Search Results for "human" - Page 6
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Showing 363 open source projects for "human"
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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Host LLMs in Production With On-Demand GPUsDeploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
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Flock
Flock is a workflow-based low-code platform for building chatbots
...The platform supports multi-agent collaboration, allowing developers to design workflows where different agents handle specialized tasks within the same system. Flock also includes features such as intent recognition, code execution nodes, and human-in-the-loop approval processes that make it suitable for production AI applications. -
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Qwen-Image
Qwen-Image is a powerful image generation foundation model
...The model excels not only in text rendering but also in a wide range of artistic styles, including photorealistic, impressionist, anime, and minimalist aesthetics. Qwen-Image supports sophisticated editing tasks such as style transfer, object insertion and removal, detail enhancement, and even human pose manipulation, making it suitable for both professional and casual users. It also includes advanced image understanding capabilities like object detection, semantic segmentation, depth and edge estimation, and novel view synthesis. -
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PySpur
Visual tool for building, testing, and deploying AI agent workflows
PySpur is a visual development environment designed to help AI engineers build, test, and iterate on agent-based workflows more efficiently. It provides a structured playground where users can define test cases, construct agents either through Python code or a graphical interface, and continuously refine their behavior. It addresses common challenges in AI agent development such as prompt tuning difficulties and lack of visibility into workflow execution. By offering a visual representation... -
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Natural Language Toolkit
NLTK Source
The Natural Language Toolkit (NLTK) is a widely used open-source Python library designed for working with human language data and building natural language processing (NLP) applications. It provides a comprehensive suite of modules, datasets, and tutorials that support both symbolic and statistical approaches to language processing. The toolkit includes implementations of many foundational NLP algorithms and utilities, enabling developers to perform tasks such as tokenization, stemming, parsing, classification, and semantic reasoning. ... -
$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
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Atropos
Language Model Reinforcement Learning Environments frameworks
...It provides foundational tooling for asynchronous RL loops where environment services communicate with trainers and inference engines, enabling complex workflow orchestration in distributed and parallel setups. This framework facilitates experimentation with RLHF (Reinforcement Learning from Human Feedback), RLAIF, or multi-turn training approaches by abstracting environment logic, scoring, and logging into reusable components. -
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PPTAgent
PPTAgent: Generating and Evaluating Presentations
...The project includes both the generation agent and an evaluation framework, PPTEval, to score content quality, design, and coherence. The repository highlights the EMNLP 2025 paper and provides links to resources for replication and study. The approach reflects human presentation practice—plan, draft, then refine with edits—yielding more coherent decks than direct one-shot generation. Community interest and stars suggest strong uptake for research and tooling around presentation automation. -
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yourself-skill
Instead of distilling others, it is better to distil yourself
yourself-skill is an AI skill framework focused on self-reflection and personalization, enabling agents to adapt their behavior based on user context and interaction history. It encourages systems to maintain awareness of user preferences, goals, and communication styles. The project emphasizes building more human-aligned interactions by incorporating memory and contextual reasoning. It can be integrated into broader AI systems to improve personalization and continuity across sessions. The design focuses on enhancing user experience through adaptive responses. It is particularly useful for conversational agents and assistants. Overall, it contributes to more context-aware and user-centered AI systems. -
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Ralph Wiggum Marketer
A Claude Code Plugin that provides an autonomous AI copywriter
...This plugin integrates with Claude Code workflows so that marketers or product teams can define high-level goals, seed their product or service context, and then have the AI autonomously draft, refine, and polish marketing materials with minimal human intervention. -
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Rasa
Open source machine learning framework to automate text conversations
...With Rasa, you can build contextual assistants on Facebook Messenger, Slack, Google Hangouts, Webex Teams, Microsoft Bot Framework, Rocket.Chat, Mattermost, Telegram, and Twilio or on your own custom conversational channels. Rasa helps you build contextual assistants capable of having layered conversations with lots of back-and-forths. In order for a human to have a meaningful exchange with a contextual assistant, the assistant needs to be able to use context to build on things that were previously discussed. Rasa enables you to build assistants that can do this in a scalable way. Rasa uses Poetry for packaging and dependency management. If you want to build it from the source, you have to install Poetry first. ... -
