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13 مستودعات

Awesome GitHub RepositoriesStructural and Formatting Frameworks

Methods for defining input syntax, output schemas, and reusable templates, focusing on the mechanical layout of interactions.

Explore 13 awesome GitHub repositories matching artificial intelligence & ml · Structural and Formatting Frameworks. Refine with filters or upvote what's useful.

Awesome Structural and Formatting Frameworks GitHub Repositories

اعثر على أفضل المستودعات باستخدام الذكاء الاصطناعي.سنبحث عن أفضل المستودعات المطابقة باستخدام الذكاء الاصطناعي.
  • langchain-ai/langchainالصورة الرمزية لـ langchain-ai

    langchain-ai/langchain

    139,458عرض على GitHub↗

    LangChain is an orchestration framework designed for building, managing, and deploying applications powered by large language models. It provides a unified integration layer that normalizes disparate model provider APIs into a consistent set of primitives, enabling developers to build complex, multi-step AI workflows that manage state, memory, and tool execution. The project distinguishes itself through a durable execution runtime that maintains persistent state across long-running processes by checkpointing progress to external storage. It models agent workflows as directed graphs, allowing

    Augments operational context by dynamically injecting relevant data and tool access into agent prompts.

    Pythonagentsaiai-agents
    عرض على GitHub↗139,458
  • gsd-build/get-shit-doneالصورة الرمزية لـ gsd-build

    gsd-build/get-shit-done

    64,457عرض على GitHub↗

    This project is an autonomous software development assistant and project management tool that utilizes a multi-agent orchestrator to automate complex workflows. It functions as an agentic framework designed to research, plan, execute, and verify software development tasks by coordinating specialized agents that manage context windows and system performance. The system distinguishes itself through a structured, interview-based requirement engineering phase that clarifies project objectives before initiating automated work. It employs atomic task decomposition to break goals into independent un

    Maintains project-specific documentation and state files to provide high-quality context for automated operations.

    JavaScriptclaude-codecontext-engineeringmeta-prompting
    عرض على GitHub↗64,457
  • addyosmani/agent-skillsالصورة الرمزية لـ addyosmani

    addyosmani/agent-skills

    60,849عرض على GitHub↗

    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

    Organizes project information into a hierarchy of global rules, architecture specs, and transient outputs to optimize agent context.

    Shellagent-skillsantigravityantigravity-ide
    عرض على GitHub↗60,849
  • plexpt/awesome-chatgpt-prompts-zhالصورة الرمزية لـ PlexPt

    PlexPt/awesome-chatgpt-prompts-zh

    60,656عرض على GitHub↗

    This project is a community-driven library of structured text inputs designed to guide large language models into specific roles, behaviors, and operational modes. It functions as a comprehensive repository of prompt engineering resources, providing reusable templates that allow users to override default model tendencies and enforce domain-specific response patterns through instruction-following logic. The collection distinguishes itself by offering specialized persona-based directives that constrain model output to simulate professional experts or functional technical environments. By utiliz

    Formatting templates enforce strict output schemas while suppressing conversational filler to ensure clean, usable data responses.

    chat-gptchatgptchatgpt3
    عرض على GitHub↗60,656
  • leonxlnx/taste-skillالصورة الرمزية لـ Leonxlnx

    Leonxlnx/taste-skill

    45,025عرض على GitHub↗

    This project is an AI frontend code generator and design system framework designed to convert visual references and images into functional frontend source code. It provides a system for translating image layouts and styling into code while ensuring layout and styling accuracy. The framework includes a prompt engineering library and portable style instructions that enforce the generation of complete, production-ready source code, preventing the use of placeholders or unfinished segments. It utilizes a multi-modal feedback loop and visual-to-code mapping to maintain consistency between high-fid

    Utilizes strict instruction sets to enforce full source code delivery and suppress conversational filler.

    Shellagentaiclaude
    عرض على GitHub↗45,025
  • outlines-dev/outlinesالصورة الرمزية لـ outlines-dev

    outlines-dev/outlines

    13,965عرض على GitHub↗

    Outlines is a guided text generation framework and structured output engine for large language models. It enforces precise structural constraints on model output during the sampling process to ensure the generation of valid data. The framework ensures that model outputs strictly adhere to predefined data models, including JSON schemas, regular expressions, and formal grammars. This enables the conversion of natural language inputs into structured arguments for function calling and the generation of valid JSON for downstream processing. The system manages model orchestration through prompt te

    Forces the generated output of the model to follow a specific regular expression pattern for precise formatting.

    Python
    عرض على GitHub↗13,965
  • tukuaiai/vibe-coding-cnالصورة الرمزية لـ tukuaiai

    tukuaiai/vibe-coding-cn

    8,294عرض على GitHub↗

    vibe-coding-cn is an AI software development workflow and prompt engineering framework designed to transform product ideas into functional applications using natural language. It functions as an AI agent orchestration system that coordinates specialized skills and quality gates to guide the incremental creation of software. The framework distinguishes itself through a project memory system that maintains architectural and design documentation to preserve context during long-term collaborations. It employs a prompt optimization library that utilizes recursive loops, chain-of-thought reasoning,

    Forces specific response styles and data formats using structured templates and response pre-filling.

    Pythonaiai-agentsclaude-code
    عرض على GitHub↗8,294
  • rockbenben/chatgpt-shortcutالصورة الرمزية لـ rockbenben

    rockbenben/ChatGPT-Shortcut

    7,806عرض على GitHub↗

    ChatGPT-Shortcut is a prompt engineering toolkit and management library designed to organize, refine, and deploy structured instructions for large language models. It functions as a browser-based prompt injector and a self-hosted prompt database, allowing users to maintain a curated collection of specialized templates. The project features a community prompt gallery where users can publish, discover, and vote on effective templates. It distinguishes itself by integrating these libraries directly into chat interfaces via userscripts or browser extensions, enabling access to prompts through sid

    Applies constraints and structural instructions to model responses to avoid repetitive patterns and filler.

