What this category's data looks like
Data for chemical fiber research reports comes from three main sources: public statistics from the China Chemical Fiber Industry Association, public disclosures from domestic integrated refining and chemical enterprises, and industry survey data from professional chemical consulting institutions. Two update schedules are used. Monthly regular industry analysis reports are updated on a natural monthly cycle. Special reports covering raw material price fluctuations or capacity adjustments are released on demand. Each individual document includes modules such as overall industry overview, core product price trends, capacity utilization rate, and raw material supply and demand gaps. Fields include product category, statistical cycle, corresponding value, and associated raw material category. Numeric units use standard industrial measurement units, including yuan/ton, ten thousand tons, and hours.
Constraints from these characteristics during model access and configuration
The standardized fields and cross-category association features of chemical fiber research reports require precise field mapping rules during model access. This prevents the model from confusing values across different products. Special reports released on demand have no fixed update cycle. The configuration must support a data source synchronization mechanism that combines manual triggers and scheduled tasks. Uniform industrial units require a unit validation node. This node automatically filters abnormal entries with mismatched units during data import. The strong correlation of core indicators requires retaining recall rules that preserve contextual associations between indicators. This ensures the model can link corresponding raw material and finished product values when generating answers.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Chemical fiber research reports contain multiple sets of associated indicators per document. Sufficient context is needed to link product and raw material data |
RECALL_TOP_N | Top 15 entries | Core indicators for chemical fiber research reports are concentrated. Too many recall results will introduce irrelevant data |
SIMILARITY_THRESHOLD | 0.72–0.78 | Indicators in the chemical fiber industry have strong numerical correlation. Low-similarity redundant recall results must be filtered |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Individual chemical fiber research reports may contain multi-page long tables, leading to longer parsing times |
SYNC_CRON_EXPRESSION | 0 0 2 * * ? | Regular monthly reports are synchronized at 2 AM each month. On-demand synchronization can be covered via manual triggers |
FIELD_MAPPING_RULES | Map product names, prices, and capacity to standardized fields | Chemical fiber research reports have many product categories. Unified field names are required to prevent model confusion |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require targeted analysis. It is recommended to test on your own samples before finalizing settings.
Three common configuration mistakes
- Scenario: After upgrading to version 9.0, calls to the m3e embedding model return failures. API keys and access addresses are configured correctly. Cause: Version 9.0 added version validation rules for embedding models. A version number parameter for the corresponding model must be added to the model configuration.
- Scenario: When deploying a reranking model locally, the interface displays "request error". The running version is 4.8.22. Cause: The port of the local reranking model is not open to the network where FastGPT is deployed, or the startup command for the reranking model does not specify the correct model path.
- Scenario: When concurrent requests increase, model response delay rises significantly. Background logs show frequent queries and writes to MongoDB. Cause: The
CONCURRENT_LIMITparameter is not configured to limit concurrent requests, leading to exhaustion of the MongoDB connection pool and slowed overall response.
How to confirm proper configuration
- Upload a single chemical fiber research report document, check parsed fields match the preset
FIELD_MAPPING_RULES, and confirm no field confusion occurs. - Submit a simulated retrieval request, verify the number of recalled documents matches the
RECALL_TOP_Nconfiguration, and no obvious irrelevant content is present. - Manually trigger a data source synchronization, review synchronization logs for abnormal entries with unit mismatches or parsing timeouts.
- Adjust concurrent request volume, observe background logs for MongoDB connection-related exceptions, and confirm the connection pool configuration aligns with the current concurrent scale.
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.