What the data for this category looks like
Data sources for general comprehensive intelligent due diligence reports cover multiple channels including industrial and commercial public information, credit reports, industry regulatory documents, and counterparty disclosure materials. Data update cycles vary by source. Industrial and commercial information is updated quarterly, credit reports monthly, and regulatory documents are released in real time.
The document structure mixes structured fields and unstructured long text. Structured fields include subject name, unified social credit code, establishment date, litigation amount, and other items. Litigation amount is measured in ten thousand yuan. Unstructured sections include long text fragments such as abnormal operation records, compliance penalty explanations, and affiliated enterprise details.
What constraints these characteristics impose on model access and configuration
Mixed multi-source data requires the access link to support both structured field extraction and long text parsing. Timeout parameters adapted to the interface latency of different sources must be configured.
The length of unstructured long text fluctuates greatly, so reasonable segmentation rules must be set to avoid exceeding the model context window. Structured fields with units require the model to support format verification and normalization, so tool calling capabilities must be enabled.
The need to upload multiple attachments also requires configuring appropriate file size limits to avoid upload failures. The difference in update cycles of data from different sources requires configuring scheduled synchronization trigger rules to match the data refresh cycle.
Recommended Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Adapts to the mixed text length of general comprehensive intelligent due diligence reports, avoiding context overflow |
HTTP_REQUEST_TIMEOUT | 600 seconds | Compatible with the return latency of regulatory and credit reporting interfaces from multiple sources |
functionCall | enabled | Supports automatic extraction of structured fields such as unified social credit code and litigation amount |
chunkSize | 1200–1800 characters | Splits long text fragments to adapt to single-segment model input limits |
PARSE_FILE_MAX_SIZE | 200 MB | Accommodates multiple attached files included with due diligence reports |
RECALL_TOP_K | Top 10 entries | Covers affiliated enterprise and compliance record data from multiple sources |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require case-by-case analysis, and it is recommended to test on your own samples before finalizing.
Three Common Configuration Mistakes
- Long text returned by workflow HTTP API calls gets truncated or causes model errors. Cause: The
chunkSizeparameter is not configured, and long text is not segmented, causing a single text segment to exceed the model context window. - The content extraction node cannot call the self-built model interface, and no valid return results appear after configuration. Cause: The access address and key of the self-built model are not correctly configured in the system configuration, or
functionCallis not enabled to support structured field extraction. - When creating a knowledge base, the locally deployed chatglm2 model cannot be selected, and the model list is empty. Cause: The mapping information for this model is not added in the oneapi configuration, or the local model of xinference V1 version does not correctly expose the port.
How to Confirm Proper Configuration
- Upload a single standard due diligence report sample, run the test workflow, and verify whether the structured extraction results cover preset fields such as subject information and litigation records.
- View the workflow execution logs to confirm that no timeout errors occur in HTTP requests, and that segmented text fragments are correctly sent to the model.
- Check the system configuration page to confirm that the locally deployed model is displayed in the access list, with no connection error prompts.
- Trigger the content extraction node to verify whether litigation amounts with units and date fields can be correctly identified and normalized.
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.