# LLM Step-by-Step Trace Debuggers

> Search results for `trace and debug agent runs step by step` on awesome-repositories.com. 120 total matches; showing the first 50.

Explore on the web: https://awesome-repositories.com/q/trace-and-debug-agent-runs-step-by-step

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## Results

- [microsoft/agent-framework](https://awesome-repositories.com/repository/microsoft-agent-framework.md) (7,277 ⭐) — The agent-framework is an LLM agent orchestration framework and multi-agent workflow engine designed for building autonomous AI agents. It provides a tool integration layer for binding external functions, APIs, and sandboxed code as executable tools for language models.

The framework distinguishes itself through a graph-based system for designing sequential and parallel task flows, featuring state management and checkpointing for long-running processes. It implements comprehensive conversational state management and an observability suite that uses telemetry to trace execution flows and monit
- [codehubapp/codehub](https://awesome-repositories.com/repository/codehubapp-codehub.md) (22,662 ⭐) — CodeHub is a mobile application designed for managing remote repositories and reviewing code changes directly from a smartphone or tablet. It functions as a mobile client for GitHub, enabling users to browse repositories, monitor project progress, and interact with pull requests while away from a desktop computer.

Beyond its repository management capabilities, the application serves as a document conversion utility and software comparison platform. It provides tools for transforming files between various formats while maintaining formatting integrity, as well as resources for evaluating and r
- [yukimotopress/programming-blockchains-step-by-step](https://awesome-repositories.com/repository/yukimotopress-programming-blockchains-step-by-step.md) (680 ⭐) — Programming Blockchains Step-by-Step book / guide. Let's build blockchains from scratch (zero) step by step. Let's start with crypto hashes...
- [confident-ai/deepeval](https://awesome-repositories.com/repository/confident-ai-deepeval.md) (13,733 ⭐) — Deepeval is a framework for testing and evaluating large language model applications. It provides a suite of tools for executing automated regression tests, validating model output quality against defined standards, and tracing the execution of complex agent workflows. By integrating these capabilities into development pipelines, the platform ensures consistent performance and reliability throughout the software lifecycle.

The platform distinguishes itself through its focus on programmatic validation and observability. It utilizes secondary language models to score output quality and employs
- [j3ssie/osmedeus](https://awesome-repositories.com/repository/j3ssie-osmedeus.md) (6,425 ⭐) — Osmedeus is an LLM security orchestration engine and AI agent framework designed to automate security workflows. It functions as a declarative workflow automator that uses YAML definitions to coordinate AI agents, shell commands, and distributed scanning tools through a directed acyclic graph.

The system distinguishes itself by deploying autonomous AI agents that use tool-calling loops and conversation memory to plan and execute complex analysis tasks. It features a specialized Agent Communication Protocol to delegate tasks to external AI binaries and supports recursive sub-agent orchestratio
- [google-research/distilling-step-by-step](https://awesome-repositories.com/repository/google-research-distilling-step-by-step.md) (595 ⭐) — Code for paper Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes
- [chainlit/chainlit](https://awesome-repositories.com/repository/chainlit-chainlit.md) (12,213 ⭐) — Chainlit is a Python framework designed for building and deploying interactive, stateful conversational AI interfaces. It provides a backend-driven platform that connects language models and agent frameworks to a web-based chat frontend, managing the complexities of session state, message history, and real-time communication.

The framework distinguishes itself by offering a component-based UI builder that allows developers to inject interactive widgets, rich media, and data visualizations directly into the chat stream. It supports the visualization of complex agent workflows, enabling users t
- [aliasrobotics/cai](https://awesome-repositories.com/repository/aliasrobotics-cai.md) (7,170 ⭐) — CAI is a framework for building autonomous security agents and an orchestration system for coordinating multiple specialized agents. It functions as an agentic workflow engine and an autonomous cyber-defense tool that maps language model reasoning to security kill chain functions for threat detection and mitigation.

The system distinguishes itself through multi-agent coordination patterns, such as swarms and hierarchies, and the use of stateful conversation handoffs. It implements multi-layer input and output guardrails to block prompt injections and validate commands before they reach the sy
- [yvettelau/step-by-step](https://awesome-repositories.com/repository/yvettelau-step-by-step.md) (700 ⭐) — 不积跬步无以至千里。
- [creationix/step](https://awesome-repositories.com/repository/creationix-step.md) (2,194 ⭐) — An async control-flow library that makes stepping through logic easy.
- [datawhalechina/hello-agents](https://awesome-repositories.com/repository/datawhalechina-hello-agents.md) (59,685 ⭐) — This project provides a comprehensive framework for building, training, and managing autonomous agents. It enables the construction of systems that utilize language models to plan, manage memory, and execute multi-step tasks through iterative reasoning loops and tool-based actions.

