What Data for This Category Looks Like
Engineering consulting research report data originates from public project review documents published by architectural decoration industry associations and housing and urban-rural development departments, as well as special reports from third-party engineering consulting institutions. The update rhythm adjusts based on project progress, with batch updates for individual project research reports from initiation to completion stages. Document structures include fields such as project unique identifier, construction location, total project cost, construction period, core technical parameters, and policy compliance clauses. The cost field uses ten thousand yuan as its unit, the construction period field uses natural days, and the area field uses square meters.
Constraints Imposed on HTTP Interfaces and External Systems by These Characteristics
The unique identifier field of engineering consulting research reports requires interfaces to support precise retrieval by project ID, to avoid duplicate matching or missing target content. The batch update feature requires external systems to pull incremental data within an update time range during integration, to reduce resource consumption from full synchronization. The requirement that multiple fields carry fixed units means unit annotations must be included in interface requests and responses, or external systems must complete unit conversion in advance, to prevent parameter ambiguity. The lengthy nature of individual research report content requires interfaces to support paged returns or segmented recall, and requires configuring a reasonable timeout threshold to avoid timeout during large text transmission.
How to Set Configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
RETRIEVE_TOP_K | Top 10-15 results | Engineering consulting research reports are professional and have many entries. Too many recall results increase context pressure, while too few fail to cover core parameters |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | A single engineering research report contains large numbers of tables and professional text, with longer parsing times than general documents, so the timeout period must be extended |
HTTP_REQUEST_TIMEOUT | 600 seconds | High-traffic requests from external systems pulling batch research reports require longer timeout periods to prevent transmission interruptions |
MAX_CONTEXT_LENGTH | 8000-12000 characters | Engineering research reports are dense with professional terms, so sufficient context is needed to accommodate multiple retrieved core paragraphs |
ENABLE_INCREMENTAL_SYNC | Enabled | Engineering research reports are released in batches as projects are updated, and incremental synchronization reduces data synchronization costs for external systems |
UNIQUE_ID_FIELD | Project Number | The project number of engineering consulting research reports is a globally unique identifier, usable for precise matching and deduplication |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require specific analysis. It is recommended to test on your own samples before finalizing the configuration.
Three Common Mistakes
- Scenario: When an external system calls the FastGPT API, the response does not include FunctionCall-related fields. The root cause is that the tool calling function was not enabled in the application configuration, resulting in the retrieval process failing to generate callable function parameters.
- Scenario: Modifying the FastGPT service to use HTTPS access fails. The root cause is that the server's SSL certificate and reverse proxy rules were not configured correctly, leading to failed port mapping or certificate verification.
- Scenario: Calling the external application creation API returns
404 Not Found. The root cause is that the FastGPT API key verification switch was not enabled, or the correctAuthorizationparameter was not included in the request header.
How to Confirm the Configuration Is Correct
- Send an HTTP retrieval request carrying the project number, and check that the research report fields returned in the response match the field list preset in the external system.
- View the interface operation logs to confirm there are no frequent timeouts or parameter parsing errors, verifying that the configured timeout and parsing rules are in effect.
- Trigger an incremental synchronization task, and check that only research report data with an update time within the specified range is returned, with no redundant outdated content.
- Call the external application creation API, and check that the returned application identifier matches the application identifier generated in the FastGPT backend.
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.