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Back to microsoft/semantic-kernel

Open-source alternatives to Semantic Kernel

30 open-source projects similar to microsoft/semantic-kernel, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best Semantic Kernel alternative.

  • stanfordnlp/dspystanfordnlp 的头像

    stanfordnlp/dspy

    35,325在 GitHub 上查看↗

    DSPy is a declarative programming framework designed for building complex language model applications. It treats model interactions as modular, composable programs, allowing developers to define task logic through typed class schemas rather than relying on manually written prompts. By organizing workflows into hierarchical, reusable Python objects, the framework enables the construction of sophisticated AI systems that manage state and execution flow independently. The framework distinguishes itself through an automated optimization engine that iteratively refines prompt instructions and few-

    Python
    在 GitHub 上查看↗35,325
  • deepset-ai/haystackdeepset-ai 的头像

    deepset-ai/haystack

    24,253在 GitHub 上查看↗

    Haystack is an orchestration framework designed for building complex search and generative AI pipelines. It functions as an agentic workflow engine, enabling the construction of automated sequences that allow AI agents to perform multi-step reasoning and data analysis. The framework utilizes a modular, component-based architecture that connects processing steps into directed acyclic graphs. By employing a provider-agnostic integration layer, it decouples core logic from specific external AI services and vector databases, allowing for the flexible exchange of underlying technologies. This desi

    MDXagentagentsai
    在 GitHub 上查看↗24,253
  • langgenius/difylanggenius 的头像

    langgenius/dify

    145,458在 GitHub 上查看↗

    Dify is an open-source platform for building, orchestrating, and deploying generative AI applications and autonomous agents. It provides a visual development environment that allows users to design complex, multi-step logic chains and conversational flows, which can then be published as APIs, web interfaces, or embedded widgets. The platform acts as a centralized infrastructure layer, managing model connections, prompt templates, and knowledge retrieval to support scalable AI-powered services. What distinguishes the platform is its focus on stateful application design and workflow orchestrati

    TypeScriptagentagentic-aiagentic-framework
    在 GitHub 上查看↗145,458

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  • langchain-ai/langchainlangchain-ai 的头像

    langchain-ai/langchain

    139,458在 GitHub 上查看↗

    LangChain is an orchestration framework designed for building, managing, and deploying applications powered by large language models. It provides a unified integration layer that normalizes disparate model provider APIs into a consistent set of primitives, enabling developers to build complex, multi-step AI workflows that manage state, memory, and tool execution. The project distinguishes itself through a durable execution runtime that maintains persistent state across long-running processes by checkpointing progress to external storage. It models agent workflows as directed graphs, allowing

    Pythonagentsaiai-agents
    在 GitHub 上查看↗139,458
  • hwchase17/langchainhwchase17 的头像

    hwchase17/langchain

    139,533在 GitHub 上查看↗

    LangChain is a framework for building applications that chain large language models with external data sources and third-party tools. It serves as an orchestrator for autonomous agents that use language models to plan and execute multi-step tasks, while providing a toolkit for linking interoperable AI components into sequences to prototype complex model behaviors. The project provides a model agnostic integration layer, allowing users to switch between different language model providers using a standardized interface. It also includes tools for observability and evaluation to track the perfor

    Python
    在 GitHub 上查看↗139,533
  • qwenlm/qwen-agentQwenLM 的头像

    QwenLM/Qwen-Agent

    13,322在 GitHub 上查看↗

    Qwen-Agent is a development framework for building autonomous software applications that leverage large language models to plan, reason, and execute complex tasks. It functions as an orchestration engine that enables models to interact with external APIs, manage persistent memory, and maintain context across multi-step workflows. The framework distinguishes itself through a multi-agent collaboration platform that allows independent agent instances to exchange structured messages and delegate sub-tasks to one another. By utilizing iterative reasoning loops and dynamic prompt injection, the sys

    Python
    在 GitHub 上查看↗13,322
  • langchain-ai/langgraphlangchain-ai 的头像

    langchain-ai/langgraph

    34,925在 GitHub 上查看↗

    LangGraph is a framework for building stateful, multi-step agentic workflows by modeling application logic as a directed graph. It provides a runtime environment where complex tasks are orchestrated through interconnected nodes and edges, allowing developers to manage state transitions, persistent memory, and control flow across long-running automated processes. The platform distinguishes itself through its native support for human-in-the-loop automation, enabling developers to define breakpoints that pause execution for manual review, modification, or approval. It also features checkpoint-ba

