What the data for this category looks like
This category's data primarily comes from internal corporate procurement systems, supplier quotation documents, budget spreadsheets, and contract systems. Core daily documents include purchase requisitions, price comparison records, formal contracts, and acceptance documents. Common fields include purchase order numbers, supplier entity information, budget amounts, contract clause details, and acceptance status. Data updates follow individual procurement workflows: a single purchase from requisition to acceptance will generate multiple associated documents. Monthly bulk updates are also a common scenario.
What constraints these characteristics impose on scheduled tasks and automation
The data sources for this category are scattered and have varied formats, requiring scheduled tasks to adapt to multi-system interface call permissions and parsing logic for different document types. Data updates follow individual procurement workflows or monthly bulk cycles, so scheduled periods must align with actual business progress to avoid overloading internal procurement systems with excessive API calls, or failing to respond to emergency procurement troubleshooting needs due to overly long cycles. Additionally, associated documents have significant field differences, so automated workflows must support dynamic matching of key information from different documents, otherwise parameter verification failures may occur.
How to Set Configurations
| Configuration Item | Recommended Values | Rationale |
|---|---|---|
| Scheduled trigger interval | 300–1800 seconds (calibrated per business scenario) | Aligns with procurement workflow update rhythms, avoids frequent calls to procurement system APIs |
| Task retry count | 2–3 times | Addresses temporary API fluctuations in procurement systems, reduces manual intervention |
| Single data pull limit | Top 10 purchase documents | Controls resource usage per task, prevents task timeouts and blockages |
| Alert trigger threshold | 2 consecutive task failures | Notifies operations personnel promptly to handle abnormal scenarios |
| Document parsing segment threshold | 800–1200 characters per segment | Adapts to text lengths of procurement contracts and acceptance documents, improves parsing accuracy |
| API timeout setting | 60 seconds | Matches typical response times of internal procurement systems, prevents task hangs |
Three Common Misconfigurations
- Symptom: A scheduled task trigger interval set to 3000 milliseconds leads to frequent calls to procurement system APIs, triggering rate limiting. Cause: Failed to match the procurement system's API call frequency limits, mistakenly using a millisecond-scale interval for internal corporate system calls.
- Symptom: After adding a custom purchase document parsing plugin to a workflow, input and output parameters do not display, and no error logs are present. Cause: The plugin configuration is not linked to the corresponding purchase document field mapping rules, or the plugin package was not correctly uploaded to the workflow directory.
- Symptom: Running an upgrade script returns a
POST /api/admin/initv4818 404error. Cause: The API path called by the upgrade script does not match the current FastGPT version, and the API address parameter in the script was not updated.
How to Confirm Configurations Are Correct
- Manually trigger a scheduled task, check the task logs in FastGPT v4.17.0, confirm the number of pulled purchase documents matches the configured single pull limit.
- Simulate a procurement system API exception, verify whether the task retries according to the configured retry count, and triggers the preset alert once the threshold is reached.
- Upload a standard procurement contract document, verify that the automated workflow correctly extracts key fields and generates structured results.
- Check the workflow plugin configuration page, confirm that the input and output parameters of the custom plugin have loaded and display correctly.
The values provided are common starting points and should be evaluated 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.