First Steps

Get started with your TrustGraph deployment and perform your first knowledge extraction and Graph RAG queries.

Prerequisites

This guide assumes you have TrustGraph already deployed using one of the installation methods. If you haven’t deployed TrustGraph yet, start with the Installation Guide.

Install TrustGraph CLI

First, install the TrustGraph command-line interface in a Python virtual environment:

python3 -m venv env
source env/bin/activate  # On Windows: env\Scripts\activate
pip install trustgraph-cli

Note: Keep this virtual environment activated for all TrustGraph CLI commands.

Verify TrustGraph Installation

Check Container Status

After deployment, it may take a while to pull all necessary components. Verify that TrustGraph processors have started:

tg-show-processor-state

Processors start quickly, but Pulsar and Cassandra can take up to 60 seconds to initialize.

If you’re using Docker Compose, check that containers are running:

docker ps

Any containers that have exited unexpectedly can be found with:

docker ps -a

Important: Allow the system to stabilize for 120 seconds before proceeding. Services may appear “stuck” if they didn’t have time to initialize correctly.

Verify Complete Startup

Check that all main services are running:

tg-show-flows

You should see a default flow. If you see an error, wait a moment and try again.

Load Sample Documents

Load some sample documents to get started:

tg-load-sample-documents

Access TrustGraph Interfaces

Web Workbench

Access the TrustGraph web interface at http://localhost:8888/

Verify the workbench is working:

  • Prompts page: Check that you can see system prompts
  • Library page: Verify you can see the sample documents you just loaded

Monitoring with Grafana

Access Grafana monitoring at http://localhost:3000/

  • Login: admin / admin
  • Dashboard: Select the TrustGraph dashboard
  • Skip password change or set a new password

After loading documents, you should see the processing backlog rise to a few hundred document chunks.

Process Your First Document

Load a Document via Workbench

  1. Go to the Library page in the workbench
  2. Select a document (“Beyond State Vigilance” is a good starting document)
  3. Click on the document to select it
  4. Click Submit in the action bar at the bottom
  5. Select a processing flow (use the default)
  6. Click Submit to start processing

Monitor Processing

Watch the processing progress in Grafana. You should see the backlog rise as the document is chunked and processed.

Verify Knowledge Graph Creation

Check that the knowledge graph is successfully parsing data:

tg-show-graph

The output should show semantic triples in N-Triples format:

<http://trustgraph.ai/e/enterprise> <http://trustgraph.ai/e/was-carried> "to altitude and released for a gliding approach" .
<http://trustgraph.ai/e/enterprise> <http://www.w3.org/2000/01/rdf-schema#label> "Enterprise" .
<http://trustgraph.ai/e/enterprise> <http://www.w3.org/2004/02/skos/core#definition> "A prototype space shuttle orbiter used for atmospheric flight testing" .

Explore Your Knowledge

  1. In the workbench, click the Vector Search tab
  2. Search for a term (e.g., “state”)
  3. Review the search results
  4. Click on results to explore the knowledge graph
  5. Use Graph View to visualize relationships

Graph RAG Queries

  1. In the workbench, click the Graph RAG tab
  2. Enter a question about your document: 
    What is this document about?
  3. Review the contextual response generated using your knowledge graph

CLI Graph RAG

You can also run Graph RAG queries from the command line:

tg-invoke-graph-rag "What are the main topics covered in the loaded documents?"

Shut Down TrustGraph

When you’re finished, properly shut down TrustGraph:

For Docker Compose:

docker-compose down -v -t 0

Verify cleanup:

# Check no containers are running
docker ps

# Check volumes are removed
docker volume ls

Next Steps

Now that you’ve successfully:

  • ✅ Verified your TrustGraph installation
  • ✅ Loaded and processed documents
  • ✅ Created knowledge graphs
  • ✅ Performed Graph RAG queries

Continue learning: