What the data for this category looks like
Investment research data for the paint and ink industry comes from public industry association reports, raw material supplier real-time quotation platforms, downstream customer formula requirement documents, and third-party testing institution reports. Update rhythms vary significantly: raw material prices update daily, industry compliance standards are revised quarterly, and in-house company formula documents update on demand.
Document structures include three categories: standardized formula component tables, performance test reports, and weekly market analysis reports. Core fields include solid content, viscosity, and VOC content, with corresponding units of percentage, centipoise (cps), grams per liter (g/L). Some documents include batch numbers and implementation standard numbers.
What constraints do these characteristics impose on model access and configuration
The investment research data structure for the paint and ink industry is complex, with significant differences in field units. This creates three constraints for model access and configuration:
- Mixed multi-format documents (formula tables, test reports, weekly market reports) require parsing modules adapted for table extraction and long text segmentation, to avoid information truncation or loss.
- Real-time updated raw material price data and low-frequency updated compliance standards require configured differentiated synchronization cycles, to avoid ineffective data pulling or lag.
- Unit consistency requirements for core fields such as VOC content and viscosity require the model to associate unit matching logic during recall, preventing incorrect association of cross-unit numerical values.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_TABLE_ENABLE | Enabled | Paint and ink documents contain a large number of standardized formula component tables. Enabling this allows complete extraction of core fields such as components, proportions, and performance parameters |
CHUNK_SIZE | 800–1200 characters | The paragraph length of single-component descriptions and performance parameters in formula documents falls within this range. Excessively long chunks lead to loss of detail in vector embeddings, while excessively short chunks undermine semantic integrity |
UPLOAD_FILE_MAX_SIZE | 500 MB | Single-file sizes of industry compliance reports and large formula library documents mostly fall within this range, preventing upload size limit errors |
SIMILARITY_THRESHOLD | 0.75–0.85 | Matching core fields such as VOC content and viscosity requires high precision. This range filters low-relevance recall results while balancing accuracy and coverage |
RECALL_TOP_N | Top 6 entries | Investment research scenarios require balancing comprehensiveness and context length limits. Too many entries increase model inference pressure, while too few fail to cover multi-source market and formula information |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Parsing large formula library documents requires longer processing time. This duration prevents premature interruption of the parsing process |
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 it is recommended to test on your own samples before finalizing settings.
Three common configuration errors
- Issue: A 500 error is returned when importing large formula library documents. Cause: The
UPLOAD_FILE_MAX_SIZEconfiguration was not adjusted, and the file size exceeds the platform's default limit. - Issue: No response is received after sending a query after configuring a third-party model. Cause: The model interface address and key verification parameters were not configured correctly, or the context length exceeds the model's supported upper limit.
- Issue: Content returned when calling DeepSeek-class models includes <think> tags. Cause: The model output cleaning configuration was not enabled, or the prompt did not specify rules to remove the tags.
How to confirm the configuration is complete
- Upload a single typical formula document, check whether core fields such as components and performance parameters are fully extracted in the parsing result, and confirm that the table parsing switch configuration is enabled.
- Initiate a search for raw material prices, verify that the update time of the recalled documents matches the actual data source update rhythm, and confirm that the synchronization cycle configuration is reasonable.
- Adjust the similarity threshold and compare the relevance of recall results, confirming that the threshold value meets the accuracy requirements of the investment research scenario.
- Call the configured third-party model, check whether the returned content includes the expected format and fields, and confirm that the interface and key configuration are correct.
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.