This document is written for FastGPT v4.17.0.
What the data for this category looks like
Core data for customer data import migration comes from customer legacy systems, CSV or Excel templates, database export files, and built-in product import operation logs. Daily deliverables include data templates, migration plans, field mapping tables, and migration validation reports. Data updates occur per order or on an irregular basis. Fields involved in a single task include business fields, mapping relationships, validation rules, and import record counts. Data formats and units vary by source: CSV files use row records as the unit, while database exports use table structures as the unit.
What constraints do these characteristics create for the citation sources and traceability process
The diverse data sources require the traceability process to support original data identifiers in different formats, to avoid traceability confusion caused by field misalignment. Irregular update cycles mean each import task’s traceability must be tied to an independent task batch, and general traceability rules cannot be reused. The large number of associated documents requires the traceability process to cover migration plans, mapping tables, and validation reports, to ensure all migration steps can be traced during reviews. Differences in fields and units require traceability to accurately match the original data’s field mapping relationships, to ensure review accuracy and credibility.
How to configure settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
quoteMaxToken | 800–1200 token | Single-batch data documents for customer data import migration are large in volume, and need to cover complete migration logs and field mapping content |
responseData | Enable original source binding | Need to associate multiple types of data sources such as customer legacy systems, CSV/Excel templates |
detail | Enable full-link traceability mode | Need to record migration step details such as import batches and field mapping relationships |
| Single search limit | Top 5 entries | Match migration-related historical documents and logs, to avoid redundant recall |
| Maximum context size | 1000 MB | Adapt to batch association needs for multiple migration plans and validation reports |
| Associated knowledge base count | Maximum 10 | Adapt to the number of associated documents for a single migration task, to avoid excessive system load |
Three common mistakes
- Symptom: A string of red numeric errors appear during citation. Cause: The original data source for the import batch is not correctly bound, so the traceability identifier cannot match the system’s preset validation rules.
- Symptom: Cannot locate the uploaded migration document text in the knowledge base. Cause: The
responseDataconfiguration is not enabled, and the original document path is not tied to the import task, resulting in missing traceability information. - Symptom: Cannot load specified migration documents after associating a knowledge base. Cause: The preset associated knowledge base count limit is exceeded, so some documents are not loaded by the system.
How to verify correct configuration
- View the import task’s operation log, confirm that each import record has a corresponding original source identifier, such as a CSV file name or database table name.
- Initiate a conversation associated with the migration knowledge base, check that the returned results include the original source information from the
responseDatafield and the import batch identifier. - Test import data from different batches, confirm that traceability results only associate migration documents from the corresponding batch, with no cross-batch data confusion.
- Adjust the value of
quoteMaxToken, verify that the recalled content covers complete migration plans, field mapping tables, and validation reports. - Check the total number of associated knowledge bases, confirm that the preset limit is not exceeded, to ensure all migration documents are loaded correctly.
The values provided here are common starting points, and should be evaluated against your 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.