Workflow Orchestration for IT Service Intelligent Due Diligence Reports

Data sources for IT service intelligent due diligence reports include qualification materials self-submitted by partner service providers of financial

What the Data for This Category Looks Like

Data sources for IT service intelligent due diligence reports include qualification materials self-submitted by partner service providers of financial institutions, compliance filing information publicly available on financial regulatory platforms, audit reports issued by third-party audit institutions, and delivery records archived from client projects.

Data update frequencies vary. Qualification certification data is updated once per year. Project delivery records are synced in real time as services are completed. Operation and maintenance response records are updated daily.

Most documents combine structured table fields and unstructured attachments. Structured fields include the service provider’s unified social credit code, qualification certification scope, past service project list, and operation and maintenance response time records. Unstructured attachments are mostly PDF-format compliance self-inspection reports and qualification scan copies. Some semi-structured data comes from operation and maintenance ledger Excel files.

What Constraints Do These Characteristics Impose on Workflow Orchestration

Multi-source and heterogeneous data sources require workflows to support multiple input nodes for connecting to public APIs, locally uploaded files, and third-party system interfaces.

Mixed structured and unstructured data structures require workflow configurations to distinguish between field extraction and full-text understanding parsing nodes, to adapt to input content in different formats.

Differences in data update frequencies require workflows to support both scheduled scheduling and real-time triggering modes, to handle batch historical data and incremental real-time data respectively.

Correlation verification logic exists between fields. For example, the qualification certification scope must match the service project list. This requires workflow configurations to include conditional branch nodes to complete compliance checks.

Some data exists as scan copy attachments, which requires workflows to pre-configure OCR parsing nodes to extract text.

Configuration Settings

The following configurations apply to workflow orchestration in FastGPT 4.10.0 and later versions.

Configuration ItemRecommended ValueRationale
maxContext10–20 itemsIT service due diligence reports need to associate multiple project records and qualification documents. Excessive context will cause redundant model processing, while insufficient context will fail to cover necessary associated information
LOOP_MAX_TIMES3 timesCycle checks for IT service due diligence, such as qualification validity verification and data consistency verification, should not exceed 3 times to avoid workflow blocking
PARSE_FILE_MODEstructured_firstIT service due diligence data includes structured ledgers and unstructured reports. Prioritizing structured field extraction can improve overall processing efficiency
CODE_RUNNER_ENABLEDEnabledIT service due diligence requires batch verification of unified social credit code compliance and calculation of service response time. Code components enable custom logic
FILE_UPLOAD_MAX_SIZE500 MBCompliance report attachments are usually multi-page PDFs or scan copies. This value covers most business scenarios
PARSE_FILE_TIMEOUT_SECONDS300 secondsParsing large compliance reports takes a long time. This setting prevents workflow interruptions due to timeouts

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

Three Common Misconfigurations

  • Symptom: The workflow executes in a loop beyond the configured LOOP_MAX_TIMES without terminating as expected. Cause: The loop termination condition is not correctly bound, or the LOOP_MAX_TIMES parameter is not set to a valid value.
  • Symptom: Uploaded scan copy compliance reports are not parsed correctly, and only garbled text is extracted. Cause: PARSE_FILE_MODE is not configured as ocr_first, so the default parsing logic cannot recognize printed text in scan copies.
  • Symptom: Workflows fail to execute after multiple code runner components are added. Cause: The global code runner pool configuration is not enabled, or independent runtime timeout parameters are not set for each code component.

How to Verify Proper Configuration

  • The workflow test page is accessed, an IT service qualification scan copy is uploaded, and the parsing node is verified to correctly extract fields including the unified social credit code and qualification scope.
  • After cycle check logic is configured, a test run is triggered, and workflow logs are reviewed to confirm the number of cycles does not exceed the set LOOP_MAX_TIMES.
  • Multiple code runner components are added, a test run is triggered, and each component’s output results are checked for correct writing to downstream nodes.
  • The context details of the AI node are reviewed, and the number of displayed context items is confirmed to match the configured maxContext.

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.