What This Category’s Data Looks Like
Reference only; verify against the target FastGPT release and deployment documentation.
What Constraints These Characteristics Impose on the "Workflow Orchestration" Link
Since public transport business data is divided into two categories: static rules and dynamic status, with large differences in update rhythms, workflows must distinguish between static configuration and dynamic invocation links to avoid resource waste caused by frequent static data refreshes. At the same time, business handling involves many fields that require legality verification. Workflows must add parameter verification nodes to ensure that input route IDs and station names match preset system formats. In addition, tickets submitted by citizens trigger in real time. Workflows must support real-time API calls and event triggering, and cannot rely on scheduled batch data pulls.
Configuration Settings
| Config Item | Recommended Value | Rationale |
|---|---|---|
| Global Variable | {"bus_line_id": "", "station_name": ""} | Match core identifiers for public transport business handling, use variables parameter to store global business context and enable cross-node parameter reuse |
| Question Optimization | Enable | Resolve coreference resolution issues in user questions, automatically associate current route or station information stored in variables |
| Node ID Binding | Bind nodeId of intermediate AI dialogue node | Filter output content of intermediate nodes, avoid redundant information appearing in final handling guidance results |
| Knowledge Base Call Timeout | 60 seconds | Adapt to typical response duration of public transport business data interfaces, reserve reasonable buffer space |
| Single Search Limit | Top 5 entries | Documents related to public transport business handling usually do not exceed 5 entries, avoid excessive irrelevant content interfering with large model output |
| Context Length | 800–1200 characters | Adapt to content length of single public transport business handling inquiries, comply with typical context limits of large models |
Three Common Errors
- Intermediate AI dialogue results included in final output: The final workflow output contains redundant content from intermediate knowledge base calls. This occurs when no
nodeIdbinding is used to filter intermediate node output, leading to merged display of results from all nodes. - Coreference resolution failure: When a user inputs "the reissue process for this route", the system cannot identify the specific route ID referenced by "this". This occurs when question optimization is not enabled, and global business context is not bound via
variables. - Knowledge base call timeout error: Timeout-related errors are returned. This occurs when the timeout setting is shorter than the actual response duration of public transport business interfaces, and sufficient network and data processing time is not reserved.
How to Confirm Proper Configuration
- Submit a test ticket, check that the final workflow output only contains handling guidance content, with no redundant information from intermediate nodes.
- Input a referential question such as "How to handle this", check that the system automatically associates current business route or station information to complete coreference resolution.
- Simulate single calls and batch calls, verify that the workflow triggers normally and no timeout errors occur.
- View
variablesglobal variable transfer logs across nodes, confirm that core business identifiers are not lost.
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.