What the data for this category looks like
Data for this category comes from centralized treasury payment systems, unified budget management systems, electronic invoice platforms, and contract management systems, and is updated daily. Daily processed documents include payment applications, fund appropriation plans, invoices, contracts, acceptance receipts, reimbursement approval forms, and payment vouchers. Each document must match core fields such as budget indicators, economic classification, and invoice compliance. Files related to a single payment must link multiple types of materials to form a complete audit chain.
What constraints these characteristics impose on the multi-turn dialogue and prompt engineering link
Daily updated data requires that multi-turn dialogue contexts be synchronized with the latest system data sources to avoid using expired budget indicator or invoice information. The audit chain formed by linking multiple types of documents requires prompts to clearly guide sequential verification in the order of payment application → fund appropriation plan → contract → acceptance receipt. The rigid requirement for field matching means that multi-turn dialogue must gradually guide the supplementation of missing key information such as economic classification and payment amount, to avoid generating incomplete audit conclusions. At the same time, the boundaries of compliance verification must be clearly defined in the dialogue, corresponding to the core requirements of fiscal audit.
How to Configure
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Dialogue message invocation | messages | Retain the last 6 rounds of interactions and material extraction results to cover the complete process of a single audit |
| Context window size | 8000-12000 token | Accommodate the text content of multiple audit documents and dialogue history, adapting to the volume of materials for single payment audits |
| Dynamic variable filling | Automatically populate variables | Dynamically substitute business fields such as the current audit budget unit and payment amount, avoiding hard-coded fixed content |
| Dialogue ID binding | Bind chatId | Ensure that the dialogue context for the same audit task is not lost, supporting the continuity of multi-round verification |
| Maximum reply rounds | 3-5 rounds | Control the number of iterations in the audit process, prevent meaningless repeated dialogues, and meet the efficiency requirements of fiscal audit |
Three Common Misconfigurations
- Using a text content extraction plugin in a workflow and configuring the number of chat history entries causes multi-turn dialogue to fail. The root cause is that the workflow node does not correctly pass the
messagesparameter, preventing context synchronization across nodes. - Calling a multimodal model to process invoice images returns an incorrect format. The root cause is not passing image files that comply with business document formats as required, and not clearly specifying the compliant types of images.
- Dialogue context is not synchronized with the latest treasury system data. The root cause is not configuring the trigger logic for daily data synchronization, leading to the use of expired budget indicator data.
How to Confirm Successful Configuration
- Initiate a simulated payment audit request, check whether the dialogue history retains the last 6 rounds of interactions and material extraction results.
- Test dynamic variable filling to confirm that fields such as the current audit budget unit and payment amount are correctly substituted into the prompt.
- Initiate a multi-round verification request to confirm that the dialogue context is correctly bound via
chatId, with no context loss. - Call the application interface to confirm that the returned results match the expected output of the audit process.
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.