Reference only; verify against the target FastGPT release and deployment documentation.
What Data for This Category Looks Like
Core data for this category comes from the territorial spatial basic information platform, natural resource survey and monitoring data, population and economic statistics, and remote sensing images. It is updated annually.
Daily processed documents include territorial spatial overall plans, detailed plans, special plans, planning implementation evaluation reports, and public opinion summaries. The overall data volume is large and multi-source heterogeneous. It includes fields such as spatial coordinates, constraint indicators, and public feedback.
This data is usually oriented to long-term regional spatial arrangements. It has obvious differences from individual planning permission-related businesses.
Constraints Imposed by These Characteristics on Multi-turn Dialogue and Prompt Engineering
The large, multi-source volume of documents requires multi-turn dialogue to retain context. This links constraint indicators across different planning files and prevents spatial layout conflicts.
Fixed annual updates mean high-frequency real-time retrieval is unnecessary. The dialogue tool must cover all annual planning documents.
For public opinion summary inquiry scenarios, prompts must guide users to supplement specific demands. This reduces vague queries.
Spatial data field characteristics require prompts to clearly bind indicator units and scopes. This prevents response deviations.
Responses related to planning approval must strictly match the provided document content. They cannot exceed the data boundary.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Chunk separator | Combine document paragraph hierarchy with custom separators | Territorial spatial planning documents have complex hierarchies. Using only title separators may cause key planning indicators to be split into different chunks |
| Overlap length | 150–200 characters | Ensure adjacent chunks cover connected planning content, and avoid forcibly splitting spatial constraint indicators |
| Maximum context | 8000–10000 token | Adapt to the long-text context requirements of planning documents, and retain historical discussion content for multi-turn dialogue |
| Single search limit | Top 8 results | Balance retrieval efficiency and content completeness, and cover core reference materials for planning compilation |
chatId | Persist to session cache | Ensure dialogue records can be read normally after window refresh, matching user usage habits |
messages | Retain the first 10 rounds of dialogue content | Support coherent discussion of multi-turn planning demands, and avoid repeated input of basic information |
Three Common Misconfigurations
- Symptom: Using #, ## and other titles as document chunk separators causes deviations in retrieval matching results. Cause: The title hierarchy of territorial spatial planning documents does not fully align with content boundaries. Using only title separators splits key planning indicators into different chunks.
- Symptom: The dialogue step returns a 422 status code. System operation guidelines cannot be output normally. Cause: Retrieved graphic and text guideline chunks contain unescaped format characters. This triggers interface verification rule interception.
- Symptom: Local dialogue records disappear after refreshing the dialogue window. Historical content remains visible in the background. Cause:
chatIdis only stored in temporary session memory. It is not persistently bound to the user session.
How to Verify Successful Configuration
- Manually split a single planning document. Check if chunked content covers key chapters of core documents such as overall plans and implementation evaluation reports.
- Initiate a multi-turn dialogue. Verify that the
messagescontext retains prior discussions including three zones and three lines coordination and special facility layout. - Test retrieval of planning data from different sources. Confirm that indicator parameters bound by
variablesmatch document content. - Refresh the dialogue window. Check if the session record bound by
chatIdloads normally without loss.
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.