What this category of data looks like
Coal transportation and sales document data comes primarily from internal transportation and sales scheduling systems, contract management modules, and settlement ledgers. Data updates for each individual transportation and sales task. A single task covers 1 to 3 coal types and multiple road or railway transport links. Standard documents include fields such as contract number, coal type name, received base low calorific value, actual shipment volume, settlement unit price, and unified social credit codes for both senders and receivers. Supported units include tons, kilocalories per kilogram, yuan per ton, and others. A single document typically contains 800 to 1500 characters.
What Constraints These Characteristics Impose on HTTP Interfaces and External Systems
Coal transportation and sales document data includes sensitive enterprise credit codes, precise calorific value and settlement parameters. HTTP interface requests must strictly match field names and units to avoid data parsing errors. The per-task update feature requires interface calls to bind the transportation and sales batch ID as a query parameter. This prevents pulling duplicate or missing data. The fixed word count range for single documents means the responseData returned by the interface must adapt to character length limits, supporting paged or truncated returns. Data updates sync with transportation and sales tasks. Interface call cycles must match task update nodes to avoid retrieving outdated or ungenerated document content. Additionally, internally deployed transportation and sales systems require interfaces to support local area network access. Authentication rules for the corresponding network environment must be configured.
How to Set Configurations
| Configuration Item | Recommended Approach | Basis for This Approach |
|---|---|---|
Authorization | Intranet-exclusive Bearer Token, with the fixed prefix Bearer followed by a 64-bit random string | Matches the intranet authentication rules of coal transportation and sales systems, prevents unauthorized external access, and adapts to the authentication parameter format of FastGPT v4.17.0 |
variables | Bind two variables: transportation and sales batch ID and coal type code, with values pulled from the batch interface of the internal system | Adapts to the batch-based data update feature, ensuring that the pulled document data corresponds to the specified transportation and sales task |
responseData | Truncate the first 1200 characters, return excess content in pages | Matches the common word count range of single documents, adapts to the context length limit of FastGPT |
| Request timeout | 300 seconds | Handles the time required to pull document data for large transportation and sales batches, avoids interrupted connections mid-process |
| Call cycle | Follow the rhythm of transportation and sales task generation, call once every 1-4 hours | Matches the update frequency of transportation and sales data, ensuring that obtained documents are the latest version |
| Intranet access configuration | Bind local area network IP whitelist | Adapts to the intranet deployment environment of coal transportation and sales systems, resolves cross-device access exceptions |
Three Common Misconfigurations
- Symptom: When other local area network devices access the FastGPT service, GET requests return the
net::ERR_INCOMPLETE_CHUNKED_ENCODINGerror. Cause: No intranet IP whitelist is configured. The interface authentication rule blocks requests from non-specified network segments. - Symptom: The
responseDatareturned after a timer triggers an interface call is empty. Cause: The transportation and sales batch ID is not bound to thevariablesparameter. The interface pulls full uncategorized raw data that cannot match the specified task for document drafting. - Symptom: Detailed error logs cannot be viewed after a large model interface call fails. Cause: FastGPT's interface call log storage configuration is not enabled. Error information cannot be retained for troubleshooting.
How to Verify Correct Configuration
- Access the FastGPT interface debugging page on a specified intranet device. Enter a request bound to the transportation and sales batch ID, then check if the returned
responseDataincludes core fields such as coal type and shipment volume. - View interface call logs to confirm the
Authorizationparameter carries the correct intranet authentication Token, with no authentication failure errors. - Adjust the timer's call cycle, then verify that pulled document data matches the latest batch data from the internal transportation and sales system.
- Simulate a request for document data exceeding the conventional word count, then confirm the interface returns content that complies with preset truncation or paging rules.
The values provided here are common starting points, and should be evaluated against the user'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 2026-09-28.