What This Category’s Data Looks Like
Chemical pharmaceutical investment and research data primarily comes from public clinical trial reports, Chinese Pharmacopoeia, global patent databases, CDE approval public notice documents, and pharmaceutical company annual R&D reports. Clinical trial reports and patent literature are core data sources, with significantly different update cadences: clinical trial data is updated quarterly or at trial milestones, patent literature is released in real time, and pharmacopoeia standards are updated annually.
Documents include structured fields and unstructured text. Structured fields include CAS registry numbers, compound molecular weights, administration doses, IC50 values, etc., with units covering professional measurement standards such as mg/kg and nmol/L. A single long document (such as a multi-center clinical trial report) can reach hundreds of pages in length.
Constraints Imposed on Citation Source and Traceability
The professionalism and document characteristics of chemical pharmaceutical data impose clear constraints on the traceability link:
- Structured fields such as CAS numbers are the core basis for uniquely identifying documents, and must be prioritized during traceability, rather than relying solely on file names.
- The long document and multi-segment content structure requires that recalled text fragments must be accurately associated with specific chapters of the original document to avoid vague traceability information.
- Frequently updated data sources require that traceability information must include the last update time of the document, to prevent investment and research personnel from using expired data.
- The presence of professional measurement units requires that relevant fields be displayed synchronously during traceability to ensure the verifiability of cited content.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
recall count | Top 3-5 entries | Chemical pharmaceutical single documents have large content volume. Excessive recall will exceed the model context limit, and easily introduce professional literature fragments unrelated to the query |
similarity threshold | 0.75-0.85 | Chemical pharmaceutical data has strong professionalism. A higher similarity threshold is needed to filter low-correlation non-target literature and avoid interfering with core conclusions |
citation display format | Include document title, last update time, CAS number | Chemical pharmaceutical documents require clear identification of unique identifiers and update status, to facilitate investment and research personnel to trace original data |
segment length | 800-1200 characters | Chemical pharmaceutical documents include structural formulas, professional formulas and long sentences. Too long segments will destroy semantic integrity, while too short segments will increase token consumption |
PARSE_FILE_TIMEOUT_SECONDS | 1200 seconds | Single chemical pharmaceutical documents (such as multi-center clinical trial reports) have large volume and long parsing time. The timeout period needs to be extended to prevent parsing failures |
maxContext | 16000 | Adapt to the total token count after long document segmentation, to avoid exceeding the context limit of mainstream large models |
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 specific analysis. It is recommended to test on your own samples before finalizing.
Three Common Configuration Mistakes
- Phenomenon: The citation document source is displayed on the debug page, but no citation content appears on the officially released chat page. Cause: The citation display switch is only enabled in debug mode, and the "display citation source" option is not enabled in the global release configuration.
- Phenomenon: The output result of the program execution node cannot be used as background knowledge for subsequent dialogue modules. Cause: The output field of the program node is not mapped to the input parameters of the knowledge base search or context splicing module, and the data link is not bound.
- Phenomenon: After setting
citation limitto 2000, the short answer still exceeds the token limit. Cause: The limit is not adjusted based on the average token count of single chemical pharmaceutical documents. Recalling 2000 entries will accumulate token consumption far exceeding the model context, and the parameters are not adjusted based on document length.
How to Verify Successful Configuration
- Initiate a query containing chemical pharmaceutical professional terms, and check whether traceability information such as document title, last update time, and CAS number is displayed at the end of the reply.
- Access the released page, and verify that the displayed content of the citation source is consistent with that displayed on the debug page, with no missing or incorrect information.
- Submit a typical chemical pharmaceutical professional document, and check whether the parsing progress is completed within the time set by
PARSE_FILE_TIMEOUT_SECONDS, with no timeout errors. - Adjust the
recall countparameter, and verify that the number of cited documents in the reply matches the expected setting, with no excessive or insufficient recall results.
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.