Search Results for "can" - Page 3
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Showing 175 open source projects for "can"
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1
AI Agent Book
Deep Understanding AI Agents
...Later material covers evaluation, supervised fine-tuning, reinforcement learning, self-improvement, multimodal interaction, robotics, and multi-agent cooperation. The repository includes 88 companion experiments, with more than 70 designed to run independently. Readers can access the source chapters, generated figures, code, and downloadable PDF or EPUB editions. Community translations provide versions in several languages alongside the original Chinese text. -
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Sinas
Open-source platform for building AI agents and serverless automation
Sinas can be managed through a web console or declarative YAML configuration, making it suitable for both interactive administration and GitOps-style workflows. Its main value is combining agents, functions, permissions, storage, and automation into one self-hosted AI application platform. -
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ex-skill
Distill your ex into an AI Skill
...The system works by ingesting various forms of personal data such as chat logs, social media content, photos, and user-provided descriptions, then structuring this information into a layered representation that combines memory and persona modeling. It is designed to run within Claude Code environments, where users can generate, manage, and interact with these personalized AI entities through command-based interfaces. The project emphasizes emotional realism by reconstructing conversational tone, habits, and contextual memories, enabling interactions that feel consistent with the original person. -
4
ReMe
Memory Management Kit for Agents
...The toolkit provides APIs to offload large, ephemeral outputs to external storage and reload them on demand, which reduces memory bloat and keeps active context concise. By combining embeddings, vector search, and summarization workflows, ReMe lets developers build agent systems that can recall and apply past knowledge in future reasoning tasks. The project fits into the broader agent-oriented programming ecosystem by supplying a standardized memory layer that integrates with agent frameworks. -
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Hello-Agents
Building an Intelligent Agent from Scratch
...It walks users through core concepts such as ReAct-style reasoning, tool usage, memory handling, and multi-step task execution, enabling hands-on experimentation with modern LLM-powered agent systems. The repository is structured as a progressive learning path, combining theory, exercises, and runnable code so users can incrementally build more capable agents. Its goal is to demystify agent engineering and help developers move from simple prompt scripts to robust autonomous systems. -
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Open Interface
Control Any Computer Using LLMs
Open Interface is a cross-platform application that allows users to control their computers using large language models (LLMs). By sending user requests to an LLM backend, it determines the necessary steps and executes them by simulating keyboard and mouse inputs. The system can adjust its actions based on real-time feedback, providing a self-driving computer experience. -
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The Fable Method
How Claude Fable 5 worked, distilled into skills
...Its rules include bounded retries, authorization gates, evidence requirements, and honest caveat reporting. It can be installed as a Claude Code plugin or as standalone skills. -
8
Hiring Agent
AI agent to evaluate and score resumes
...It reads a resume PDF and converts the content into Markdown-like text. It then uses a local or hosted language model to extract structured candidate information into sectioned JSON. The system can enrich that resume data with GitHub profile and repository signals when a profile is available. After the data is collected, it produces an explainable evaluation with category scores, supporting evidence, bonus points, and deductions. It can run locally with Ollama or use Google Gemini, which makes it flexible for teams that want either private local processing or hosted model access. -
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PixelRAG
The beginning of scalable pixel-native search
...It renders web pages, PDFs, and images into screenshot tiles, then performs retrieval over those visual representations. This approach preserves layout, tables, charts, diagrams, infographics, and other visual structure that traditional HTML or text parsing can miss. The project includes tools for rendering, chunking, embedding, indexing, and serving visual search indexes. It also provides a hosted API with a prebuilt Wikipedia index, plus local pipelines for building indexes from custom documents. PixelRAG can be used with Claude through the pixelbrowse skill, giving agents the ability to inspect pages visually instead of relying only on raw markup. -
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10
uAgents
A fast and lightweight framework for creating decentralized agents
uAgents is a library developed by Fetch.ai that allows for creating autonomous AI agents in Python. With simple and expressive decorators, you can have an agent that performs various tasks on a schedule or takes action on various events. -
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BlenderMCP
Blender Model Context Protocol Integration
...It allows users to control Blender using natural language prompts, effectively turning AI into a co-creator for 3D modeling, scene construction, and asset manipulation. The system establishes a two-way communication channel between Blender and the AI, where commands can be sent and results retrieved in real time. It includes features for object manipulation, material editing, and scene inspection, giving the AI deep control over the modeling environment. The project also supports integration with external asset sources such as Sketchfab and Poly Haven, expanding the range of available resources. ... -
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Haystack
Haystack is an open source NLP framework to interact with your data
Apply the latest NLP technology to your own data with the use of Haystack's pipeline architecture. Implement production-ready semantic search, question answering, summarization and document ranking for a wide range of NLP applications. Evaluate components and fine-tune models. Ask questions in natural language and find granular answers in your documents using the latest QA models with the help of Haystack pipelines. Perform semantic search and retrieve ranked documents according to meaning,... -
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Three.js Object Sculptor
Codex plugin that turns attached object images into code-only
...Codex then follows staged passes from blockout and structural work through surface detail, interaction design, and optimization. Generated models include meaningful sockets and anchors for animation, transformation, physics, and destruction. Reference and rendered screenshots can be combined for AI vision review and scored self-correction. The workflow targets browser-friendly props and stylized reconstructions rather than photogrammetry or exact mesh extraction. -
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Agent Apprenticeship
The living ecosystem where AI agents complete tasks
