What the data for this category looks like
Chemical raw materials investment research data comes from multiple sources. These include industry association monthly supply and demand reports, listed company segment annual reports, customs import and export declarations, supplier real-time quotation sheets, Material Safety Data Sheets (MSDS), and patent literature. Data update rhythms vary widely. Spot quotations are updated daily. Industry supply and demand reports are released monthly or quarterly. Annual reports and patents are updated annually or on an irregular basis. Document formats include structured production capacity, price, and inventory tables. They also include semi-structured PDF analysis reports, and plain-text industry interpretation content. Core fields include CAS number, purity, production capacity unit, price unit, total inventory, and other related fields.
What constraints these characteristics impose on context and token processing
The multi-format and varied update rhythms of chemical raw materials investment research data create multiple constraints for context and token processing. Structured tables contain large numbers of numerical and unit fields. The token usage of a single table is higher than plain text content. When splitting chunks, structural integrity and token limits must be balanced. Real-time spot quotations are updated at high frequency. Knowledge base context recall must prioritize matching the latest data, which expands the effective context filtering scope. Single industry analysis reports or patent literature generally have high token lengths. Documents exceeding basic chunking thresholds require splitting. Splitting must avoid disrupting field logic that links upstream and downstream industrial chains. Field content that uses multiple units requires extra verification of unit consistency during context splicing. This prevents invalid token usage.
Configuration settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
Segment Length | 800–1200 characters | Balances the structural integrity of structured tables and single-chunk token usage, prevents single chunks from exceeding model context limits, and adapts to the multi-format characteristics of chemical raw materials documents |
maxContext | 4000–6000 tokens | Chemical raw materials investment research requires linking upstream and downstream supply and demand, historical quotations, and industry analysis, so sufficient context space is needed to carry associated information, while adapting to the standard context windows of mainstream large models |
UPLOAD_FILE_MAX_SIZE | 50 MB | Adapts to the batch upload needs of single industry reports, patent literature, or multiple supplier quotation sheets, and reserves reasonable file storage and parsing space |
Recall Count | Top 8–12 entries | Covers the multi-dimensional data entries required for chemical raw materials investment research, while avoiding excessive redundant token usage of context quotas, and balancing recall accuracy and resource usage |
Chunk Overlap Length | 50–100 characters | Prevents loss of cross-chunk field associations, such as upstream and downstream industrial chain connection data, and numerically ordered sequences with unified units |
PARSE_FILE_TIMEOUT_SECONDS | 120 seconds | Adapts to the parsing time of large structured tables and long PDF industry reports, and ensures complete completion of the chunking and token calculation process |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by document format, data volume, and business rules. Specific issues require specific analysis. It is recommended to test on your own samples before finalizing settings.
Three common configuration mistakes
- Phenomenon: Context fragments returned after knowledge base parsing lose table structure, or single-segment content is truncated. Cause: The
segment lengthwas not adjusted based on the structured table characteristics of chemical raw materials. An overly short chunking threshold was used, leading to table splitting and damage. - Phenomenon: Token limit exceeded prompts appear during calls, even if the model maxToken setting is adjusted to a high value. Cause: The
maxContextconfiguration was not adjusted synchronously. The total token count of context recalled by the knowledge base exceeds the actual bearable window of the model, and does not match the model's own maxToken setting. - Phenomenon: Some images fail to parse after upload, while others load normally. Cause: The
UPLOAD_FILE_MAX_SIZElimit was not set, or the rules for converting images to text tokens were not adapted to the multimodal needs of chemical raw materials investment research. Token conversion for oversized images exceeds configuration limits.
How to confirm correct configuration
- Upload a typical chemical raw materials industry PDF report. Check the number of parsed chunks and the integrity of single-chunk content. Confirm the adaptability of
segment lengthandchunk overlap length. - Initiate an investment research query. Verify that the number of recalled context entries matches the
recall countconfiguration. Confirm that the total context token count does not exceed the preset limit. - Test uploading structured tables and image files of different sizes. Confirm that the upload and parsing processes do not trigger timeout or limit error prompts. Verify the rationality of the
UPLOAD_FILE_MAX_SIZEandPARSE_FILE_TIMEOUT_SECONDSconfigurations. - Check the knowledge base parsing logs. Confirm that the post-chunking token calculation results match the
maxContextconfiguration interval. Avoid potential context overflow issues.
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.