For conversational interfaces, the strongest matches are m1heng/clawdbot-feishu (This project provides a self-hosted conversational assistant framework focused), rasahq/rasa (Rasa is a comprehensive conversational AI framework providing natural) and microsoft/botframework-sdk (This conversational AI software development kit provides dialogue management). langgenius/dify and botpress/botpress round out the shortlist. Each is ranked by relevance to your query, popularity and recent activity.
Hand-picked open-source conversational interface frameworks, ranked by GitHub stars and activity. Compare the top tools and find the right one.
This project is a framework for integrating Large Language Models into the Feishu messaging platform to create automated assistants. It functions as a self-hosted AI assistant and a chatbot gateway that routes messages between chat platforms and remote AI cloud providers. The system features a multi-channel messaging bridge and provider-agnostic model routing, allowing for orchestration between different AI models with automatic failover management. It includes a browser automation agent capable of programmatically controlling web browsers and capturing page snapshots to extend the assistant'
This project provides a self-hosted conversational assistant framework focused on messaging platform integration and AI model routing, though it lacks explicit built-in dialogue management and native speech processing features.
Rasa is a chatbot development platform and conversational AI framework used to design, deploy, and integrate multi-turn conversational agents. It functions as an LLM orchestration engine and NLU dialogue manager, combining large language model fluency with structured business logic to control agent behavior. The framework enables the development of conversational assistants that automate text and voice interactions. It allows for the definition of conversational flows using flexible sequences and provides tools to inspect agent decisions to debug and validate the internal reasoning process.
Rasa is a comprehensive conversational AI framework providing natural language processing, dialogue management, and multi-channel integration for building advanced chatbots and assistants.
This project is a conversational AI software development kit and framework used to build interactive chatbots that engage in natural language conversations and execute tasks for end users. It provides a multi-channel bot framework that connects conversational agents to various external messaging services using standardized adapters. The SDK includes a conversational workflow orchestrator and a natural language processing toolkit for analyzing user intent and extracting entities to route conversation flows. It further incorporates a speech integration framework that enables bidirectional audio
This conversational AI software development kit provides dialogue management, natural language understanding, multi-channel adapters, and speech integration for building voice and text assistants.
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
Dify is a self-hostable generative AI platform that provides visual workflow orchestration, multi-channel deployment, dialogue management, and built-in speech capabilities for building conversational interfaces and assistants.
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
Botpress is a conversational AI platform and chatbot builder that provides visual workflows, multi-channel integrations, and orchestration tools for building LLM-powered assistants.
mi-gpt is a voice assistant bridge and agent orchestrator that connects smart speakers to large language models. It functions as an integration layer that routes audio requests from hardware speakers to AI providers and converts generated text back into speech via a customizable synthesis system. The project features a retrieval-augmented generation knowledge base that uses embeddings and external documents to provide context-aware responses. It includes a persona definition system for configuring behavioral rules, system prompts, and roleplay characteristics, alongside a plugin architecture
This project serves as a voice assistant bridge and agent orchestrator that connects smart speakers to language models, delivering natural language conversational features and speech synthesis while operating within a narrower hardware-integration scope than a general-purpose chatbot platform.
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
Chainlit is a Python framework built specifically for creating interactive conversational AI interfaces with chat frontends, though it focuses more on frontend visualization and agent workflows than providing end-to-end multi-channel bot integration.
AstrBot is an orchestration framework designed for building and managing autonomous agents that integrate multimodal artificial intelligence with secure, isolated execution environments. It serves as a platform for coordinating complex agentic workflows, allowing users to connect diverse language, speech, and vision models while maintaining personalized agent personas and domain-specific knowledge bases. The platform distinguishes itself through a modular plugin architecture and a centralized visual dashboard, which together enable users to extend agent capabilities and manage operational set
AstrBot is an orchestration framework and chatbot platform that supports multi-channel integrations, text-to-speech, and self-hosted deployment, making it well-suited for building conversational agents.
Pipecat is a framework and software development kit for building real-time multimodal AI agents and speech-to-speech systems. It utilizes a frame-based data pipeline to route audio, video, and text through a modular sequence of processors, enabling the orchestration of low-latency conversational AI. The project is distinguished by its ability to coordinate complex multimodal services, including speech-to-text, language models, and text-to-speech, within a single pipeline. It features semantic voice activity detection for natural turn-taking, state-machine conversation flows for dialogue manag
Pipecat is a framework for building real-time conversational AI and voice assistants with modular data pipelines, supporting speech-to-speech and dialogue management as requested, though it requires custom integration for multi-channel deployment.
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
Vercel AI is a TypeScript framework for building AI-powered chat interfaces and language model applications, providing robust tools for streaming responses and frontend integration, though it leans more toward general LLM orchestration than full out-of-the-box dialogue management.
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
This framework enables building conversational user interfaces and multi-agent workflows through message-passing orchestration, though it focuses more on autonomous agent collaboration than traditional chatbot development.
Botkit is a multi-platform chatbot framework designed to build conversational bots that operate across different messaging services using a unified interface. It provides a core system for multi-platform development, utilizing a platform adaptation layer to translate service-specific API payloads into a standardized internal format. The framework features a conversational dialog manager that coordinates multi-turn interactions through state-tracking, branching logic, and scripted flows. It employs a message processing middleware pipeline to intercept, normalize, and enrich incoming and outgoi
Botkit is a well-established chatbot framework providing a unified interface and dialogue management for multi-channel messaging apps, though it lacks built-in self-hosted LLM integrations and native voice capabilities without external extensions.
