agents and ALM research. It aims to simplify the process of building, testing, and evaluating agents by providing essential components. The framework allows for easy agent assembly with a single config, reducing the effort required for tuning and sharing agents. Although in early development stages with unstable APIs, Synthora welcomes feedback and contributions to enhance its stability and functionality.
agentsociety
AgentSociety is an advanced framework designed for building agents in urban simulation environments. It integrates LLMs' planning, memory, and reasoning capabilities to generate realistic behaviors. The framework supports dataset-based, text-based, and rule-based environments with interactive visualization. It includes tools for interviews, surveys, interventions, and metric recording tailored for social experimentation.
llmesh
LLM Agentic Tool Mesh is a platform by HPE Athonet that democratizes Generative Artificial Intelligence (Gen AI) by enabling users to create tools and web applications using Gen AI with Low or No Coding. The platform simplifies the integration process, focuses on key user needs, and abstracts complex libraries into easy-to-understand services. It empowers both technical and non-technical teams to develop tools related to their expertise and provides orchestration capabilities through an agentic Reasoning Engine based on Large Language Models (LLMs) to ensure seamless tool integration and enhance organizational functionality and efficiency.
awesome-algorand
Awesome Algorand is a curated list of resources related to the Algorand Blockchain, including official resources, wallets, blockchain explorers, portfolio trackers, learning resources, development tools, DeFi platforms, nodes & consensus participation, subscription management, security auditing services, blockchain bridges, oracles, name services, community resources, Algorand Request for Comments, metrics and analytics services, decentralized voting tools, and NFT marketplaces. The repository provides a comprehensive collection of tools, tutorials, protocols, and platforms for developers, users, and enthusiasts interested in the Algorand ecosystem.
nuwa
Nuwa is an AI platform where users pay directly to developers for AI models and agents. Payments are made using cryptocurrencies secured by blockchain. User data and authentications are based on Decentralized Identity (DID). Nuwa aims to reduce friction for users, enhance their daily AI experience, and provide direct monetization for developers. The platform offers an agent-first approach, protocol-powered solutions, and user-aligned services. It includes a Nuwa Client for AI chat with DID-based authentication and cryptocurrency payments, and Nuwa Kit for developers to build and launch AI models and agents into Caps (capabilities). The repository contains various components of the Nuwa Protocol, including Nuwa Improvement Proposals, smart contracts, client agent implementation, development kits, reference implementations of key services, and websites for documentation and landing pages.
CodeFuse-muAgent
CodeFuse-muAgent is a Multi-Agent framework designed to streamline Standard Operating Procedure (SOP) orchestration for agents. It integrates toolkits, code libraries, knowledge bases, and sandbox environments for rapid construction of complex Multi-Agent interactive applications. The framework enables efficient execution and handling of multi-layered and multi-dimensional tasks.
llmariner
LLMariner is an extensible open source platform built on Kubernetes to simplify the management of generative AI workloads. It enables efficient handling of training and inference data within clusters, with OpenAI-compatible APIs for seamless integration with a wide range of AI-driven applications.
floki
Floki is an open-source framework for researchers and developers to experiment with LLM-based autonomous agents. It provides tools to create, orchestrate, and manage agents while seamlessly connecting to LLM inference APIs. Built on Dapr, Floki leverages a unified programming model that simplifies microservices and supports both deterministic workflows and event-driven interactions. By bringing together these features, Floki provides a powerful way to explore agentic workflows and the components that enable multi-agent systems to collaborate and scale, all powered by Dapr.
