What this category's data looks like
Typical documents for this category include territorial spatial master plans, detailed plans, special plans, planning implementation evaluation reports, and public opinion summaries. Data sources include spatial vector data from the territorial and spatial basic information platform, field survey data from natural resource survey and monitoring, population and economic statistical ledgers, and remote sensing image metadata. Data updates occur annually. Document structures include standardized planning indicators, spatial coordinate fields, department feedback opinions, and public-submitted request text. Single document lengths vary widely, from dozens of pages of special plans to hundreds of pages of regional comprehensive evaluation reports.
Constraints on vector models and indexes
Multi-source heterogeneous data features require indexes to support both text semantic retrieval and spatial attribute association. This avoids data fragmentation during ledger summary. The annual update rhythm means real-time indexes are unnecessary. Use batch incremental updates to reduce resource consumption. Varying document lengths require chunking strategies that adapt to both long texts and short entries. This ensures semantic integrity. The strong association between planning indicators and spatial coordinates requires vector models to align text content with metadata fields. This improves association accuracy during report generation. Errors directly affect planning approval progress. Index recall accuracy must meet business verification requirements. This avoids missing key constraint indicators.
Configuration settings
| Config Item | Recommended Value | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapts to the text length of documents in this category and the semantic integrity of spatial metadata, avoiding overly fragmented single chunks |
| Overlap Length | 100–150 characters | Reduces cross-chunk semantic breaks and ensures the coherence of long sentences in planning text |
| Similarity Threshold | 0.75–0.85 | Accurately matches planning indicators and ledger entries, filtering low-relevance redundant search results |
| Single Search Limit | Top 10 entries | Balances the information completeness of ledger summary and the response speed of report generation |
| maxToken | 16000 | Adapts to the model context limit of FastGPT v4.17.0, meeting the generation requirements of regional comprehensive planning reports |
| defaultToken | 4096 | Balances the accuracy of ledger entry parsing and the response efficiency of single requests |
Three common configuration mistakes
- Phenomenon: "invalid api key" or request timeout errors occur when calling the OpenAI interface. Cause: The proxy address and key binding rules of one API are not configured correctly, causing interface requests to fail to route normally to the target model.
- Phenomenon: Index recall results are empty or do not match the expected number of entries. Cause: Dedicated retrieval rules are not set for the spatial coordinate fields of territorial spatial data, causing metadata and text content to fail to associate, resulting in loss of key associated information during ledger summary.
- Phenomenon: Context overflow errors are triggered during report generation. Cause: The maxToken parameter is not adjusted reasonably, causing the aggregated multi-source ledger data to exceed the context length limit that the model can process.
How to confirm correct configuration
- Upload a single special planning document. Perform a chunking parsing test. Confirm that chunk length and overlap length match the preset configuration. Ensure no content chunks have obvious semantic breaks.
- Enter a retrieval request containing planning indicators and spatial scope. Confirm that recall results include relevant entries of the corresponding document. Verify that the quantity matches the set single search limit.
- Test calling the OpenAI interface via one API. Confirm that normal text responses are returned. Check that there are no key or routing related error messages.
- Import annual updated planning data. Run a batch index construction task. Confirm that index update progress is normal. Ensure there are no abnormal interruptions or error logs.
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.