# LLM Agent Reasoning and Planning

> Search results for `planning and reasoning loops for LLM agents` on awesome-repositories.com. 116 total matches; showing the first 50.

Explore on the web: https://awesome-repositories.com/q/planning-and-reasoning-loops-for-llm-agents

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## Results

- [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
- [agentscope-ai/agentscope](https://awesome-repositories.com/repository/agentscope-ai-agentscope.md) (26,895 ⭐) — Agentscope is a comprehensive toolkit for developing and orchestrating autonomous multi-agent systems. It provides a unified framework for building agents that can reason, execute tools, and manage memory, enabling the creation of complex, collaborative workflows where multiple specialized agents interact to solve multi-step objectives.

The platform distinguishes itself through a robust orchestration engine that supports both sequential and concurrent agent pipelines. It utilizes a centralized event bus for real-time telemetry, allowing developers to track agent reasoning, tool usage, and sys
- [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
- [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
- [maitrix-org/llm-reasoners](https://awesome-repositories.com/repository/maitrix-org-llm-reasoners.md) (2,345 ⭐) — LLM Reasoners is a library to enable LLMs to conduct complex reasoning, with advanced reasoning algorithms. It approaches multi-step reasoning as planning and searches for the optimal reasoning chain, which achieves the best balance of exploration vs exploitation with the idea of "World Model"…
- [dair-ai/prompt-engineering-guide](https://awesome-repositories.com/repository/dair-ai-prompt-engineering-guide.md) (75,678 ⭐) — This project is a comprehensive educational resource and technical guide focused on the development, optimization, and application of large language models. It provides a structured curriculum for mastering prompt engineering, ranging from foundational principles of instruction design to advanced techniques for improving model reasoning, accuracy, and reliability.

The guide distinguishes itself by offering deep technical insights into agentic workflows and autonomous system design. It covers the implementation of multi-step reasoning chains, tool integration through function calling, and stat
- [datawhalechina/tiny-universe](https://awesome-repositories.com/repository/datawhalechina-tiny-universe.md) (4,505 ⭐) — Tiny Universe is an educational monorepo that delivers multiple independent implementations of core AI subsystems as self-contained Jupyter notebooks. It provides from-scratch constructions of foundational architectures including a complete Transformer model built from the original paper specification, a denoising diffusion probabilistic model for image generation, and a ReAct-style autonomous agent framework that equips an LLM with tools for planning and multi-step task execution.

The project distinguishes itself by covering the full lifecycle of modern AI systems through hands-on implementa
- [harishsg993010/llm-reasoner](https://awesome-repositories.com/repository/harishsg993010-llm-reasoner.md) (488 ⭐) — Make any LLM to think deeper like OpenAI o1 and deepseek R1!
- [conductor-oss/conductor](https://awesome-repositories.com/repository/conductor-oss-conductor.md) (31,962 ⭐) — Conductor is a durable workflow engine designed to orchestrate complex, long-running business processes and autonomous agent loops. It functions as a stateful execution platform that persists the entire history of a process, ensuring that workflows remain reliable and recoverable across infrastructure failures, system restarts, and transient network errors. By managing task lifecycles, worker polling, and state transitions, it provides a centralized coordination layer for distributed systems.

The platform distinguishes itself through its specialized support for AI agent orchestration, allowin
- [eosphoros-ai/db-gpt](https://awesome-repositories.com/repository/eosphoros-ai-db-gpt.md) (18,999 ⭐) — DB-GPT is an agentic data analysis platform and business intelligence AI that functions as a large language model data assistant. It provides a text-to-SQL interface and a sandboxed code execution environment to translate natural language into executable database queries and Python scripts.

The platform utilizes iterative agentic reasoning to plan and execute multi-step data analysis workflows through tool calls. It features a modular skill-based extension system that allows domain knowledge and analysis workflows to be packaged into reusable functional components.

The system integrates data
- [dontriskit/awesome-ai-system-prompts](https://awesome-repositories.com/repository/dontriskit-awesome-ai-system-prompts.md) (5,206 ⭐) — This project is a comprehensive library of structured system prompts and configuration templates designed to define the behavior, persona, and operational boundaries of autonomous artificial intelligence agents. It serves as a framework for prompt engineering, providing modular instructions that help models parse complex tasks, maintain consistent interaction tones, and adhere to specific domain constraints.