AgentConnect
AgentConnect is an open-source implementation of the Agent Network Protocol (ANP) aiming to define how agents connect with each other and build an open, secure, and efficient collaboration network for billions of agents. It addresses challenges like interconnectivity, native interfaces, and efficient collaboration by providing authentication, end-to-end encryption, meta-protocol handling, and application layer protocol integration. The project focuses on performance and multi-platform support, with plans to rewrite core components in Rust and support Mac, Linux, Windows, mobile platforms, and browsers. AgentConnect aims to establish ANP as an industry standard through protocol development and forming a standardization committee.
bedrock-agentcore-starter-toolkit
Amazon Bedrock AgentCore Starter Toolkit enables developers to deploy and operate highly effective AI agents securely at scale using any framework and model. It provides tools and capabilities to make agents more effective and capable, purpose-built infrastructure to securely scale agents, and controls to operate trustworthy agents. The toolkit includes modular services like Runtime, Memory, Gateway, Code Interpreter, Browser, Observability, Identity, and Import Agent for seamless migration of existing agents. It is currently in public preview and offers enterprise-grade security and reliability for accelerating AI agent development.
nextpy
Nextpy is a cutting-edge software development framework optimized for AI-based code generation. It provides guardrails for defining AI system boundaries, structured outputs for prompt engineering, a powerful prompt engine for efficient processing, better AI generations with precise output control, modularity for multiplatform and extensible usage, developer-first approach for transferable knowledge, and containerized & scalable deployment options. It offers 4-10x faster performance compared to Streamlit apps, with a focus on cooperation within the open-source community and integration of key components from various projects.
For similar tasks
OpenAGI
OpenAGI is an AI agent creation package designed for researchers and developers to create intelligent agents using advanced machine learning techniques. The package provides tools and resources for building and training AI models, enabling users to develop sophisticated AI applications. With a focus on collaboration and community engagement, OpenAGI aims to facilitate the integration of AI technologies into various domains, fostering innovation and knowledge sharing among experts and enthusiasts.
GPTSwarm
GPTSwarm is a graph-based framework for LLM-based agents that enables the creation of LLM-based agents from graphs and facilitates the customized and automatic self-organization of agent swarms with self-improvement capabilities. The library includes components for domain-specific operations, graph-related functions, LLM backend selection, memory management, and optimization algorithms to enhance agent performance and swarm efficiency. Users can quickly run predefined swarms or utilize tools like the file analyzer. GPTSwarm supports local LM inference via LM Studio, allowing users to run with a local LLM model. The framework has been accepted by ICML2024 and offers advanced features for experimentation and customization.
AgentForge
AgentForge is a low-code framework tailored for the rapid development, testing, and iteration of AI-powered autonomous agents and Cognitive Architectures. It is compatible with a range of LLM models and offers flexibility to run different models for different agents based on specific needs. The framework is designed for seamless extensibility and database-flexibility, making it an ideal playground for various AI projects. AgentForge is a beta-testing ground and future-proof hub for crafting intelligent, model-agnostic autonomous agents.
atomic_agents
Atomic Agents is a modular and extensible framework designed for creating powerful applications. It follows the principles of Atomic Design, emphasizing small and single-purpose components. Leveraging Pydantic for data validation and serialization, the framework offers a set of tools and agents that can be combined to build AI applications. It depends on the Instructor package and supports various APIs like OpenAI, Cohere, Anthropic, and Gemini. Atomic Agents is suitable for developers looking to create AI agents with a focus on modularity and flexibility.
LongRoPE
LongRoPE is a method to extend the context window of large language models (LLMs) beyond 2 million tokens. It identifies and exploits non-uniformities in positional embeddings to enable 8x context extension without fine-tuning. The method utilizes a progressive extension strategy with 256k fine-tuning to reach a 2048k context. It adjusts embeddings for shorter contexts to maintain performance within the original window size. LongRoPE has been shown to be effective in maintaining performance across various tasks from 4k to 2048k context lengths.
ax
Ax is a Typescript library that allows users to build intelligent agents inspired by agentic workflows and the Stanford DSP paper. It seamlessly integrates with multiple Large Language Models (LLMs) and VectorDBs to create RAG pipelines or collaborative agents capable of solving complex problems. The library offers advanced features such as streaming validation, multi-modal DSP, and automatic prompt tuning using optimizers. Users can easily convert documents of any format to text, perform smart chunking, embedding, and querying, and ensure output validation while streaming. Ax is production-ready, written in Typescript, and has zero dependencies.
