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Back to deepset-ai/haystack

Open-source alternatives to Haystack

30 open-source projects similar to deepset-ai/haystack, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best Haystack 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-

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  • microsoft/semantic-kernelmicrosoft 的头像

    microsoft/semantic-kernel

    27,262在 GitHub 上查看↗

    Semantic Kernel is an artificial intelligence orchestration framework designed to integrate large language models with existing codebases. It functions as an agentic workflow engine, providing a standardized interface that connects generative models to traditional application logic, data sources, and external tools to automate complex, multi-step business tasks. The platform distinguishes itself through a modular plugin architecture and a planner-based reasoning engine that decomposes high-level goals into executable sequences of functions. By utilizing a connector-based abstraction layer, it

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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

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  • 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

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  • neuml/txtaineuml 的头像

    neuml/txtai

    12,660在 GitHub 上查看↗

    txtai is an artificial intelligence platform designed for building semantic search applications, managing vector storage, and orchestrating language model workflows. It functions as a comprehensive engine for processing unstructured data, enabling the development of autonomous agents and complex content automation pipelines. The platform distinguishes itself through a hybrid indexing architecture that combines dense vector embeddings with relational graph structures, allowing for multi-dimensional retrieval across both semantic meaning and entity relationships. It supports multimodal analysis

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  • llmware-ai/llmwarellmware-ai 的头像

    llmware-ai/llmware

    14,838在 GitHub 上查看↗

    llmware is a Python framework for AI agent orchestration and model management, designed to coordinate multi-model workflows and autonomous agents. It provides a unified model catalog and standardized interface to execute specialized language models for complex research, analysis, and structured data generation. The project distinguishes itself through its heavy emphasis on local execution and quantized inference, allowing models to run on private infrastructure using CPU, GPU, and NPU acceleration via runtimes like ONNX and OpenVino. It features a specialized ability to translate natural lang

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  • 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

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  • 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
  • google/adk-pythongoogle 的头像

    google/adk-python

    17,847在 GitHub 上查看↗

    This project is a Python library designed for building, testing, and deploying autonomous agents that execute complex workflows. It functions as a multi-agent orchestration framework, enabling the creation of systems where specialized agents communicate, delegate tasks, and integrate with external services to complete multi-step automated processes. The framework distinguishes itself by combining deterministic code execution with adaptive language model reasoning. It utilizes structured graph-based logic and state-machine execution to maintain persistent context across multi-turn interactions

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  • botpress/botpressbotpress 的头像

    botpress/botpress

    14,748在 GitHub 上查看↗

    Botpress is a conversational AI builder and LLM agent platform used to design chatbot workflows and orchestrate agents powered by large language models. It provides a framework for managing the entire lifecycle of these agents, from initial creation through to deployment across various production environments. The platform includes a custom integration SDK for developing and publishing third-party connectors that extend agent capabilities. These tools allow for the creation of custom plugins that connect AI agents to external APIs and third-party services. The system supports both visual des

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  • 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

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  • github/gh-awgithub 的头像

    github/gh-aw

    3,280在 GitHub 上查看↗

    gh-aw is a GitHub automation platform and orchestration framework that uses an agentic workflow engine to automate repository management and code reviews. It translates natural language markdown and configuration files into secure, automated task sequences driven by large language models. The system integrates a Model Context Protocol gateway to route calls between AI agents and external tools. It distinguishes itself through a comprehensive security guardrail system that provides sandboxed execution for protocol servers, network egress controls via domain allowlists, and human-in-the-loop ap

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    rowboatlabs/rowboat

    14,974在 GitHub 上查看↗

    Rowboat is an LLM orchestration platform and multimodal AI agent framework. It coordinates large language models with external tools, automated web monitoring, and local data vaults to execute actions and retrieve real-time information. The system operates as a local-first knowledge base, converting meeting notes and emails into a linked markdown knowledge graph. It functions as an automated market intelligence tool that tracks competitors and trends across the web to maintain updated information summaries. The platform covers a broad range of productivity and automation capabilities, includ

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    camel-ai/owl

    19,864在 GitHub 上查看↗

    Owl is a framework for agentic workflow automation and multi-agent orchestration. It functions as a system for coordinating autonomous large language model agents to decompose and execute complex tasks through shared communication and collaborative planning. The project distinguishes itself through a multi-modal toolset for processing images, audio, and video, alongside a synthetic data generator that produces domain-specific datasets using self-instruct and verifier loops. It further incorporates a retrieval-augmented generation pipeline framework that integrates long-term memory and real-ti

