What Data for This Category Looks Like
The data for special steel intelligent due diligence reports primarily comes from special steel enterprises’ production execution systems, quality inspection reports, raw material purchase ledgers, downstream customer order data, and industry supply and demand monitoring information. Data update frequencies vary: production batch-related data updates after each furnace production is completed, quality inspection reports are generated upon completion of each product batch inspection, and industry supply and demand data updates monthly.
Documents primarily consist of a mix of structured Excel ledgers and unstructured PDF quality inspection reports, including fields such as production batch identifiers, alloy composition test items, mechanical performance parameters, raw material purchase batches, and downstream order delivery requirements. They involve professional industrial measurement units including weight, duration, and mechanical performance units.
What Constraints These Characteristics Impose on Deployment and Upgrade
The mixed document structure of special steel data requires configuring adaptation rules for both structured and unstructured parsing during deployment, to avoid generic parsing logic damaging the integrity of specialized fields.
Discrete update frequencies require adapting batch-style incremental synchronization logic during upgrades, to reduce invalid data processing. Dedicated industrial fields and measurement units require configuring custom field mapping rules, to prevent generic parsing modules from misidentifying parameter items.
Additionally, the size of individual quality inspection reports is typically larger than standard office documents, which imposes higher requirements on upload file limits and parsing timeout thresholds.
How to Set Configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 1000 MB | Individual special steel quality inspection reports often exceed the default general limit, requiring adaptation to the actual size of industrial documents |
PARSE_SPLIT_CHUNK_SIZE | 1500 characters | Special steel test reports contain multiple sets of related industrial parameters; segmentation must cover complete parameter groups to avoid parsing breaks |
PARSE_STRUCTURED_FIELDS | Bind custom field rules by uploaded file type | Special steel data includes dedicated industrial fields; extraction logic for items such as alloy composition and mechanical performance must be specified |
SYNC_INCREMENTAL_TRIGGER | Triggered by new file uploads | Special steel production batch data is generated discretely, adapting to the incremental update rhythm of batch-style data |
VECTOR_MODEL_MLA_ENABLE | Enabled | Special steel has a large number of specialized terms; the MLA vector model can optimize recall accuracy for long texts and specialized terms |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Parsing long quality inspection reports takes more time; extending the timeout threshold avoids parsing interruptions |
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 individual analysis, and testing on internal samples prior to finalizing settings is recommended.
Three Common Misconfigurations
- After upgrading to version v17, calls to the GPT-4o-mini model via the OpenAI channel return a
400 Bad Requesterror. The interface parameter adaptation rules for the channel model were not updated synchronously, and the legacy configuration does not comply with the input format requirements of the new model version. - Uploading a 2 MB special steel quality inspection report triggers an upload failure prompt. The
UPLOAD_FILE_MAX_SIZEparameter was not adjusted, and the default general small file limit was retained, failing to adapt to the size requirements of special steel industrial documents. - When configuring the DeepSeek model, the vector model MLA function does not take effect, and professional term recall results do not meet expectations. The
VECTOR_MODEL_MLA_ENABLEswitch was not enabled, or the corresponding MLA-optimized vector model was not bound.
How to Confirm Proper Configuration
- Upload a standard-sized special steel quality inspection report, check that the upload progress bar completes without error prompts, confirming that the upload limit configuration is active.
- Trigger an incremental synchronization for a new batch of data, review the synchronization log to confirm only newly uploaded batch data is displayed, verifying that the incremental synchronization trigger rule is correct.
- Call the DeepSeek model to test recall of professional industrial parameters, review the vector recall results to confirm correct field information is included, verifying that the MLA function is enabled.
- Review the structured parsing results to confirm dedicated fields such as alloy composition and mechanical performance are correctly extracted, verifying that the structured field mapping rules match the special steel data format.
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.