Open-source alternatives to Dify

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-

The agent-framework is an LLM agent orchestration framework and multi-agent workflow engine designed for building autonomous AI agents. It provides a tool integration layer for binding external functions, APIs, and sandboxed code as executable tools for language models. The framework distinguishes itself through a graph-based system for designing sequential and parallel task flows, featuring state management and checkpointing for long-running processes. It implements comprehensive conversational state management and an observability suite that uses telemetry to trace execution flows and monit

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

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

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

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

Hermes-agent is an autonomous AI agent framework and runtime designed to execute complex tasks and synthesize new skills from execution traces. It includes a provider-agnostic gateway for routing requests across multiple model backends and a serverless runtime that suspends idle agent instances and resumes them on demand across containers and virtual machines. The project provides a desktop automation toolset that controls native GUI workflows on Linux by querying accessibility APIs and injecting input events. It further distinguishes itself with the ability to generate procedural skills from

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

Langchain-Chatchat is a system for building retrieval-augmented generation applications and autonomous AI agents. It integrates a knowledge base management system and an agent framework to enable language models to interact with private documents and execute multi-step tasks through external tools. The platform supports local deployment of language models on private infrastructure to operate without an internet connection. It includes a multimodal AI platform that combines vision models for image analysis with text-to-image generation capabilities. The system provides a web-based conversatio

This project is a Python framework for building autonomous, event-driven agent systems. It provides a unified runtime for orchestrating multi-agent workflows, managing persistent conversation state, and executing code within secure, isolated sandbox environments. The framework is designed to handle complex task delegation, allowing agents to invoke other agents as tools while maintaining context across multi-turn interactions. The framework distinguishes itself through its deep integration with the Model Context Protocol, enabling agents to connect to external data sources and remote services

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

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

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

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

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

MaxKB is a self-hosted retrieval-augmented generation platform designed to connect internal document repositories with large language models. It functions as an enterprise knowledge management system that enables organizations to query private data through a conversational interface, providing automated responses based on uploaded files and internal business information. The platform distinguishes itself by normalizing diverse data sources into a unified index, which is then processed through chunking and vector-based retrieval to ensure context-aware results. It manages session state and pro

This project is an LLM agent framework and orchestration engine designed for building autonomous agents that reason, utilize tools, and execute multi-step plans. It provides a system for implementing the ReAct pattern, which interleaves reasoning and action cycles to solve complex problems through iterative observation and self-correction. The framework includes a tool integration layer that connects language models to external functions and APIs using structured schemas and embedding-based routing. It also features a memory management system to persist conversation history and user preferenc

Chainlit is a Python framework designed for building and deploying interactive, stateful conversational AI interfaces. It provides a backend-driven platform that connects language models and agent frameworks to a web-based chat frontend, managing the complexities of session state, message history, and real-time communication. The framework distinguishes itself by offering a component-based UI builder that allows developers to inject interactive widgets, rich media, and data visualizations directly into the chat stream. It supports the visualization of complex agent workflows, enabling users t

This project is an AI-powered IDE extension and LLM coding assistant that provides a conversational interface for generating, refactoring, and debugging code. It functions as an AI agent framework and a Model Context Protocol client, connecting AI models to external data sources and tools to automate complex development tasks. The system is distinguished by its use of autonomous AI agents capable of multi-step task execution, including the ability to read files, modify code, and run terminal commands iteratively. It supports recursive agent orchestration through subagent delegation and employ

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

Deepagents is an LLM agent orchestration platform and stateful application server designed for deploying and managing AI agents built with computational graphs. It provides a containerized runtime environment that handles agent execution, state persistence, and the versioning of AI assistants. The platform distinguishes itself through deep integration with the Model Context Protocol, allowing agents to function as servers that expose tools and capabilities to external clients. It features a sophisticated observability suite for capturing execution traces, performing LLM-based evaluations agai

mcp-use is a development framework designed for building, deploying, and managing servers, clients, and autonomous agents using the Model Context Protocol. It provides a comprehensive toolkit for creating servers that expose custom tools, data resources, and prompts to compatible AI agents. The project distinguishes itself by offering a complete lifecycle for protocol-based applications, including a dedicated hosting platform for production servers and a compliance validator to ensure servers meet marketplace publishing requirements. It also features an observability suite for tracing protoco

Plano is an AI agent orchestrator and LLM gateway proxy that unifies access to multiple AI providers through a single interoperable interface. It functions as a model routing engine that decouples applications from specific vendors using semantic aliases, allowing traffic to be shifted between providers without modifying application code. The system distinguishes itself with intent-based agent routing, which directs prompts to specialized agents based on semantic analysis. It features an interceptor-based filter chain system that acts as guardrail middleware to enforce safety policies, rewrit

Quivr is a retrieval-augmented generation platform designed to transform raw documents into searchable knowledge bases. It functions as a centralized environment where users can ingest files, index them into vector databases, and interact with language models to receive contextually relevant, data-backed responses. The platform distinguishes itself through an agentic workflow orchestrator that sequences retrieval tasks, tool execution, and model interactions to resolve complex, multi-step queries. This engine is entirely configuration-driven, allowing users to define document ingestion, chunk

This project is a comprehensive framework for building AI-powered applications, providing a unified toolkit for orchestrating language models, autonomous agents, and interactive user interfaces. It serves as a central library for managing the entire lifecycle of AI interactions, from initial prompt generation and model provider abstraction to complex, multi-step reasoning and tool execution. The framework distinguishes itself through its deep integration with frontend development, specifically by enabling generative user interfaces that render dynamic components directly from model outputs. I

Opcode is a desktop interface designed for managing AI-assisted software development workflows. It provides a centralized workspace to organize interactive programming sessions, configure specialized automated agents, and maintain oversight of development tasks through a visual environment. The platform distinguishes itself by integrating version control for AI conversations, allowing developers to create checkpoints and branches to navigate, compare, and revert between different interaction states. It also functions as a client for standardized context protocols, enabling the connection of e

fastmcp is a Python library and framework for building servers and clients that implement the Model Context Protocol. It serves as a tool integration library designed to connect large language models to external tools and data sources. The framework features an interactive tool user interface renderer, which allows for the display of visual interfaces for tools directly within a conversational flow. It also provides a library for automatically generating schemas and validation for tools used by language models. The project covers server and client development, including tool and resource exp