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    Parlant is an agentic workflow engine and orchestration framework designed for building conversational AI that adheres to strict behavioral guidelines. It provides a platform for managing multi-turn interactions through state-machine-based logic, allowing developers to define complex, hierarchical conversational flows that can adapt, skip, or revisit steps based on real-time user input. The framework distinguishes itself through its focus on behavioral governance and observability. It enables developers to define precise domain terminology and enforce instruction compliance through prioritize

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  • joaomdmoura/crewaijoaomdmoura 的头像

    joaomdmoura/crewai

    53,752在 GitHub 上查看↗

    CrewAI is a multi-agent orchestration framework and autonomous agent workflow engine. It provides a system for coordinating autonomous AI agents with specific roles and goals to solve complex tasks through collaborative intelligence. The framework distinguishes itself through a collaborative AI agent system that enables multiple language model instances to share intelligence and execute multi-step objectives via role-playing. It incorporates human-in-the-loop mechanisms, allowing for manual review checkpoints to validate decisions and refine outcomes within autonomous execution paths. The pl

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    在 GitHub 上查看↗53,752
  • block/gooseblock 的头像

    block/goose

    49,564在 GitHub 上查看↗

    Goose is an extensible agentic AI platform designed for autonomous task orchestration and developer-centric assistance. It provides a workflow engine that manages complex, multi-step objectives by delegating tasks to specialized subagents, all while maintaining stateful session continuity. The system is built to integrate directly into terminal and coding environments, allowing for automated file manipulation and context-aware interaction. The platform distinguishes itself through a secure, sandboxed runtime environment that enforces granular permission controls and policy-driven guardrails.

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  • 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

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  • mervinpraison/praisonaiMervinPraison 的头像

    MervinPraison/PraisonAI

    5,592在 GitHub 上查看↗

    PraisonAI is an autonomous AI agent platform that coordinates multiple LLM-powered agents for research, planning, and execution of complex workflows. It functions as a multi-agent orchestration framework, a workflow builder, and a Model Context Protocol server, while also providing retrieval-augmented generation through vector knowledge bases. Agents can interact via CLI, web, or standardized protocols with sandboxed code execution. The platform distinguishes itself with a rich set of agent communication protocols, including A2A, REST, WebSocket, voice and telephony integration, and MCP, allo

    Pythonagentsaiai-agent-framework
    在 GitHub 上查看↗5,592
  • weaviate/verbaweaviate 的头像

    weaviate/Verba

    7,715在 GitHub 上查看↗

    Verba is a retrieval-augmented generation interface and chatbot that uses Weaviate to provide factual answers based on private datasets. It functions as a vector database knowledge base, combining a hybrid search engine with an orchestration interface to connect various large language model providers and embedding services. The system differentiates itself through a RAG pipeline manager for adjusting text chunking rules and retrieval settings, alongside a 3D vector space visualization tool for analyzing the spatial organization and clustering of high-dimensional embeddings. It employs a modul

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    在 GitHub 上查看↗7,715
  • yoheinakajima/babyagiyoheinakajima 的头像

    yoheinakajima/babyagi

    22,309在 GitHub 上查看↗

    This is a framework for building autonomous agents that use large language models to plan, execute, and refine their own tasks. It functions as an autonomous task orchestrator and agent framework, utilizing a function registry to manage the code-based tools and plugins the agents use to achieve complex goals. The system is distinguished by its ability to perform autonomous code generation, where the agent analyzes requirements to write new reusable functions on the fly. It employs a recursive loop-based planning model to continuously update its goal list and refine its performance based on ex

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    在 GitHub 上查看↗22,309
  • modelscope/agentscopemodelscope 的头像

    modelscope/agentscope

    26,928在 GitHub 上查看↗

    AgentScope is a multi-agent framework and orchestration platform designed for building and coordinating teams of language model agents. It provides a system for managing multiple agents that collaborate to solve complex tasks through structured communication and state sharing. The project distinguishes itself with a focus on production-ready deployment and security, featuring a multi-tenant hosting service that ensures session isolation between different users. It includes a sandboxed tool execution environment and fine-grained permission controls to manage how agents access system resources