    Pythonagentsaiai-agents
    在 GitHub 上查看↗34,925
  • openai/swarmopenai 的头像

    openai/swarm

    21,640在 GitHub 上查看↗

    Swarm is a framework for building conversational systems that coordinate multi-agent workflows. It functions as an orchestration engine that manages persistent, multi-turn dialogues by routing tasks between specialized agents and executing local functions. The system is designed to handle complex, multi-step processes by maintaining shared state and context across agent interactions. The framework distinguishes itself through its approach to dynamic task delegation and execution control. It enables agents to hand off tasks to one another by returning agent objects, allowing for modular, domai

    Python
    在 GitHub 上查看↗21,640
  • mastra-ai/mastramastra-ai 的头像

    mastra-ai/mastra

    21,221在 GitHub 上查看↗

    Mastra is an orchestration framework designed for building, deploying, and managing autonomous AI agents and multi-agent systems. It provides a comprehensive suite of primitives for creating resilient AI applications, including durable workflow orchestration, event-driven agent loops, and semantic memory management. By integrating these core components, the platform enables developers to build complex, multi-step processes that can reason about goals and execute tasks without manual intervention. The framework distinguishes itself through its focus on observability and secure, isolated execut

    TypeScriptagentsaichatbots
    在 GitHub 上查看↗21,221
  • assafelovic/gpt-researcherassafelovic 的头像

    assafelovic/gpt-researcher

    27,739在 GitHub 上查看↗

    GPT Researcher is an autonomous agent framework designed to automate the process of gathering, synthesizing, and documenting information from diverse web and local sources. It functions as a research-oriented execution environment that orchestrates specialized agents to perform complex, multi-branch research tasks, transforming raw data into structured, factual, and cited reports. The project distinguishes itself through a graph-based orchestration layer that manages state transitions and information flow between specialized agents. It employs recursive tree-search execution to explore comple

    Pythonagentaiautomation
    在 GitHub 上查看↗27,739
  • camel-ai/camelcamel-ai 的头像

    camel-ai/camel

    17,253在 GitHub 上查看↗

    This project is a comprehensive framework for building and managing autonomous agent systems. It provides a unified architecture for orchestrating multi-agent societies, where specialized agents collaborate through roleplay to decompose and solve complex tasks. The system integrates language models with external environments, enabling agents to perform real-world actions through a standardized tool-calling abstraction layer. The framework distinguishes itself through its focus on iterative reasoning and data reliability. It employs automated feedback loops to refine agent outputs and self-eva

    Pythonagentai-societiesartificial-intelligence
    在 GitHub 上查看↗17,253
  • prefecthq/marvinPrefectHQ 的头像

    PrefectHQ/marvin

    6,170在 GitHub 上查看↗

    an ambient intelligence library

    Python
    在 GitHub 上查看↗6,170
  • tmc/langchaingotmc 的头像

    tmc/langchaingo

    9,416在 GitHub 上查看↗

    langchaingo is an LLM application framework for Go designed for building language model-powered applications and autonomous agents. It serves as an orchestration library and tool integration framework that allows developers to link prompt sequences and model calls into complex, multi-step workflows. The project provides a toolkit for implementing retrieval-augmented generation pipelines by processing unstructured documents and retrieving relevant context via vector search. It includes a dedicated integration layer for indexing high-dimensional embeddings and performing similarity searches acr

    Go
    在 GitHub 上查看↗9,416
  • mudler/localaimudler 的头像

    mudler/LocalAI

    46,889在 GitHub 上查看↗

    LocalAI is a self-hosted inference server that enables the execution of machine learning models directly on local hardware. By providing a unified interface for text, image, and audio processing, it allows users to maintain full control over data privacy and infrastructure costs while eliminating dependencies on external network services. The platform functions as an API gateway that mimics standard cloud-based artificial intelligence interfaces, allowing existing applications to integrate local models as drop-in replacements. It utilizes a container-based architecture to package runtimes and

    Goaiapiaudio-generation
    在 GitHub 上查看↗46,889
  • huggingface/smolagentshuggingface 的头像

    huggingface/smolagents

    27,885在 GitHub 上查看↗

    This framework provides a development toolkit for building autonomous agents that utilize language models to solve complex, non-deterministic tasks. Its core design centers on a code-executing architecture where agents generate and run Python code snippets to perform logic, data manipulation, and tool interactions. By moving beyond structured data formats, the system enables agents to manage program flow and object state through iterative reasoning cycles. The project distinguishes itself through its focus on code-based agent implementation and secure execution environments. Developers can ch

    Python
    在 GitHub 上查看↗27,885
  • significant-gravitas/autogptSignificant-Gravitas 的头像

