What Data for This Category Looks Like
Data for this category is generated for individual tender projects. Sources include tender announcements, tender documents, enterprise qualification databases, and supplier quotation databases. Daily deliverable documents include tender documents, qualification certificates, business deviation tables, and technical deviation tables. Each field must strictly match the format and content requirements of the tenderer, with no unified fixed format. Data updates are triggered per project, and new version iterations are created each time a round of tender response or qualification verification is completed.
Constraints Imposed on Forms and Interactions
Format requirements for tender announcements and documents change for each project. This requires forms to support dynamic field loading to adapt to the structure of different tender projects. Real-time verification needs for qualification and quotation databases require the interaction link to support rapid multi-source data checks, to avoid manual entry errors. The document structure of a single tender project is tightly bound to tender requirements. Fixed form structures matching tender formats must be generated by external systems. Free field combination and partitioning are prohibited, to prevent deviations from tender requirements. The per-project data update feature requires the interaction link to retain a version traceability entry, to avoid accidental use of old data for new tenders. Consequences of errors include bid disqualification, score deductions, or margin losses. External business systems must implement strict verification logic to block submissions that do not meet tender requirements. The FastGPT formInput node only collects input and passes it to subsequent nodes.
How to Configure
The following configurations apply to FastGPT v4.17.0.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
Form Input Node formInput | Test example: Select 3 fields from tender document preparation as required inputs; actual fields are determined by the task | This node collects user input. Missing required fields requires checking interaction status to prevent subsequent nodes from failing to receive complete input |
User Selection Node userSelect | Test example: Set 2 business options, check corresponding branches one by one | This node handles user selection. Querying and filtering records related to tender document preparation must be implemented by subsequent interfaces or external systems |
| Post-submission Field Passing | Test example: Prepare 10 tender document preparation input samples, covering full completion, missing required fields, and canceled operations | Compare input and node output to verify whether subsequent nodes receive corresponding fields. Result thresholds are determined by actual tasks |
| External Implementation Item: Form Field Dynamic Loading | Must be implemented separately by external systems; generate corresponding chapter structures via external tender document parsing systems | Match the requirement that tender documents must strictly follow tender formats, and automatically adapt to field differences across different tender projects |
| External Implementation Item: Single Search and Loading Limit | Must be implemented separately by external systems; top 5 results, 20 fields (to be tested) | Response clauses in tender documents require precise matching. Excessive recalled or loaded content increases screening and rendering costs, handled by the front-end interaction link |
| External Implementation Item: Operation Debounce Duration | Must be implemented separately by external systems; 300 milliseconds (to be tested) | Reduce frequently triggered form verification requests and lower front-end interaction latency, handled by the front-end interaction link |
Three Common Mistakes
- When selecting associated variable values in the tender form, front-end drag lag and operational delay occur. Deleting the corresponding bound variables restores normal interface performance. The cause is failing to limit the data source scale associated with the external business system. Excessively associated tender clause fields lead to excessive front-end rendering load.
- API call response clauses differ significantly from online chat results, and the matching degree of recalled qualification data is low. The cause is failing to use tender original text as the benchmark for prompt optimization. External API calls use default generic prompts by default, and do not adapt to the format requirements of tender documents.
- After configuring the model selection for prompt optimization, the saved configuration fails to take effect. The cause is failing to correctly associate external environment variables with the model selection link, resulting in configuration parameters failing to load.
How to Verify Successful Configuration
- Import a local tender document, and verify whether form fields automatically match the chapter and clause structure of the tender document via the external tender document parsing system.
- Trigger the qualification material verification process, confirm that external business systems (enterprise qualification database and supplier quotation database) can provide corresponding enterprise qualification documents for the
userSelectcomponent. - Launch external API calls and online chat tests, compare the response clause matching results of both, and adjust the configuration rules for the optimization benchmark.
- Submit test content with missing required fields, confirm that the system pops up corresponding prompts to block the submission.
The values provided here are common starting points, and should be evaluated against your own specific 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.