What the data for this category looks like
Urban public transport policy and regulatory basis data mainly comes from Ministry of Transport industry management specifications, provincial and municipal transportation authorities' operating rules, public transport group internal implementation documents, and local regulations. There is no fixed update cycle, and data is synchronized simultaneously when new fare adjustments, subsidy policies, or operating rules are released. Most documents are in official document format, containing fields such as document number, issuing unit, effective date, applicable region, specific clauses, and implementation requirements. Some scanned documents require OCR parsing, and field units mostly involve industry-specific units such as yuan/passenger, yuan/ticket.
What constraints these characteristics impose on deployment and upgrade
Since policy sources cover multiple levels including ministry and local levels and are relatively scattered, multi-source data import paths must be configured during deployment to support batch import of policy files from different channels. As policy updates have no fixed cycle, the incremental synchronization mechanism must be adjusted during upgrades to support manual trigger or synchronization triggered by policy release nodes, without requiring fixed periodic scheduling. Additionally, although official document structures are unified, field requirements are strict. Dedicated field extraction rules must be configured during deployment to adapt to special fields such as document number and effective date, avoiding generic chunking logic from damaging clause integrity.
Configuration Setup
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
DB_MAX_LINK | 10–15 | Urban public transport policy documents have a moderate scale; this setting avoids exhausting database connection resources |
REDIS_URL | redis://localhost:6379 | Used to cache policy metadata and retrieval results; intranet deployment prioritizes local instances |
STORAGE_S3_ENDPOINT | Configure per local object storage service endpoint | Stores batch-imported original policy files and parsed text blocks |
FE_DOMAIN | http://localhost:3000 | Configures the intranet-deployed frontend access domain, adapting to local testing scenarios |
| File upload size limit | Within 50 MB | Adapts to the size of scanned documents or long texts from single public transport policy files |
Three Common Configuration Mistakes
- Phenomenon: After deploying via Docker on Windows, accessing the frontend page fails to load or returns a connection error. Cause: The
FE_DOMAINparameter is not configured correctly, or the host port mapping conflicts with the local service port. - Phenomenon: During intranet docker-compose deployment, logs prompt database connection refused, and the database service status is normal. Cause: The FastGPT container and database container are not configured in the same custom network, or the database connection string parameters are configured incorrectly.
- Phenomenon: The policy Q&A model API responds normally when called directly, but the response delay increases significantly when called in FastGPT. Cause: The
REDIS_URLis not configured to enable caching, resulting in repeated full policy document retrieval and parsing for each Q&A.
How to Confirm the Configuration Is Complete
- Run container status check commands to confirm all FastGPT-related service containers are running normally.
- Access the configured frontend access address, verify that the page loads normally and there are no resource loading failure prompts.
- Import a local urban public transport policy test file, initiate a test Q&A, verify that the corresponding policy clause content can be returned.
- Check system logs to confirm there are no error messages for database and cache service connection requests.
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.