What the Data for This Category Looks Like
Reference only; verify against the target FastGPT release and deployment documentation.
What Constraints Do These Characteristics Impose on Workflow Orchestration
The clause-based structure of policy documents requires workflows to split content along clause boundaries to avoid semantic fragmentation. No fixed update cycle requires workflows to support regular re-embedding into the knowledge base to ensure data timeliness. Metadata such as effective dates and reserve categories in fields requires configuring filtering rules in workflows to only recall policies that match the applicable scope. Since documents come from official, authoritative sources, recalled content must strictly correspond to the original document text without unauthorized modification. Additionally, policy documents vary widely in length, so workflow logic must adapt to different content lengths.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Grain reserve policy documents are mostly clause-based long texts. This length can fully cover a single policy clause and avoid semantic fragmentation |
| Single Search Limit | Top 8 entries | The number of valid clauses in grain reserve policies is concentrated. Excessive recall will introduce irrelevant content and reduce answer accuracy |
| Reranking | Enabled | The priority of policy clauses is strongly correlated with release time and applicable scope. Reranking can place high-matching clauses first |
| Maximum Context | 4000 token | Core clauses of grain reserve policies are mostly within 4000 tokens. Exceeding this will lead to redundant context |
variables | Bind the "Policy Effective Date" and "Grain Reserve Category" variables | Need to filter expired policies based on release time and match corresponding clauses by reserve category |
nodeId | Bind the unique identifier of the grain reserve policy knowledge base | Ensure the workflow only calls the dedicated knowledge base and avoids mixing policy data from other categories |
Three Common Misconfigurations
- Phenomenon: Workflow query merge module returns duplicate or missing results. Cause: Failed to configure chunking parameters according to the clause-based structure of grain reserve policy documents, leading to failure to split content along policy clause boundaries during merging.
- Phenomenon: Global variables selected for custom knowledge base fail to trigger knowledge base recall normally. Cause: Failed to correctly configure the binding rules for
variables, and failed to limit the optional scope of variables to the grain reserve policy dedicated knowledge base. - Phenomenon: Workflow cannot upload policy documents for verification. Cause: Failed to enable the file upload node permission of the workflow, and failed to configure verification logic for red-headed document formats.
How to Confirm Proper Configuration
- Trigger a test query by entering "Policy basis for central reserve grain rotation", and check if the returned results include the original text of the policy clauses corresponding to the document number.
- View the workflow run log to confirm that the policy effective date parameter bound by
variableshas been correctly passed, and that only policy documents within the corresponding time range are recalled. - Upload a grain reserve red-headed document to confirm that the workflow can normally parse and extract clause content without format errors.
- Test the query merge module to confirm that the number of returned results matches the configured single search limit, with no duplicate content.
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.