What This Category of Data Looks Like
This category of data mainly comes from state-owned assets supervision information systems, enterprise asset management systems, property rights exchange systems, evaluation agency reports and financial statements. The update frequency is monthly. Daily processed documents include property rights registration forms, asset evaluation reports, property rights transfer plans, on-site transaction announcements and asset disposal approval forms. Most document fields cover entity details such as ownership number, original asset value, evaluation value and transaction base price. There is no unified standardized format. Associated information must be checked one by one for each individual document.
Constraints Imposed by These Characteristics on Multi-turn Dialogue and Prompt Engineering
Monthly updated data requires limiting the context window during multi-turn dialogue. This prevents expired data from interfering with review logic. Heterogeneous documents from multiple sources require specifying the required matching field range via prompts. This stops irrelevant information across documents from causing confusion. Sensitive fields such as ownership and transaction base price need format verification during dialogue. This avoids compliance issues caused by entry errors. Multi-turn dialogue must retain asset number associations within a single session. This ensures reviewers can trace previously supplemented material information during the review process, without repeating basic background explanations.
Configuration Specifications
This document follows the configuration guidelines for FastGPT v4.17.0.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
| Context window retention turns | 10–12 most recent dialogue turns | Declaration review requires tracing multi-turn supplemented material information; overly long context increases model processing load |
chatId | Bind the unique identifier of the corresponding asset batch | Must associate all file documents submitted in the same batch to avoid cross-session data confusion |
messages | Filter out non-business-related casual chat content | Ensure the model only processes dialogue information related to declaration review |
| Global variable configuration | Preset two global variables: asset ownership number and evaluation report number | Quickly locate document data for the corresponding batch and reduce repeated input |
| Session timeout reset time | Automatically reset after 7 days of no interaction | Matches the monthly data update rhythm and avoids using expired declaration data |
| Maximum character count per response | 6000–8000 characters | Must fully output comparison results and rectification suggestions for file review |
Three Common Mistakes
- Phenomenon: Prompts fail to correctly identify space-separated field values in documents, leading to failed ownership number matching. Cause: The prompt does not explicitly specify the field format to be split by spaces; the model will ignore consecutive spaces or special separators by default.
- Phenomenon: Applications created through the API release channel lose multi-turn dialogue context and cannot trace back previous declaration material supplement requests. Cause: The
messagesparameter is not correctly passed during API calls, or a fixedchatIdis not bound, causing sessions to be split. - Phenomenon: Dialogue logs are missing and previous file review records cannot be traced. Cause: Session log persistent storage is not configured, or the log directory is not correctly mounted in the Docker configuration, resulting in log loss after container restart.
How to Verify Successful Configuration
- Initiate a query that includes the asset ownership number, and check whether the model automatically associates the preset global variables to quickly locate the corresponding documents.
- Submit multiple consecutive requests for supplementing materials, and check whether the model retains the previous dialogue context without repeating the asset batch information.
- Simulate re-initiating a dialogue after 7 days of no interaction, and check whether the model resets the context to avoid using expired declaration data.
- Call the API interface to send a test request, and check whether the returned results include the correct
chatIdand completemessagescontext list.
The values provided here 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.