What this category of data looks like
Data for railway operations declaration materials and file review originates from railway transportation dispatch systems, station operation terminals, and shipper or passenger declaration portals. Declaration materials are submitted in real time during daily transportation operations. File documents are centrally archived on a monthly or quarterly basis. Each document follows a fixed structure, with fields including declaration number, train number, operation type, submission time, approval status, and associated attachment list. Common field units include train number, piece, and hour. Attachment types cover electronic forms, scanned documents, small engineering drawings, and more. Some documents require linking to multiple travel logs as supporting materials.
Constraints on Deployment and Upgrade
Real-time submitted declaration materials require the deployed FastGPT service to have low-latency concurrent processing capabilities. This prevents submission failures caused by insufficient connection limits. The centralized archiving of file documents requires storage configurations with sufficient expansion space. This accommodates high-volume batch import requests. The fixed field structure requires strict matching of preset fields during knowledge base import. This avoids metadata confusion. The variety of attachment types requires the file processing module to support parsing of multiple formats. It also requires compliance with internal network storage access permission rules. Cross-department data synchronization requirements also demand database connections that adapt to railway internal network isolation rules.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
DB_MAX_LINK | 150–250 concurrent connections | Adapts to peak concurrent submission volumes for railway declaration services, prevents connection exhaustion |
STORAGE_S3_ENDPOINT | Access endpoint for railway internal compliant object storage | Ensures secure and compliant file archiving, adapts to internal network access rules |
REDIS_URL | Address of an internally deployed Redis instance, connection timeout set to 600 seconds | Caches retrieval results to reduce database load, adapts to long-period file queries |
MONGODB_URI | Connection string for railway government cloud MongoDB cluster | Stores structured declaration metadata, ensures data security |
FILE_TOKEN_KEY | Unified internal railway file access key | Restricts access permissions for declaration attachments, complies with internal security specifications |
Three Common Configuration Mistakes
- Phenomenon: The reranker model passes tests, but the reranking result is false after each retrieval. Cause: The custom request address was not configured as the railway internal network model service address, resulting in insufficient cross-network request permissions or timeout.
- Phenomenon: FastGPT fails to start after upgrading fastgpt-mcp-server. Cause: The version matching relationship between the main service and mcp-server was not updated synchronously, resulting in protocol version incompatibility.
- Phenomenon: Chinese garbled characters appear after importing a CSV file into the knowledge base. Cause: The correct character encoding was not specified. CSV files exported internally for railway declarations use GBK encoding by default, and the corresponding encoding was not selected during import.
How to Verify Correct Configuration
- Log in to the FastGPT v4.17.0 console, navigate to the storage configuration page, check the connectivity test result for
STORAGE_S3_ENDPOINT, confirm it returns normally. - Submit a test declaration material, check the logs for the vector retrieval and reranking process, confirm there are no errors and the reranking result is normal.
- Import a CSV test file of railway declaration files, check that field mapping is correct and there are no Chinese garbled characters.
- Restart the fastgpt-mcp-server service, check that the startup logs have no version incompatibility related errors.
All provided configuration values are common starting points, and should be evaluated against the reader's specific 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.