What the data for this category looks like
The data for urban public transit business process guidance comes primarily from three sources: internal transit group operation management systems, ticket settlement systems, and offline outlet registration records. There are two data update frequencies. Real-time data covers passenger consultation frequency and daily station queue wait times. Static data covers station adjustments, new route launches, and business handling material lists. Static data updates once daily. Each business document includes four core fields: process nodes, handling time limits, required materials, and consultation phone numbers. Process nodes are measured in "steps". Handling time limits are measured in "workdays".
What constraints these characteristics impose during deployment and upgrade
The low-latency requirement for real-time business data demands adjusting the value of DB_MAX_LINK during deployment. This ensures the database connection pool supports high-frequency consultation requests. The daily update schedule for static data requires configuring a scheduled synchronization script during upgrades. This ensures business documents stay aligned with internal group systems. The multi-field document structure demands targeted chunking of business nodes during deployment. This prevents irrelevant information from being included during vector recall. Additionally, the user base for public transit business inquiries spans all age groups. Consultation content has high similarity. A reasonable recall limit must be configured to avoid returning invalid results.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
DB_MAX_LINK | 20–30 connections | The concurrent consultation volume for urban public transit business is high, requiring a sufficient database connection pool to support high-frequency requests |
REDIS_URL | Local Redis instance on port 6379 | High-frequency business process data for consultations must be cached to reduce database query pressure |
STORAGE_S3_ENDPOINT | Access address of the internal transit group’s object storage | Static files such as scanned copies of business handling materials and route announcement images must be stored. Internal storage ensures data security |
MONGODB_URI | Cluster connection address with read-write separation configuration | Query and update operations for business documents are separated to improve processing efficiency for real-time data |
FILE_TOKEN_KEY | Encryption key aligned with the internal file system | Legitimacy of uploaded business handling materials must be verified to prevent unauthorized file imports |
Three common mistakes
- The first issue appears when an error triggers during upload of business handling images or documents, and the problem persists after redeployment. This occurs because
FILE_TOKEN_KEYis not configured correctly, causing signature verification to fail for file uploads. - The second issue appears when vector recall results do not match actual business processes, with key steps missing from recalled content. This occurs because chunking logic is not adjusted based on the structure of public transit business documents, leading to incorrect splitting of long documents and loss of process node information.
- The third issue appears when a "model not found" error triggers while calling a lightweight vector model, with no option to add models without GPU compatibility in the platform. This occurs because
REDIS_URLis not configured correctly, causing model configuration caching to fail, so the platform cannot recognize newly added model parameters.
How to confirm configurations are correct
- Use the database connection test tool included with FastGPT v4.17.0 to send a test request. Check whether the number of connections for
DB_MAX_LINKfalls within the configured range, with no connection timeout errors. - Upload a scanned copy of a public transit business handling material. Verify that the file can be stored normally and returns a valid access link, with no signature verification failure errors.
- Trigger a static business data synchronization task. Check whether daily updated route announcement files are generated in the internal object storage to confirm the synchronization logic is working.
- Send a simulated public transit business consultation request. Verify that vector recall results include core information such as complete process nodes and handling time limits.
The values provided are common starting points and should be measured against the user'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.