Design a state graph for an incident analysis system on industrial equipment with parallel document search and SQL, using live coding.

For an incident analysis system on industrial equipment with parallel document and SQL search, a LangGraph state diagram can be designed as follows:

1. States:

• Idle — waiting for new data or requests
• DataIngestion — receiving and preparing incident data
• Preprocessing — cleaning and normalizing data
• ParallelSearch — running searches in parallel:
  • DocSearch — document search
  • SQLSearch — database search
• MergeResults — merging search results
• Analysis — analyzing combined data, identifying patterns
• AlertGeneration — generating alerts or reports
• Completed — processing finished

2. Transitions:

• Idle → DataIngestion when new data arrives
• DataIngestion → Preprocessing after data load
• Preprocessing → ParallelSearch
• In ParallelSearch, DocSearch and SQLSearch are launched simultaneously
• After both searches complete, transition to MergeResults
• MergeResults → Analysis
• Analysis → AlertGeneration upon incident detection
• AlertGeneration → Completed
• Completed → Idle

3. Sample Java code (simplified):

enum State { IDLE, DATA_INGESTION, PREPROCESSING, DOC_SEARCH, SQL_SEARCH, MERGE_RESULTS, ANALYSIS, ALERT_GENERATION, COMPLETED }

class LangGraph {
    private State currentState = State.IDLE;

    void onNewData() {
        currentState = State.DATA_INGESTION;
        // load data
        currentState = State.PREPROCESSING;
        // clean data
        currentState = State.DOC_SEARCH;
        // run SQL_SEARCH in parallel
        // after both finish
        currentState = State.MERGE_RESULTS;
        // merge results
        currentState = State.ANALYSIS;
        // analyze
        currentState = State.ALERT_GENERATION;
        // generate alerts
        currentState = State.COMPLETED;
        currentState = State.IDLE;
    }
}

This graph allows clear control of the system state and parallel execution of searches across different sources.