Reference only; verify against the target FastGPT release and deployment documentation.
What this category of data looks like
The business process data for rail transit equipment mainly comes from official maintenance regulations, production process manuals, spare parts management ledgers, and fault troubleshooting guides. Data is stored classified by vehicle model and component. Individual document lengths range from several thousand to tens of thousands of characters. Core fields include component model, rated parameters, maintenance cycle, fault codes and corresponding disposal procedures. Units cover specialized measurement standards such as millimeters, kilonewtons, and operating hours. Data updates follow annual version iterations, and are also synchronized via temporary change notifications.
What constraints these characteristics impose on the multi-turn dialogue and prompt configuration link
The professional data structure and specialized measurement standards of rail transit equipment impose multiple constraints on multi-turn dialogue and prompt configuration. chatId must be used to bind context for different handling scenarios. The context length of messages must be limited to avoid overflow from long documents. Prompts must clearly restrict the retrieval scope to the component documents corresponding to the current handling link, to avoid interference from irrelevant information. Returned content must strictly use the fields and specialized units from the documents, to ensure accuracy of business descriptions. Real-time retrieval of temporary change data must also be supported, to ensure that conversations use the latest version of business data.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Context window length | 800–1200 characters | Matches the length of single-segment business documents for rail transit equipment, avoids information overflow |
| Multi-turn dialogue context binding | Associate via chatId | Distinguishes exclusive data for different handling scenarios, prevents cross-user confusion |
| Variable input parameters | Input vehicle model and component number | Filters retrieval scope, matches specialized fields and measurement units |
| Prompt constraint rules | Mandate use of specialized units from documents | Ensures accuracy of business descriptions |
| Single retrieval count | Top 3 entries | Avoids excessive irrelevant data interfering with dialogue logic |
| Timeout setting | 600 seconds | Matches processing duration for long document retrieval and complex business processes |
Three common mistakes
- Business process output content is not displayed in dialogue results. Cause: Correct business link parameters were not passed in
variables, leading to retrieval scope deviating from the current handling process. - Cross-vehicle model business data confusion occurs in multi-turn dialogue. Cause: Independent context was not bound via
chatId, causing interference between conversation data from different users. - Dialogue return content uses units not specified in the documents. Cause: Prompts did not clearly require use of specialized measurement standards from documents, leading to generated content that does not comply with business specifications.
How to confirm correct configuration
- Launch a simulated business handling conversation, check that the context only includes relevant data for the currently specified vehicle model and component.
- Trigger retrieval, verify that the units of returned results match the specialized measurement standards from the documents.
- Test switching handling scenarios in multi-turn dialogue, check that the context binding updates correctly.
- Launch a test for complex business processes, confirm that response duration meets the configured timeout requirement.
The values provided here 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 2026-09-28.