What the data for this category looks like
This category of data mainly comes from advertising platform backends, attribution systems, CRM lead management systems, and landing page data collection tools. Data update cycles are divided into daily updates and real-time updates. Core documents include daily delivery reports, weekly delivery reports, real-time price adjustment records, material A/B test tables, and optimization review ledgers. Data fields include impressions, clicks, conversion cost, budget balance, and more. Corresponding units are times, times, yuan, and yuan respectively. Some indicators such as cost per thousand impressions have custom units. The data structure uses individual delivery plans as the smallest unit, associated with conversion link data for the corresponding time period.
Constraints on the citation and traceability process
The data characteristics of this category impose multiple constraints on the citation and traceability process. Decentralized storage of multi-source data requires traceability configurations to support cross-platform association queries across advertising platforms, attribution systems, and CRM systems, with clear unique identifier mapping rules for each data source. Real-time updated delivery data requires traceability APIs to support low-latency response capabilities. Failure to match real-time adjusted context will lead to invalid citations. Diverse document types and inconsistent field naming require standardized field mapping logic to be configured during traceability, to avoid indicator confusion across different ledgers. The unique identifier of delivery plans must run through the entire citation process to ensure traceability results are accurately bound to the corresponding delivery unit. Unit differences across different indicators need to be supplemented and marked in traceability outputs to avoid data interpretation bias.
How to configure settings
The following configurations are explained based on FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
quoteMaxToken | 800–1200 token | Adapts to the length of single records in delivery optimization documents, avoiding truncation of key delivery indicators and unique identifiers |
detail | Enabled | Retains complete field details of raw data, matching the traceability requirements for multi-dimensional indicators in delivery optimization scenarios |
responseData | Includes source ID and document path | Ensures citation results can be directly linked to original delivery ledgers or data interfaces |
| Traceability query timeout | 300 seconds | Adapts to the time consumption of multi-source data queries across advertising platforms and attribution systems |
| Number of traceability matches | Top 3–5 entries | Controls output information volume, avoiding redundant data interfering with delivery optimization decisions |
Three common configuration mistakes
- Forged citation IDs appear in outputs. This occurs when the source ID verification logic for
responseDatais not configured, and placeholder identifiers generated directly by the large model are used instead of real traceability data. - The phrase "Citation Mark: [1]" appears in output content. This occurs when the automatic rendering switch for citation marks is not turned off, exposing internal system citation identifiers directly in the final output.
- Uncleaned citation information remains in generated files. This occurs when a citation data filtering node is not added to the workflow, and internal identifier fields generated during the traceability process are not stripped.
How to confirm successful configuration
- Initiate a test query that includes a specific delivery plan ID, check whether the returned results contain real source IDs and document paths.
- Adjust the value of
quoteMaxToken, verify that delivery documents of different lengths are fully retained without truncation. - Trigger a traceability query, confirm that the response time meets the preset timeout setting, and there are no frequent timeout errors.
- Review the generated output content, confirm that undefined citation marks or forged source identifiers do not appear.
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.