What the Data for This Category Looks Like
This category uses data from government information disclosure platforms, agency archive systems, document management systems, departmental business ledgers, and relevant specifications from the Regulations on Government Information Disclosure. The system updates data irregularly, synchronizing with new applications, archived documents, or regulatory updates. Staff process daily documents including government information disclosure application forms, correction notification letters, third-party opinion solicitation letters, response letters, service receipts, and administrative reconsideration response materials. Core fields cover applicant information, application content orientation, public attribute judgment basis, response content, and remedy explanations. Individual documents have widely varying character lengths.
Constraints for Multi-turn Dialogue and Prompt Engineering Workflows
The dialogue system must support cross-system retrieval and integration to handle multiple data sources. Write prompts to explicitly guide the model to prioritize calling retrieval tools for corresponding data sources. Configure dialogue applications to support on-demand knowledge base synchronization, to avoid using outdated document content for irregular data update cycles. Design prompts to adapt to formatting requirements for different document types. For example, response letters must strictly include remedy explanations. Use multi-turn dialogue to track dynamic information such as applicant correction requests and third-party opinion feedback for individual case handling. Set the messages parameter to fully transmit historical interaction context, to ensure consistent judgment of applicant demands. Write prompts to guide the model to first complete information existence verification and public attribute judgment, before generating formal responses for the most time-consuming retrieval and drafting stages.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Single Search Limit | Top 5 results | Applications in this category target specific government information. Excessive search results will interfere with the model's localization and judgment of core information |
| Maximum Context Length | 8000–12000 token | Full retention of multi-turn applicant questions, historical correction information, and past response content is required, to avoid context truncation |
| Query Optimization | Enabled | Applicant statements may be vague or incomplete. Optimized queries can improve the accuracy of retrieval keywords |
| Reranking | Enabled | Search results must be sorted by relevance, to ensure the model prioritizes the most relevant document content as the basis for responses |
| Citation Limit | Top 3 results | Response letters must clearly cite supporting materials. Excessive citations will lead to content redundancy, which does not meet the concise requirements of government administrative documents |
| Knowledge Base Sync Trigger | Calibrated based on actual testing | Data update cycles are irregular. Synchronization timing must be adjusted based on actual archiving rhythms |
Reference only; verify against the target FastGPT release and deployment documentation.
Three Common Misconfigurations
- An "unauthorized access" prompt appears after calling a configured API key, or the log returns a 403 status code. This occurs because the API key is not bound to the knowledge base permission scope of the current application, or the permission configuration does not cover the access requirements of the corresponding data source.
- After increasing the citation limit, the model response does not cite any retrieved content. This occurs because the reranking threshold is set too high, causing the relevance score of search results to fail to meet the model's citation requirements, or the prompt does not explicitly require the model to generate responses based on retrieved content.
- Retrieval results include the paragraph ID field of the knowledge base, and the model includes this ID in the response content. This occurs because paragraph ID information was not cleaned during knowledge base chunking, or the prompt does not explicitly require hiding non-essential technical identifiers.
How to Verify Proper Configuration
- Initiate a simulated government information disclosure upon application dialogue. Check whether the system correctly loads the historical interaction context corresponding to
chatId, to verify the coherence of multi-turn dialogue. - Adjust the citation limit to Top 2 results. Initiate a test application. Check that the model response only cites the specified number of search results, with no additional redundant content.
- Upload a test government information disclosure application form. Check whether the system correctly identifies applicant information and application content in the document, to verify that the
variablesparameter correctly extracts core fields. - View the knowledge base synchronization log. Confirm that the latest archived documents such as response letters and correction notification letters have been correctly indexed, with no omissions or errors.
All configuration values listed here are common starting points. Adjust them based on your own specific samples and use cases.
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.