trustgraph/README.md

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The semantic infrastructure for agents

TrustGraph is a comprehensive semantic infrastructure for agents built around context graphs — structured, queryable representations of your domain knowledge that ground every agent query in verified, explainable facts in private deployments with sovereign control. The platform is the full stack for agentic systems: context graphs, memory, retrieval, orchestration, and inference for deterministic agent workloads.

The platform:

• Multi-model and multimodal database system
  • Tabular/relational, key-value
  • Document, graph, and vectors
  • Images, video, and audio
• Context Graph engine
  • Automated entity and relationship extraction
  • Ontology-driven graph construction
  • Graph-grounded retrieval for explainable outputs
• Automated data ingest and loading
  • Quick ingest with semantic similarity retrieval
  • Ontology structuring for precision retrieval
• Out-of-the-box RAG pipelines
  • DocumentRAG
  • GraphRAG
  • OntologyRAG
• 3D GraphViz for exploring context
• Fully Agentic System
  • Single or Multi Agent
  • ReAct, Plan-then-Execute, and Supervisor patterns
  • MCP integration
• Run anywhere
  • Deploy locally with Docker
  • Deploy in cloud with Kubernetes
• Support for all major LLMs
  • API support for Anthropic, Cohere, Gemini, Mistral, OpenAI, and others
  • Model inferencing with vLLM, Ollama, TGI, LM Studio, and Llamafiles
• Developer friendly
  • REST API Docs
  • Websocket API Docs
  • Python API Docs
  • CLI Docs

No API Keys Required

How many times have you cloned a repo and opened the .env.example to see the dozens of API keys for 3rd party dependencies needed to make the services work? There are only 3 things in TrustGraph that might need an API key:

• 3rd party LLM services like Anthropic, Cohere, Gemini, Mistral, OpenAI, etc.
• 3rd party OCR like Mistral OCR
• The API key you set for the TrustGraph API gateway

Everything else is included.

• Managed Multi-model storage in Cassandra
• Managed Vector embedding storage in Qdrant
• Managed File and Object storage in Garage (S3 compatible)
• Managed High-speed Pub/Sub messaging fabric with Pulsar
• Complete LLM inferencing stack for open LLMs with vLLM, TGI, Ollama, LM Studio, and Llamafiles

Quickstart

There's no need to clone this repo, unless you want to build from source. TrustGraph is a fully containerized app that deploys as a set of Docker containers. To configure TrustGraph on the command line:

npx @trustgraph/config

The config process will generate an app config that can be run locally with Docker, Podman, or Minikube. The process will output:

• deploy.zip with either a docker-compose.yaml file for a Docker/Podman or resources.yaml for Kubernetes
• Deployment instructions as INSTALLATION.md

For a browser based configuration, try the Configuration Terminal.

Watch What is a Context Graph?

Watch Context Graphs in Action

Getting Started with TrustGraph

• Getting Started Guides
• Using the Workbench
• Developer APIs and CLI
• Deployment Guides

Context Graph UI

The UI provides tools for all major features of TrustGraph. The UI deploys on port 8888 by default.

• Agent Console — Query your agents directly with streaming responses and live explainability event tracking, so you can watch reasoning unfold in real time
• GraphRAG View — Interactive graph RAG queries with a visual explainability DAG and inline provenance display, making it easy to see exactly where answers came from
• Context Explorer — An interactive 3D context graph explorer with dynamic graph loading, BFS neighborhood extraction, edge pulse animation, and multiple navigation views
• Document Ingestion — A complete upload and submission workflow with page and chunk inspection and document structure browsing
• Ontology Workbench — A full ontology editor with class and property trees, OWL/XML and Turtle import/export with round-trip fidelity, circular dependency detection, and safe-delete confirmation dialogs
• Schema Workbench — Interactive schema management with list, create, edit, and delete operations including field and index management
• Flow Management — Flow creation and detail views with configurable parameters, temperature controls, and grouped storage layout
• Workspace UX — Workspace selection and management surfaced directly in the interface
• Prompt Editor — A dedicated prompt editing workflow

TypeScript Library for UIs

There are 3 libraries for quick UI integration of TrustGraph services.

• @trustgraph/client
• @trustgraph/react-state
• @trustgraph/react-provider

Context Cores

Context Cores are how TrustGraph treats context like code. A Context Core is a portable, versioned bundle of context that you can ship between projects and environments, pin in production, and reuse across agents. It packages the “stuff agents need to know” (structured knowledge + embeddings + evidence + policies) into a single artifact, so you can treat context like code: build it, test it, version it, promote it, and roll it back. TrustGraph is built to support this kind of end-to-end context engineering and orchestration workflow.

What’s inside a Context Core

A Context Core typically includes:

• Ontology (your domain schema) and mappings
• Context Graph (entities, relationships, supporting evidence)
• Embeddings / vector indexes for fast semantic entry-point lookup
• Source manifests + provenance (where facts came from, when, and how they were derived)
• Retrieval policies (traversal rules, freshness, authority ranking)

Tech Stack

TrustGraph provides component flexibility to optimize agent workflows.

LLM APIs

• Anthropic
  
• AWS Bedrock
  
• AzureAI
  
• AzureOpenAI
  
• Cohere
  
• Google AI Studio
  
• Google VertexAI
  
• Mistral
  
• OpenAI
  

LLM Orchestration

• LM Studio
  
• Llamafiles
  
• Ollama
  
• TGI
  
• vLLM
  

Multi-model storage

• Apache Cassandra
  

VectorDB

• Qdrant
  

File and Object Storage

• Garage
  

Observability

• Prometheus
  
• Grafana
  
• Loki
  

Data Streaming

• Apache Pulsar
  
• RabbitMQ
  
• Apache Kafka
  

Clouds

• AWS
  
• Azure
  
• Google Cloud
  
• OVHcloud
  
• Scaleway
  

Observability & Telemetry

Once the platform is running, access the Grafana dashboard at:

http://localhost:3000

Default credentials are:

user: admin
password: admin

The default Grafana dashboard tracks the following:

Telemetry

• LLM Latency
  
• Error Rate
  
• Service Request Rates
  
• Queue Backlogs
  
• Chunking Histogram
  
• Error Source by Service
  
• Rate Limit Events
  
• CPU usage by Service
  
• Memory usage by Service
  
• Models Deployed
  
• Token Throughput (Tokens/second)
  
• Cost Throughput (Cost/second)
  

Contributing

Developer's Guide

License

TrustGraph is licensed under Apache 2.0.

Copyright 2024-2025 TrustGraph

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

   http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

Support & Community

• Bug Reports & Feature Requests: Discord
• Discussions & Questions: Discord
• Documentation: Docs