trustgraph

LLM Agnostic Knowledge Agent Development Platform

? Full Documentation ?‍? CLI ? Use Cases ? Join the Discord ? YouTube ? Blog

The TrustGraph Engine provides all the tools, services, Graph Stores, and VectorDBs needed to deploy reliable, scalable, and accurate AI agents. The AI Engine includes:

• Bulk document ingestion
• Automated Knowledge Graph Building
• Automated Vectorization
• Model Agnostic LLM Integration
• RAG combining both Knowledge Graphs and VectorDBs
• Enterprise Grade Reliability, Scalability, and Modularity
• Data Privacy enablement with local LLM deployments with Ollama and Llamafile

Ingest your sensitive data in batches and build reusable and enhanced knowledge cores that transform general purpose LLMs into knowledge specialists. The observability dashboard allows you to monitor LLM latency, resource management, and token throughput in realtime. Visualize your enhanced data with Neo4j.

TrustGraph Control Plane

There are two primary ways of interacting with TrustGraph:

• TrustGraph CLI
• Dev Configuration UI

The TrustGraph CLI installs the commands for interacting with TrustGraph while running. The Configuration UI enables customization of TrustGraph deployments prior to launching.

Install the TrustGraph CLI

pip3 install trustgraph-cli==0.13.2

Note

The TrustGraph CLI version must match the desired TrustGraph release version.

Developer Config UI

While TrustGraph is endlessly customizable, the configuration editor can build a custom configuration in seconds with Docker.

Launch the Developer Config UI ?

TrustGraph-Deploy.mp4

Launch Steps:

• For the selected Model Deployment, follow the instructions in Model credentials section to configure any required environment variables or paths
• Fill in the desired LLM name in the Model Name field that corresponds to your selected Model Deployment
• Set all desired Model Parameters
• Click GENERATE under the Deployment configuration section
• Follow the instructions under Launch

Once deploy.zip has been unzipped, launching TrustGraph is as simple as navigating to the deploy directory and running:

docker compose up -d

When finished, shutting down TrustGraph is as simple as:

docker compose down -v

TrustGraph Releases

TrustGraph releases are available here. Download deploy.zip for the desired release version.

Release Type	Release Version
Latest	0.14.6
Stable	0.13.2

TrustGraph is fully containerized and is launched with a YAML configuration file. Unzipping the deploy.zip will add the deploy directory with the following subdirectories:

• docker-compose
• minikube-k8s
• gcp-k8s

Each directory contains the pre-built YAML configuration files needed to launch TrustGraph:

Model Deployment	Graph Store	Launch File
AWS Bedrock API	Cassandra	tg-bedrock-cassandra.yaml
AWS Bedrock API	Neo4j	tg-bedrock-neo4j.yaml
AzureAI API	Cassandra	tg-azure-cassandra.yaml
AzureAI API	Neo4j	tg-azure-neo4j.yaml
AzureOpenAI API	Cassandra	tg-azure-openai-cassandra.yaml
AzureOpenAI API	Neo4j	tg-azure-openai-neo4j.yaml
Anthropic API	Cassandra	tg-claude-cassandra.yaml
Anthropic API	Neo4j	tg-claude-neo4j.yaml
Cohere API	Cassandra	tg-cohere-cassandra.yaml
Cohere API	Neo4j	tg-cohere-neo4j.yaml
Google AI Studio API	Cassandra	tg-googleaistudio-cassandra.yaml
Google AI Studio API	Neo4j	tg-googleaistudio-neo4j.yaml
Llamafile API	Cassandra	tg-llamafile-cassandra.yaml
Llamafile API	Neo4j	tg-llamafile-neo4j.yaml
Ollama API	Cassandra	tg-ollama-cassandra.yaml
Ollama API	Neo4j	tg-ollama-neo4j.yaml
OpenAI API	Cassandra	tg-openai-cassandra.yaml
OpenAI API	Neo4j	tg-openai-neo4j.yaml
VertexAI API	Cassandra	tg-vertexai-cassandra.yaml
VertexAI API	Neo4j	tg-vertexai-neo4j.yaml

Once a configuration launch file has been selected, deploy TrustGraph with:

Docker:

docker compose -f  up -d

Kubernetes:

kubectl apply -f 

Core TrustGraph Features

• PDF decoding
• Text chunking
• On-Device SLM inference with Ollama or Llamafile
• Cloud LLM infernece: AWS Bedrock, AzureAI, Anthropic, Cohere, OpenAI, and VertexAI
• Chunk-mapped vector embeddings with HuggingFace models
• RDF Knowledge Extraction Agents
• Apache Cassandra or Neo4j as the graph store
• Qdrant as the VectorDB
• Build and load Knowledge Cores
• RAG query service using both the Graph Store and VectorDB
• Grafana telemetry dashboard
• Module integration with Apache Pulsar
• Container orchestration with Docker, Podman, or Minikube

Architecture

TrustGraph is designed to be modular to support as many Language Models and environments as possible. A natural fit for a modular architecture is to decompose functions into a set of modules connected through a pub/sub backbone. Apache Pulsar serves as this pub/sub backbone. Pulsar acts as the data broker managing data processing queues connected to procesing modules.

Pulsar Workflows

• For processing flows, Pulsar accepts the output of a processing module and queues it for input to the next subscribed module.
• For services such as LLMs and embeddings, Pulsar provides a client/server model. A Pulsar queue is used as the input to the service. When processed, the output is then delivered to a separate queue where a client subscriber can request that output.

Knowledge Agents

TrustGraph extracts knowledge from a text corpus (PDF or text) to an ultra-dense knowledge graph using 3 automonous knowledge agents. These agents focus on individual elements needed to build the RDF knowledge graph. The agents are:

• Topic Extraction Agent
• Entity Extraction Agent
• Node Connection Agent

The agent prompts are built through templates, enabling customized extraction agents for a specific use case. The extraction agents are launched automatically with the loader commands.

PDF file:

tg-load-pdf 

Text or Markdown file:

tg-load-text 

RAG Queries

Once the knowledge graph and embeddings have been built or a knowledge core has been loaded, RAG queries are launched with a single line:

tg-query-graph-rag -q "Write a blog post about the 5 key takeaways from SB1047 and how they will impact AI development."

Deploy and Manage TrustGraph

? Full Deployment Guide ?

TrustGraph Developer's Guide

Developing for TrustGraph