What this category of data looks like
Data is primarily sourced from the unified budget management system, departmental staffing system, prior-year final accounts, project repository, and the annual budget preparation notice issued by the Ministry of Finance. Update frequency is annual. Daily produced documents include departmental budget drafts, project application forms, performance target forms, personnel expense calculation forms, budget approval documents, and more. Document structures typically include modules such as unit basic information, personnel expense calculation details, project expenditure lists, and performance target setting. Fields include authorized number of staff, public expense quotas, project budget amounts, performance indicators, and other relevant items. Standard metrics commonly used by fiscal authorities, such as ten thousand yuan and person, are adopted for units.
What constraints these characteristics impose on the multi-turn dialogue and prompt engineering link
The annual update requirement means dialogue context must be bound to the current year’s budget preparation rules, to avoid mixing cross-year data. Multiple data sources mean dialogue must sequentially associate information from staffing, project repository, final accounts and other data sources. Multi-turn dialogue is needed to gradually clarify the data scope. The complexity of document fields means prompts must accurately specify the types of fields to extract, to prevent generated content from deviating from standard budget preparation formats. The serious consequences of errors mean the dialogue flow must include a parameter verification step, to ensure generated documents meet fiscal review requirements.
Configuration Settings
Under FastGPT v4.17.0, refer to the following configuration items and values:
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
chatId | Bind the unique identifier of the current budget preparation year | Differentiate budget preparation sessions across years, avoid context confusion |
messages | Populate pre-prompts and user dialogue content sequentially according to budget preparation stages, retain context from no more than the first 3 turns | Budget preparation data is fixed per year, excessive context will introduce irrelevant historical data |
variables | Preset variables such as authorized unit staffing number, project repository list, annual quota standards, pull values from corresponding systems | Ensure generated content matches actual business data, avoid deviations from generic templates |
| Context window limit | 8000–12000 characters | Cover core document content for single-department budget preparation, avoid context overflow |
| Prompt module division | Set up modules separately for personnel expenses, project expenditures, and performance targets | Correspond to the fixed structure of budget documents, improve standardization of generated content |
Three Common Mistakes
- Phenomenon: The generated budget document does not include the specified performance target fields when calling the
/api/v1/chat/completionsAPI. Cause: The dedicated prompt for the performance target form was not correctly embedded in themessagesparameter, so the model did not match the document structure. - Phenomenon: Cross-year budget data is mixed during multi-turn dialogue. Cause: The unique identifier of the current preparation year was not bound via
chatId, so the session context loaded prior-year budget data. - Phenomenon: Generated content does not comply with the budget preparation rules of the corresponding department when using a global API key to initiate a dialogue. Cause: Department-specific preparation parameters were not passed via the
variablesparameter, so the model used generic rules to generate content.
How to Confirm Proper Configuration
- Initiate a test dialogue, input the current year’s budget preparation requirements, and check if the generated content includes specified fields such as authorized number of staff and project budget amount.
- View session logs, confirm that the
chatIdparameter carries the unique identifier of the current year, with no cross-year context remaining. - Check the
variablesparameter when calling the API, confirm that latest data synchronized from corresponding business systems has been passed in. - Switch between Chinese and English input, confirm that the dialogue flow correctly matches the current language environment.
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.