    Significant-Gravitas/AutoGPT

    184,973在 GitHub 上查看↗

    AutoGPT is an orchestration platform designed for building, managing, and deploying autonomous agents. It provides a visual canvas-based environment where users can assemble agents by connecting modular blocks that represent actions, data flows, and conditional logic. The platform supports the entire agent lifecycle, including task scheduling, execution monitoring, and configuration management, while offering a marketplace for discovering and sharing community-built workflows. The project includes a legacy framework for command-line agent execution and an extensible component system for devel

    Pythonaiartificial-intelligenceautonomous-agents
    在 GitHub 上查看↗184,973
  • flowiseai/flowiseFlowiseAI 的头像

    FlowiseAI/Flowise

    53,641在 GitHub 上查看↗

    Flowise is a low-code platform designed for building and deploying complex language model workflows through a visual, node-based interface. It functions as an orchestrator for autonomous multi-agent systems, allowing users to construct conversational pipelines by connecting language models, memory stores, and external tools on a drag-and-drop canvas. The platform distinguishes itself through its support for sophisticated agentic patterns, including supervisor-worker delegation and iterative reasoning strategies. Users can design directed acyclic graphs to manage conditional branching, state p

    TypeScriptagentic-aiagentic-workflowagents
    在 GitHub 上查看↗53,641
  • letta-ai/lettaletta-ai 的头像

    letta-ai/letta

    21,168在 GitHub 上查看↗

    Letta is a framework for building, deploying, and managing autonomous AI agents that maintain persistent state across long-term interactions. It provides a comprehensive suite of primitives for defining agents with configurable personas, modular memory blocks, and tool-use capabilities, enabling them to retain user preferences and conversation history over extended sessions. The platform distinguishes itself through its advanced memory management and orchestration capabilities. It allows agents to autonomously update their own memory, perform retrieval-augmented generation, and coordinate com

    Pythonaiai-agentsllm
    在 GitHub 上查看↗21,168
  • langroid/langroidlangroid 的头像

    langroid/langroid

    3,894在 GitHub 上查看↗

    Langroid is a multi-agent orchestration framework and tool integration suite designed for building complex AI applications. It serves as a multi-modal integration layer that connects diverse local and remote language models with an agentic retrieval-augmented generation system. The project distinguishes itself through a collaborative message-exchange paradigm, allowing specialized agents to delegate tasks hierarchically and coordinate via structured communication. It features an advanced state management system for conversational AI, including the ability to rewind and prune conversation hist

    Pythonagentsaichatgpt
    在 GitHub 上查看↗3,894
  • langflow-ai/langflowlangflow-ai 的头像

    langflow-ai/langflow

    149,735在 GitHub 上查看↗

    Langflow is a visual interface for building and orchestrating workflows, allowing users to construct complex systems through a drag-and-drop canvas. It provides tools for managing autonomous agents, configuring memory settings, and integrating custom code-based components. Users can organize their work into projects, track component versions, and group multiple elements into reusable units. The platform includes an interactive playground for testing workflows, monitoring tool calls, and debugging chat sessions with unique identifiers. Once built, workflows can be executed via RESTful or OpenA

    Pythonagentschatgptgenerative-ai
    在 GitHub 上查看↗149,735
  • microsoft/autogenmicrosoft 的头像

    microsoft/autogen

    59,002在 GitHub 上查看↗

    This framework provides a development environment for building collaborative systems where autonomous agents interact to solve complex tasks through conversational workflows. It functions as a conversational workflow engine and event-driven runtime, coordinating multi-step processes by translating high-level goals into structured dialogue sequences between specialized agents. The system distinguishes itself through its message-passing orchestration, which manages state transitions and task delegation between independent participants. It supports dynamic conversation state management to provid

    Pythonagenticagentic-agiagents
    在 GitHub 上查看↗59,002
  • cloudwego/einocloudwego 的头像

    cloudwego/eino

    9,675在 GitHub 上查看↗

    Eino is an AI agent development kit and LLM application framework designed for building autonomous agents and orchestrating complex language model workflows. It serves as a multi-agent orchestration engine and workflow orchestrator, providing a graph-based execution model to route data between models, tools, and retrievers. The framework distinguishes itself through a robust set of multi-agent coordination patterns, including supervisor-led management, sequential flows, and autonomous reasoning loops like ReAct. It features advanced agent execution controls such as active turn preemption, che

    Goaiai-applicationai-framework
    在 GitHub 上查看↗9,675
  • stangirard/quivrStanGirard 的头像

    StanGirard/quivr

    39,167在 GitHub 上查看↗

    Quivr is a framework for building retrieval-augmented generation pipelines that connect large language models to custom knowledge bases. It serves as a generative AI integration layer that abstracts the process of transforming diverse document sources into searchable context for AI responses. The project orchestrates the end-to-end flow between document ingestion, vector storage management, and model provider interfaces. It features a vector-store-agnostic retrieval system and a modular API layer that allows for flexible switching between different generative model providers. The system cove

