What the data for this category looks like
Public industry association reports, customs import and export filing data, annual public information from production enterprises, and compliance reports from third-party testing institutions provide the primary source of due diligence data for chemical raw materials. Data update cycles fall into three categories: spot price data updates monthly, production capacity and import and export volume updates quarterly, and industry compliance standards update annually. A single standardized due diligence document includes fields such as product name, CAS number, production capacity and output, monthly average price, import and export scale, hazardous chemical classification and grade, and list of upstream and downstream cooperative enterprises. The CAS number is a 10-character string with hyphens. Price units use yuan per ton, production capacity units use ten thousand tons per year, and compliance indicator fields include clear grading standards.
What constraints these characteristics impose on multi-turn dialogue and prompt engineering
Unique field requirements for chemical raw material data require multi-turn dialogue to verify the format of precise identifiers such as CAS numbers, to avoid query deviations. The scattered document structure across multiple fields requires prompts to clearly specify rules for recalling relevant documents, to prevent missing upstream and downstream or compliance data in returned results. Frequently updated spot price data requires multi-turn dialogue to proactively prompt users to specify a data update cycle, to avoid using expired information. Unified unit specifications require prompts to enforce standardized wording for price and capacity units, to prevent misunderstandings caused by mixed units across categories.
How to set configurations
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Chemical raw material due diligence reports contain multiple types of scattered fields. Multi-turn dialogue needs to accommodate multi-round parameter queries and associated results. Sufficient context ensures coherent dialogue logic. |
RECALL_TOP_N | Top 6–8 results | Chemical raw material data has many and scattered fields. A sufficient number of recalled related documents is required to cover multiple types of information such as production capacity, prices, and compliance. |
SIMILARITY_THRESHOLD | 0.75–0.85 | Precise fields such as CAS numbers require high similarity to ensure matching accuracy. Thresholds can be appropriately relaxed for vague information such as price trends. |
PARSE_FILE_TIMEOUT_SECONDS | 120 seconds | A single chemical raw material due diligence report may contain multiple pages of test data and tables. Parsing takes longer than for general documents. |
maxTokens | 2000–3000 characters | Due diligence report responses need to cover detailed descriptions of multiple types of fields, to avoid truncation of critical information due to token limits. |
KNOWLEDGE_BASE_REFRESH_INTERVAL | 7 days | Spot prices are updated monthly. Regularly refreshing the knowledge base ensures the timeliness of returned data. |
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. It is recommended to test on your own samples before finalizing settings.
Three Common Mistakes
- Phenomenon: The maximum response tokens for some questions automatically switch to 200, and reply content gets truncated. Cause: The global
maxTokensconfiguration is set to 200, and no separate adjustment is made to token allocation rules for dialogue rounds to support the long content requirements of chemical raw material due diligence. - Phenomenon: Format errors appear after entering guidance configurations in the debug preview interface. Cause: The custom thesaurus does not include chemical raw material-specific fields such as CAS number and ten thousand tons per year, triggering the system's format verification block.
- Phenomenon: The question optimization phase of multi-turn dialogue takes more than 5 seconds. Cause: The
fast_prompt_optimizeswitch is not enabled. Using full context to generate prompts increases computational load.
How to Confirm Successful Configuration
- Initiate a query that includes a specified CAS number, and verify that returned results include accurate information for corresponding fields such as product name and price.
- Initiate three consecutive progressive queries, such as first asking about production capacity, then asking about the corresponding monthly price, and finally asking about upstream and downstream enterprises. Verify that the dialogue context retains key parameters from prior queries.
- View the knowledge base refresh log, and confirm that chemical raw material-related documents from the past 7 days have completed automatic updates.
- Test a query that includes unit confusion, such as mentioning both yuan per ton and yuan per kilogram. Verify that recalled results filter data with non-specified units according to configuration rules.
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.