Open-source alternatives to Wenda

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

The BeeAI Framework is an LLM agent framework and multi-agent orchestration engine used to build autonomous agents that coordinate reasoning, tool execution, and complex workflows. It functions as a structured AI output controller and RAG integration library, providing a unified interface to manage multiple language model providers. The framework is distinguished by its implementation of the Model Context Protocol, allowing agents, tools, and models to be shared between different AI platforms and hosted as agentic tooling servers. It enables the design of collaborative agent teams through dec

Superagent is a framework for AI assistant orchestration and agent security. It provides the tools to build intelligent assistants that integrate external APIs and maintain conversation memory to automate complex tasks. The project focuses on AI agent security through adversarial testing, red teaming, and the detection of prompt injections and malicious tool calls. It includes automated vulnerability patching, which scans codebases and configurations for security flaws and generates pull requests with fixes. The platform supports retrieval augmented generation by connecting language models t

Casibase is an open-source platform that orchestrates multi-turn conversations with large language models and manages retrieval-augmented knowledge bases from a single interface. It provides a unified system for connecting to over 30 AI model providers, ingesting documents into vector embeddings for semantic search, and running autonomous agent loops that can drive a browser, search the web, execute commands, and integrate with external tools. The platform distinguishes itself by combining AI conversation management with infrastructure and application orchestration capabilities. It includes a

This project provides a dockerized AI workflow stack and orchestration templates for deploying a self-hosted AI environment. It establishes a localized infrastructure for building autonomous agents and model chains that process private data on-premises without external cloud dependencies. The environment is designed to support autonomous agent development, allowing models to dynamically select tools, execute shell commands, and interact with local file systems. It includes integrated vector database support to enable retrieval augmented generation and private document analysis. The stack cov

LangChain.js is a framework for building, executing, and monitoring stateful agentic applications. It provides an orchestration engine that models workflows as directed graphs, allowing developers to connect language models, data sources, and external tools into modular, multi-step processes. The platform distinguishes itself through its focus on stateful execution and human-in-the-loop control. It manages agent lifecycles by persisting execution state across threads, enabling fault tolerance and the ability to pause workflows at designated breakpoints for manual review or modification. This

This project is a comprehensive toolkit for adapting large language models to the Chinese language, providing a specialized framework for fine-tuning, inference, and local deployment. It serves as a coordinated suite for language-specific adaptation, including tools for expanding tokenizers and implementing retrieval-augmented generation. The project distinguishes itself through a complete pipeline for model adaptation, featuring multilingual tokenizer expansion and a fine-tuning framework that supports instruction-based supervised training and adapter merging. It also includes a dedicated de

gpt4free-ts is a TypeScript-based LLM API proxy and gateway that provides a unified interface for accessing large language models without paid subscriptions or official API keys. It functions as a containerized AI bridge that routes requests to various free third-party providers to retrieve chat completions. The project acts as an OpenAI API wrapper, translating requests and responses into the standard OpenAI chat completions format to ensure compatibility with existing AI tools. It utilizes a provider-based routing system to distribute request loads across available endpoints. The gateway s

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

This project is an MCP browser automation server that connects large language models to headless cloud browsers. It functions as an autonomous web workflow engine and an LLM web agent interface, enabling the translation of natural language instructions into browser actions and structured data retrieval. The system distinguishes itself through a managed headless browser cloud API that supports concurrent Chromium sessions with integrated stealth modes, CAPTCHA solving, and proxy traffic routing. It utilizes self-healing element selection to maintain automation resilience when page structures c

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

Llama-stack is a standardized orchestration stack and generative AI API gateway. It provides a unified communication layer and a consistent interface for deploying, managing, and interacting with various large language model providers and deployments. The system functions as an agent framework that manages tool execution and versioned skill bundles to automate complex tasks. It includes a batch processing system for handling large volumes of asynchronous requests through offline processing and a vector database interface for storing and searching documents to enable retrieval augmented genera

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

ChatGpt-Web is a web-based application designed to provide a responsive interface for interacting with large language models. It functions as a centralized dashboard that enables users to exchange text prompts with generative AI services while managing conversation history and system resources through a modular, component-based architecture. The platform distinguishes itself by incorporating a backend proxy layer that routes client requests to external artificial intelligence providers. This infrastructure allows for the masking of sensitive API keys and the redirection of network traffic to

This project is a comprehensive learning resource and set of demonstrations focused on large language model integration, deployment, and fine-tuning. It provides educational content and practical guides for working with artificial intelligence models. The resource includes specific tutorials and courses on adapting pre-trained models to specialized datasets using parameter-efficient fine-tuning techniques. It also provides instructional content for running quantized models on consumer hardware and building retrieval augmented generation pipelines using vector databases and document indexing.