The framework distinguishes itself by offering specialized capabilities for interacting with graphical user interfaces and legacy software, allowing agents to perceive visual elements and perform actions like a human user. It supports complex, cross-application workflows through graph-based orchestration and provid
- [jenkinsci/docker](https://awesome-repositories.com/repository/jenkinsci-docker.md) (7,530 ⭐) — This project is a containerized build automation system and self-hosted DevOps platform provided as a Docker image. It serves as a distributed build orchestrator and a Dockerized continuous integration and delivery server, ensuring consistent execution environments across different infrastructure.

The system distinguishes itself through a distributed execution model that separates a primary controller from multiple remote agents connected via SSH, TCP, or web sockets. It utilizes a modular extensibility framework that allows the core system functionality to be augmented through the installati
- [andrewyng/aisuite](https://awesome-repositories.com/repository/andrewyng-aisuite.md) (14,692 ⭐) — This project is a framework for managing generative AI services through a unified provider interface and adapter layer. It provides a standardized API for calling multiple cloud-based and locally hosted models, translating provider-specific parameters and responses into a uniform format.

The system includes an agent orchestrator designed for long-running tasks, featuring state persistence for resuming runs and execution tracing to monitor decision-making processes. It integrates the Model Context Protocol to connect models to external servers and filesystems and employs a policy-based executi
- [ace-step/ace-step](https://awesome-repositories.com/repository/ace-step-ace-step.md) (4,088 ⭐) — ACE-Step is a high-fidelity audio synthesis system and diffusion model designed to generate music and vocals from text descriptions. It functions as a music generator and vocal synthesizer, using a diffusion transformer decoder to produce audio across various languages and genres.

The project provides tools for text-guided audio editing, including the ability to extend the duration of tracks, regenerate specific song segments, and perform latent-space audio inpainting to modify lyrics or styles. It also includes a framework for audio style fine-tuning using low-rank adaptation to adapt vocal
- [expo/expo](https://awesome-repositories.com/repository/expo-expo.md) (50,111 ⭐) — Expo is a universal mobile framework designed to build native iOS and Android applications from a single codebase using web-standard technologies. It provides a comprehensive development environment that includes a unified runtime for testing, cloud-based infrastructure for compiling and signing native binaries, and automated tools for managing the entire mobile release lifecycle, including app store submission.

The framework distinguishes itself through a plugin-based native configuration engine that programmatically modifies project files, allowing developers to integrate native modules wit
- [agno-agi/agno](https://awesome-repositories.com/repository/agno-agi-agno.md) (40,717 ⭐) — Agno is an agent operating system designed to manage the lifecycle, tool execution, and persistent state of autonomous agents across distributed infrastructure. It provides a unified runtime environment that wraps diverse agent frameworks into a consistent, interoperable protocol, allowing developers to build and deploy complex multi-agent systems that coordinate tasks and delegate sub-processes.

The platform distinguishes itself through a robust governance and orchestration layer that includes human-in-the-loop approval gates, role-based access control, and a centralized API gateway. It feat
- [ace-step/ace-step-1.5](https://awesome-repositories.com/repository/ace-step-ace-step-1-5.md) (6,002 ⭐) — ACE Step 1.5 is a local text-to-music generation and audio editing system that runs on consumer hardware. It transforms plain-language descriptions into full-length songs with lyrics, and can edit existing audio through cover generation, vocal removal, track separation, and selective repainting. The system supports multilingual prompts and lyrics in over 50 languages, and provides precise control over musical structure including duration, BPM, key, and time signature.

The project distinguishes itself through a dual-stream diffusion architecture that processes separate latent streams for vocal
- [portkey-ai/gateway](https://awesome-repositories.com/repository/portkey-ai-gateway.md) (12,091 ⭐) — This project is an artificial intelligence gateway that functions as a centralized middleware layer for managing, securing, and observing interactions with language, vision, and audio models. It provides a unified interface that standardizes requests across multiple providers, enabling teams to integrate AI capabilities into their applications through a consistent set of tools and protocols.