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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Open SWE
Open source async coding agent that plans, codes, and opens PRs
Open SWE is an open source asynchronous coding agent designed to automate software engineering workflows across entire repositories. Built with LangGraph, it can understand a codebase, generate a structured plan, and execute code changes from start to finish without constant human intervention. It operates in a cloud-based environment where tasks are processed asynchronously, allowing multiple coding jobs to run in parallel in isolated sandboxes. It integrates directly with development workflows by responding to triggers from tools like GitHub, enabling users to initiate tasks through issues or comments. Open SWE is capable of creating commits and automatically opening pull requests once implementation is complete, effectively closing the loop on development tasks. ... -
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HumanLayer
Open source IDE for orchestrating AI coding agents in large codebases
...HumanLayer introduces advanced context management techniques that help AI agents understand large repositories and operate effectively across multiple tasks. It also supports collaborative workflows where developers and AI agents can work together with human oversight and control. -
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MLE-bench
AI multi-agent framework for automating data-driven R&D workflows
RD-Agent is an open source AI framework designed to automate research and development workflows in data-driven domains. It uses large language models and multiple collaborating agents to simulate the typical cycle of research, experimentation, and improvement that human data scientists follow. It separates the process into two core phases: a research stage that proposes hypotheses and ideas, and a development stage that implements and evaluates them through code execution and experiments. By iterating through these stages, the framework continuously refines models and strategies using feedback from previous results. ... -
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NagaAgent
A simple yet powerful agent framework for personal assistants
NagaAgent is an experimental framework for building interactive virtual agents capable of autonomous reasoning, dialog, and task execution using components that mirror human cognitive patterns. It provides abstractions for representing goals, context, and state so that agents can plan sequences of actions, evaluate outcomes, and adjust behavior over time. The project includes mechanisms for semantic memory, reasoning pipelines, and integration points with external data sources and language models so that agents can interpret natural language instructions and produce coherent multi-step outputs. ... -
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TraceRoot
Find the Root Cause in Your Code's Trace
...It offers interactive trace exploration with zoomable log clusters, span and latency views, and code-linked insights. Lightweight SDKs for Python and TypeScript enable seamless instrumentation using OpenTelemetry, with support for both self-hosted and cloud deployment. Human-in-the-loop interaction is central: developers can guide reasoning by selecting relevant spans or logs, then verify agent reasoning through traceable context. -
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Laminar
Open-source all-in-one platform for engineering AI products
...Tracing of text and image models is supported, audio models are coming soon. You can set up LLM-as-a-judge or Python script evaluators to run on each received span. Evaluators label spans, which is more scalable than human labeling, and especially helpful for smaller teams. Laminar lets you go beyond a single prompt. You can build and host complex chains, including mixtures of agents or self-reflecting LLM pipelines. -
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MODMAIL
A feature rich discord Modmail bot
...When a member sends a direct message to the bot, Modmail will create a channel or "thread" into a designated category. All further DM messages will automatically relay to that channel; any available staff can respond within the channel. Schedule tasks in human time, e.g. ?close in 2 hours silently. Editing and deleting messages are synced. Support for the diverse range of message contents (multiple images, files). Paginated commands interfaces via reactions. When you close a thread, Modmail will generate a log link and post it to your log channel. -
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Interpretable machine learning
Book about interpretable machine learning
...The later chapters focus on analyzing complex models and their decisions. In an ideal future, machines will be able to explain their decisions and make a transition into an algorithmic age more human. -
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Stop Slop
A skill file for removing AI tells from prose
Stop Slop is a writing skill file designed to remove the obvious tells of AI-generated prose. It gives an assistant concrete editing rules for making text sound more direct, human, specific, and trustworthy. The project targets common AI habits such as filler openings, overused contrasts, unnecessary adverbs, vague language, passive phrasing, and metronomic sentence rhythm. It also includes a scoring rubric that rates drafts across dimensions such as directness, rhythm, trust, authenticity, and density. The skill is useful for drafting, editing, polishing, and quality-checking prose before publication. ... -