Agent Apprenticeship is an open infrastructure project for turning real AI-agent work into reusable learning signals. It lets local agents complete tasks through iterative workflow loops, then records the process as experience that can improve future agents. Apprentice agents can be paired with mentor agents, human reviewers, or domain experts depending on the selected mode. The project supports Codex, Cursor, Claude Code, OpenClaw, OpenCode, Hermes Agent, and custom agent commands. Its seed dataset includes curated tasks, reusable lessons, execution traces, work episodes, and structured experience records. ... -
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Omnigent
A meta-harness for all your AI agents
Omnigent is a meta-harness for managing many AI agents through one shared layer. It works with Claude Code, Codex, Cursor, Pi, and custom YAML-defined agents, so users can swap or combine agent runtimes without rebuilding their workflows. Sessions can move across terminal, browser, desktop, and mobile interfaces while keeping messages, files, terminals, and subagents in sync. The platform supports collaboration, shared live sessions, co-driving, conversation forking, and remote access from deployed servers. ... -
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Vision Agents
Open Vision Agents by Stream. Build voice and vision agents quickly
Vision Agents is an open-source Python framework for building real-time voice and video AI agents. It is designed for applications that need to watch, listen, understand, and respond with very low latency. The framework can combine vision models, speech models, LLMs, and real-time transport providers into one agent workflow. It supports use cases such as live coaching, telehealth, customer support, security monitoring, interactive video assistants, and voice-controlled tools. Vision Agents is model-agnostic, so developers can connect providers such as OpenAI, Gemini, Claude, Hugging Face, YOLO, Roboflow, and others. ... -
17
ASSERT
Requirement-driven evaluation harness for AI agents and LLM
ASSERT is a requirement-driven evaluation harness for AI agents and LLM applications. It turns natural-language specifications, policies, product requirements, and launch criteria into structured tests that can be reviewed, executed, scored, and improved. The pipeline derives behavior categories, generates single-turn and multi-turn test cases, runs them against a target system, and uses an LLM judge to score conversations against the stated policies. It can evaluate hosted models, custom agents, multi-agent systems, REST clients, and frameworks such as LangGraph, CrewAI, AutoGen, DSPy, LlamaIndex, and OpenAI Agents SDK. ... -
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geo-seo-claude
GEO-first SEO skill for Claude Code
...The system focuses on producing structured and keyword-optimized pages that align with search engine ranking factors, including localized relevance and semantic context. It is particularly useful for agencies, marketers, and businesses that need to manage large volumes of localized landing pages efficiently. Geo SEO Claude can integrate with existing content pipelines, enabling automated generation and deployment of SEO assets. It also supports customization of content templates, allowing users to maintain brand consistency while scaling output. -
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TypeAgent Python
Structured RAG: ingest, index, query
TypeAgent Python is an experimental Python implementation of Microsoft’s TypeAgent architecture designed to explore how large language models can interact with structured software systems. The project focuses on implementing structured Retrieval-Augmented Generation workflows that allow agents to ingest information, index it in structured form, and answer queries using language models. Instead of relying solely on free-form prompts, the architecture emphasizes converting natural language interactions into structured representations that can be processed by deterministic software components. ... -
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Claude Agent SDK for Python
Python SDK for Claude Agent
...The SDK wraps the core functionality of Claude Code and exposes high-level asynchronous and synchronous interfaces to query prompts, manage sessions, and orchestrate tool use — so you can build agents that understand code, make edits, run bash commands, interact with files, and handle workflows without writing low-level agent loop logic yourself. It ships with a bundled Claude Code CLI for convenience, though you can also point it to a custom installation, and supports defining custom tools and hooks directly in Python, which become callable by the agent during execution. -
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nanobot
🐈 nanobot: The Ultra-Lightweight Clawdbot / OpenClaw
...Its research-ready architecture makes it easy for developers to understand, customize, and extend for experimentation or production use. With simple one-click deployment and a straightforward CLI, users can get a working AI assistant running in minutes. Inspired by Clawdbot but radically simplified, nanobot proves that capable AI agents don’t need massive codebases. -
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OpenAGI
When LLM Meets Domain Experts
OpenAGI is a package for AI agent creation designed to connect large language models with domain-specific tools and workflows in the AIOS (AI Operating System) ecosystem. It provides a structured Python framework, pyopenagi, for defining agents as modular units that encapsulate execution logic, configuration, and dependency metadata. Agents are organized in a well-defined folder structure that includes code (agent.py), configuration (config.json), and extra requirements... -
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CAMEL AI
Finding the Scaling Law of Agents. A multi-agent framework
...Our approach involves using inception prompting to guide chat agents toward task completion while maintaining consistency with human intentions. We showcase how role-playing can be used to generate conversational data for studying the behaviors and capabilities of chat agents, providing a valuable resource for investigating conversational language models. -
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Claude Codex Settings
My personal Claude Code and OpenAI Codex setup
...It is designed to help developers fine-tune how Claude and similar models behave within coding workflows, ensuring more consistent and high-quality outputs. The project emphasizes practical usability, offering ready-to-use configurations that can be directly integrated into development environments. It also includes guidelines for structuring prompts, managing context, and optimizing interactions with AI systems. The repository serves as both a toolkit and a reference for improving developer productivity when working with AI assistants. It is particularly useful for users who want to standardize their workflows and reduce variability in results. ... -
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GenericAgent
Self-evolving autonomous agent framework
The GenericAgent project is a flexible framework for building autonomous AI agents that can operate across diverse tasks and environments. It is designed around modularity, allowing developers to define agents with interchangeable components such as tools, memory systems, and reasoning strategies. The architecture emphasizes generality, enabling the same agent framework to be adapted for different domains including coding, research, and task automation.