What this demo is about
Voice-enabled Knowledge Graph RAG with Speech-to-Text and Text-to-Speech.
RAG & NLP • Browser • 35-45 min
Voice Graph RAG
Voice-enabled Knowledge Graph RAG with Speech-to-Text and Text-to-Speech.
Standard demo guide
Use this demo in a logical learning sequence
Starts in browser, but first load may take 10-30 seconds if heavier assets initialize.
Learning objectives
- Explain the main rag/nlp decision that Voice Graph RAG is designed to support.
- Change input assumptions and predict how the output should respond before running the demo.
- Interpret the result in plain language, not just as a number, chart, or AI recommendation.
Run mode and expectations
- Supported modes: Browser
- Starts in browser, but first load may take 10-30 seconds if heavier assets initialize.
Step 1: Inputs
- Start with the default assumptions, then change one variable at a time so students can isolate cause and effect.
- Treat each input as a lever that changes the scenario, baseline, or business context behind the result.
Step 2: Decision buttons
- Use the main run or simulate action to compute the scenario after inputs are set.
- Use export or reset actions, when present, to compare runs or return to a classroom-safe baseline.
Step 3: Outputs and what to notice
- Read the top-line result first, then look for supporting metrics, tables, or narratives that explain why it changed.
- Students should explain whether the output is descriptive, predictive, simulated, or recommended.
- Look for spoken query, graph retrieval, entities, relationships, and answer
- Observe how voice input changes retrieval errors and answer clarity
Available run modes
- Browser: available for this demo.
How to proceed
- Choose the run mode that fits the class: Browser.
- Review the default assumptions before changing anything.
- Change one or two inputs, then use `Run the main action`.
- Read the output first, then compare any supporting metrics, charts, or AI text.
- Capture one insight, one limitation, and one action recommendation.