The gateway distinguishes itself through its comprehensive infrastructure governance and traffic management capabilities. It allows for policy-driven routing, automated failover, and load balancing across
- [phidatahq/phidata](https://awesome-repositories.com/repository/phidatahq-phidata.md) (40,734 ⭐) — Phidata is an LLM agent framework and agentic workflow orchestrator used to build autonomous agents that integrate custom data, tools, and memory. It provides a production environment for serving these agents as services via APIs, utilizing server-sent events and websockets for real-time communication.

The system distinguishes itself through a human-in-the-loop control layer that requires manual approval and administrative sign-off for specific tool executions. It also implements a multi-tenant AI infrastructure that uses token-based roles to ensure data isolation between different tenants.
- [fastapi/fastapi](https://awesome-repositories.com/repository/fastapi-fastapi.md) (99,260 ⭐) — FastAPI is a web framework for building APIs with Python. It leverages standard language type hints to provide automatic data validation, request parsing, and interactive API documentation generation. The framework supports asynchronous request handling and manages execution contexts to prevent blocking the main event loop.

The project includes a dependency injection system that allows for the resolution and injection of reusable components into request handlers. This system supports request-scoped caching, lifecycle management, and integration with security mechanisms like OAuth2 and JSON We
- [vitalets/playwright-magic-steps](https://awesome-repositories.com/repository/vitalets-playwright-magic-steps.md) (0 ⭐) — Auto-transform JavaScript comments into Playwright steps.
- [tarekalabd/flutter-steps-tracker](https://awesome-repositories.com/repository/tarekalabd-flutter-steps-tracker.md) (116 ⭐) — It's an open source project for the steps tracking (Pedometer) built with Flutter and integrated with Firebase as the initial backend service.
- [openai/openai-agents-python](https://awesome-repositories.com/repository/openai-openai-agents-python.md) (27,191 ⭐) — This project is a Python framework for building autonomous, event-driven agent systems. It provides a unified runtime for orchestrating multi-agent workflows, managing persistent conversation state, and executing code within secure, isolated sandbox environments. The framework is designed to handle complex task delegation, allowing agents to invoke other agents as tools while maintaining context across multi-turn interactions.

The framework distinguishes itself through its deep integration with the Model Context Protocol, enabling agents to connect to external data sources and remote services
- [infobyte/faraday](https://awesome-repositories.com/repository/infobyte-faraday.md) (6,523 ⭐) — Faraday is a vulnerability management platform and security tool aggregator designed to centralize security findings from multiple scanners into a single dashboard. It utilizes a relational security database to catalog hosts, services, and security flaws, enabling users to track remediation and analyze organizational risk.

The platform distinguishes itself through a plugin-based system that normalizes diverse security tool outputs into a unified data model. It supports deep integration with a wide array of scanners and CLI tools, intercepting shell command output or parsing report files to ag
- [fastapi/typer](https://awesome-repositories.com/repository/fastapi-typer.md) (19,632 ⭐) — This project is a Python framework for building command-line interfaces by converting standard functions into executable programs. It uses type hints to automatically infer and generate argument parsers, validation logic, and help documentation, allowing developers to define complex terminal applications through simple function signatures.

The framework distinguishes itself through a decorator-driven registration system that enables the construction of hierarchical command trees. It supports dependency injection to manage shared state and runtime configuration across subcommands, and it utili
- [dusty-nv/jetson-inference](https://awesome-repositories.com/repository/dusty-nv-jetson-inference.md) (8,734 ⭐) — jetson-inference is a set of libraries and tools for executing optimized deep learning models on embedded GPU hardware. Its primary purpose is to enable real-time computer vision and AI inference at the edge with low latency and high throughput.

The project distinguishes itself through high-performance streaming analytics and the ability to execute concurrent AI pipelines on auto-grade silicon. It provides specialized support for multi-sensor stream processing, utilizing zero-copy data transport to load camera frames directly into GPU memory.

The codebase covers a broad surface of capabiliti
- [24ark/react-native-step-indicator](https://awesome-repositories.com/repository/24ark-react-native-step-indicator.md) (1,458 ⭐) — A simple react-native implementation of step indicator widget compatible with the ViewPager and ListView.
- [emcie-co/parlant](https://awesome-repositories.com/repository/emcie-co-parlant.md) (18,119 ⭐) — Parlant is an agentic workflow engine and orchestration framework designed for building conversational AI that adheres to strict behavioral guidelines. It provides a platform for managing multi-turn interactions through state-machine-based logic, allowing developers to define complex, hierarchical conversational flows that can adapt, skip, or revisit steps based on real-time user input.