Deep Searcher is an open-source retrieval-augmented generation engine that indexes private documents into a vector database and uses large language models to answer complex questions with cited reasoning. It functions as both a command-line interface and a web API research tool, enabling users to load data and generate comprehensive reports by combining indexed private information with LLM-powered analysis. The system distinguishes itself through a plugin-based provider architecture that supports multiple embedding models, LLM providers, vector databases, and file loaders as interchangeable c

Shell GPT is an AI-powered command-line interface that generates shell commands and source code from natural language prompts. It serves as a terminal-based tool for automating technical tasks, producing executable commands, and generating code snippets directly within the shell. The tool distinguishes itself through a read-eval-print loop for interactive chatting and the ability to maintain stateful conversational history via named sessions. It supports flexible backend routing, allowing users to connect to cloud-based APIs or local language model hosts for offline operation and data privacy

OpenGpt is an agent orchestration platform and multimodal interface designed for building and deploying specialized AI personas. It allows users to create task-oriented agents with custom system prompts and behavioral constraints to automate professional, creative, and technical workflows. The project features a prompt engineering workflow that transforms simple user inputs into structured instructions to improve model accuracy. It integrates retrieval-augmented generation by connecting vector databases to the chat interface, enabling context-aware responses from private datasets. The platfo

ruby_llm is an LLM integration framework and AI agent orchestrator designed to connect applications to multiple large language model providers through a unified interface. It serves as a toolkit for building autonomous assistants with custom personas, managing structured output via JSON schemas, and implementing vector embedding engines for semantic search. The project distinguishes itself as an observability suite and multimodal toolkit. It provides specialized capabilities for tracking token usage, calculating model costs, and tracing workflows via OpenTelemetry, while supporting the proces

QAnything is a retrieval-augmented generation application framework and self-hosted AI interface. It functions as a system that combines a vector database knowledge base, a document parsing service, and a hybrid search engine to generate answers based on private user data. The project features a modular pipeline architecture that allows users to independently replace components such as parsers, embedding models, and reranking engines. It supports local-first model deployment and offline operation to ensure data privacy, and includes a two-stage retrieval pipeline that merges dense vector embe

This project is a terminal-based command line interface client and agent orchestrator for interacting with multiple large language model providers. It functions as an OpenAI API client and a local API gateway that exposes chat completions and embeddings through an HTTP server. The system distinguishes itself by providing a retrieval-augmented generation tool for indexing local files and URLs into a vector database to provide custom document context. It allows for the creation of specialized AI agents that combine custom system prompts with tool calling and external function execution. The to

OpenAgent is an autonomous AI agent framework designed to orchestrate language models and retrieved context to execute complex user goals. It functions as a platform for building autonomous agents that utilize iterative loops to select tools and process information. The project features a multi-model gateway that abstracts various large language model providers, allowing users to switch between models on a per-conversation basis without modifying code. It also includes a RAG knowledge base system that ingests documents and generates embeddings to provide semantic context during inference. Th

mini-swe-agent is an autonomous software engineering system designed to develop features and fix bugs by combining large language models with a bash interface. It operates as an agentic framework that executes coding tasks and documentation updates through a continuous cycle of model reasoning and tool execution. The project differentiates itself with a strong focus on safety and evaluation, utilizing container-based sandbox execution via Docker or Singularity to isolate command execution. It includes a batch-parallel evaluation harness to measure code-fixing accuracy against standardized sof

This project is an AI-driven phone agent platform and telephony gateway designed to automate inbound and outbound voice interactions. It functions as a conversational voicebot system that utilizes large language models to conduct natural language phone conversations for customer support and data collection. The platform distinguishes itself through the integration of retrieval-augmented generation, allowing voice agents to search internal knowledge bases for domain-specific answers during live calls. It features automated language detection to support multilingual conversations and a system f

Koog is an LLM agent framework used to build autonomous entities that execute tool-based workflows. It utilizes a graph-based workflow engine to define agent behaviors and decision paths as a directed graph of nodes and edges. The framework distinguishes itself through a model provider orchestrator that enables dynamic switching, load balancing, and automatic fallbacks between different AI backends. It implements the Model Context Protocol to connect agents to remote tool servers and features a RAG memory system using vector embeddings to maintain long-term conversation context. The project

Hermes-webui is a self-hosted AI orchestrator and web interface for managing autonomous agents. It serves as a multi-provider gateway that connects cloud and local large language models, providing a central hub to execute scheduled background jobs, run shell commands, and manage agent memory on private hardware. The system distinguishes itself through a persistent memory manager that utilizes knowledge graphs and markdown files for long-term context across sessions. It features a model context protocol host for extending agent capabilities with standardized tools and supports the orchestratio