HTTP Interfaces and External Systems for Semiconductor Intelligent Due Diligence Reports

Semiconductor intelligent due diligence report data comes primarily from wafer foundry public capacity reports, semiconductor equipment manufacturer

What Data for This Category Looks Like

Semiconductor intelligent due diligence report data comes primarily from wafer foundry public capacity reports, semiconductor equipment manufacturer shipment ledgers, industry association supply and demand statistics, patent database authorization records, and listed companies’ regular announcements. Update cycles cover monthly (capacity, supply chain), quarterly (industry supply and demand), and real-time (patent dynamics). Documents center on structured tables, supplemented by industry trend analysis text. Fields include production scale, supply chain proportion values, patent application count, revenue range, and more. Corresponding units are wafers per month, no explicit unit (proportions presented as numerical values), count, millions of USD, and others.

Constraints Imposed on HTTP Interfaces and External Systems

Multi-source data access requires connecting multiple heterogeneous HTTP interfaces. Adaptation to different authentication protocols and request formats is necessary. Data sources with different update cycles need matching scheduled scheduling rules to avoid duplicate requests or delayed updates. There are many structured fields with significant unit differences. Strict field mapping for interface requests and responses is required to prevent unit conversion errors. Some data sources return large single data volumes, which increases HTTP request bandwidth usage and timeout waiting periods. Request parameters must be adjusted for these cases.

Configuration Settings

Configuration ItemRecommended ValueRationale
UPLOAD_FILE_MAX_SIZE2000 MBRaw data files for semiconductor due diligence reports typically contain batch structured tables, with larger sizes than general documents, so adaptation to large file upload requirements is needed
PARSE_FILE_TIMEOUT_SECONDS600 secondsParsing due diligence files with multi-page structured tables takes longer. The default timeout duration is insufficient, so extension is required to avoid parsing interruptions
HTTP_REQUEST_TIMEOUT30 secondsMost semiconductor industry data source interface response times fall within the 10-25 second range. A reasonable buffer is reserved to cover network fluctuations
FIELD_MAPPING_RULEDual matching by field name + unitSemiconductor due diligence data fields include similar indicators such as production capacity and shipment volume but have large unit differences. Dual matching can avoid data misalignment
SCHEDULER_CRON_EXPRConfigured per data source, e.g., 0 0 2 1 * * for monthly data sources, */30 * * * * * for real-time data sourcesMatches the update cycles of different semiconductor data sources to avoid duplicate requests or delayed synchronization
API_AUTH_TYPEMultiple protocols availableSemiconductor data sources include multiple authentication methods such as API keys and OAuth2. Flexible configuration support is required to adapt to different access requirements

The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.

Three Common Configuration Errors

  • When calling the Embedding interface, the error Host '10.100.3.144' is not allowed to connect is returned. The cause is that the external system’s access whitelist does not include the IP address of the FastGPT deployment node, resulting in blocked interface requests.
  • Configured HTTP synchronization tasks fail to trigger execution. The cause is incorrect configuration of the SCHEDULER_CRON_EXPR parameter, or the scheduled task trigger time does not align with the data source’s update window.
  • Garbled characters appear after uploading a semiconductor due diligence CSV file. The cause is failure to specify the correct file encoding format. The default FastGPT encoding does not match the original file’s encoding, leading to abnormal field parsing.

How to Confirm Successful Configuration

  • Initiate a manual HTTP interface test request. Verify that returned fields fully match the configured mapping rules, and confirm that authentication protocols and request header configurations are active.
  • Upload a small semiconductor due diligence CSV file. Check that parsed fields and units match the original file, confirming normal file upload and parsing configurations.
  • Review scheduled task execution logs. Confirm that tasks matching the corresponding update cycles have triggered as planned, with no timeout or blocking errors.
  • Check the external system’s access logs. Confirm that FastGPT requests have been properly received, with no IP blocking or permission errors.

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.