trustgraph/docs/README.quickstart-docker-compose.md

Getting Started

Preparation

Tip

Before launching TrustGraph, be sure to have the Docker Engine or Podman Machine installed and running on the host machine.

• Install the Docker Engine
• Install the Podman Machine

Note

TrustGraph has been tested on Linux and MacOS with Docker and Podman. Windows deployments have not been tested.

Tip

If using Podman, the only change will be to substitute podman instead of docker in all commands.

Create the configuration

This guide talks you through the Compose file launch, which is the easiest way to lauch on a standalone machine, or a single cloud instance. See README for links to other deployment mechanisms.

To create the deployment configuration, go to the deployment portal and follow the instructions.

• Select Docker Compose or Podman Compose as the deployment mechanism.
• Use Cassandra for the graph store, it's easiest and most tested.
• Use Qdrant for the vector store, it's easiest and most tested.
• Chunker: Recursive, chunk size of 1000, 50 overlap should be fine.
• Pick your favourite LLM model:
  • If you have enough horsepower in a local GPU, LMStudio is an easy starting point for a local model deployment. Ollama is fairly easy.
  • VertexAI on Google is relatively straightforward for a cloud model-as-a-service LLM, and you can get some free credits.
• Max output tokens as per the model, 2048 is safe.
• Customisation, check LLM Prompt Manager and Agent Tools.
• Finish deployment, Generate and download the deployment bundle. Read the extra deploy steps on that page.

Preparing TrustGraph

Below is a step-by-step guide to deploy TrustGraph, extract knowledge from a PDF, build the vector and graph stores, and finally generate responses with Graph RAG.

Install requirements

python3 -m venv env
. env/bin/activate
pip install trustgraph-cli

Running TrustGraph

docker-compose -f docker-compose.yaml up -d

After running the chosen Docker Compose file, all TrustGraph services will launch and be ready to run Naive Extraction jobs and provide RAG responses using the extracted knowledge.

Verify TrustGraph Containers

On first running a Docker Compose file, it may take a while (depending on your network connection) to pull all the necessary components. Once all of the components have been pulled.

A quick check that TrustGraph processors have started:

tg-show-processor-state

Processors start quickly, but can take a while (~60 seconds) for Pulsar and Cassandra to start.

If you have any concerns, check that the TrustGraph containers are running:

docker ps

Any containers that have exited unexpectedly can be found by checking the STATUS field using the following:

docker ps -a

Tip

Before proceeding, allow the system to stabilize. A safe warm up period is 120 seconds. If services seem to be "stuck", it could be because services did not have time to initialize correctly and are trying to restart. Waiting 120 seconds before launching any scripts should provide much more reliable operation.

Everything running

An easy way to check all the main start is complete:

tg-show-flows

You should see a default flow. If you see an error, leave it and try again.

Load some sample documents

tg-load-sample-documents

Workbench

A UI is launched on port 8888, see if you can see it at http://localhost:8888/

Verify things are working:

• Go to the prompts page see that you can see some prompts
• Go to the library page, and check you can see the sample documents you just loaded.

Load a document

• On the library page, select a document. Beyond State Vigilance is a smallish doc to work with.
• Select the doc by clicking on it.
• Select Submit at the bottom of the screen on the action bar.
• Select a processing flow, use the default.
• Click submit.

Look in Grafana

A Grafana is launched on port 3000, see if you can see it at http://localhost:3000/

• Login as admin, password admin.
• Skip the password change screen / change the password.
• Verify things are working by selecting the TrustGraph dashboard
• After a short while, you should see the backlog rise to a few hundred document chunks.

Once some chunks are loaded, you can start to work with the document.

Graph Parsing

To check that the knowledge graph is successfully parsing data:

tg-show-graph

The output should be a set of 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 and landing at the Mojave Desert test center.
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.

Work with the document

Back on the workbench, click on the 'Vector search' tab, and search for something e.g. state. You should see some search results. Click on results to start exploring the knowledge graph.

Click on Graph view on an explored page to visualize the graph.

Queries over the document

On workbench, click Graph RAG and enter a question e.g. What is this document about?

Shutting Down TrustGraph

When shutting down TrustGraph, it's best to shut down all Docker containers and volumes. Run the docker compose down command that corresponds to your model and graph store deployment:

docker compose -f document-compose.yaml down -v -t 0

Tip

To confirm all Docker containers have been shut down, check that the following list is empty:

docker ps

To confirm all Docker volumes have been removed, check that the following list is empty:

docker volume ls