The repository distinguishes itself by offering specialized configurations for agent safety and security, including protocols to prevent prompt injection and unauthorized data access. It
- [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
- [agi-edgerunners/plan-and-solve-prompting](https://awesome-repositories.com/repository/agi-edgerunners-plan-and-solve-prompting.md) (0 ⭐) — Code for our ACL 2023 Paper "Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models".
- [rlhflow/self-rewarding-reasoning-llm](https://awesome-repositories.com/repository/rlhflow-self-rewarding-reasoning-llm.md) (232 ⭐) — TL;DL: this is the repo for " Self-rewarding Correction for Mathematical Reasoning "
- [virattt/dexter](https://awesome-repositories.com/repository/virattt-dexter.md) (27,085 ⭐) — Dexter is an autonomous research platform designed to decompose complex inquiries into structured, multi-step workflows. It functions as an agent orchestration system that utilizes iterative tool-calling loops and language models to gather data, perform analysis, and validate findings against internal criteria to ensure accuracy.

The platform distinguishes itself through its specialized focus on financial research and messaging integration. It autonomously interprets real-time market data, including income statements and regulatory filings, to generate evidence-based insights. By connecting d
- [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
- [vercel/ai](https://awesome-repositories.com/repository/vercel-ai.md) (21,885 ⭐) — This project is a comprehensive framework for building AI-powered applications, providing a unified toolkit for orchestrating language models, autonomous agents, and interactive user interfaces. It serves as a central library for managing the entire lifecycle of AI interactions, from initial prompt generation and model provider abstraction to complex, multi-step reasoning and tool execution.

The framework distinguishes itself through its deep integration with frontend development, specifically by enabling generative user interfaces that render dynamic components directly from model outputs. I
- [oxbshw/llm-agents-ecosystem-handbook](https://awesome-repositories.com/repository/oxbshw-llm-agents-ecosystem-handbook.md) (529 ⭐) — A practical operating manual for building, evaluating, securing, and shipping modern LLM agent systems.
- [tmc/langchaingo](https://awesome-repositories.com/repository/tmc-langchaingo.md) (9,416 ⭐) — langchaingo is an LLM application framework for Go designed for building language model-powered applications and autonomous agents. It serves as an orchestration library and tool integration framework that allows developers to link prompt sequences and model calls into complex, multi-step workflows.

The project provides a toolkit for implementing retrieval-augmented generation pipelines by processing unstructured documents and retrieving relevant context via vector search. It includes a dedicated integration layer for indexing high-dimensional embeddings and performing similarity searches acr
- [flowiseai/flowise](https://awesome-repositories.com/repository/flowiseai-flowise.md) (53,641 ⭐) — Flowise is a low-code platform designed for building and deploying complex language model workflows through a visual, node-based interface. It functions as an orchestrator for autonomous multi-agent systems, allowing users to construct conversational pipelines by connecting language models, memory stores, and external tools on a drag-and-drop canvas.

The platform distinguishes itself through its support for sophisticated agentic patterns, including supervisor-worker delegation and iterative reasoning strategies. Users can design directed acyclic graphs to manage conditional branching, state p
- [3lf/llm-for-humans](https://awesome-repositories.com/repository/3lf-llm-for-humans.md) (75 ⭐) — برای آدمیزاد LLM آموزش / Teaching LLM in Persian
- [atfortes/awesome-llm-reasoning](https://awesome-repositories.com/repository/atfortes-awesome-llm-reasoning.md) (3,640 ⭐) — From Chain-of-Thought prompting to OpenAI o1 and DeepSeek-R1 🍓
- [crewaiinc/crewai](https://awesome-repositories.com/repository/crewaiinc-crewai.md) (53,687 ⭐) — CrewAI is a multi-agent orchestration framework designed for building autonomous systems that execute complex, multi-step workflows. It provides a development platform where specialized agents are defined with specific roles, goals, and tool sets to perform tasks collaboratively. By leveraging a declarative workflow engine, the system manages task dependencies, state transitions, and execution logic, allowing for the creation of structured, stateful sequences of operations.

The framework distinguishes itself through its hierarchical management capabilities, which utilize manager agents to coo
- [tencentcloudadp/youtu-agent](https://awesome-repositories.com/repository/tencentcloudadp-youtu-agent.md) (4,576 ⭐) — Youtu Agent is an open-source framework for building, running, and evaluating autonomous agents powered by large language models. It provides the core infrastructure for creating agents that follow reasoning loops, use toolkits, and coordinate with other agents to solve complex tasks, all managed through YAML-driven configuration files.

The framework distinguishes itself through its support for multi-agent orchestration, where a planner agent decomposes tasks and coordinates specialized worker agents, and through its integration with the Model Context Protocol for connecting to external toolk
- [huggingface/smolagents](https://awesome-repositories.com/repository/huggingface-smolagents.md) (27,885 ⭐) — This framework provides a development toolkit for building autonomous agents that utilize language models to solve complex, non-deterministic tasks. Its core design centers on a code-executing architecture where agents generate and run Python code snippets to perform logic, data manipulation, and tool interactions. By moving beyond structured data formats, the system enables agents to manage program flow and object state through iterative reasoning cycles.

The project distinguishes itself through its focus on code-based agent implementation and secure execution environments. Developers can ch
- [tencent/weknora](https://awesome-repositories.com/repository/tencent-weknora.md) (16,974 ⭐) — WeKnora is a multi-tenant retrieval-augmented generation (RAG) knowledge platform and autonomous AI agent framework. It transforms raw documents into queryable knowledge bases and integrates large language models with vector databases to provide grounded AI responses. The system also functions as a Model Context Protocol (MCP) tool server, exposing knowledge search and agentic capabilities to external AI clients.

The platform distinguishes itself through an autonomous agent framework that utilizes iterative reasoning, tool calling, and web search to solve multi-step tasks. It implements a sta
- [miserlou/loop](https://awesome-repositories.com/repository/miserlou-loop.md) (696 ⭐) — UNIX's missing `loop` command
- [claude-code-best/claude-code](https://awesome-repositories.com/repository/claude-code-best-claude-code.md) (20,272 ⭐) — Claude Code is a command-line interface and multi-agent orchestration framework designed for autonomous software engineering. It enables AI agents to perform codebase modifications, debugging, and Git workflow management while coordinating multiple specialized agents to decompose and execute complex engineering tasks in parallel.

The system distinguishes itself through a high degree of isolation and safety, utilizing Git worktrees to create independent working directories for concurrent agents and implementing a tiered permission system that combines user rules, project policies, and OS-level
- [briland/llm-security-and-privacy](https://awesome-repositories.com/repository/briland-llm-security-and-privacy.md) (54 ⭐) — LLM security and privacy
- [swe-agent/mini-swe-agent](https://awesome-repositories.com/repository/swe-agent-mini-swe-agent.md) (2,947 ⭐) — mini-swe-agent is an autonomous software engineering system designed to develop features and fix bugs by combining large language models with a bash interface. It operates as an agentic framework that executes coding tasks and documentation updates through a continuous cycle of model reasoning and tool execution.

The project differentiates itself with a strong focus on safety and evaluation, utilizing container-based sandbox execution via Docker or Singularity to isolate command execution. It includes a batch-parallel evaluation harness to measure code-fixing accuracy against standardized sof
- [stanfordnlp/dspy](https://awesome-repositories.com/repository/stanfordnlp-dspy.md) (35,325 ⭐) — DSPy is a declarative programming framework designed for building complex language model applications. It treats model interactions as modular, composable programs, allowing developers to define task logic through typed class schemas rather than relying on manually written prompts. By organizing workflows into hierarchical, reusable Python objects, the framework enables the construction of sophisticated AI systems that manage state and execution flow independently.

