What the data for this category looks like
Data for pharmaceutical distribution ledgers comes from internal enterprise ERP systems, warehouse WMS systems, and drug regulatory traceability platforms. Updates are synchronized in real time with purchase and warehousing, sales and outbound operations. Full inventory ledger updates are completed after daily inventory checks. Individual ledger documents include fields such as generic drug name, dosage form, specification, production batch number, expiration date, purchase quantity, sales quantity, inventory quantity, warehouse temperature and humidity values, inbound and outbound times, and regulatory traceability codes. Units include boxes, vials, tablets, degrees Celsius, and others. Some fields must comply with fixed format specifications from drug regulatory authorities.
Constraints on Multi-turn Dialogue and Prompt Engineering
The field diversity of multi-source data requires that multi-turn dialogue contexts accurately retain unique identification fields such as drug batch numbers and regulatory traceability codes, to avoid mixing data across batches. Drug regulatory format specifications require prompts to explicitly specify field output order and corresponding units. Results that do not meet these requirements cannot pass compliance checks. Real-time updated inventory and temperature and humidity data require that the valid duration of dialogue contexts be limited to 24 hours, to avoid calling outdated warehouse status data. For enumeration value restrictions on some fields, prompts must preset valid option ranges such as dosage forms and manufacturers, to reduce invalid matching.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Maximum Context | Previous 15 turns of dialogue or 12000 characters | Matches the number of fields in pharmaceutical distribution ledgers, avoids context overload |
| Context Filtering Rules | Only retain dialogue fragments containing drug batch numbers and temperature and humidity values | Reduces irrelevant information interference, focuses on core ledger data |
| Prompt Template | Fixed field order + unit requirements + drug regulatory compliance reminder | Complies with drug regulatory format specifications, ensures output meets regulatory requirements |
chatId | Bind exclusive identifiers per session | Distinguishes ledger sessions for different drug batches, avoids cross-session data mixing |
variables | Preset drug category and regulatory version variables | Quickly adapts to ledger aggregation requirements for different categories |
messages | Retrieve the first 10 historical messages in reverse chronological order | Controls context length, adapts to model processing capabilities |
Three Common Configuration Errors
- After submitting a model dialogue, a connection error prompt appears, and the issue persists after enabling a network proxy. The cause is failure to bind the model API key configured in
variablesto the proxy rules of the current access environment, resulting in failed request routing. - Drug images returned by the knowledge base cannot be correctly displayed by the model. The cause is that the prompt does not explicitly require the model to recognize and return the standard format of image links, or the knowledge base image storage path variable is not configured.
- Cross-batch drug data mixing occurs during multi-turn dialogue. The cause is failure to bind
chatIdfor session isolation, resulting in mixed invocation of dialogue fragments from different drug ledgers.
How to Confirm Configuration Is Complete
- Initiate a new ledger aggregation session, check whether a unique
chatIdidentifier is generated in the session details. - Enter a query containing multiple sets of drug data, confirm that the dialogue context only retains field fragments related to the current query.
- Submit the preset prompt template, check whether the output result matches the preset field order and unit requirements.
- Trigger a model request timeout scenario, confirm that the system's error prompt matches the configured timeout rules.
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.