What the data for this category looks like
Data for this category primarily comes from the national land spatial planning one-map system, project approval and supervision platform, land use status database, and ecological protection redline data. Update frequency is irregular. Associated daily documents include land pre-examination and site selection opinions, construction land planning permits, construction engineering planning permits, redline drawings, and planning conditions. Data fields include project site selection scope, land scale, control requirements, and approval node status. There is no unified fixed unit; values match corresponding standards for specific approval matters. Typical service subjects include natural resources department land use control and planning permit offices, administrative examination and approval bureaus, and project units.
What constraints these characteristics impose on conversation logs and audit workflows
Data sources for this category are scattered, and updates follow no fixed cycle. Conversation logs must be linked to unique identifiers of corresponding data sources to ensure traceability of original basis during audits. Daily documents include multiple types of pre-approval documents. Logs must fully retain document fragments and approval node information referenced during interaction, to avoid audit failure due to incomplete information. Error consequences affect project approval and construction. Logs must retain complete request parameters, response content, and verification results. They must also distinguish interaction links between party building learning Q&A and business approval to facilitate compliance audits. Data fields change dynamically with each matter, so logs must retain complete structures of original requests and responses, with no forced field truncation.
Configuration Settings
This configuration is formulated for FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chatId | Bind to the project approval unique code | Ensure strong association between logs and corresponding land pre-examination projects, enabling quick session location during audits |
responseChatItemId | Link to unique identifier of document fragments | Facilitate traceability of original approval documents such as redline drawings and planning conditions referenced in conversations |
detail | Enable full log storage | Retain original requests, responses, and intermediate verification results to meet public service audit requirements |
| Log retention period | 180 days | Aligns with conventional retention cycles for audit archives in public service sectors |
| Single conversation context count | First 10 entries | Covers multi-turn interaction needs for party building learning Q&A and pre-reference requirements for business approval |
| Log storage limit | 1000 MB per project | Adapts to log data volume for single-project approval in this category, preventing resource overflow |
Three Common Misconfigurations
- Phenomenon: The conversation log panel only displays the first 50 interaction entries, making historical conversations beyond the threshold unavailable. Cause: The log retention count configuration was not adjusted; the default threshold is too low and does not match the long interaction requirements of multi-step approval for this category.
- Phenomenon: The interface for retrieving application history returns credential errors, even after confirming the credential configuration is correct. Cause:
chatIdwas not bound to the project approval unique code, causing interface verification to fail to match a valid session identifier. - Phenomenon: During multi-turn party building learning Q&A, the model cannot associate content from previous rounds and has no prior interaction memory. Cause: Correct context association logic was not configured, or logs did not retain complete
responseChatItemIdlinks, preventing the model from obtaining historical interaction basis.
How to Verify Proper Configuration
- Initiate a party building learning Q&A related to land pre-examination, and check if the bound project approval unique code is included in the log details.
- Call the interface for retrieving application history, and verify that the returned log content includes complete
detailfield information with no forced truncation. - Initiate multi-turn party building learning Q&A and business consultation, confirm that the model can access context content from previous interactions, and that logs retain all document fragments associated with
responseChatItemId. - Check the usage of the log storage directory, confirm that it does not exceed the preset 1000 MB per project threshold.
The values provided 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.