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Expect
Let agents test your code in a real browser
Expect is a developer-focused utility designed to simplify validation, testing, and assertion workflows across software environments by providing a clean and expressive interface for defining expected outcomes. The project likely centers on improving readability and maintainability in testing scenarios, allowing developers to write expectations in a concise and human-readable format. It may support chaining conditions, enabling complex validation logic without introducing unnecessary verbosity. The design suggests a focus on productivity, reducing cognitive load when writing and reviewing tests or validation scripts. It is likely adaptable across multiple contexts, including unit testing, integration testing, and runtime assertions. ... -
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One-Person Company
One-Person Company AI Tools Series
One Person Company is an open-source project that provides a conceptual and technical framework for building fully automated businesses powered by AI agents, enabling individuals to operate scalable digital ventures with minimal human intervention. It explores the idea of leveraging AI tools for tasks such as content generation, marketing, customer support, and product development, effectively replacing traditional team structures with intelligent automation. The repository includes workflows, strategies, and system designs that demonstrate how multiple AI agents can collaborate to run different aspects of a business in a coordinated manner. ... -
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AgentHub
GitHub is for humans. AgentHub is for agents
...The project functions as a lightweight infrastructure layer that combines a Git repository with a message-board-style communication system, allowing multiple agents to coordinate development tasks within the same workspace. Rather than focusing solely on human collaboration, the system is designed around an “agent-first” paradigm where AI agents can contribute code, discuss changes, and coordinate problem solving. The platform treats code repositories not just as storage for files but as active environments where agents can propose modifications, review changes, and exchange structured messages. ... -
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Auto-Deep-Research
Your Fully-Automated Personal AI Assistant
Auto-Deep-Research is a system designed to fully automate deep research workflows using language models, retrieval, planning, and multi-stage reasoning to produce structured research artifacts such as surveys, benchmarks, reports, and even prototypes without heavy human intervention. Users provide a research topic or multifaceted goal, and the system autonomously breaks the objective down into subtasks like literature collection, critical summarization, cross-comparison, citation extraction, metric evaluation, and structured writing. Auto-Deep-Research integrates retrieval from academic and web sources, processes document corpora for relevance and key insights, and organizes outputs into coherent chapters or sections according to research standards. ... -
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AI-Researcher
AI-Researcher: Autonomous Scientific Innovation
AI-Researcher is an open-source system designed to automate complex research tasks end-to-end using large language models and structured workflows, aiming to replicate parts of a human research assistant’s capabilities. It lets users input high-level research goals or questions in natural language and then automatically plans, decomposes, and executes tasks such as literature surveying, summarization, synthesis, experiment design, and draft generation. The system integrates retrieval mechanisms to pull in external knowledge sources, contextually analyze documents and papers, and build structured representations of ideas and arguments that can later be turned into coherent reports or drafts. ... -
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Portia SDK Python
Portia Labs Python SDK for building agentic workflows
portia‑sdk‑python is an open-source Python SDK by Portia Labs for creating reliable, stateful, authenticated multi-agent AI workflows. It supports tool-backed agents capable of real-world interactions—like web browsing, API access, and human-in-the-loop clarifications—while maintaining transparency and auditability through structured plans and execution hooks. Designed for production environments, the SDK integrates with local or cloud LLMs (e.g. OpenAI, Anthropic, Mistral, Gemini) and supports extensive tool registries, session handling, and memory management. -
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AutoGen
An Open-Source Programming Framework for Agentic AI
...AutoGen aims to provide an easy-to-use and flexible framework for accelerating development and research on agentic AI, like PyTorch for Deep Learning. It offers features such as agents that can converse with other agents, LLM and tool use support, autonomous and human-in-the-loop workflows, and multi-agent conversation patterns. AutoGen provides multi-agent conversation framework as a high-level abstraction. With this framework, one can conveniently build LLM workflows. AutoGen offers a collection of working systems spanning a wide range of applications from various domains and complexities. AutoGen supports enhanced LLM inference APIs, which can be used to improve inference performance and reduce cost.