What Data for This Category Looks Like
Data for this category originates from state-owned asset supervision information systems, enterprise asset management systems, property rights exchange systems, valuation agency reports, and financial statements. The update frequency is monthly. Daily processed documents include property rights registration forms, asset valuation reports, property rights transfer plans, on-site transaction announcements, and asset disposal approval forms. Fields covered include asset numbers, ownership subjects, evaluation benchmark values, transaction status, approval nodes, and more. The length of individual documents varies widely, ranging from hundreds to thousands of characters.
Constraints on Multi-turn Dialogue and Prompt Engineering
Data for this category is dispersed across multiple sources, uses fixed update cycles, and has significant differences in document structure. These factors create multiple constraints for multi-turn dialogue and prompt configuration. First, multi-source data requires cross-system integration. Multi-turn dialogue must accurately associate business fragments from different sources to avoid information deviation caused by broken context. Second, the monthly update frequency requires the knowledge base synchronization cycle to match the business data update rhythm. This prevents the use of expired asset ownership or transaction data. Third, large differences in fields and formats across documents require prompts to clearly specify processing rules for each document type. This ensures the LLM can correctly identify core business fields such as asset numbers and ownership subjects. Fourth, verification requirements for core business links require multi-turn dialogue to gradually guide users to supplement or verify key data. This avoids omissions that affect transaction compliance.
Configuration Recommendations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Maximum context length | 8000–12000 token | Single documents such as property rights transfer plans and asset valuation reports have considerable length, requiring coverage of multi-turn dialogue history interactions and associated business data |
| History retention period | 30 days | Matches the monthly update frequency of business data, preventing expired data from interfering with subsequent conversations |
| Number of recalled documents per request | Top 5 | Matches the volume of core asset data in state-owned asset management scenarios, avoiding excessive redundant information that disrupts LLM reasoning |
messages field format | Sort by role and timestamp | Ensures clear contextual logic for multi-turn dialogue, enabling the LLM to accurately associate historical interaction content |
variables invocation rule | Inject only after triggering knowledge base search | Ensures prompts only call verified business data, reducing invalid output |
chatId persistence configuration | Bind to department permission scope | Complies with confidentiality requirements for state-owned asset management, restricting cross-department access to conversation data |
Three Common Misconfigurations
- Unable to view conversation history in MongoDB. Cause: Persistent storage rules for
chatIdare not configured, or the storage path does not match the permission control requirements of the business system. - Knowledge base search functions normally during workflow debugging, but the AI dialogue does not reference knowledge base content. Cause: The
messagesfield does not correctly carry context fragments recalled from the knowledge base, or the prompt does not clearly specify rules for associating business documents. - Unable to use program execution results as background knowledge input for the next AI dialogue module. Cause: The execution result is not bound to the current conversation context via
variables, or the prompt does not declare the format for referencing this variable.
How to Confirm Successful Configuration
- Initiate a multi-turn dialogue that includes an asset number. Check that the
messagesfield records all interaction content in chronological order, and includes associated business document fragments. - Trigger a knowledge base search. Confirm that the conversation context includes core document fragments for this category, such as property rights registration form or asset valuation report content.
- After configuring the
variablesinjection rule, initiate a test dialogue. Verify that the LLM correctly references preset business variable content. - Wait 30 days, then retrieve historical conversation records. Confirm that records remain accessible normally, matching the configured retention period.
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.