Projects sharing features with Llama Cloud Services

Lucida is a multimodal AI assistant framework and containerized microservice orchestrator. It provides a platform for building agents that process and integrate speech, vision, and text inputs to perform intelligent tasks, supported by a retrieval-augmented generation system for storing and querying factual data from texts, URLs, and images. The framework features a state-graph workflow engine to route user requests through a sequence of microservices using a predefined state machine. It also includes an extensible plugin interface that allows for the integration of custom functional modules

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

This project is an LLM knowledge base builder and personal knowledge management tool. It is a desktop application designed to transform diverse documents into a persistent, interlinked wiki through LLM analysis and incremental ingestion. The system distinguishes itself with a knowledge graph visualizer that uses community detection algorithms to map relationships between concepts and identify topical clusters. It features a hybrid retrieval system that combines keyword matching, vector embeddings, and graph relevance to locate information. The platform covers a wide range of capabilities inc

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

This is an open-source Python SDK for building and orchestrating production-grade AI agents. It provides a unified framework for creating conversational agents that can use tools, maintain state, and coordinate across multiple language model providers including OpenAI, Anthropic, Google, Amazon Bedrock, and locally-hosted models. The SDK supports multi-agent orchestration through graphs, teams, and swarms, allowing several specialized agents to collaborate on complex tasks. Agents can be composed as callable tools that other agents invoke, and the framework includes policy handlers that inspe

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

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

ChatLaw is a specialized large language model legal assistant designed to provide automated consulting and question answering within Chinese legal frameworks. It functions as a system for legal knowledge management, processing complex legal texts to deliver accurate statutory answers and advisory services. The system utilizes a mixture-of-experts modeling approach and multi-agent coordination to research information and generate professional consultation reports. To ensure factual reliability and minimize hallucinations, it integrates a legal knowledge graph and a standardized operating proce

This project is a .NET Core content management system and multi-site management platform designed to organize and publish structured digital content across independent websites from a centralized interface. It functions as both a headless CMS and a static site generator, rendering dynamic templates into HTML files to increase loading speed and scalability. The system integrates retrieval-augmented generation to transform website documents and content into searchable AI knowledge bases. It includes a visual AI workflow orchestrator to define the logic between user queries and large language mo

gbrain is an agent framework and retrieval-augmented generation system that combines a durable task queue, a git-synced vector store, and a knowledge graph engine. It provides a foundation for building AI agents that interact with structured knowledge bases using the Model Context Protocol. The system synchronizes markdown files from a git repository into a database for high-performance semantic retrieval and creates typed edges between data pages by extracting entity references and wikilinks. It uses a database-backed queue to execute persistent background jobs and tool loops, ensuring relia

Blinko is a personal knowledge management system and an LLM-powered knowledge base that enables users to capture and organize thoughts through a bi-directional knowledge graph. It functions as a RAG-enabled note-taking application and a self-hosted Markdown editor, allowing for the creation of permanent documentation and fleeting notes. The project distinguishes itself by integrating retrieval-augmented generation to provide conversational querying and AI-powered analysis of private document libraries. It supports both cloud-based and local AI model integration, enabling users to perform sema

Nexent is an enterprise AI control plane and LLM agent orchestration platform. It provides a zero-code environment for designing, deploying, and managing production AI agents through a multi-agent collaboration framework that coordinates specialized autonomous agents using standardized messaging protocols. The platform integrates the Model Context Protocol to connect agents with external tools, plugins, and services via a universal communication interface. It further distinguishes itself with a dedicated RAG knowledge base manager that imports unstructured documents and utilizes hybrid search

AI0x0.com is a multimodal AI desktop assistant and cross-application wrapper. It provides a floating interface overlay that integrates large language models into any active software application to facilitate global querying and text automation. The system distinguishes itself through the ability to process real-time screen captures for visual analysis and utilize a voice pipeline for hands-free speech-to-text and text-to-speech interaction. It further enables direct AI content injection by simulating keyboard input to insert generated responses into active software fields. The project includ

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

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

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

Local Deep Research is an autonomous research system consisting of an LLM research agent, a local model orchestrator, and a multi-engine search aggregator. It is designed to execute deep research by decomposing complex questions into atomic facts and synthesizing cited reports from academic, technical, and private document sources. The system features an encrypted research workspace that ensures zero-knowledge privacy through isolated, per-user encrypted databases. It utilizes a local RAG knowledge base to index research sources into searchable vector stores, allowing for retrieval-augmented

DeepTutor is a framework for personalized AI tutoring and educational content generation. It functions as an agentic workflow system that executes reasoning loops to complete multi-step tasks, transforming raw sources into structured learning materials such as interactive books, quizzes, and concept graphs. The platform distinguishes itself through an extensible skill architecture that allows the installation and auditing of third-party capability packages from community registries. It utilizes persona-driven tool policies to deploy persistent AI companions with unique behavioral profiles and

Yuxi-Know is an LLM agent orchestration platform that coordinates multiple AI agents through graph-based workflows to decompose and execute complex reasoning tasks. It functions as a multi-tenant AI workspace with an agentic chat interface, combining retrieval-augmented generation with knowledge graph management for enterprise document processing and retrieval. The platform distinguishes itself through graph-based agent orchestration, where directed acyclic graphs define execution dependencies between reasoning steps, enabling parallel or sequential task decomposition. It provides multi-tenan

Odysseus is a self-hosted AI workspace and autonomous agent framework designed for deploying and managing large language models. It serves as a centralized platform for orchestrating agentic tasks, utilizing a model context protocol server to connect AI models to external system utilities, browser automation, and local hardware. The system distinguishes itself through a combination of retrieval-augmented generation and a RAG knowledge base, using vector stores and local embeddings to provide persistent semantic memory. It further integrates AI-driven communication management to triage email i

Unstructured is an enterprise-grade data orchestration engine designed to transform raw, unstructured files into structured, machine-readable formats. It functions as a comprehensive platform for document ingestion, partitioning, and enrichment, specifically engineered to prepare complex data for retrieval-augmented generation and agentic AI workflows. The platform distinguishes itself through its sophisticated document processing strategies, which combine rule-based extraction with vision-language models to handle diverse file layouts, tables, and images. It provides a modular architecture t

Baserow is a no-code relational database and application builder that allows users to create structured data tables and business tools through a visual interface. It functions as a headless REST API data backend and a self-hosted data workspace, providing a platform for managing collaborative databases while maintaining full control over data residency. The platform integrates large language models to serve as an LLM-powered data platform, capable of generating database structures, record content, and technical workflows from natural language. It also acts as a Model Context Protocol server,

Papra is a self-hosted document management system designed for digital archiving, organization, and retrieval. It serves as a centralized platform for storing files with a focus on security, providing an encrypted file archive using AES-256-GCM and a programmatic interface for managing documents and metadata via a REST API, SDK, and command line tools. The system distinguishes itself through an automated document ingestion engine that imports files via email forwarding, monitored folders, and webhook listeners. It further enhances discoverability by acting as an OCR document indexer, extracti

Spring AI is an application framework for Java that provides a portable, fluent API for integrating AI models, tools, and vector stores into applications. It wraps multiple AI providers behind a common interface, allowing developers to switch between chat, embedding, image, and speech models without changing application code. The framework includes a chainable chat client API similar to WebClient or RestClient, supports both synchronous and streaming interactions, and offers structured output conversion that transforms unstructured AI responses into strongly-typed Java objects. The framework

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