What this category of data looks like
This category of data originates from the unified budget management system, centralized treasury payment system, accounting system, and asset management system. This data updates annually. Daily documents include department final account statements, balance sheets, income and expenditure final account statements, final account explanations, and government financial reports. It contains structured and unstructured content such as revenue and expenditure subjects, asset and liability details, and final account caliber explanations. Most fields carry fixed codes and amount units. Some documents require cross-system data association to complete verification.
What constraints do these characteristics impose on the multi-turn dialogue and prompts link
The annual update requirement means multi-turn dialogue contexts must permanently lock the current query’s annual data range to avoid confusion across annual data. The coexistence of multiple document types requires prompt setup to distinguish two scenarios: structured report field queries and final account explanation interpretations, and match different content extraction logic. The cross-system data source feature means the dialogue flow must guide users to clearly specify the system and version to which the report belongs, to ensure accurate data traceability. At the same time, since error consequences directly link to audit and compliance requirements, multi-turn dialogue must retain context to track query correction steps and assist in verifying data caliber consistency.
How to set configurations
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
chatId | Generate a unique identifier per session lifecycle | Bind multi-turn dialogue context for a single user, avoid cross-session data interference, and adapt to the single-query range of annual data |
messages | Retain the last 10 rounds of dialogue content, with no more than 800 characters per round | Adapt to the annual update data feature, filter redundant historical information, and avoid context overflow |
variables | Pre-set three fixed variables: "annual range", "report type", and "affiliated system" | Constrain the query boundary of multi-turn dialogue, and match the cross-system and multi-document data source characteristics |
| Maximum context length | No more than 12000 tokens | Adapt to the content volume of a single batch of department final account documents, and avoid exceeding model processing limits |
| Query optimization | Enabled | Convert scattered queries into structured queries with clear ranges, adapting to business requirements for multi-turn traceability of differences |
Three common misconfigurations
- A conversation request triggers an input limit error that is not intercepted. The interface returns a "context length exceeded limit" error or no response. The cause is that the maximum context length limit is not configured, and the total content of
messagesis not verified in the multi-turn dialogue flow. - Dialogue records cannot be deleted. The record still exists after calling the delete interface. The cause is that
chatIdis not bound for precise deletion, and global session data is accidentally deleted. - Dialogue returns no cite reference ID. No cite reference ID appears in the interface return fields. The cause is that document traceability configuration is not enabled, and the original data source system identifier of department final accounts is not associated.
How to confirm configurations are properly set
- Use the dialogue node of FastGPT v4.17.0 to initiate cross-system and cross-annual multi-turn queries, and verify whether the context retains the previously specified report type and annual range.
- Trigger a request where the input content exceeds the preset threshold, and verify whether the system intercepts the request before an error occurs and prompts for content simplification.
- Call the dialogue delete interface, and verify whether the session record for the specified
chatIdis completely cleared. - View the interface return results, and verify whether the associated original data source identifier is included.
The values provided are common starting points and should be measured 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.