What the Data for This Category Looks Like
Semiconductor due diligence data sources include monthly or quarterly shipment statistics from industry associations, process parameter documents published by wafer foundries, semiconductor-related patent application documents from patent databases, and public quotation filings from supply chain enterprises.
Update frequencies vary: Industry statistics are updated quarterly, process parameters are updated irregularly alongside technology iterations, patent data is added in real time, and quotation data is updated monthly.
A single due diligence document typically includes fields such as wafer process nodes, single-wafer production capacity, upstream raw material unit prices of the supply chain, core patent authorization periods, and downstream application field proportions. Units follow these standards: process is measured in nanometers, production capacity in ten thousand wafers per month, and raw material unit prices in US dollars per kilogram.
What Constraints Do These Characteristics Bring to Workflow Orchestration?
Dispersed data sources covering multiple types of public documents require multiple data source access nodes in the workflow. Connect these nodes to industry association APIs, patent database interfaces, and public financial report crawler nodes respectively. Different data sources have varying update frequencies. Set differentiated scheduled trigger cycles for each node to avoid frequent pulling of low-update-frequency data. Many document fields have inconsistent units. Add a field standardization processing node to the workflow to unify unit formats and field names for data from different sources. Single due diligence documents have lengthy content. Configure a long text splitting node to avoid context overflow that disrupts subsequent analysis links.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600-900 seconds | Semiconductor due diligence documents usually contain long texts of process parameters and supply chain data, and conventional timeout periods are insufficient to complete full parsing |
maxContext | 8000-12000 characters | The core content of a single semiconductor due diligence document is lengthy, requiring configuration adapted to long context processing requirements |
RECALL_COUNT | Top 8-12 entries | Semiconductor due diligence data has many scattered fields, requiring sufficient recalled associated data to support subsequent analysis links |
SIMILARITY_THRESHOLD | 0.75-0.85 | Semiconductor industry terminology is highly professional, requiring a high threshold to filter irrelevant general documents and ensure the relevance of recalled data |
WORKFLOW_TRIGGER_CRON | 0 0 2 * * * | Industry statistics are usually updated daily in the early morning, and scheduled workflow triggers ensure data timeliness |
UPLOAD_FILE_MAX_SIZE | 500 MB | Attachments of single semiconductor due diligence reports, such as process drawings and supply chain tables, are usually large in size, requiring adaptation to large file upload requirements |
The parameter values provided on this page are conventional recommendations used as a starting point for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require case-by-case analysis, and it is recommended to conduct tests on your own samples before finalizing settings.
Three Common Mistakes
- The symptom is that after deployment, workflow configurations and knowledge base lists become blank after a period of time, while interface calls function normally. The cause is incorrect permissions for container mount directories, which prevents normal reading of persistent storage configuration files.
- The symptom is that the knowledge base selection node fails to correctly load the data source referenced by a variable. The cause is that the scope of the data source is not declared in the variable configuration, so the node cannot recognize the referenced variable parameters.
- The symptom is that the workflow can only execute a single query, and cannot implement multi-turn questions and answers or follow-up questions. The cause is that a conversation context persistence node is not configured, so the workflow does not retain session information from historical interactions.
How to Confirm Successful Configuration
- Execute a single workflow trigger, check the node execution logs, and confirm that all data source nodes have successfully pulled corresponding data.
- Test variable references in the knowledge base selection node, and confirm that preset data source parameters can be loaded correctly.
- Trigger the scheduled workflow, and check whether the latest configuration backup file is generated in the persistent storage directory.
- Test multi-turn interaction scenarios, and confirm that the workflow can retain historical session information and complete follow-up questions.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.