What the data for this category looks like
Organizations including national pharmaceutical product regulatory authorities, the Ministry of Commerce, and provincial and municipal drug regulatory departments publish official public announcements that serve as the source of policy data for the pharmaceutical distribution sector. This data updates irregularly alongside new regulatory policy releases and adjustments to circulation standards. Documents are multi-chapter official communications, containing document numbers, issuing entities, effective dates, applicable scenario clauses, penalty provisions, attachment lists, and more. Fields include unique policy identifiers, applicable regions, execution periods, compliance requirement entries, with units typically being serial numbers, monetary amounts in yuan, and standard date formats.
What constraints these characteristics impose on model integration and configuration
The authoritative nature of official policy data requires integrated models to accurately output compliant content. The long-text official document structure requires models to support long-context processing to fully retain the associative relationships between policy clauses. The irregular update cycle requires knowledge base synchronization configurations to support flexible trigger mechanisms that adapt to update requirements from temporarily released policies. The multi-field structured document format requires the retrieval link to accurately match fields such as policy identifiers and applicable regions, to avoid mismatching policies across scenarios.
How to set configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Range | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Pharmaceutical distribution policy documents are mostly long texts, requiring complete retention of contextual associations to accurately link policy clauses |
maxTokens | 2000–3000 token | Policy Q&A requires complete output of clause content, avoiding truncation of critical compliance information |
quoteMaxToken | 1500 characters | Accurate quoting of original policy text fragments requires controlling the length of individual quoted segments to ensure answer clarity |
temperature | 0.1–0.3 | Policy Q&A requires strict accuracy; reducing random output avoids compliance risks |
AIPROXY_API_ENDPOINT | Locally deployed model interface address | Ensures local processing of policy data meets regulatory compliance requirements |
AIPROXY_API_TOKEN | Custom secure access token | Restricts unauthorized interface access to protect the security of policy data access |
Three common configuration mistakes
- Symptom: Model interface call returns 401 unauthorized error. Cause:
AIPROXY_API_TOKENis not configured correctly, or the token permissions do not cover the current access scenario. - Symptom: AI model dropdown list is empty in workflows. Cause: Model integration configuration is not completed, or the interface address has formatting errors.
- Symptom: Policy content output by the model has truncated clauses. Cause:
maxTokensvalue is too low, failing to meet the length requirements of complete policy clauses.
How to confirm configuration is complete
- Verify that the filled content of
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKENmatches the locally deployed model interface parameters. - Upload a single pharmaceutical distribution policy document, launch targeted Q&A testing, and check whether the model can accurately return the corresponding policy clauses.
- Adjust the
temperatureparameter and launch multiple tests to confirm that the rigor of the output content meets expectations. - Trigger a knowledge base synchronization operation, check that there are no abnormal errors in the synchronization log, and verify that the update process functions normally.
The values provided are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.