What this category of data looks like
Policy data for refined petroleum product sales comes from official announcements and formal documents issued by the National Energy Administration and local commercial authorities. Update timing aligns with policy releases, with no fixed cycle. Most documents are formal papers with uniform document numbers. Their structure includes sections such as issuing authority, effective date, and clause details. Fields covered include policy document number, applicable region, execution standards, and penalty clauses. Units include refined petroleum product measurement and pricing units such as yuan per liter, ton, and liter. Individual document lengths range from several pages to dozens of pages.
What constraints these characteristics impose on workflow orchestration
Refined petroleum product policy data consists of structured formal documents that include key information such as region, validity period, and measurement units. Workflows must first verify that the query scenario’s region matches the policy’s effective scope. Long documents must be split by clause to prevent semantic breaks across clauses. Policy updates follow no fixed cycle, so a sync trigger mechanism adapted to non-fixed update rhythms must be configured. Additionally, pricing and measurement units from policies must retain their original format in the workflow to avoid content deviations from conversion errors.
How to set configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
| Chunking Rule | Split by policy clauses, single chunk 800–1200 characters | The length of refined petroleum product policy clauses falls within this range, preserving complete semantics |
| Variable Extraction | Bind policy document number and region fields in variables | Used to accurately match policy content for specific regions and document numbers |
| Node Trigger | Trigger the corresponding policy library based on the user's query region, bind the nodeId of the corresponding library | Refined petroleum product policies have regional implementation differences, so the recall scope must be narrowed |
| Context Limit | Retain the top 3 recall results | Policy clauses are highly correlated; excessive content may exceed the context window |
| Validity Check | Configure a node to verify the policy effective date | Avoid returning expired or invalid policy clauses |
| Sync Trigger | Trigger sync via new policy announcement pushes | Adapt to the non-fixed update rhythm of refined petroleum product policies |
Three Common Misconfigurations
- Symptom: Custom knowledge base selection global variables cannot be called in the judge node. Cause: The call permission for this global variable was not declared in the workflow's
variablesconfiguration. - Symptom: Large model output exceeds the preset word limit. Cause: The workflow has no context truncation rule configured, causing recalled policy document content to occupy the large model's response space.
- Symptom: Parsing failure error occurs when processing policy PDFs, returning the prompt "unable to recognize document structure". Cause: The chunking rule does not adapt to the chapter structure of policy documents, causing semantic breaks in clauses split across pages, which cannot be correctly identified.
How to Confirm the Configuration is Correct
- Initiate a policy query with a clear region, verify that the applicable region of the returned content matches the query conditions, confirming the node trigger configuration is effective.
- View the workflow's chunking log, confirm that the document split preserves the complete semantics of policy clauses with no cross-clause truncation.
- Configure the judgment condition for a custom global variable, trigger the test flow, confirming the judge node can normally execute the logical branch.
- Trigger a policy document sync task, confirm that newly uploaded policy files can be correctly parsed and included in the recall scope.
The values provided here 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.