The framework distinguishes itself through an automated optimization engine that iteratively refines prompt instructions and few-
- [truhnlab/contrastive-agent-reasoning](https://awesome-repositories.com/repository/truhnlab-contrastive-agent-reasoning.md) (4 ⭐) — by Zihao Zhao, Frederik Hauke, Juliana De Castilhos, Sven Nebelung, and Daniel Truhn
- [sahat/hackathon-starter](https://awesome-repositories.com/repository/sahat-hackathon-starter.md) (35,226 ⭐) — This project is a Node.js web application boilerplate designed to accelerate development by providing a pre-configured foundation with integrated routing, templating, and developer tooling. It serves as a comprehensive starter kit that includes a full-stack authentication system, a payment integration starter, and an LLM agent framework.

The framework distinguishes itself with specialized tools for AI development, including a retrieval-augmented generation implementation kit with vector search and semantic caching. It enables the creation of reasoning agents featuring tool-calling loops and r
- [aishwaryanr/awesome-generative-ai-guide](https://awesome-repositories.com/repository/aishwaryanr-awesome-generative-ai-guide.md) (24,755 ⭐) — This project is a community-driven knowledge repository and technical learning resource focused on the field of generative artificial intelligence. It serves as a centralized hub for developers and practitioners to access curated research, tutorials, and foundational concepts necessary for building and deploying modern artificial intelligence applications.

The platform distinguishes itself through a collaborative, distributed contribution model that aggregates diverse learning materials into a structured, searchable knowledge base. It covers a wide range of specialized topics, including retri
- [microsoft/ai-agents-for-beginners](https://awesome-repositories.com/repository/microsoft-ai-agents-for-beginners.md) (67,369 ⭐) — This project is a structured educational resource and technical guide for designing and implementing autonomous systems using large language models. It provides a comprehensive curriculum and code samples focused on agentic design patterns, autonomous development, and the creation of systems capable of planning and executing multi-step tasks.

The resource details the implementation of agentic retrieval-augmented generation, where models autonomously plan and refine data searches. It covers a wide array of orchestrators and design patterns, including metacognitive reflection for self-correctin
- [weitianxin/awesome-agentic-reasoning](https://awesome-repositories.com/repository/weitianxin-awesome-agentic-reasoning.md) (1,275 ⭐)
- [javascript-tutorial/en.javascript.info](https://awesome-repositories.com/repository/javascript-tutorial-en-javascript-info.md) (25,344 ⭐) — This project is a comprehensive JavaScript programming tutorial and language reference. It serves as a web development education resource providing instruction on modern language fundamentals, object-oriented design, and advanced asynchronous programming patterns.

The resource functions as both a frontend development guide and a technical reference. It covers core language features such as closures, prototypes, promises, and typed arrays, while providing practical lessons on managing browser data and handling network requests.

The content spans several key capability areas, including browser
- [brexhq/prompt-engineering](https://awesome-repositories.com/repository/brexhq-prompt-engineering.md) (9,538 ⭐) — This project is a comprehensive guide and framework for large language model prompt engineering. It provides a collection of techniques and patterns for optimizing model responses through structured system prompts, context management, and a variety of implementation patterns.

The project focuses on several specialized domains, including the creation of autonomous agents through reasoning loops and the implementation of retrieval augmented generation to inject semantic context into prompts. It also provides methods for enforcing structured outputs in serialization formats like JSON or YAML for
- [addyosmani/agent-skills](https://awesome-repositories.com/repository/addyosmani-agent-skills.md) (60,849 ⭐) — Agent-skills is a collection of structured instructions and behavioral personas designed to standardize how AI coding agents perform engineering tasks. It functions as a workflow orchestrator that maps natural language intent to repeatable technical sequences and verification checklists.

The project distinguishes itself through the use of specialized markdown-defined roles, such as security auditors or test engineers, to apply targeted domain expertise. It employs an evidence-based verification model that requires runtime data or passing tests as mandatory exit criteria to ensure AI-generated
- [sport-agents/sport-agents](https://awesome-repositories.com/repository/sport-agents-sport-agents.md) (21 ⭐) — SPORT introduces an online self-exploration loop that enables multimodal agents to self-improve via AI-generated tasks and LLM-verified preference tuning without human annotations.
- [prefecthq/fastmcp](https://awesome-repositories.com/repository/prefecthq-fastmcp.md) (22,994 ⭐) — FastMCP is a Python framework designed for building servers that expose functions, resources, and prompts to AI models using the Model Context Protocol. It simplifies the development process by automatically deriving tool metadata, input schemas, and documentation directly from Python function signatures and type hints. The framework provides a unified container for managing these components, allowing developers to build modular applications that integrate seamlessly with AI assistants.

