What this category of data looks like
Typical stakeholders include natural resources authorities’ land use control and planning permit divisions, administrative examination and approval bureaus, and project entities. Daily business documents include land pre-examination and site selection opinions, construction land planning permits, construction engineering planning permits, red line drawings, and planning conditions. Data sources include the national integrated land spatial planning map, project approval and supervision platform, current land use database, and ecological protection red line data. Update frequency is irregular, with no fixed cycle. Data fields include project site selection scope, land scale, control requirements, prior examination conditions, and some documents contain spatial coordinates and graphic information.
What constraints these characteristics impose on the multi-turn dialogue and prompt words link
Data sources cover multiple types of spatial and examination and approval information. Prompt words must clearly define retrieval scope to avoid recalling policy content from unrelated categories. Daily documents include unstructured red line drawings and planning conditions. Multi-turn dialogue must guide users to supplement specific project details such as site location and project type to match corresponding documents. Update frequency is irregular. Prompt words must note data timeliness, and require dialogue results to only reference the latest currently available policy content. Errors may lead to severe consequences. Multi-turn dialogue must add a verification step to confirm no conflicts between project site selection, control requirements, and land scale.
How to set the configuration
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
variables | Bind project type, site selection coordinates, examination and approval stage | Pass exclusive business variables for land pre-examination to narrow retrieval and dialogue scope |
chatId | Generate based on project approval number | Associate full-process dialogue for a single project, avoid context confusion, and ensure accurate conversation history |
messages | Retain 8000–12000 characters of recent conversation context | Policy documents related to land pre-examination are relatively long in individual length, requiring complete transmission of historical dialogue and original policy text |
| Single retrieval recall count | Top 6 entries | Match the conventional number of policy documents related to land pre-examination, avoid information overload |
| Conversation history retention period | 7 days | Cover the conventional cycle of project examination and approval, meet cross-time-period dialogue needs |
| Prompt word template | Limit to only use land spatial planning category policy documents | Clarify retrieval data sources, prevent recalling documents from other categories such as real estate registration |
Three Common Misconfigurations
- Issue: Garbled text appears in dialogue responses. Cause: No OCR preprocessing was applied to unstructured documents such as scanned red line drawings and planning conditions. Direct embedding causes text parsing failure.
- Issue: Conversation logs for local deployments are not automatically retained. Cause: Conversation log persistence configuration was not enabled, causing conversation records to be lost upon instance restart.
- Issue: Retrieval results include policy content unrelated to land pre-examination. Cause: The data source scope was not defined in the prompt words, leading to recall of documents from other natural resource categories such as real estate registration.
How to Verify Proper Configuration
- Initiate a test dialogue that includes specific project site selection coordinates, check that returned content only includes policy documents related to land pre-examination and planning permits.
- Generate a
chatIdfor different projects to initiate dialogue, check that conversation history only associates context content for the corresponding project, with no cross-project confusion. - Upload a scanned red line drawing and initiate a dialogue, check that the returned text has no garbled characters and the OCR recognition result is accurate.
- View the prompt word template configuration, confirm that
variablessuch as project type and examination and approval stage have been bound.
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.