// rag · trustgraph-ai/trustgraph

trustgraph

trustgraph est un projet de RAG et connaissances open source, créé par trustgraph-ai (trustgraph-ai/trustgraph sur GitHub). Il compte 2 787 étoiles sur GitHub et 330 forks, il est publié sous la licence Apache-2.0 et a été mis à jour pour la dernière fois sur GitHub le 7 octobre 2026.

The semantic intelligence layer for ontologies — governed, traceable knowledge for AI agents

★ 2,8 k étoiles⑂ 330 forksApache-2.0mis à jour oct. 2026
▦ visuel — le README de ce projet ne contient aucune capture intégrable,
voici donc un emplacement réservé. Le guide ci-dessous est complet malgré tout.
// détails du projet

Détails du projet

Étoiles GitHub
2 787
Forks
330
Licence
Apache-2.0
Dernière mise à jour sur GitHub
7 octobre 2026
Type de fiche
Guide d'installation complet
Site officiel
Official site
// fonctionnement

Comment ça marche

  1. Clarify your goal

    Identify the domain knowledge agents must answer about unambiguously, and bring an OWL ontology, build one, or start from a domain standard.

  2. Get TrustGraph

    No clone is needed unless building from source — the config tool generates a deployment bundle for Docker, Podman or Minikube.

  3. Install and configure

    Run the config tool, follow the generated INSTALLATION.md, and connect your LLM provider (or a self-hosted open-weight model).

  4. Run your first task

    Ingest documents (PDF, DOCX, XLSX, PPTX, HTML, Markdown, CSV, images), then ask a natural-language question in the UI on port 8888.

// fonctionnalités

Pourquoi on l'adore

Ontology-native semantics

RDF 1.2 named graphs with OWL ontology enforcement: typed entities, defined relationships and logical inference instead of fuzzy chunk similarity.

Built-in provenance

W3C PROV-O-based provenance: extraction lineage, query traces and agent behavior are stored as queryable graph data.

Unstructured ingest

Converts PDF, DOCX, XLSX, PPTX, HTML, Markdown, CSV and image files into structured semantic knowledge.

Agent runtime

A native agent runtime that traces behavior and links decisions to source knowledge, plus an API gateway for bring-your-own frameworks.

Knowledge lifecycle

Workspaces, Collections, Flows and reusable Knowledge Cores isolate, govern and version knowledge over time.

Full LLM stack included

Managed Cassandra storage, Qdrant vectors, S3-compatible object storage, Pulsar/RabbitMQ messaging, and vLLM/TGI/Ollama/LM Studio options ship with the platform.

Advertisement
// lancez-le

Lancez-le vous-même

  1. Clone the repo

    Clone TrustGraph only if building from source; the normal deploy path is step 2.

    git clone https://github.com/trustgraph-ai/trustgraph.git
    cd trustgraph
  2. Generate a deployment

    The README quickstart generates an app config (deploy.zip with docker-compose.yaml or Kubernetes resources, plus INSTALLATION.md).

    npx @trustgraph/config
  3. Deploy and open the UI

    Start the generated deployment with Docker/Podman/Minikube; the TrustGraph UI serves on port 8888 by default.

    # follow the generated INSTALLATION.md — see README for the exact command
// cas d'usage

Ce que vous pouvez créer

Advertisement
// faq

Questions fréquentes

Who maintains TrustGraph?

trustgraph-ai maintains it (copyright TrustGraph, 2024–2026), with docs at docs.trustgraph.ai and a Discord community.

Is TrustGraph free?

Yes, it is Apache-2.0 licensed and self-hosted.

Does it need a paid API key?

Almost nothing does: the README notes the only possible keys are a third-party LLM service (or self-host open-weight models instead), optional third-party OCR, and the API key you set yourself for its gateway.

How does it compare to Neo4j or plain GraphRAG?

The README's comparison: Neo4j is a general property-graph database with schema-optional semantics and no native provenance or ingest; TrustGraph is purpose-built as an ontology-enforced semantic layer with ingest, retrieval and agent tracing included.

How do I get started?

Run npx @trustgraph/config, deploy the generated bundle, ingest a document, and query it from the UI on port 8888.

// continuez l'exploration

Outils similaires

RAG et connaissances

pipeshub-ai

The open-source, permission-aware context layer that lets agents search all your company knowledge.

★ 3,8 k étoilesApache-2.0
Voir le guide →
RAG et connaissances

Utopia

Utopia — an open-source enterprise world model: a bitemporal knowledge substrate that learns from your documents and gives agents a governed, auditable memory

★ 8,4 k étoilesApache-2.0
Voir le guide →
RAG et connaissances

autonomie

Open rag & knowledge for "autonomie" is a highly semantic, responsive, accessibl.

★ 103 étoilesMIT
Voir le guide →
RAG et connaissances

ecommerce-ai-skills

A trilingual e-commerce knowledge base agents can install.

★ 80 étoilesCC0-1.0
Voir le guide →
RAG et connaissances

infigraph

AST-powered code intelligence engine — graph database plus hybrid semantic search across 62 languages, zero LLM dependency.

★ 91 étoilesNOASSERTION
Voir le guide →
RAG et connaissances

SAG

A new state of the art for RAG: an open knowledge base for humans and agents.

★ 2,5 k étoilesMIT
Voir le guide →
// alternatives

Alternatives en RAG et connaissances

Les autres projets de la catégorie RAG et connaissances avec le plus d'étoiles du catalogue LibreAI — la sélection réaliste d'alternatives si trustgraph ne vous convient pas.

// plus en rag

Plus en RAG et connaissances

Projets de la catégorie RAG et connaissances proches dans le catalogue, les plus proches en étoiles de trustgraph — continuez à explorer de part et d'autre.

Obtenir trustgraph

Gratuit et ouvert : récupérez le code source, mettez une étoile au dépôt et commencez à créer.