What problem does it solve?
Setting up the soccer analytics agent workshop requires many ordered, failure-prone steps: starting an Oracle AI Database container, creating users with the right grants, loading FIFA match data, training or validating ML models, loading an ONNX embedding model, and populating LangChain OracleVS hybrid retrieval and LangGraph OracleDB observability stores. This Skill walks an AI agent through the entire bootstrap sequence with known failure hints for each step.
Core Features & Use Cases
- End-to-end environment bootstrap: Starts the Oracle AI Database Free container (Docker or Podman, with Apple Silicon image detection), creates the workshop user with required grants including CREATE MINING MODEL, and loads the Kaggle international football results dataset.
- ML and vector pipeline setup: Validates or trains XGBoost prediction artifacts, loads an augmented ONNX embedding model via onnx2oracle, loads precomputed predictions, and populates the SOCCER_LANGCHAIN_DOCS hybrid retrieval store and semantic memory.
- Verification and observability: Runs verify.py and smoke_test.py to confirm predictions, hybrid retrieval, and LangGraph OracleDB step observability, plus builds and polishes the React front-end.
- Use Case: An instructor preparing a workshop asks the agent to set up the environment; the Skill runs all 15 steps in order, gates on required OCI GenAI credentials, and surfaces exact fixes for common errors like ORA-01031 or ORA-54426.
Quick Start
Ask the agent to set up the soccer analytics workshop environment from scratch and verify it is ready for the demo.
