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Showing 30 open source projects for "teams"
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Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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SwanLab
An open-source, modern-design AI training tracking and visualization
...The tool records training metrics, hyperparameters, model outputs, and experiment configurations so that developers can easily understand how different experiments perform over time. It provides a modern user interface for visualizing results, enabling teams to compare runs, track model performance trends, and collaborate on machine learning research. SwanLab supports both cloud and self-hosted deployments, allowing organizations to run the system privately or integrate it into shared development environments. The platform integrates with a wide range of machine learning frameworks including PyTorch, Transformers, Keras, and other widely used training ecosystems. -
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Superagent
Superagent protects your AI applications
...Superagent is designed for low-latency production environments and works with any major LLM provider. It enables teams to prove compliance with modern AI security and regulatory standards. -
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Cybersecurity AI
Cybersecurity AI (CAI), the framework for AI Security
...Rather than being a single-purpose tool, CAI is positioned as a framework that supports building multiple security automations and integrating them into existing processes. It is designed for real-world usability, aiming to reduce friction for teams experimenting with AI agents in security operations, assessment, and response contexts. The framework emphasizes extensibility so users can connect models, tools, and supporting components depending on their environment and constraints. -
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Strix
Open-source AI hackers to find and fix your app’s vulnerabilities
...Unlike traditional vulnerability scanners that rely heavily on static analysis, Strix agents actively run code, probe systems, and attempt exploitation to confirm whether vulnerabilities are genuinely exploitable. The platform is intended for developers and security teams that need rapid security assessments without the overhead of manual penetration testing engagements. Strix can orchestrate multiple cooperating agents that divide investigation tasks and collaboratively analyze complex applications or infrastructure. -
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
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LLaMA 3
The official Meta Llama 3 GitHub site
...Even as a deprecated repo, it documents the transition path and preserves references that clarify how Llama 3 releases map into the current ecosystem. Practically, it functioned as a bridge between Llama 2 and later Llama releases by standardizing distribution and starter code for inference and fine-tuning. Teams still treat it as historical reference material for version lineage and migration notes. -
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HolmesGPT
CNCF Sandbox Project
HolmesGPT is an open-source AI agent designed to help DevOps and site reliability engineering teams diagnose and resolve production incidents. The system aggregates signals from observability tools such as logs, metrics, alerts, and distributed traces, then analyzes them using large language models to identify potential root causes. Rather than requiring engineers to manually correlate large volumes of monitoring data, HolmesGPT automatically synthesizes evidence and presents explanations in natural language. ... -
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AI-Codereview-Gitlab
GitLab automatic code review tool based on large models
...The system monitors GitLab repositories and analyzes commits or merge requests using AI models to identify potential issues, coding mistakes, and quality improvements before the code is merged. By leveraging multiple large language model providers—including OpenAI, DeepSeek, ZhipuAI, or local models through Ollama—the platform allows teams to choose the AI engine that best fits their infrastructure and privacy requirements. When code changes occur, the system can automatically generate review comments and feedback that are posted directly into GitLab merge requests, allowing developers to see suggestions alongside human reviewer comments. In addition to code analysis, the tool can produce daily development summaries and notifications that help teams track progress and review activity across projects. -
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Paddler
Open-source LLM load balancer and serving platform for hosting LLMs
...Paddler also includes tools for monitoring, request buffering, and autoscaling integration so that deployments can adapt dynamically to changing workloads. A built-in administrative interface allows developers and operations teams to manage models, observe system performance, and test inference endpoints. -
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LlamaDeploy
Deploy your agentic worfklows to production
llama_deploy is an open-source framework designed to simplify the deployment and productionization of agent-based AI workflows built with the LlamaIndex ecosystem. The project provides an asynchronous architecture that allows developers to deploy complex multi-agent workflows as scalable microservices. It enables teams to move from experimental prototypes to production systems with minimal changes to existing LlamaIndex code, making it easier to operationalize AI agents. The system supports orchestrating multiple services, handling communication between agents, and managing workflow execution in distributed environments. Developers can define workflows that involve multiple steps such as data retrieval, reasoning, tool invocation, and response generation, then deploy them using the framework’s infrastructure tools. ... -
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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Beelzebub
A secure low code honeypot framework
...By using AI models to simulate realistic system behavior, the honeypot becomes harder for attackers to identify, increasing the likelihood that malicious activity can be observed and analyzed. The framework is designed with a low-code configuration approach so security teams can easily deploy honeypots for multiple services and ports. -
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LangWatch
The platform for LLM evaluations and AI agent testing
...By collecting telemetry data from AI applications, LangWatch allows developers to understand how their systems perform in real-world usage scenarios. The platform includes dashboards that visualize model behavior, enabling teams to monitor trends in response quality and reliability over time. It also provides evaluation tools that allow developers to test prompts and compare outputs across different models or configurations. Through integration with popular AI development frameworks, LangWatch can be embedded directly into AI pipelines to provide continuous monitoring and evaluation. -
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Easy DataSet
A powerful tool for creating datasets for LLM fine-tuning
...The system includes automated question-generation capabilities, hierarchical label trees, and answer generation pipelines that use LLM APIs to produce coherent paired data with customizable templates. Beyond dataset creation, Easy-dataset also provides a built-in evaluation system with model testing and blind-test features, helping teams validate model performance using curated test sets. -
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LLaMA Models
Utilities intended for use with Llama models
...Model lineages and size variants are documented externally (e.g., Llama 3.x and beyond), with this repo providing the “single source of truth” links and utilities. In practice, teams use llama-models as a reference when selecting variants, aligning licenses, and wiring in helper scripts for deployment. -
