awesome-repositories.com
Blog
MCP
awesome-repositories.com

Discover the best open-source repositories with AI-powered search.

ExploreCurated searchesOpen-source alternativesSelf-hosted softwareBlogSitemap
ProjectMCP serverAboutHow we rankPress
LegalPrivacyTerms
© 2026 Bringes Technology SRL·VAT RO45896025·hello@awesome-repositories.com
Back to floomai/floom

Open-source alternatives to Floom

30 open-source projects similar to floomai/floom, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best Floom alternative.

  • microsoft/semantic-kernelmicrosoft avatar

    microsoft/semantic-kernel

    27,262View on GitHub↗

    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

    C#aiartificial-intelligencellm
    View on GitHub↗27,262
  • stanfordnlp/dspystanfordnlp avatar

    stanfordnlp/dspy

    35,325View on GitHub↗

    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
    View on GitHub↗35,325
  • deepset-ai/haystackdeepset-ai avatar

    deepset-ai/haystack

    24,253View on GitHub↗

    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
    View on GitHub↗24,253

AI search

Explore more awesome repositories

Describe what you need in plain English — the AI ranks thousands of curated open-source projects by relevance.

Find more with AI search
  • hwchase17/langchainhwchase17 avatar

    hwchase17/langchain

    139,533View on GitHub↗

    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
    View on GitHub↗139,533
  • paddlepaddle/paddlenlpPaddlePaddle avatar

    PaddlePaddle/PaddleNLP

    12,953View on GitHub↗

    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
    View on GitHub↗12,953
  • datajuicer/data-juicerdatajuicer avatar

    datajuicer/data-juicer

    6,574View on GitHub↗

    Data-Juicer is an open-source framework for cleaning, filtering, deduplicating, and transforming multimodal datasets to prepare them for training large language and vision models. It functions as a distributed data pipeline engine that runs processing jobs across Ray clusters, handling billions of samples with automatic operator fusion and adaptive parallelism. The framework provides a library of operators that leverage large language models for semantic extraction, filtering, and data synthesis within processing pipelines. The project distinguishes itself through a YAML-based data recipe sys

    Pythondatadata-analysisdata-pipeline
    View on GitHub↗6,574
  • agentops-ai/agentopsAgentOps-AI avatar

    AgentOps-AI/agentops

    5,654View on GitHub↗

    AgentOps is an observability platform and developer toolkit for monitoring the execution, performance, and reliability of autonomous agents powered by large language models. It serves as a system for tracking AI agent behavior, debugging complex workflows, and benchmarking model performance. The platform is distinguished by its ability to visualize multi-agent workflows through execution path graphing and session replays. It provides specific tools for calculating financial spend across various language model providers and supports a self-hosted observability stack for users who require full

    Python
    View on GitHub↗5,654
  • agentlabs-inc/agentlabsagentlabs-inc avatar

    agentlabs-inc/agentlabs

    550View on GitHub↗

    Universal AI Agent Frontend. Build your backend we handle the rest.

    TypeScript
    View on GitHub↗550
  • agent-field/agentfieldAgent-Field avatar

    Agent-Field/agentfield

    702View on GitHub↗
    Goagentagent-authagent-authentication
    View on GitHub↗702
  • agentsmesh/agentsmeshAgentsMesh avatar

    AgentsMesh/AgentsMesh

    2,218View on GitHub↗

    The AI Agent Workforce Platform. Run a hundred AI coding agents across your own machines — schedule, isolate, and steer them all from one console.

    Go
    View on GitHub↗2,218
  • agi-merge/waggle-danceagi-merge avatar

    agi-merge/waggle-dance

    172View on GitHub↗

    Knowledge work automation with AI agents

    TypeScript
    View on GitHub↗172
  • agiresearch/aiosagiresearch avatar

    agiresearch/AIOS

    5,168View on GitHub↗

    AIOS is an LLM agent operating system and orchestration kernel designed to manage memory, resource scheduling, and tool execution for multiple autonomous AI agents. It serves as a comprehensive framework for developing and deploying agents, featuring a dedicated resource manager that coordinates model backends, GPU memory, and isolated kernel instances. The system distinguishes itself through a semantic memory engine that uses vector search and autonomous clustering for long-term knowledge management, and a semantic file system that allows users to control computer files and system operations

    Python
    View on GitHub↗5,168
  • agno-agi/agnoagno-agi avatar

    agno-agi/agno

    40,717View on GitHub↗

    Agno is an agent operating system designed to manage the lifecycle, tool execution, and persistent state of autonomous agents across distributed infrastructure. It provides a unified runtime environment that wraps diverse agent frameworks into a consistent, interoperable protocol, allowing developers to build and deploy complex multi-agent systems that coordinate tasks and delegate sub-processes. The platform distinguishes itself through a robust governance and orchestration layer that includes human-in-the-loop approval gates, role-based access control, and a centralized API gateway. It feat

    Pythonagentsaiai-agents
    View on GitHub↗40,717
  • agno-ai/agnoA

    agno-ai/agno

    0View on GitHub↗
    View on GitHub↗0
  • agentsmd/agents.mdagentsmd avatar

    agentsmd/agents.md

    22,264View on GitHub↗

    Agents.md is a configuration framework designed to standardize how AI coding assistants interact with a repository. It provides a structured format for defining project context, behavioral guidelines, and operational instructions, ensuring that AI tools maintain consistency and adhere to project-specific standards throughout the development process. The system distinguishes itself through a hierarchical configuration approach, allowing developers to define settings that inherit and override instructions across different subdirectories. By utilizing markdown-based files, it enables the injecti