    Python
    在 GitHub 上查看↗39,167
  • openbmb/chatdevOpenBMB 的头像

    OpenBMB/ChatDev

    33,427在 GitHub 上查看↗

    ChatDev is an automated software engineering platform that orchestrates the end-to-end development lifecycle through a multi-agent framework. It functions as a programmable engine that coordinates specialized autonomous agents to handle design, coding, testing, and documentation tasks by transitioning through predefined phases of a software project. The system distinguishes itself by using role-based agent specialization to simulate a professional engineering team, assigning distinct personas and knowledge bases to individual agents. It employs prompt-driven task decomposition to break high-l

    Python
    在 GitHub 上查看↗33,427
  • e2b-dev/awesome-ai-agentse2b-dev 的头像

    e2b-dev/awesome-ai-agents

    25,903在 GitHub 上查看↗

    This project is a curated repository and directory focused on the artificial intelligence agent ecosystem. It serves as a centralized knowledge base for developers and researchers to discover frameworks, platforms, and autonomous software entities designed for reasoning, planning, and executing complex tasks. The directory distinguishes itself through a community-driven curation model, where contributors maintain and update the collection via a distributed version control system. This collaborative approach ensures that the index remains current with the latest academic resources, open-source

    agentaiartificial-intelligence
    在 GitHub 上查看↗25,903
  • badboysm890/claraversebadboysm890 的头像

    badboysm890/ClaraVerse

    3,833在 GitHub 上查看↗

    ClaraVerse is a self-hosted orchestration platform for deploying and managing local language models, autonomous agents, and automated workflows on private infrastructure. It functions as a containerized backend manager that orchestrates services, databases, and model providers within local containers to maintain data sovereignty. The platform features a visual workflow builder with a drag-and-drop interface for designing complex parallel task sequences. It utilizes a multi-model abstraction layer to normalize interactions across diverse local and remote AI endpoints and includes a retrieval a

    Go
    在 GitHub 上查看↗3,833
  • x-plug/mobileagentX-PLUG 的头像

    X-PLUG/MobileAgent

    7,218在 GitHub 上查看↗

    MobileAgent is an LLM-powered mobile automation agent and framework designed to navigate mobile user interfaces and execute multi-step tasks. It functions as a device interface automation system that maps semantic commands to screen coordinates to perform input events across mobile operating systems. The project operates as a cross-app workflow orchestrator, switching between native on-screen interface actions and external API tools to complete sophisticated operations. It includes a visual grounding system that analyzes screenshots and interface metadata to identify elements and validate the

    Pythonagentandroidapp
    在 GitHub 上查看↗7,218
  • danny-avila/librechatdanny-avila 的头像

    danny-avila/LibreChat

    39,276在 GitHub 上查看↗

    LibreChat is an artificial intelligence orchestration platform that provides a unified interface for interacting with multiple language models. It functions as a centralized workspace where users can switch between different intelligence engines, manage complex conversational workflows, and maintain persistent memory across sessions through a vector-database-backed storage system. The platform distinguishes itself through an extensible agent framework that supports autonomous task execution and the integration of external tools. It features a secure, containerized environment for executing co

    TypeScriptaianthropicartifacts
    在 GitHub 上查看↗39,276
  • automatic1111/stable-diffusion-webuiAUTOMATIC1111 的头像

    AUTOMATIC1111/stable-diffusion-webui

    163,743在 GitHub 上查看↗

    Stable Diffusion Web UI is a browser-based interface designed for managing text-to-image generation tasks. It provides a centralized dashboard for controlling generative processes, including native support for multi-stage model architectures to facilitate high-quality image refinement. The platform distinguishes itself through granular control over the generation process, offering tools for precise parameter management and advanced prompt engineering. Users can customize generation styles and capabilities by integrating external model-extension formats, such as textual inversions, low-rank ad

    Pythonaiai-artdeep-learning
    在 GitHub 上查看↗163,743
  • paddlepaddle/paddlenlpPaddlePaddle 的头像

    PaddlePaddle/PaddleNLP

    12,953在 GitHub 上查看↗

    PaddleNLP is a development library and toolkit for training, fine-tuning, and deploying large and small language models using the PaddlePaddle framework. It provides a comprehensive suite for the entire natural language processing lifecycle, from model development to high-performance inference. The project features a standardized model zoo for loading and managing pre-trained models and tokenizers through a unified interface. It distinguishes itself with a specialized model compression framework that reduces memory footprints via weight precision conversion and lossless size optimization, alo

    Python
    在 GitHub 上查看↗12,953