The framework distinguishes itself through its focus on behavioral governance and observability. It enables developers to define precise domain terminology and enforce instruction compliance through prioritize
- [astral-sh/uv](https://awesome-repositories.com/repository/astral-sh-uv.md) (86,451 ⭐) — uv is a high-performance Python package manager and project build tool designed to handle dependency resolution, virtual environment orchestration, and Python interpreter management. It functions as a comprehensive workspace orchestrator, enabling developers to manage complex, multi-package repositories and ensure reproducible builds across different platforms.

The tool distinguishes itself through its use of a global, content-addressable cache and hard-link-based environment provisioning, which allow for near-instant environment creation and minimal disk usage. It employs a high-performance
- [tkwant/react-steps](https://awesome-repositories.com/repository/tkwant-react-steps.md) (19 ⭐) — React Stepper which can also be used on mobile devices
- [moonshotai/kimi-cli](https://awesome-repositories.com/repository/moonshotai-kimi-cli.md) (6,503 ⭐) — Kimi is a terminal-based AI agent that autonomously plans and executes software development tasks by reading, editing, and running code. It operates as an intelligent command-line agent that breaks down high-level goals into sequences of shell commands and code edits, carrying them out without manual step-by-step guidance. The agent can run in an interactive loop, switch to a shell mode for direct terminal command execution, and operate in non-interactive or one-shot modes suitable for scripting.

The project distinguishes itself through multiple integration and execution modes. It can run as
- [jovanbulck/sgx-step](https://awesome-repositories.com/repository/jovanbulck-sgx-step.md) (475 ⭐) — A practical attack framework for precise enclave execution control
- [a2aproject/a2a](https://awesome-repositories.com/repository/a2aproject-a2a.md) (24,404 ⭐) — A2A is a standardized framework designed to enable interoperability, discovery, and orchestration among independent artificial intelligence agents. It provides a common communication protocol that allows heterogeneous agents to exchange data, verify identities, and collaborate across diverse programming languages and computing environments. By establishing a unified messaging standard, the project facilitates the creation of complex, multi-agent workflows where tasks are routed and managed between specialized services.

The project distinguishes itself through a capability-based architecture t
- [step-/nathans-wallpaper](https://awesome-repositories.com/repository/step-nathans-wallpaper.md) (0 ⭐)
- [dagster-io/dagster](https://awesome-repositories.com/repository/dagster-io-dagster.md) (14,974 ⭐) — Dagster is a data orchestration platform designed to manage the entire lifecycle of data assets through declarative modeling and version-controlled code. It functions as a workflow engine that treats data assets as first-class primitives, allowing teams to define, schedule, and monitor complex pipelines while maintaining clear visibility into lineage, dependencies, and data quality.

The platform distinguishes itself by using a code-as-configuration framework that enables standard software engineering practices, such as unit testing and local mocking, to be applied directly to data workflows.
- [mlflow/mlflow](https://awesome-repositories.com/repository/mlflow-mlflow.md) (26,554 ⭐)
- [activepieces/activepieces](https://awesome-repositories.com/repository/activepieces-activepieces.md) (20,887 ⭐) — Activepieces is an open-source, self-hosted workflow automation platform designed to connect third-party applications through modular triggers and actions. It provides a low-code integration framework that allows users to build, manage, and execute complex business logic sequences within isolated, sandboxed environments.

The platform distinguishes itself through its focus on embeddability and enterprise-grade security. It features an embedded automation builder that can be integrated into external applications via iframes, supported by comprehensive identity and access management tools such a
- [coco0106/mo-step](https://awesome-repositories.com/repository/coco0106-mo-step.md) (8 ⭐)
- [getstream/vision-agents](https://awesome-repositories.com/repository/getstream-vision-agents.md) (6,029 ⭐)
- [langchain-ai/langchainjs](https://awesome-repositories.com/repository/langchain-ai-langchainjs.md) (17,818 ⭐) — 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
- [karminski/one-small-step](https://awesome-repositories.com/repository/karminski-one-small-step.md) (6,699 ⭐) — One Small Step is an educational resource that explains core AI and large language model concepts through short, accessible articles designed to be read in under five minutes. It covers the structure and function of key LLM components like attention mechanisms and tokenization, as well as foundational machine learning mathematics such as matrix rank and overfitting.