    TypeScript
    View on GitHub↗22,264
  • agenta-ai/agentaAgenta-AI avatar

    Agenta-AI/agenta

    3,860View on GitHub↗

    Agenta is a Prompt Ops lifecycle manager and prompt management platform that decouples prompt engineering from application code. It serves as a centralized system for developing, versioning, and deploying prompt templates and model configurations across different environments. The platform functions as an AI agent orchestrator with a visual interface for building agent workflows and connecting models to external tools. It further acts as an evaluation framework and observability tool, utilizing OpenTelemetry to capture execution traces, monitor latency, and track token costs. The system cove

    TypeScriptagentsevaluationllm-as-a-judge
    View on GitHub↗3,860
  • alaeddine-13/thinkgptalaeddine-13 avatar

    alaeddine-13/thinkgpt

    1,583View on GitHub↗

    Agent techniques to augment your LLM and push it beyong its limits

    Python
    View on GitHub↗1,583
  • aiwaves-cn/agentsaiwaves-cn avatar

    aiwaves-cn/agents

    5,932View on GitHub↗

    This is an LLM agent framework and symbolic learning system designed for building self-evolving autonomous agents. It functions as a computational graph orchestrator that organizes agent interactions and tool sequences as a trainable graph of nodes. The framework focuses on data-centric agent optimization, allowing agent pipelines and prompts to be upgraded through data-driven training rather than manual engineering. It utilizes a symbolic learning process that applies language-based loss and textual reflections to refine the operational logic and symbolic components of an agent. The system

    Pythonautonomous-agentslanguage-modelllm
    View on GitHub↗5,932
  • alipay/agentuniverseA

    alipay/agentUniverse

    0View on GitHub↗
    View on GitHub↗0
  • all-hands-ai/openhandsAll-Hands-AI avatar

    All-Hands-AI/OpenHands

    77,468View on GitHub↗

    OpenHands is an autonomous AI software engineer and coding assistant designed to execute software engineering tasks by interacting directly with codebases and development environments. It functions as a platform for running AI agents that can write code and manage files to automate complex development workflows. The system distinguishes itself through a container-based execution environment that isolates agent actions within a sandboxed Linux environment. It employs an autonomous agent loop of observation, planning, and action, supported by a standardized communication protocol that allows it

    Python
    View on GitHub↗77,468
  • arize-ai/phoenixArize-ai avatar

    Arize-ai/phoenix

    8,605View on GitHub↗

    Arize Phoenix is an LLM observability platform and evaluation framework designed to capture execution traces and monitor large language model applications. It serves as a prompt management system for versioning and testing templates, and as a self-hosted AI operations infrastructure for managing telemetry and experiments. The platform differentiates itself through a specialized embedding visualization tool used to detect data drift and optimize vector search. It provides a comprehensive evaluation suite that utilizes judge-based evaluators and ground-truth datasets to score model outputs, and

    Jupyter Notebookagentsai-monitoringai-observability
    View on GitHub↗8,605
  • ashishpatel26/500-ai-agents-projectsashishpatel26 avatar

    ashishpatel26/500-AI-Agents-Projects

    32,572View on GitHub↗

    This project is a curated directory and educational resource focused on the development and implementation of autonomous AI agents. It serves as a comprehensive knowledge repository that organizes practical use cases and open-source projects into a structured taxonomy, helping developers explore how intelligent systems can be applied across diverse industry sectors. The repository distinguishes itself through a community-driven approach that maps diverse agentic workflows to a common schema, facilitating cross-framework evaluation. By providing modular educational scaffolding, it guides users

    Pythonai-agentsgenai
    View on GitHub↗32,572
  • askbudi/roundtableaskbudi avatar

    askbudi/roundtable

    114View on GitHub↗

    Zero-configuration MCP server that unifies multiple AI coding assistants (Codex, Claude Code, Cursor, Gemini) through intelligent auto-discovery and standardized interface

    Pythonclaude-codecursorgemini-cli
    View on GitHub↗114
  • assafelovic/gpt-researcherassafelovic avatar

    assafelovic/gpt-researcher

    27,739View on GitHub↗

    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
    View on GitHub↗27,739
  • awslabs/multi-agent-orchestratorA

    awslabs/multi-agent-orchestrator

    0View on GitHub↗
    View on GitHub↗0
  • axar-ai/axaraxar-ai avatar

    axar-ai/axar

    162View on GitHub↗

    Minimal typescript agent framework that keeps it simple and gives you control - no BS

    TypeScript
    View on GitHub↗162
  • badboysm890/claraversebadboysm890 avatar

    badboysm890/ClaraVerse

    3,833View on GitHub↗

    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
    View on GitHub↗3,833
  • bizarrecake/fmr.aiB

    BizarreCake/fmr.ai

    0View on GitHub↗
    View on GitHub↗0
  • block/gooseblock avatar

    block/goose

    49,564View on GitHub↗

    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.

    Rustmcp
    View on GitHub↗49,564
  • agentskills/agentskillsagentskills avatar

    agentskills/agentskills

    10,303View on GitHub↗

    Agent Skills is a framework for bundling executable scripts and metadata to extend the capabilities and tool-use of language model agents. It provides a standardized directory structure for packaging specialized workflows, technical instructions, and portable agent capabilities for distribution across different AI platforms. The project features a tool optimization suite used to refine skill triggers and evaluate the reliability of agent-activated capabilities. It includes a context-aware knowledge manager that organizes technical references into a hierarchy, loading them on demand to reduce

    Pythonagent-skills
    View on GitHub↗10,303