What Data for This Category Looks Like
The core data for this category comes from the national land and spatial planning one-map platform, project approval and supervision platform, current land use database, and ecological protection redline data, with irregular update frequency. Daily processed documents include land pre-examination and site selection opinions, construction land planning permits, construction engineering planning permits, redline drawings, and planning conditions. Fields include project name, land location, land scale, redline coordinates, approval status, and more. Land scale units are mostly hectares or square meters. Redline drawings contain longitude and latitude coordinate points. Each document corresponds to a unique project approval node.
Constraints Imposed on Multi-turn Dialogue and Prompt Engineering
As data sources are scattered and updated irregularly, multi-turn dialogue must be bound to a specific project to avoid mixing information from different approval processes. Document types include text and vector formats. Prompts must clearly distinguish extraction rules for different documents to ensure accuracy of professional fields such as land scale and redline coordinates. There are many project approval links, and the consequences of errors are severe. Multi-turn dialogue must retain context information from prior approvals for compliance verification, while strictly limiting the scope of dialogue content to prevent irrelevant data from interfering with result generation.
Configuration Settings
The following configurations apply to FastGPT v4.17.0.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
chatId | Generate based on the project's unique identifier | Must bind to a specific land project to avoid mixing data across project dialogues |
messages | Retain the most recent 20 rounds of dialogue content | Adapt to the context requirements of multi-turn land pre-examination approvals, retain information from prior approval nodes |
variables | Inject project number and redline coordinate range | Quickly locate ledger and planning documents for the corresponding project |
| Single-turn dialogue token limit | 8000–12000 tokens | Accommodate text from multiple planning documents and dialogue history content |
| Prompt format verification | Enable mandatory field verification | Ensure extracted land information complies with business specifications |
Three Common Mistakes
- Phenomenon: Output content is plain markdown source text, not rendered into visual formatting. Cause: The prompt did not explicitly require format rendering, and did not inject rendering rules via
variables, causing the system to output as plain text. - Phenomenon: Unable to view input and output token count statistics for the dialogue. Cause: Did not bind the token counting logic for
messagescontext, or did not enable dialogue statistics configuration. - Phenomenon: No ledger data for the corresponding project is obtained after initiating a multi-turn dialogue. Cause: Did not use
chatIdto specify the target project, causing the system to call approval data for an unrelated project.
How to Confirm Proper Configuration
- Initiate a test dialogue, enter a specific project number, check if the returned result only associates documents for that project's land pre-examination and planning permit.
- View the dialogue history interface, confirm that input and output token count statistics are displayed.
- Submit a prompt containing markdown formatting, check if the output is rendered into visual content according to the format.
- Initiate a dialogue with more than 15 rounds, check if the system can normally retain context and continue interaction.
The values given 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.