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5 dépôts

Awesome GitHub RepositoriesLLM-Based Analysis

Uses large language models to interpret code changes and generate natural language feedback.

Distinct from Git-Based Code Analysis Platforms: Distinct from general Git-based analysis by using LLMs for semantic interpretation rather than just statistics.

Explore 5 awesome GitHub repositories matching devops & infrastructure · LLM-Based Analysis. Refine with filters or upvote what's useful.

Awesome LLM-Based Analysis GitHub Repositories

Trouvez les meilleurs dépôts grâce à l'IA.Nous recherchons les dépôts les plus pertinents grâce à l'IA.
  • vikparuchuri/markerAvatar de VikParuchuri

    VikParuchuri/marker

    36,164Voir sur GitHub↗

    Marker is an LLM-powered document parser and OCR pipeline designed to convert PDFs and unstructured files into structured markdown, JSON, and HTML. It functions as a data preprocessor that transforms complex documents into machine-readable formats while preserving tables, equations, and layout structures. The system utilizes large language models to refine OCR accuracy, clean mathematical notation, and merge fragmented tables across multiple pages. It employs model-based layout analysis to predict block types and bounding boxes, ensuring a more precise conversion of document elements. Capabi

    Uses large language models to refine OCR accuracy, clean mathematical notation, and merge fragmented tables.

    Python
    Voir sur GitHub↗36,164
  • qodo-ai/pr-agentAvatar de qodo-ai

    qodo-ai/pr-agent

    11,630Voir sur GitHub↗

    PR Agent is an AI-powered code analysis tool and pull request reviewer that uses large language models to automate version control workflows. It functions as a programmatic agent that integrates with version control platforms to provide automated quality checks, explain code changes, and manage pull request documentation. The system distinguishes itself by enforcing organizational engineering standards through a customizable rule-based system. It leverages retrieval-augmented generation to inject repository context and organizational guidelines into its analysis, ensuring that feedback remain

    Uses large language models to analyze source code changes and provide natural language feedback within version control.

    Pythoncode-reviewcodereviewcoding-assistant
    Voir sur GitHub↗11,630
  • nvidia/skillspectorAvatar de NVIDIA

    NVIDIA/SkillSpector

    10,778Voir sur GitHub↗

    SkillSpector is a security scanner designed to detect vulnerabilities and malicious patterns in AI agent plugins and extensions before they are installed. It functions as a runtime guardrail that calculates numeric risk scores and assigns severity labels to provide installation recommendations or block risky external extensions. The project distinguishes itself by using language models to perform semantic code analysis, evaluating code intent and context to reduce false positives. It also employs fingerprint-based issue suppression to track and ignore previously accepted risks across repeated

    Uses large language models to evaluate code intent and context, reducing false positives in security detection.

    Python
    Voir sur GitHub↗10,778
  • usagi-org/ai-goofish-monitorAvatar de Usagi-org

    Usagi-org/ai-goofish-monitor

    9,002Voir sur GitHub↗

    ai-goofish-monitor is an AI-driven marketplace monitor and containerized web scraper designed to track online listings. It uses multimodal large language models and natural language prompts to analyze product text and images, determining if items meet specific requirements. The system employs an anti-detection workflow that rotates network proxies and authenticated accounts to bypass rate limits. It captures browser cookies and session states to mimic real user behavior during automated requests. The project includes a task scheduler using cron expressions and an embedded SQLite database for

    Uses multimodal AI and natural language prompts to automatically evaluate product listings.

    Pythonaiplaywright
    Voir sur GitHub↗9,002
  • k8sgpt-ai/k8sgptAvatar de k8sgpt-ai

    k8sgpt-ai/k8sgpt

    7,922Voir sur GitHub↗

    k8sgpt est une suite d'outils axés sur Kubernetes conçus pour le débogage assisté par IA, les diagnostics de cluster et l'auto-guérison. Il fonctionne comme un analyseur et débogueur automatisé qui utilise des modèles de langage étendus (LLM) pour expliquer les erreurs de cluster, suggérer des étapes de remédiation et identifier les défaillances de ressources. Le projet se distingue par un framework d'analyse extensible qui prend en charge des plugins de diagnostic personnalisés et un serveur Model Context Protocol, qui expose les diagnostics de cluster comme des outils pour les assistants IA. Il inclut un agent d'auto-guérison capable de générer et d'appliquer automatiquement des correctifs pour les anomalies détectées, ainsi qu'un middleware d'anonymisation des données pour masquer les informations sensibles avant leur transmission à des fournisseurs d'IA externes. L'ensemble d'outils couvre un large éventail de capacités opérationnelles, y compris la surveillance continue de la santé via un opérateur, l'audit de conformité par rapport aux moteurs de politique, et l'orchestration multi-cluster pour identifier les modèles de défaillance étendus. Il fournit également des fonctionnalités d'observabilité telles que l'exportation des résultats de diagnostic, l'intégration des métriques d'observabilité et le dépannage des défaillances de pods.

    Sends Kubernetes resource data to generative AI backends for human-readable technical analysis.

    Go
    Voir sur GitHub↗7,922
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  5. Git-Based Repositories
  6. Git-Based Code Analysis Platforms
  7. LLM-Based Analysis

Explorer les sous-tags

  • Document Content RefinementUsing language models to improve the accuracy and structural integrity of parsed document content. **Distinct from LLM-Based Analysis:** Focuses on cleaning OCR and merging tables in documents rather than analyzing source code changes.
  • Document Content RefinersAI-driven tools for cleaning and correcting text, notation, and structural elements within documents. **Distinct from LLM-Based Analysis:** Distinct from LLM-Based Analysis: focuses on cleaning and merging content rather than analyzing code changes.
  • Infrastructure AnalysisUse of large language models to analyze system infrastructure state and resource data. **Distinct from LLM-Based Analysis:** Applies LLM analysis to live cluster resource data rather than static code changes in a VCS.
  • Product Listing EvaluationUsing LLMs to evaluate if a product listing matches a set of natural language requirements. **Distinct from LLM-Based Analysis:** Focuses on retail product evaluation rather than code analysis.
  • Security Intent AnalysisUsing language models to evaluate the intent and context of code specifically for security vulnerability detection. **Distinct from LLM-Based Analysis:** Focuses on security-specific intent and vulnerability detection rather than general code change interpretation.