What the data for this category looks like
Brand agency financial report data primarily comes from monthly operating ledgers provided by brand partners, transaction details exported from e-commerce platform backends, and monthly reports from third-party e-commerce data analysis tools. Data is updated once per month. Documents are presented in structured table format, including fields such as operating cycle, shop ID, total transaction value, per-customer consumption amount, repeat visit count, marketing campaign cost, supply chain procurement expenditure. Field units include RMB yuan and visit count. No nested complex unstructured paragraph content is included.
What these characteristics impose on workflow orchestration
The multi-data-source feature requires the workflow to be configured with cross-source pull nodes to integrate financial report data from different channels. The monthly update rhythm means the workflow does not need high-frequency triggering, only a scheduled trigger rule needs to be configured. The structured table format requires the parsing node to specify column mapping rules to avoid extracting irrelevant content. The coexistence of multiple types of fields requires the workflow to be configured with a field verification node to distinguish operational and financial data and prevent indicator confusion. Overall, the workflow needs to balance the completeness of data integration and the accuracy of indicator classification, requiring customized document parsing and verification logic.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Brand agency financial report files usually contain detailed data for multiple shops and cycles, so parsing takes a long time, and sufficient processing time must be reserved |
maxContext | 10–30 entries | Financial report analysis requires associating multiple periods of operating data. Sufficient context ensures logical consistency of AI nodes and adapts to multi-dimensional indicator comparison requirements |
triggerMode | Scheduled trigger | Financial report data is updated monthly, so real-time response is not needed. Scheduled triggers match the data update rhythm and reduce invalid executions |
splitChunkSize | 800–1200 characters | The data volume per page of financial report tables is moderate. This chunk length balances parsing accuracy and processing efficiency, avoiding indicator fragmentation caused by overly small chunks |
similarityThreshold | 0.75–0.85 | Core indicator fields in financial reports need to be accurately matched. This threshold filters low-correlation field matching results and ensures the accuracy of data extraction |
loopMaxTimes | 3 times | Financial report corrections usually require up to two rounds of adjustments. This value avoids invalid loops while covering normal correction requirements |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material format, data volume and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.
Three common mistakes
- The symptom is that
maxContextis configured to 30 entries, but only 2 context entries are displayed in the conversation details, and the reply content cannot associate multi-period financial report data. The cause is that in FastGPT 4.10.0, the global context parameter and the node-specific configuration are not synchronized, resulting in the actual number of context entries called by the node not matching the set value. - The symptom is that the loop node has no termination signal after triggering, and the workflow runs infinitely. The cause is that the
loopMaxTimesparameter is not configured or is set to 0, so the maximum number of loop executions is not limited. - The symptom is that the file parsing node reports an error indicating abnormal field format, and shop ID and marketing cost fields cannot be extracted. The cause is that the column mapping rule for the financial report table is not specified, so the node cannot identify the unique business fields of agency operations and can only extract general table contents.
How to confirm correct configuration
- Manually trigger the workflow once, check the output logs of the file parsing node, and confirm that the extracted financial report fields fully match the column names and values of the original document.
- Test the exception branch of the loop node, input unqualified financial report data, and confirm that the workflow automatically terminates after reaching the number of times set by
loopMaxTimes. - Check the global settings and the
maxContextparameter of the workflow node, confirm that their values are consistent, trigger a test conversation, and verify the number of displayed context entries. - Configure the scheduled trigger rule, set a test task 1 minute later, and confirm that the workflow automatically executes at the specified time without generating error logs.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.