What data for this category looks like
Data for this category primarily comes from government information disclosure platforms, official agency archive systems, internal document systems, departmental business ledgers, and relevant public disclosure norms. Daily processed documents include government information disclosure application forms, supplementary notification letters, third-party opinion solicitation letters, response letters, service receipts, and administrative reconsideration response materials. Data updates have no fixed cycle, and are synchronized with the processing progress of each individual government information disclosure application. Each data entry contains fields such as applicant information, application matters, retrieval scope, public attribute judgment results, response content, and relief pathway descriptions. The minimum processing unit is a single application matter.
What constraints do these characteristics impose on the multi-turn dialogue and prompt configuration link
The data characteristics of this category impose clear constraints on multi-turn dialogue and prompt configuration. First, data is scattered across multiple business systems. Multi-turn dialogue must bind the full-process context of a single application via chatId to avoid mixing information from different applications. Second, document types are diverse and field requirements are strict. Prompts must define information extraction and verification rules separately for different documents such as application forms and response letters. Third, data updates have no fixed cycle. Multi-turn dialogue must support real-time synchronization of context content for the latest processing progress. Fourth, processing errors will trigger administrative relief. Prompts must enforce verification of key content such as legal relief pathways and public attribute judgments to ensure response compliance.
How to set the configuration
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chatId | Bind to the unique number of a single application, consistently use {application number} as the identifier | Ensure multi-turn dialogue context for each government information disclosure application is independent, avoid mixing information across applications |
messages | Retain the most recent 15 rounds of dialogue content | Cover communication records across the full application processing cycle, while avoiding excessive context that causes inference delays |
variables | Pre-set three global variables: applicant information, application matters, response status | Quickly call the latest data synchronized from various business systems, reduce repetitive data entry operations |
| Prompt template grouping | Group by document type into three categories: application form parsing, response letter generation, ledger summary | Adapt to the diverse document structures and processing links of this category, improve the accuracy of information extraction and generation |
| Context retention duration | 30 days | Cover the processing cycle of most government information disclosure applications, ensure historical communication records are traceable |
| Post-tool-call output filtering | Only retain the final AI-generated content and ledger entries | Avoid debug information from the tool call process interfering with internal review and response output |
Three common mistakes
- Phenomenon: After tool calls are completed, dialogue results include tool call logs and parameter content, instead of only displaying AI-generated responses. Cause: No post-tool-call output filtering rules are configured, and no requirement to hide tool execution process information is included in the prompt.
- Phenomenon: Using the same global identifier to start dialogues for multiple different applications, resulting in mixed application information and misplaced response content. Cause: No exclusive
chatIdis bound to each application, leading to multi-turn dialogue contexts not being isolated by application. - Phenomenon: When importing Markdown format documents, image links lose their domain name prefix, making images unable to load normally in dialogues. Cause: No image link completion logic is configured in the document preprocessing link, and no fixed domain name parameter is synchronized via
variables.
How to confirm the configuration is correct
- Launch a multi-turn dialogue for a test application, check if context from different rounds only associates information for the current application, with no mixed content across applications.
- Switch document types, verify that prompts can correctly extract exclusive fields for corresponding documents, such as applicant information from application forms or relief pathway content from response letters.
- Trigger a tool call operation, check if the output result only retains the final AI-generated content, with no redundant logs from tool execution.
- View the context retention duration configuration, confirm that historical dialogue records for the test application can be normally retrieved within the processing cycle.
The values listed 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.