What this category of data looks like
This category of data is typically produced and maintained by data project managers, data engineers, or customer algorithm teams. Core documents include dataset descriptions, version records, delivery checklists, and acceptance reports. Data sources cover object storage, data warehouses, annotation platforms, and customer acceptance feedback. Update cycles align with each batch delivery or version iteration. Data fields include version number, sample count, storage path, difference description, acceptance status, etc. Units are mostly characters, items, and GB. There is no unified mandatory format, and matching corresponding delivery specifications is required.
What constraints these characteristics impose on the citation sources and traceability link
Decentralized data sources require traceability processes to support cross-system association of different types of data sources. Unfixed update cycles mean traceability must bind specific version identifiers to avoid mixing data across versions. The diverse document structure requires traceability configurations to be compatible with delivery checklists and version records in different formats. The lack of unified field formats requires traceability to support matching custom fields for precise association. The need for delivery integrity verification requires traceability to associate both sample-level data and the overall delivery package, ensuring the integrity of cited content. The complexity of version number management requires traceability to bind cited content to the current delivery version, ensuring training results are reproducible.
How to configure settings
These configurations are designed for FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
quoteMaxToken | 800–1200 token | Matches the average length of a single dataset description or version record, to avoid truncating critical traceability information |
responseData | Return only version number, storage path, and sample ID fields | Reduces invalid content occupying context, focusing on core identifiers required for traceability |
detail | Enable full traceability mode | Loads sample difference description fields in the delivery checklist to ensure complete context for cited content |
| Single search limit | Top 3 entries | Matches the typical sample count per batch delivery, avoiding interference from excessive irrelevant data |
| Version binding switch | Enabled | Forces cited content to be bound to the current dataset version, preventing cross-version data mixing |
Three common configuration mistakes
- Symptom: Empty values or incorrect identifiers are returned when using
{{id}}in citation templates. Cause: TheresponseDataconfiguration is not set to return the unique ID field of the dataset, and the knowledge base collection ID is mistakenly used as the single data ID. - Symptom: Temperature parameter cannot be adjusted after enabling variable reference mode. Cause: The enable switch for conversation parameters is not retained in the configuration, and variable reference mode overrides some interface settings by default.
- Symptom: Traceability results include dataset content across versions. Cause: The version binding switch is not enabled, causing cited content to not be associated with the current delivery version and resulting in data mixing.
How to verify correct configuration
- Initiate a technical document query, and check if the returned cited content includes the core fields specified in the configuration, such as version number and storage path.
- View the variable list in the citation template, and confirm that
{{id}}corresponds to the unique identifier field of the dataset. - Switch between different dataset versions to initiate queries, and verify that the returned cited content is only bound to the currently selected version.
- Check the token consumption of the context window, and confirm that it does not exceed the
quoteMaxTokenconfiguration limit, with no content truncation.
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 2026-10-19.