What the data for this category looks like
Urban public transport policy and regulatory basis data comes primarily from official public documents released by local transportation authorities and municipal public transport groups. Updates trigger when new policies launch or existing policies are revised, with no fixed schedule. Single documents are mostly structured text with clear fields, including policy document number, issuing authority, effective date, applicable route scope, enforcement clauses, and other fields. Some files include attachments with operational specification details. All fields use plain text format, with no nested structured attachments. Individual document lengths range from hundreds to tens of thousands of characters.
What constraints these characteristics impose on the workflow orchestration link
Scattered sources and non-standardized formats of urban public transport policy data require adding data source aggregation and field standardization nodes to the workflow. These nodes unify formats for fields such as policy document numbers and effective dates across different cities. The lack of a fixed update cycle requires configuring a timed-triggered data source synchronization step to ensure calls use the latest policy versions. The wide range of document lengths requires setting adaptive chunking parameters in the workflow to prevent long texts from exceeding the large model's context limits. Differences in the applicable route scope field require adding route matching filters during the retrieval step to narrow the recall range.
How to Set Configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
| Question Classification | Divide by core policy scenarios (fare pricing, route adjustments, safety specifications) | Urban public transport policies are categorized around core operational scenarios, which narrows the recall range |
variables | Bind the queried city name and route number | Accurately match exclusive policy documents for the corresponding city and route |
| Maximum Context | 800–1200 characters | Aligns with the length range of core clauses of urban public transport policies, avoiding interference from redundant content |
| Single Search Limit | Top 3 results | Policy documents for the same scenario mostly fall within 3 entries, reducing the large model's processing load |
| Loop Trigger Condition | Trigger secondary generation when the answer lacks the policy effective date | User questions often require clear policy implementation timelines, which need supplementation if not included initially |
nodeId | Assign a fixed identifier to the data source synchronization node | Simplifies associating timed update tasks with the corresponding data source node |
Three Common Misconfigurations
- Phenomenon: Only 2 context entries appear in conversation details, and policy document content cannot be linked. Cause: The city and route parameters bound by
variableswere not added to the context recall rules, so the system recalls general context by default. - Phenomenon: The workflow loop fails to terminate correctly after triggering. Cause: No clear termination condition was configured in the loop node, such as failing to verify if the AI answer includes complete policy clauses.
- Phenomenon: Uploaded policy files are not correctly parsed into retrievable text. Cause: No node was configured to pass files directly to the large model, and the system's default text parsing process was used instead, leading to format loss.
How to Verify Proper Configuration
- Run a test workflow, input a policy question that includes city and route details, and check if the recalled documents match the specified city and route.
- Review workflow logs to confirm the
variablesparameters are correctly bound to the currently queried city and route information. - Trigger the timed update task, and confirm the data source node synchronizes the latest policy files as planned.
- Simulate a loop scenario, input a question that does not include the effective date, and confirm the workflow triggers secondary generation to supplement relevant information.
The values provided 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.