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csghub-server
csghub-server is the backend server for CSGHub
csghub-server is the backend component of the CSGHub platform, an open-source infrastructure designed to manage and operate large language models, datasets, and AI development workflows within a private deployment environment. The server acts as a centralized management layer that allows teams to store, organize, and operate AI assets such as models, datasets, and machine learning applications in a manner similar to artifact repositories used in software engineering. Built primarily in the Go programming language, the system enables organizations to run model inference, training, and fine-tuning tasks within a unified platform. ... -
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Neuron AI
The PHP Agentic Framework to build production-ready AI driven apps
...The framework provides an Agent class that can be extended to inherit core capabilities like memory, tools, function calling, and retrieval-augmented generation. Its design is modular, so developers can swap model providers with minimal changes to their application code, which makes it practical for teams that need flexibility across vendors. The project also supports structured output, monitoring, MCP connectivity, and workflow patterns that include human-in-the-loop intervention when automated flows need review or correction. -
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AWS GenAI LLM Chatbot
A modular and comprehensive solution to deploy a Multi-LLM
...The project is built as a modular blueprint that helps organizations stand up a production-oriented chat experience rather than a simple demo, combining model access, knowledge retrieval, storage, security, and user interface components into one deployable system. It supports multiple model providers and endpoints, giving teams flexibility to work with Amazon Bedrock, SageMaker-hosted models, and additional model access patterns through related integrations. A major part of the design is its RAG layer, which enables the chatbot to pull contextual knowledge from connected data sources so responses can be grounded in enterprise content rather than relying only on model memory. -
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OpenKnowledge
Beautiful, AI-native markdown editor and LLM Wiki
...It integrates with tools such as Claude, Codex, Cursor, MCP, and CLI-based agent harnesses so AI agents can work with the same knowledge base. Overall, it is useful for teams and individuals who want private, local, Git-backed documentation that can also serve as a structured second brain for AI systems. -
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ChatJS
Production-ready AI chat. Start here and make it your own
ChatJS is a production-ready AI chat foundation for developers who want to launch customizable chat applications without rebuilding common infrastructure from scratch. The project presents itself as a starting point that already includes authentication, model access, streaming, and tool support so teams can focus on their own product-specific features. Its stack is centered on modern TypeScript web development, using technologies such as Next.js, AI SDK tooling, PostgreSQL, Redis, and type-safe configuration patterns. The repository highlights access to more than 120 models through a unified interface, covering providers such as Claude, GPT, Gemini, and Grok. ... -
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Sage Chat
Chat with any codebase in under two minutes | Fully local
...Developers can ask natural language questions about a project, and the system responds with explanations supported by references to the relevant code, documentation, or external technical resources. The project aims to act as a contextual knowledge layer for software teams by combining language models with repository indexing and documentation retrieval. Sage can operate locally or connect to external AI services, depending on the configuration, providing flexibility for privacy-sensitive environments. -
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Bedrock Chat
AWS-native chatbot using Bedrock
Bedrock Chat is a mirrored version of an open-source project that provides a conversational interface for interacting with large language models and AI services through a chat-style application. The project typically focuses on delivering a user interface that allows individuals or teams to communicate with AI models, manage conversations, and experiment with prompts and responses. Implementations like Bedrock Chat often integrate with model hosting platforms or APIs that provide access to generative AI systems. The mirror hosted on SourceForge exists primarily to ensure long-term accessibility of the source code and provide alternative download options for developers. ... -
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TokenSpeed
TokenSpeed is a speed-of-light LLM inference engine
TokenSpeed is an LLM inference engine designed for high-performance production agent workloads. It aims to combine TensorRT-LLM-level speed with vLLM-level usability, making it relevant for teams that need fast generation without sacrificing developer ergonomics. The project is focused on the specific needs of agentic systems, where latency, throughput, and efficient scheduling matter across many short or tool-heavy requests. It builds on ideas and components from the broader open-source inference ecosystem while presenting its own execution stack. ... -
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PeterCat
A conversational Q&A agent configuration system
PeterCat is an open-source conversational agent framework designed to create automated question-and-answer assistants for GitHub repositories and technical projects. The system allows developers to build AI-powered bots that understand project documentation, GitHub issues, and other repository content in order to answer questions from users or contributors. By simply providing the repository name or URL, the platform can automatically collect relevant project information and construct a... -
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Kernel Memory
Research project. A Memory solution for users, teams, and applications
Kernel Memory is an open-source reference architecture developed by Microsoft to help developers build memory systems for AI applications powered by large language models. The project focuses on enabling applications to store, index, and retrieve information so that AI systems can incorporate external knowledge when generating responses. It supports scenarios such as document ingestion, semantic search, and retrieval-augmented generation, allowing language models to answer questions using... -
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Purple Llama
Set of tools to assess and improve LLM security
...CyberSecEval, one of its flagship components, provides repeatable evaluations for security risk, including agent-oriented tasks such as automated patching benchmarks. The aim is to make safety practical: ship testable baselines, publish metrics, and provide drop-in implementations that reduce friction for teams adopting Llama. Documentation and sites attached to the repo walk through setup, usage, and the rationale behind each safeguard, encouraging community contributions. -
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ERNIE
The official repository for ERNIE 4.5 and ERNIEKit
...The repository positions ERNIEKit as an industrial-grade development toolkit, emphasizing end-to-end workflows that span high-performance pre-training, supervised fine-tuning, and alignment. It supports both full-parameter training and parameter-efficient approaches so teams can choose between maximum quality and lower-cost adaptation depending on their constraints. The project also emphasizes optimization techniques for large-scale training, including mixed-precision and hybrid-parallel strategies that are commonly needed for multi-node GPU clusters. In addition to training, it includes guidance and example materials intended to help developers adopt ERNIE models for real product scenarios rather than only research demonstrations.