The project also serves as a guide to the GGUF file format, which packages all model parameters and metadata into a single compact binary file for cross-platform deployment without external dependencies. It explains how this forma
- [camel-ai/camel](https://awesome-repositories.com/repository/camel-ai-camel.md) (17,253 ⭐) — This project is a comprehensive framework for building and managing autonomous agent systems. It provides a unified architecture for orchestrating multi-agent societies, where specialized agents collaborate through roleplay to decompose and solve complex tasks. The system integrates language models with external environments, enabling agents to perform real-world actions through a standardized tool-calling abstraction layer.

The framework distinguishes itself through its focus on iterative reasoning and data reliability. It employs automated feedback loops to refine agent outputs and self-eva
- [fspecii/ace-step-ui](https://awesome-repositories.com/repository/fspecii-ace-step-ui.md) (4,138 ⭐) — ace-step-ui is an AI music production workspace and interface for generating, editing, and organizing synthetic audio tracks and vocals. It provides a technical control panel for managing prompts, seeds, and style parameters to produce high-quality audio.

The project includes a digital audio workstation interface for trimming and fading files, alongside an audio stem separation tool that splits mixed tracks into individual components such as drums, bass, and vocals. It also features a music video creator for generating visual content and procedural album art to accompany generated music.

The
- [github/awesome-copilot](https://awesome-repositories.com/repository/github-awesome-copilot.md) (35,119 ⭐) — Awesome Copilot is a comprehensive framework for autonomous software development, providing the infrastructure to orchestrate multi-agent teams and automate complex coding workflows. It functions as a centralized platform for managing AI-driven development, enabling developers to deploy specialized agents that interact with local files, terminal commands, and external APIs to execute end-to-end software delivery tasks.

The project distinguishes itself through its focus on governance and extensibility, offering a suite of security controls, policy-based execution guardrails, and audit trails t
- [memorilabs/memori](https://awesome-repositories.com/repository/memorilabs-memori.md) (15,358 ⭐) — Memori is an AI agent memory middleware platform designed to provide persistent, context-aware recall for language models. It functions as a non-intrusive layer that intercepts outbound model requests to automatically capture interaction history and execution traces, ensuring that agents maintain continuity across sessions without requiring modifications to existing application logic.

The platform distinguishes itself through a dual-model storage architecture that maintains information as both structured relational primitives for precise fact retrieval and rolling narrative summaries for situ
- [alirezarezvani/claude-skills](https://awesome-repositories.com/repository/alirezarezvani-claude-skills.md) (18,240 ⭐) — This project is a framework for integrating modular instruction packages and domain-specific tools into large language model agents. It provides a system for managing agent context and extending coding assistants through a modular prompt library of persona-based instruction sets and skill trees.

The framework distinguishes itself through a persistent memory layer that tracks architectural decisions and infrastructure patterns to prevent regressions during autonomous code modifications. It includes an orchestrator for managing multi-agent swarms and autonomous coding loops that cycle through g
- [mastra-ai/mastra](https://awesome-repositories.com/repository/mastra-ai-mastra.md) (21,221 ⭐) — 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
- [step-security/harden-runner](https://awesome-repositories.com/repository/step-security-harden-runner.md) (1,206 ⭐) — Harden-Runner is a CI/CD security agent that works like an EDR for GitHub Actions runners. It monitors network egress, file integrity, and process activity on those runners, detecting threats in real-time.
- [web-infra-dev/midscene](https://awesome-repositories.com/repository/web-infra-dev-midscene.md) (11,720 ⭐) — Midscene is a multimodal automation framework designed to enable AI agents to perceive, navigate, and manipulate graphical user interfaces across web, mobile, and desktop environments. By leveraging vision-capable AI models, the platform interprets interface screenshots to execute tasks based on natural language instructions, removing the reliance on traditional, brittle code-based selectors.

The framework distinguishes itself through its ability to decompose high-level goals into autonomous, multi-step sequences that function consistently across diverse platforms. It provides a visual ground
- [run-llama/llama-agents](https://awesome-repositories.com/repository/run-llama-llama-agents.md) (404 ⭐) — Llama Agents + Workflows are an event-driven, async-first, step-based way to control the execution flow of AI applications like agents.