    TypeScriptaiai-toolschatgpt
    عرض على GitHub↗7,806
  • nirdiamant/prompt_engineeringالصورة الرمزية لـ NirDiamant

    NirDiamant/Prompt_Engineering

    7,159عرض على GitHub↗

    This project is a comprehensive guide and framework for designing, optimizing, and securing inputs to improve the accuracy and reasoning of large language model outputs. It provides core methodologies for implementing logical reasoning steps, example-based learning, and reusable template systems. The framework distinguishes itself through a focus on security guardrails and ethical auditing, implementing primitives to prevent adversarial prompt injection attacks and identify biases. It also emphasizes structured generation, using persona assignment and negative constraints to control the tone,

    Implements rule-based constraints to ensure outputs adhere to specific formats, boundaries, or schemas.

    Jupyter Notebookaigenaillm
    عرض على GitHub↗7,159
  • deanpeters/product-manager-skillsالصورة الرمزية لـ deanpeters

    deanpeters/Product-Manager-Skills

    5,187عرض على GitHub↗

    هذا المشروع عبارة عن مجموعة من قواعد المعرفة الموحدة ونماذج الكفاءة التي تحدد منهجيات مهنية لممارسي إدارة المنتجات ووكلاء الذكاء الاصطناعي. يوفر إطار عمل منظماً للمهارات والمعرفة المهنية لضمان مستوى متسق من جودة المخرجات عبر اكتشاف المنتج، والاستراتيجية، ومواءمة أصحاب المصلحة. يركز المستودع على أطر عمل متخصصة لإدارة منتجات النماذج اللغوية الكبيرة، بما في ذلك إرشادات لتقييم جاهزية الذكاء الاصطناعي، وهندسة السياق، وتنسيق سير العمل متعدد الوكلاء. يستخدم هيكلة المعرفة القائمة على markdown لتوجيه وكلاء الذكاء الاصطناعي في إنتاج مخرجات مهنية وتحليل استراتيجي بدلاً من المخرجات العامة. يغطي المشروع مجموعة واسعة من إمكانيات إدارة المنتجات، بما في ذلك تحليل مقاييس الأعمال لصحة العمليات، واكتشاف العملاء والتحقق من الفرضيات، وتخطيط خارطة الطريق الاستراتيجية باستخدام نماذج تحديد الأولويات. يتضمن أيضاً أطر عمل لتأليف وثائق متطلبات المنتج وقصص المستخدم، ورسم خرائط تأثير أصحاب المصلحة، والتدريب التنفيذي للانتقالات القيادية.

    Implements systems for organizing domain knowledge and operational constraints into prompts to guide AI agent orchestration.

    Shell
    عرض على GitHub↗5,187
  • microsoft/pomlالصورة الرمزية لـ microsoft

    microsoft/poml

    4,853عرض على GitHub↗

    Poml is a prompt management framework and templating engine designed for authoring, versioning, and rendering structured prompts for large language models. It uses a semantic markup language to organize prompts into reusable templates, combining them with dynamic context and data to generate formatted inputs. The system distinguishes itself by decoupling core prompt logic from final presentation through a stylesheet-based approach. It provides a dedicated JSON schema output generator to enforce strict, machine-parsable model responses and a configuration interface for managing function tool s

    Dictates the specific structural format for the response, such as JSON, XML, or CSV.

    TypeScriptllmmarkup-languageprompt
    عرض على GitHub↗4,853
  • zai-org/glm-4.5الصورة الرمزية لـ zai-org

    zai-org/GLM-4.5

    4,210عرض على GitHub↗

    GLM-4.5 is a multimodal large language model and advanced reasoning system. It functions as an AI coding assistant, an autonomous AI agent, and a multimodal content generator capable of processing and generating text, images, audio, and video within a single unified system. The project is distinguished by its deep reasoning capabilities, utilizing chain-of-thought processing to solve complex mathematical, logical, and technical problems. It features an agentic architecture that allows for autonomous task execution, long-horizon goal planning, and the ability to interact with external tools an

    Enforces structured output schemas, such as JSON, to ensure the model's responses integrate seamlessly with other software.

    Pythonagentglmllm
    عرض على GitHub↗4,210
  • datawhalechina/all-in-ragالصورة الرمزية لـ datawhalechina

    datawhalechina/all-in-rag

    3,989عرض على GitHub↗

    This project is a retrieval augmented generation framework designed to build pipelines that connect unstructured data and knowledge graphs with large language models. It functions as a vector database orchestrator for indexing text and multimodal content, as well as a system for translating natural language queries into structured database commands. The framework integrates a hybrid retrieval engine that combines dense vector search with sparse keyword matching to increase the precision of retrieved contexts. It further enhances reasoning and relationship mapping through a graph-augmented ret

    Enforces specific output schemas and formats on language model responses to ensure consistency.

    Pythonaideepseekembedding
    عرض على GitHub↗3,989
  1. Home
  2. Artificial Intelligence & ML
  3. Prompt Engineering
  4. Structural and Formatting Frameworks

استكشف الوسوم الفرعية

  • Context EngineeringSystems that dynamically provide relevant information and tools to enhance the operational context of AI agents.
  • Output Formatting ConstraintsInstructions and techniques that enforce specific output schemas or formats while suppressing conversational filler from models.