    Python
    在 GitHub 上查看↗26,928
  • truefoundry/cognitatruefoundry 的头像

    truefoundry/cognita

    4,317在 GitHub 上查看↗

    Cognita is a retrieval augmented generation orchestration framework used to build pipelines that connect document stores and language models to provide grounded answers. It functions as a document ingestion pipeline and a vector database integrator, managing the process of loading, parsing, and indexing files into a searchable knowledge base. The system includes a language model gateway proxy that provides a unified API to interact with multiple different model providers. This routing layer decouples the application from specific vendors, allowing requests to be proxied through a provider-agn

    Pythonagentaiapplication
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  • coze-dev/coze-studiocoze-dev 的头像

    coze-dev/coze-studio

    19,900在 GitHub 上查看↗

    Coze Studio is a development platform for building intelligent agents and conversational applications. It provides a visual environment where users construct agents by linking workflows, knowledge bases, and custom prompts to automate complex tasks. The system functions as a central hub for managing AI model services, allowing developers to connect various providers to serve as the intelligence layer for their applications. The platform distinguishes itself through a node-based workflow orchestrator that enables the design of automated logic sequences on a visual canvas. It includes a modular

    TypeScriptagentagent-platformai-plugins
    在 GitHub 上查看↗19,900
  • microsoft/promptflowmicrosoft 的头像

    microsoft/promptflow

    11,165在 GitHub 上查看↗

    Promptflow is a development framework and orchestrator for building applications powered by large language models. It functions as a suite of tools for designing, orchestrating, and deploying AI workflows by linking prompts, custom Python code, and language models into executable sequences. The project is distinguished by a visual AI workflow designer that allows for the creation of directed acyclic graphs of logic nodes. It provides a dedicated prompt engineering environment for versioning and comparing templates, alongside stateful execution tracing to record function calls and variable val

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  • kilo-org/kilocodeKilo-Org 的头像

    Kilo-Org/kilocode

    15,616在 GitHub 上查看↗

    Kilocode is an autonomous engineering platform designed to orchestrate AI agents for complex software development tasks. It functions as a comprehensive system for automating coding, testing, and repository management by integrating directly with your codebase and terminal. The platform provides a unified gateway for model orchestration, allowing for the management of agentic workflows, event-driven automation, and persistent session state across distributed development environments. The platform distinguishes itself through its federated task management and policy-based access control, which

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    在 GitHub 上查看↗15,616
  • comet-ml/opikcomet-ml 的头像

    comet-ml/opik

    17,787在 GitHub 上查看↗

    Opik is an observability and evaluation platform designed for generative AI applications and agentic workflows. It provides a centralized environment for tracing execution flows, managing prompt templates, and monitoring production performance, allowing teams to gain visibility into complex model interactions and tool usage without requiring manual application code changes. The platform distinguishes itself through its integrated approach to the AI development lifecycle, combining distributed trace instrumentation with automated evaluation frameworks. It supports model-as-a-judge scoring, syn

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    bytedance/deer-flow

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    Deer-flow is an autonomous agent orchestration platform designed to manage multi-step workflows where AI agents reason, plan, and execute tasks. It functions as a development framework for building agents that utilize various large language models to solve complex problems through structured, sequential, and parallel reasoning. The platform distinguishes itself through a secure, sandboxed execution engine that isolates generated code and system operations from the host environment. This architecture allows agents to safely test and validate solutions within ephemeral containers, ensuring that

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    在 GitHub 上查看↗71,310
  • huggingface/transformershuggingface 的头像

    huggingface/transformers

    161,630在 GitHub 上查看↗

    Transformers is a comprehensive library for machine learning that provides a unified interface for training, fine-tuning, and deploying transformer-based models. It supports a wide range of tasks, including text classification, language modeling, question answering, and sequence-to-sequence translation, while offering specialized architectures for both text and vision processing. The framework includes tools for managing the entire model lifecycle, from data preprocessing and tokenization to distributed training and inference. The library features extensive support for model optimization and

    Pythonaudiodeep-learningdeepseek
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  • explosion/spacyexplosion 的头像

    explosion/spaCy

    33,688在 GitHub 上查看↗

    spaCy is a Python natural language processing framework designed for industrial-scale text processing. It converts raw text into structured data for machine learning pipelines through a combination of statistical language model trainers, transformer-based text processors, and syntactic dependency parsers. The project enables the integration of pretrained transformer architectures to perform complex linguistic analysis and multi-task learning. It also provides a specialized system for neural named entity recognition to identify and categorize key entities within text. The framework covers a b

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