Botman is an extensible PHP library for building chatbots that work across multiple messaging platforms from a single codebase. It provides a framework-agnostic foundation for creating chat bots that can operate on platforms like Slack, Telegram, and Facebook Messenger without requiring platform-specific code. The library abstracts each chat platform behind a common driver interface, allowing developers to send and receive messages uniformly. It includes a conversation state machine for managing multi-turn dialogues, a message matching engine that triggers responses based on keywords or patte
Botman is a PHP-based framework for building conversational user interfaces that handles multi-platform messaging and dialogue flow, though it lacks built-in self-hosting server infrastructure and native speech processing.
This project is an autonomous agent framework designed to integrate large language models with popular messaging platforms. It functions as a middleware platform that enables automated, multimodal interactions by decomposing complex user goals into sequential plans, executing them through external tools, and maintaining persistent context across sessions. The framework distinguishes itself through a modular skill architecture and a hybrid memory system. Users can extend system capabilities by installing custom logic modules from community hubs or generating them through natural language. The
This project serves as a messaging integration framework that connects large language models to platforms like WeChat, offering multi-channel bridging and conversational capabilities though it is more focused on client integration than a general-purpose dialogue builder.
LiveKit is a comprehensive framework for building and orchestrating real-time, multimodal AI agents that interact with users through voice, video, and text. It provides a centralized, event-driven architecture to manage the entire lifecycle of automated participants, from initialization and session state management to graceful shutdown. By utilizing a selective forwarding unit, the platform efficiently routes media streams between participants and agents, ensuring low-latency communication and secure, token-based authentication for all connections. The platform distinguishes itself through it
LiveKit provides a comprehensive real-time multimodal framework for building voice and text AI agents with low-latency media routing, covering the core conversational capabilities and self-hostability needed for interactive assistants.
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
This Python framework provides foundational building blocks and runtime orchestration for managing conversational agent state and multi-turn workflows, though it focuses more on autonomous agent systems than traditional chatbot platforms.
snips-nlu is a Python library and natural language understanding engine designed to convert unstructured text into structured data. It identifies user intents and extracts associated entities from natural language sentences to enable machine-readable command processing. The engine functions as a multilingual parser capable of processing text across multiple languages. It maps identified entities to canonical values or standardized ISO formats, such as timestamps, to ensure data consistency. The project covers intent classification and named entity recognition, utilizing sequence labeling and
Snips-nlu is a Python-based natural language understanding library that handles intent classification and entity extraction, providing a foundational natural language processing capability for building conversational interfaces and chatbots.
Agentscope is a comprehensive toolkit for developing and orchestrating autonomous multi-agent systems. It provides a unified framework for building agents that can reason, execute tools, and manage memory, enabling the creation of complex, collaborative workflows where multiple specialized agents interact to solve multi-step objectives. The platform distinguishes itself through a robust orchestration engine that supports both sequential and concurrent agent pipelines. It utilizes a centralized event bus for real-time telemetry, allowing developers to track agent reasoning, tool usage, and sys
AgentScope provides a robust multi-agent orchestration framework well-suited for building advanced conversational interfaces and LLM-driven workflows, though it focuses more on autonomous agent collaboration than traditional chatbot dialogue management.
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
Mastra is an AI agent orchestration framework providing workflow management and memory systems for building conversational applications, though it is geared more toward autonomous agent loops than traditional chatbot platforms.
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
Flowise is a low-code visual builder for orchestrating language model workflows and chatbots, though it relies on external speech and multi-channel integrations rather than providing them natively.
CopilotKit is an agentic framework designed to integrate large language models into application frontends, enabling natural language control over software features and data. It provides the infrastructure to build intelligent assistants that manage conversation history, track application state, and execute complex workflows through conversational prompts. The framework distinguishes itself by its ability to render dynamic, interactive user interface components in real time based on model outputs. By utilizing a standardized communication protocol, it maps natural language intents to executabl
CopilotKit is an agentic TypeScript framework for building conversational interfaces and AI assistants directly into React frontends, though it focuses more on generative UI and application integration than traditional multi-channel bot deployment.
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 repository provides a web-based conversational interface and RAG platform with local model deployment, though it is primarily focused on document retrieval rather than general multi-channel dialogue management.
Obot is an orchestration platform designed for the deployment and management of autonomous agents that automate complex business workflows. It provides a framework for connecting intelligent models to internal infrastructure and external services, enabling agents to perform tasks through conversational interfaces. The platform functions as a centralized system for infrastructure governance, incorporating a secure gateway to route, filter, and monitor network traffic between distributed services. It maintains a registry of server capabilities and agent skills, allowing for the discovery and ut
Obot is an autonomous agent orchestration platform that features conversational interfaces and workflow automation, though it is tailored more toward enterprise agent deployment than general-purpose chatbot building.
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
LibreChat is a self-hostable AI orchestration and chat platform that unifies multiple language models with conversational memory and agent workflows, though it functions primarily as an end-user interface rather than a foundational developer framework.
| Repository | Stars | Language | License | Last push |
|---|---|---|---|---|
| m1heng/clawdbot-feishu | 3.3K | TypeScript | mit | |
| rasahq/rasa | 21.2K | Python | Apache-2.0 | |
| microsoft/botframework-sdk | 7.8K | JavaScript | MIT | |
| langgenius/dify | 145.5K | TypeScript | NOASSERTION | |
| botpress/botpress | 14.7K | TypeScript | MIT | |
| idootop/mi-gpt | 12.5K | TypeScript | MIT | |
| chainlit/chainlit | 12.2K | Python | Apache-2.0 | |
| astrbotdevs/astrbot | 34.8K | Python | AGPL-3.0 | |
| pipecat-ai/pipecat | 12.8K | Python | BSD-2-Clause | |
| vercel/ai | 21.9K | TypeScript | other |