What the data for this category looks like
The data for this category mainly comes from the territorial spatial basic information platform, natural resource survey and monitoring data, population and economic statistics data, and remote sensing images. The update frequency is annual. Daily processed documents include territorial spatial overall plans, detailed plans, special plans, planning implementation evaluation reports, and public opinion summaries. The data contains fields such as spatial coordinates, constraint indicators, and implementation progress. There are no unified fixed units. Corresponding field analysis rules must be matched based on specific planning types.
What Constraints These Characteristics Impose on the Deployment and Upgrade Link
Annual updated multi-source spatial data requires the deployment link to support batch offline synchronization or incremental update configuration. This avoids excessive system resource occupation from full data pulls. The heterogeneous structure of multiple types of planning documents requires adaptation to analysis rules for different documents during upgrade. This ensures the integrity and accuracy of field extraction. The spatial attribute association of multi-source data requires configuring cross-data source index matching logic during deployment. This avoids data conflicts. The party building learning Q&A scenario needs to synchronize planning business data and party building policy documents. The deployment link must reserve docking interfaces for dual data sources. This ensures the two types of data can be called collaboratively.
How to Set Configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGODB_URI | mongodb://localhost:27017/fastgpt | Core database for storing planning documents and Q&A conversations. Must match the network path of the local deployment. |
REDIS_URL | redis://localhost:6379/0 | Caches high-frequency queried planning data and party building Q&A context. Reduces database load. |
DB_MAX_LINK | 20–30 | Adapts to concurrent connection counts for annual batch data synchronization. Avoids exhausting database connections. |
PG_URL | postgresql://fastgpt:pass@localhost:5432/fastgpt | Stores workflow configurations and Q&A logs. Adapts to structured query requirements for planning data. |
STORAGE_S3_ENDPOINT | http://localhost:9000 | Stores large-volume files such as remote sensing images and planning reports. Adapts to storage requirements for multi-source data. |
FILE_TOKEN_KEY | Determined through actual testing | Generates access tokens for planning documents. Ensures document access security in private deployments. |
Three Common Misconfigurations
- Symptom: The model interface cannot be called via port 3005 after startup. A 502 error is returned. Cause: Environment variables for the model channel are not configured correctly. FastGPT fails to associate the interface address of the corresponding model.
- Symptom: Large-volume remote sensing image files fail to load normally after Docker deployment. Cause:
STORAGE_S3_ENDPOINTis not configured, or the storage path is incorrect. The system cannot adapt to storage requirements for large planning files. - Symptom: Workflow runs with slow response. Timeouts occur even on an 8-core 32G machine. Cause:
DB_MAX_LINKis configured too low. Insufficient database connections during batch data synchronization slows down Q&A response speed.
How to Verify a Successful Configuration
- Log in to the system settings page of the FastGPT backend. Check the database connection status. Confirm that the configurations of
MONGODB_URIandPG_URLcan connect normally. - Upload a planning implementation evaluation report. Test the document analysis and vector database ingestion process. Confirm that data can be normally called by the Q&A workflow.
- Start the party building learning Q&A workflow. Input planning-related questions. Check that the response duration matches the preset configuration.
- View the Docker container runtime logs. Confirm that there are no connection errors for
REDIS_URLandSTORAGE_S3_ENDPOINT.
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.