What the data for this category looks like
Data for this category primarily comes from search ad backends, search term reports, bidding ranking data, and landing page data. Daily produced documents include keyword lists, negative keyword lists, bid records, and search term reports. Document fields include keyword text, match type, bid amount, search volume, conversion cost, and more. Units include RMB, times, characters, and more. Data update frequency is typically daily or weekly. Single document volume varies with account scale. Monthly data per single account can reach tens of thousands of entries.
Constraints on Citation Sources and Traceability
Data sources are scattered across multiple search ad backends and business reports. Citation traceability requires matching unique identifiers across different data sources to avoid mixing data across accounts and cycles. Data update frequencies differ between daily and weekly cycles. Incremental pull logic must be configured per corresponding cycle to prevent repeated citation of expired data. Document fields include numerical values with units such as bid amount and conversion cost. Full fields and units must be retained during citation, otherwise the reference value of change reviews will be reduced. Single account data volume is large. The scale of content cited in a single round must be limited to avoid exceeding context processing limits.
Configuration Settings
This configuration applies to FastGPT v4.17.0.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
quoteMaxToken | 800–1200 token | Matches the typical citation length of a single search ad keyword report or negative keyword list, avoiding exceeding context processing limits |
responseData | Return original data source fields | Retain original fields such as keywords, match type, bid amount, conversion cost to ensure complete traceability information |
detail | Enable full-field traceability | Display report batch, update time, data source platform and other information to assist accuracy verification of change reviews |
| Single citation data source limit | Top 5 matching data sources | Control the number of data sources cited in a single round to avoid redundant information interfering with review logic |
| Incremental pull cycle | Configure daily/weekly pull per account | Match the daily or weekly update frequency of search ad data to prevent citation of expired data |
Three Common Misconfigurations
- Phenomenon: After initiating a POST request to call the citation interface, the interface returns a normal status code but no content return value. Cause: The value of
quoteMaxTokenexceeds the system processing limit, or the data source pull timeout is not configured with a retry mechanism. - Phenomenon: The cited data source link cannot download the original text normally. Cause: An Nginx proxy is configured but the proxy rule for the knowledge base original link is not updated synchronously, resulting in link jump failure.
- Phenomenon: The cited thought process and data source content are spliced into a messy format with poor readability. Cause: The
detailconfiguration is not enabled, or citation information is not spliced according to the original document's field order.
How to Verify Proper Configuration
- Perform a citation test for a single keyword list, check whether the returned content includes the original fields required by the configuration.
- View system logs to confirm that the data source pull cycle matches the preset update frequency.
- Adjust the value of
quoteMaxTokento verify that the returned content length meets the expected context window requirements. - Test the accessibility of the citation link to confirm that the proxy configuration covers the relevant data source domain names.
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.