What this category of data looks like
Data sources include internal enterprise production scheduling logs, inventory and sales data from supply chain collaboration systems, and monthly industry supply and demand reports and policy documents publicly available. Production and inventory and sales data are updated daily, while industry report data is updated weekly. Document structure falls into two categories: structured tables and unstructured text. Structured fields include product model, daily production capacity, inventory balance, ex-factory unit price, and downstream application scenarios, with corresponding units of ton, piece, yuan/ton, and %. Unstructured documents include industry research reports, competitor marketing materials, and internal marketing script libraries, with two format types: standard tables and free text.
What Constraints These Characteristics Impose on Model Integration and Configuration
Structured data with multiple fields and complex units requires precise field mapping and unit conversion rules to avoid model input format errors. Daily updated real-time data requires configuring scheduled pull or event-triggered synchronization mechanisms during the integration phase to ensure data timeliness. Diverse formats of unstructured materials require configuring custom document parsing rules to adapt to industry documents and marketing materials with different layouts. Detailed downstream application scenario fields require configuring tag-based recall rules to ensure that the marketing content recalled by the model matches precise target customer groups. Access requirements from multiple data sources require configuring multi-account permission management to adapt to parallel calls of multiple sets of production and sales data within the enterprise.
How to Set Configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Coal chemical industry research reports and large inventory and sales logs have lengthy content; 300 seconds allows complete parsing |
UPLOAD_FILE_MAX_SIZE | 2048 MB | Adapts to the maximum storage specification for single coal chemical production logs and industry reports |
maxContext | 8000–12000 characters | Covers complete marketing content context including coal chemical product parameters, downstream applications, and policy information |
RECALL_TOP_N | Top 6–10 entries | Coal chemical downstream application scenarios have many subdivisions; 6-10 recall results can cover main customer group needs |
SIMILARITY_THRESHOLD | 0.78–0.82 | Balances relevance and coverage of marketing content, avoiding recall of irrelevant or low-precision content |
MULTI_ACCOUNT_ENABLE | Enabled | Coal chemical enterprises typically have multiple sets of production and sales data accounts; multi-account access permissions need to be configured |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require case-by-case analysis, and testing on internal samples should be conducted before finalizing settings.
Three Common Misconfigurations
- Symptom: An error message
invalid configuration parameter name "hnsw.max_scan_tuple"is returned during knowledge base search. Cause: Vector database parameter naming rules are not configured correctly. The multi-field attribute of coal chemical structured data causes a conflict between the parameter name and the system's preset rules. - Symptom: When multiple model accounts are configured, only the first account can successfully call
qwen-max. Cause: Independent call permissions and quotas are not bound to each account, and the multi-account access configuration item is not enabled. - Symptom: When parsing coal chemical production logs, the production capacity values of some products cannot be extracted correctly. Cause: Custom field parsing rules are not configured, and the numerical field format with mixed units in the logs is not adapted.
How to Confirm Configurations Are Correctly Set
- Upload a coal chemical industry research report, check the completeness of the parsing result, and adjust parsing timeout and file size configurations until parsing succeeds.
- Initiate a content recall test, verify the quantity and relevance of the recall results, and adjust the value range of the number of recalled entries and similarity threshold according to the subdivided scenarios of target customer groups.
- Configure multiple data accounts and initiate a data synchronization test, confirm that all accounts can normally pull information from corresponding data sources, and verify that multi-account access permissions take effect.
- Initiate a model generation test based on integrated data, confirm that the model can generate content matching marketing needs, and verify that the context length configuration adapts to content carrying requirements.
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.