The project distinguishes itself through its support for interactive, server-defined user interface compone
- [livekit/livekit](https://awesome-repositories.com/repository/livekit-livekit.md) (19,358 ⭐) — LiveKit is a comprehensive framework for building and orchestrating real-time, multimodal AI agents that interact with users through voice, video, and text. It provides a centralized, event-driven architecture to manage the entire lifecycle of automated participants, from initialization and session state management to graceful shutdown. By utilizing a selective forwarding unit, the platform efficiently routes media streams between participants and agents, ensuring low-latency communication and secure, token-based authentication for all connections.

The platform distinguishes itself through it
- [josh-xt/agent-llm](https://awesome-repositories.com/repository/josh-xt-agent-llm.md) (3,200 ⭐) — AGiXT is a dynamic AI Agent Automation Platform that seamlessly orchestrates instruction management and complex task execution across diverse AI providers. Combining adaptive memory, smart features, and a versatile plugin system, AGiXT delivers efficient and comprehensive AI solutions.
- [pguso/ai-agents-from-scratch](https://awesome-repositories.com/repository/pguso-ai-agents-from-scratch.md) (3,130 ⭐) — This project is an LLM agent framework and orchestration engine designed for building autonomous agents that reason, utilize tools, and execute multi-step plans. It provides a system for implementing the ReAct pattern, which interleaves reasoning and action cycles to solve complex problems through iterative observation and self-correction.

The framework includes a tool integration layer that connects language models to external functions and APIs using structured schemas and embedding-based routing. It also features a memory management system to persist conversation history and user preferenc
- [onjas-buidl/llm-agent-game](https://awesome-repositories.com/repository/onjas-buidl-llm-agent-game.md) (52 ⭐) — LLM-based autonomous world
- [elves/elvish](https://awesome-repositories.com/repository/elves-elvish.md) (6,325 ⭐) — Elvish is a shell that combines interactive command-line use with a structured scripting language, designed to make both everyday terminal work and automation tasks more predictable and readable. It parses, compiles, and executes code in three phases, catching syntax and variable errors before any code runs, and it aborts execution on command failure by default to prevent silent errors.

The shell introduces value-oriented pipelines that pass structured data like lists, maps, and closures between commands, preserving types without serialization. It also mixes traditional byte streams with thes
- [nndl/llm-beginner](https://awesome-repositories.com/repository/nndl-llm-beginner.md) (6,421 ⭐) — This project is a collection of educational resources and technical guides focused on the development and implementation of large language models. It provides a comprehensive curriculum covering transformer architectures, training methods, and deployment strategies.

The materials provide detailed instructions for building autonomous agents using reasoning loops and tool integration, as well as guides for fine-tuning models through supervised learning and preference optimization. It also includes tutorials for constructing retrieval augmented generation pipelines and implementing transformer m
- [florinpop17/app-ideas](https://awesome-repositories.com/repository/florinpop17-app-ideas.md) (95,036 ⭐) — App-ideas is a development platform that integrates autonomous AI agents into local environments to orchestrate code review, automated fix application, and workflow management. It functions as a command-line interface that connects external AI assistants to your codebase, enabling iterative development cycles through plugin-based integration and natural language triggers.

The platform distinguishes itself through a robust static analysis engine that traverses syntax trees to enforce structural coding standards and identify violations. Users can define custom review rules, architectural prefer
- [beyond-all-reason/beyond-all-reason](https://awesome-repositories.com/repository/beyond-all-reason-beyond-all-reason.md) (3,991 ⭐) — Main game repository for Beyond All Reason.
- [apollographql/reason-apollo](https://awesome-repositories.com/repository/apollographql-reason-apollo.md) (547 ⭐) — Reason binding for Apollo Client and React Apollo