What the Data for This Category Looks Like
The data for biologics intelligent due diligence reports primarily comes from the National Medical Products Administration batch issuance database, publicly available clinical trial registration materials from enterprises, and quality standard documents published in the Pharmacopoeia. Data update frequency changes based on declaration progress and batch issuance cycles, with no fixed schedule. Each document is divided into a structured field section and a long text description section. Structured fields include active ingredient content, production batch number, expiration date, batch issuance number, and similar items. The long text section includes clinical trial data, production process descriptions, and other content.
Constraints Imposed on Workflow Orchestration by These Characteristics
Multiple data sources with no fixed update cycle require workflows to support dynamic access to multi-source data nodes, and configure flexible triggering mechanisms to adapt to different declaration and batch issuance rhythms. Documents contain both structured fields and long text content, requiring workflows to support both structured field extraction and long text chunk parsing, and adapt to input in different formats such as PDF forms and Word reports. Fields include special units and customized naming rules, requiring workflows to configure field mapping and verification nodes to avoid inconsistent data formats after extraction, which would affect subsequent due diligence report generation.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Biologics documents include long clinical trial text, so parsing takes longer than general documents. 600 seconds covers parsing needs for most scenarios |
BATCH_EXECUTE_MAX_ITEMS | 30–50 items | A single due diligence report requires processing multiple batches of batch issuance data. Limiting the number of batch sub-items prevents node execution overload |
LLM_THINKING_CONTROL | Manually enable/disable per node | Biologics due diligence requires rigorous reasoning. Enable thinking chains for complex process analysis, disable them for simple field verification to improve efficiency |
UPLOAD_FILE_MAX_SIZE | 200 MB | Attachments for clinical trial reports often include high-resolution images and raw data. 200 MB covers upload requirements for most conventional attachments |
GLOBAL_VAR_APPEND_MODE | Append in execution order | Sub-item results from batch execution nodes must be passed outside the loop in execution order to ensure the result order of the due diligence report matches the batch order |
The parameter values provided on this page are common recommendations for establishing configuration baselines. Actual values are affected by material format, data volume, and business rules. Specific issues require targeted analysis. Testing on local samples is recommended before finalizing settings.
Three Common Configuration Mistakes
- Symptom: After all sub-items of a batch execution node complete execution, only the result of the last sub-item is obtained outside the loop. Cause:
GLOBAL_VAR_APPEND_MODEis not configured to append in execution order. The default logic overwrites the global variable and does not retain all sub-item content. - Symptom: After an error occurs in a model request node, the workflow terminates directly with no error prompt. Cause: Error capture configuration for the node is not enabled, and no subsequent processing flow is configured for the error branch.
- Symptom: Thinking chains are always enabled for model nodes and cannot be turned off via configuration. Cause: The
LLM_THINKING_CONTROLparameter is not configured correctly, and the logic between the global switch and per-node independent configuration is confused.
How to Verify Proper Configuration
- Upload a test biologics document containing both structured fields and long text, confirm that parsed fields cover active ingredient content, production batch number, and similar items, and verify that the parsing configuration adapts to the document structure.
- Initiate a batch execution test, submit multiple simulated batch issuance data sets, confirm that the global variable retains all sub-item results in execution order, and verify that the append configuration is active.
- Trigger a model node error scenario, confirm that the error branch is triggered and corresponding error logs are generated, and verify that the error capture configuration is active.
- Upload multiple test files, confirm that the workflow recognizes all uploaded files and proceeds to subsequent processing steps, and verify that the multi-file upload configuration is active.
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.