Awesome-AI-Agents
Awesome-AI-Agents is a curated list of projects, frameworks, benchmarks, platforms, and related resources focused on autonomous AI agents powered by Large Language Models (LLMs). The repository showcases a wide range of applications, multi-agent task solver projects, agent society simulations, and advanced components for building and customizing AI agents. It also includes frameworks for orchestrating role-playing, evaluating LLM-as-Agent performance, and connecting LLMs with real-world applications through platforms and APIs. Additionally, the repository features surveys, paper lists, and blogs related to LLM-based autonomous agents, making it a valuable resource for researchers, developers, and enthusiasts in the field of AI.
CodeFuse-muAgent
CodeFuse-muAgent is a Multi-Agent framework designed to streamline Standard Operating Procedure (SOP) orchestration for agents. It integrates toolkits, code libraries, knowledge bases, and sandbox environments for rapid construction of complex Multi-Agent interactive applications. The framework enables efficient execution and handling of multi-layered and multi-dimensional tasks.
For similar jobs
sweep
Sweep is an AI junior developer that turns bugs and feature requests into code changes. It automatically handles developer experience improvements like adding type hints and improving test coverage.
teams-ai
The Teams AI Library is a software development kit (SDK) that helps developers create bots that can interact with Teams and Microsoft 365 applications. It is built on top of the Bot Framework SDK and simplifies the process of developing bots that interact with Teams' artificial intelligence capabilities. The SDK is available for JavaScript/TypeScript, .NET, and Python.
ai-guide
This guide is dedicated to Large Language Models (LLMs) that you can run on your home computer. It assumes your PC is a lower-end, non-gaming setup.
classifai
Supercharge WordPress Content Workflows and Engagement with Artificial Intelligence. Tap into leading cloud-based services like OpenAI, Microsoft Azure AI, Google Gemini and IBM Watson to augment your WordPress-powered websites. Publish content faster while improving SEO performance and increasing audience engagement. ClassifAI integrates Artificial Intelligence and Machine Learning technologies to lighten your workload and eliminate tedious tasks, giving you more time to create original content that matters.
chatbot-ui
Chatbot UI is an open-source AI chat app that allows users to create and deploy their own AI chatbots. It is easy to use and can be customized to fit any need. Chatbot UI is perfect for businesses, developers, and anyone who wants to create a chatbot.
BricksLLM
BricksLLM is a cloud native AI gateway written in Go. Currently, it provides native support for OpenAI, Anthropic, Azure OpenAI and vLLM. BricksLLM aims to provide enterprise level infrastructure that can power any LLM production use cases. Here are some use cases for BricksLLM: * Set LLM usage limits for users on different pricing tiers * Track LLM usage on a per user and per organization basis * Block or redact requests containing PIIs * Improve LLM reliability with failovers, retries and caching * Distribute API keys with rate limits and cost limits for internal development/production use cases * Distribute API keys with rate limits and cost limits for students
uAgents
uAgents is a Python library developed by Fetch.ai that allows for the creation of autonomous AI agents. These agents can perform various tasks on a schedule or take action on various events. uAgents are easy to create and manage, and they are connected to a fast-growing network of other uAgents. They are also secure, with cryptographically secured messages and wallets.
griptape
Griptape is a modular Python framework for building AI-powered applications that securely connect to your enterprise data and APIs. It offers developers the ability to maintain control and flexibility at every step. Griptape's core components include Structures (Agents, Pipelines, and Workflows), Tasks, Tools, Memory (Conversation Memory, Task Memory, and Meta Memory), Drivers (Prompt and Embedding Drivers, Vector Store Drivers, Image Generation Drivers, Image Query Drivers, SQL Drivers, Web Scraper Drivers, and Conversation Memory Drivers), Engines (Query Engines, Extraction Engines, Summary Engines, Image Generation Engines, and Image Query Engines), and additional components (Rulesets, Loaders, Artifacts, Chunkers, and Tokenizers). Griptape enables developers to create AI-powered applications with ease and efficiency.
