What this category of data looks like
Generating entities for this category of data include central enterprise internal control departments, audit departments, finance departments, subordinate enterprises, and external audit institutions. Data sources cover enterprise internal control systems, ERP systems, financial sharing systems, audit management systems, and procurement contract project systems. Daily generated documents include internal control self-evaluation reports, audit notices, audit working papers, issue lists, rectification ledgers, and rectification closure certificates. The data update frequency is annual. Core fields include issue description, rectification measures, responsible entities, completion deadlines, supporting material identifiers, and more. Most documents combine structured tables and unstructured reports.
Constraints imposed on multi-turn dialogue and prompt engineering
The annual update frequency of this category of data means multi-turn dialogue contexts do not require frequent full data refreshes. Fixed context caching can reduce call overhead. Documents include both structured tables and unstructured reports, so prompt engineering must adapt separately to field extraction (such as responsible entities and completion deadlines in rectification ledgers) and text summarization (such as issue extraction from audit working papers). Core time-consuming links focus on sample extraction, issue formation, and rectification tracking. Multi-turn dialogue must split interaction nodes according to business processes to avoid overloading single inputs. Data is sourced from multiple systems, so dialogue must clearly prompt users to supplement document identifiers from corresponding systems to ensure accurate retrieval scope. At the same time, since errors may lead to regulatory notifications and accountability, multi-turn dialogue must add verification links to ensure output content matches enterprise preset data.
Configuration settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Maximum context length | 8000–12000 token | Adapts to the total length of full annually updated documents, avoids exceeding context thresholds |
| Maximum reply tokens per dialogue | 2000–3000 token | Matches the single-section content length of rectification ledgers and audit working papers, ensures complete output of rectification requirements |
| Variable binding | Enabled | Binds the variables parameter to associate system preset fields, quickly calls data such as rectification responsible entities and completion deadlines |
| Multi-turn dialogue history retention period | 7 days | Adapts to the standard cycle of audit projects, retains historical interaction records for rectification tracking and review |
| Attachment upload size limit | 100 MB | Matches the standard file size of audit working papers and self-evaluation reports, avoids errors from large file transfers |
| Historical message synchronization | Enabled | Enables the messages parameter to synchronize session history, ensures coherent context across multi-turn interactions |
Reference only; verify against the target FastGPT release and deployment documentation.
Three common misconfigurations
- Phenomenon: An error of "fail to create post presigned url" is prompted when uploading attachments such as audit working papers and rectification ledgers, or RAG file upload fails, while the template import function operates normally. Cause: The signature parameters of the S3 storage configuration were not synchronized after an upgrade, or the attachment upload size limit is set lower than the actual size of the uploaded file.
- Phenomenon: The responsible entity field of the rectification ledger cannot be extracted correctly during multi-turn dialogue. Cause: The prompt engineering does not clearly distinguish extraction rules for structured and unstructured documents, and the
variablesparameter is not bound to associate preset system fields. - Phenomenon: Subsequent interactions cannot associate historical context after a multi-turn dialogue session is interrupted. Cause: The
chatIdparameter is not enabled to automatically generate session identifiers, or historical message synchronization configuration is not enabled.
How to verify successful configuration
- Upload a single audit working paper under 100 MB, confirm no upload errors occur.
- Initiate a multi-turn dialogue, input an instruction to extract audit issue lists, verify that returned results include preset fields of issue description and rectification measures.
- Verify the coherence of multi-turn dialogue context, confirm that historical interaction records are retained with the session.
- Check whether the
chatIdparameter is automatically generated for new sessions, ensure that each interaction has a unique session identifier.
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.