This configuration is based on FastGPT v4.17.0.
What the data for this category looks like
Data for this category typically comes from CRM systems, product usage backends, ticket statistics ledgers, and contract management systems. Update cycles follow weekly or monthly schedules. Core documents include customer health reports, renewal forecast sheets, high-risk customer lists, and cross-department meeting minutes. Data fields include customer unique identifiers, health scores, renewal risk levels, contract expiration dates, recent cycle usage frequency, and more. There are no unified fixed units. Adaptation is required based on the document's usage scenario.
What constraints do these characteristics impose on the citation sources and traceability link?
Multi-data source collection logic requires the traceability link to bind unique data identifiers for each system. This ensures cited content can be traced back to the original ledger. Weekly or monthly update cycles limit the valid time window for cited data. Configurations must restrict calls to datasets that have completed updates in the current cycle. Diverse document formats require traceability rules to adapt to mapping logic for different fields. This avoids field mismatches during cross-document citations. Clear business risk consequences require traceability information to include complete operation links. This facilitates subsequent verification and adjustments.
How to set the configuration
| Config Item | Recommended Setting | Rationale for This Setting |
|---|---|---|
| Maximum citation token count | 800–1200 token | Matches the typical content length of renewal health reports, avoids exceeding context limits |
| Number of citations per request | Top 3–5 entries | Adapts to the typical display quantity of high-risk customer lists, avoids information overload |
| Citation data scope | Datasets from the most recent update cycle | Adapts to weekly or monthly update cycles, ensures data timeliness |
| Citation field mapping rules | Bind corresponding fields by document type | Adapts to diverse daily document structures, avoids field mismatches |
detail parameter switch | Enabled | Used to output complete citation source details, meets traceability verification needs |
responseData return format | Structured JSON | Facilitates automated parsing of citation links later, adapts to reporting needs of customer success teams |
quoteMaxToken parameter | Calibrated based on actual testing | Adapts to high-risk customer list content of different scales, avoids truncation of critical information |
Three common mistakes
- Phenomenon: The API returns status code 200, but the
responseDatafield is empty. Cause: The return configuration for theresponseDataparameter is not enabled, or the citation data scope exceeds the valid dataset of the current update cycle. - Phenomenon: Cited content displays messy formatting, including redundant original document field names. Cause: No field mapping rules bound by document type are configured, and full field content of raw data is cited directly.
- Phenomenon: Cited content is truncated or garbled. Cause: The
quoteMaxTokenparameter value is too small, causing long text content to be forcibly truncated, or the encoding format of multi-system data sources is not adapted.
How to confirm the configuration is complete
- Check the
detailfield returned by the API, confirm it includes the source system, update time, and original document identifier of the cited data. - Randomly select one dataset corresponding to a document type, verify the matching degree between the returned cited content and the original document fields.
- Call the API to test the return of long text content, confirm no forced truncation occurs.
- Compare the currently updated dataset with the citation data scope configuration, confirm only content within the valid cycle is called.
The values provided here are common starting points, and should be evaluated using samples from the specific deployment in use.
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.