What the Data for This Category Looks Like
Data for this category originates from ticketing systems, customer interview records, CRM systems, and product roadmaps. It is stored in requirement pool lists, requirement evaluation forms, customer feedback records, and version planning documents. Updates occur weekly or in line with product version iterations. Core fields include customer identifiers, requirement priority levels, merge tags, and version association items. The most common duplicate requirement merge process generates large volumes of associated validation data.
What Constraints These Characteristics Impose on Deployment and Upgrade
This category’s data is sourced from multiple dispersed locations and requires regular updates. Deployment workflows must support flexible external interface integration, to avoid hardcoding that limits data source expansion. Fields such as customer identifiers and priority levels include associated items, so data validation rules must be configured during deployment to prevent format conflicts across different sources. The weekly or version-level update frequency requires upgrade workflows to support incremental data migration, to avoid business interruptions caused by full replacement. Additionally, real-time access to customer feedback requires stable port and domain binding rules to be configured during deployment, to ensure normal routing of external requests.
How to Set the Configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGODB_URI | mongodb://username:password@host:port/dbname?authSource=admin | Stores core business data including requirement pool lists and customer feedback records, requires correct authentication and database name parameters |
REDIS_URL | redis://:password@host:port/0 | Caches frequently accessed requirement priority and merge tag data, recommends setting a connection timeout of 30 seconds |
FE_DOMAIN | https://your-fastgpt-domain.com | Binds the frontend access domain, ensures normal cross-domain handling for callback requests from external channels such as enterprise WeChat |
DB_MAX_LINK | 10–20 | Adapts to concurrent requests from weekly bulk requirement merging and evaluation, prevents connection pool exhaustion |
STORAGE_S3_ENDPOINT | Set based on actual testing | Stores document attachments such as version planning documents, must match the cloud service provider’s endpoint address |
ROOT_KEY | Custom complex string of at least 16 characters | Configures the system administrator’s highest privilege key, ensures security of background operations for requirement pool management |
Three Common Mistakes
- Symptom: Frontend pages cannot be accessed, returns 404 or connection timeout. Cause:
FE_DOMAINparameter is not configured correctly, leading to a mismatch between the frontend domain and backend service binding, and cross-domain requests are blocked. - Symptom: External model calls return connection refused. Cause: Host and port parameters for
PG_URLorREDIS_URLare not configured correctly, breaking the link between the model service and requirement pool management, preventing normal request forwarding. - Symptom: Duplicate data remains after bulk requirement merging. Cause:
DB_MAX_LINKis configured too low, leading to insufficient connection pool during concurrent processing, some merge operations fail to complete submission, and data consistency is compromised.
How to Confirm Configurations Are Correct
- Log in to the FastGPT v4.17.0 backend data source configuration page, and verify that the
MONGODB_URIandREDIS_URLparameters match the values entered during deployment. - Submit a test customer feedback entry, check that backend logs show normal request reception and storage records, with no error prompts.
- Access the configured
FE_DOMAINaddress, confirm that the frontend page loads normally and can submit test requirements. - Run a simulated bulk requirement merge operation, confirm that data validation rules take effect, with no format conflict errors.
The values listed are common starting points, and should be evaluated against the user’s own operational samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-10-19.