What this category of data looks like
Data related to land pre-examination and planning permit is sourced from the national land and spatial planning one-map platform, project approval and supervision platform, land use status database, and ecological protection redline data. Update frequency is irregular. Daily business documents include land pre-examination and site selection opinion, construction land planning permit, construction engineering planning permit, redline drawings, and planning conditions. Core fields include project site selection scope, land scale, control redline coordinates, pre-approval conditions, etc. The data structure is dynamically adjusted along with project approval stages.
What constraints these characteristics impose on the "multi-turn dialogue and prompt engineering" capability area
Since data sources are multiple and update frequency is irregular, multi-turn dialogue must remind users to confirm the timeliness of the data being used in each interaction, to avoid referencing expired control redline or approval data. Daily documents include unstructured content such as visual redline drawings and planning conditions. Multi-turn dialogue must guide users to upload or clearly reference the field information of corresponding documents. Core approval stages require verification of multi-dimensional content such as site compliance, land scale, and preconditions. Multi-turn dialogue must split interaction steps according to approval nodes, to avoid asking users to provide too much information at one time.
How to set the configuration
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting Range | Rationale |
|---|---|---|
| Maximum context length | 8000–12000 characters | Adapts to the long-text context requirements of approval documents related to land pre-examination and planning permit |
| Maximum tokens per single dialogue | 5000–7000 tokens | Matches the information density of approval materials to avoid dialogue interruptions |
| Number of retained multi-turn dialogue context entries | First 10 entries | Filters redundant historical information and focuses on core data of the current approval stage |
Prompt variable variables | Bind project number and redline coordinate fields | Extracts standardized business fields from user input to reduce manual input errors |
| Knowledge base recall upper limit | First 5 entries | Focuses on the latest land and spatial planning control data to avoid interference from redundant information |
Three common mistakes
- Symptom: Documents uploaded by users during dialogue, such as redline drawings and planning conditions, are not automatically stored in the knowledge base. Cause: The
variablesbinding for document fields to be stored in the knowledge base is not configured, and the automatic storage trigger rule for dialogue content is not enabled. - Symptom: Token consumption statistics data for the dialogue cannot be viewed. Cause: The global token statistics switch is not enabled, and the statistics display is not turned on in the chat page corresponding to
chatId. - Symptom: Approval data obtained after workflow SQL query cannot be correctly displayed in the AI dialogue box. Cause: The SQL query result is not bound to the
messagescontext, and the prompt word for result formatting is not configured.
How to confirm the configuration is correct
- Initiate a test dialogue, upload a planning condition document, and check whether a matching entry is added to the corresponding knowledge base.
- Enter the conversation details page, view the token consumption statistics data, and confirm that the statistics logic is running normally.
- Configure the SQL query workflow, execute a test query, and check whether the result is correctly rendered on the dialogue interface.
- Send an approval prompt in Markdown format to the test account, and check whether the format meets expectations.
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.