What the data for this category looks like
The core data for this category covers three roles: advertising platform compliance teams, agency legal teams, and brand marketing teams. Daily documents include four core file types: advertising review forms, qualification attachments, delivery records, and rectification notices. Data sources include advertising platform backends, customer qualification systems, contract management systems, and public regulatory rule databases. Update frequency follows individual advertising campaign cycles, with monthly syncs for new campaigns. Data fields include campaign ID, review status, qualification number, delivery time window, rectification requirements, and more. There is no fixed single-data entry length. Values adjust dynamically based on campaign scale.
What constraints these characteristics impose on multi-turn dialogue and prompt engineering
Scattered data sources require multi-turn dialogue to integrate field information from different systems. Prompts must adapt to multiple document structures such as advertising review forms and delivery records. Update cycles tied to individual campaigns require dialogue context to be limited to the corresponding campaign period. This prevents interference from invalid data across different campaigns. The high-stakes nature of errors requires multi-turn dialogue to fully retain all consultation and response content. This supports subsequent compliance traceability. The most time-consuming tasks of qualification archiving and rectification evidence organization require prompts to automatically extract key information from conversations. This reduces manual organization costs.
How to set up configurations
The following configurations are based on FastGPT v4.17.0 feature logic:
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
chatId | Bind to the campaign ID corresponding to a single consultation | Ensure multi-turn dialogue context for the same campaign is not mixed up, and facilitate subsequent compliance archiving and traceability |
messages | Retain the most recent 30 dialogue context entries | Cover the full consultation chain within a single advertising campaign cycle, avoid token overflow or context truncation |
variables | Bind dedicated field variables for advertising review forms and delivery records | Automatically retrieve field information from corresponding business documents, reduce manual input for prompts |
| Maximum context length | 8000–12000 characters | Match the total content of multi-turn dialogue and business documents required for compliance record-keeping. This is a calibrated adjustable range based on testing |
| Prompt trigger rule | Match corresponding templates by consultation type | Automatically call matching business document fields for different scenarios such as compliance consultations, qualification queries, and rectification follow-ups |
Three common configuration mistakes
- Symptom: Multi-turn dialogue context cannot be referenced by subsequent questions. Returned results only include content from the current single-turn query. Cause: The
chatIdparameter is not correctly bound. Each request generates a separate session ID, and historical dialogue context is not carried over. - Symptom: Token limit exceeded errors are returned when calling the interface. Complete delivery records and rectification notices cannot be loaded. Cause: The number of retained
messagesentries is not limited. Accumulated context exceeds the system allowed length. - Symptom: Customer qualification attachment content cannot be retrieved during dialogue, and prompt fields are empty. Cause: No data source mapping for qualification attachments is configured in
variables. Prompts cannot automatically obtain associated information from the corresponding files.
How to confirm configurations are correct
- Launch a simulated compliance consultation. Input keywords from historical campaign delivery records. Verify that returned content includes context information from the corresponding historical dialogue.
- Call the interface with
chatIdvalues for different campaigns. Confirm that each session’s context only links to consultation content for the corresponding campaign, with no cross-campaign data mixing. - Upload test qualification attachments. Trigger a qualification query command in the dialogue. Verify that relevant field information from the attachments is correctly retrieved.
- Launch multiple consecutive queries. Confirm that the system correctly accumulates dialogue content, with no context truncation or loss.
The values provided here are common starting points, and should be evaluated against the user’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 2026-10-19.