What this category of data looks like
Power generation equipment manufacturing policy and regulatory basis data originates from official documents issued by the National Energy Administration, the Ministry of Industry and Information Technology, and the State-owned Assets Supervision and Administration Commission of the State Council. Updates are synced to the knowledge base immediately after official policy release. Document structures include fields such as document number, issuing authority, effective date, clause text, applicable equipment category, and quantitative indicators. These fields cover rated power of power generation equipment, environmental emission limits, manufacturing cycle, and more. Common units include megawatts, milligrams per cubic meter, hours, and others. Single special policy documents can span dozens of pages, with highly professional content.
What constraints these characteristics impose on workflow orchestration
The fields of power generation equipment manufacturing policies contain a large number of professional quantitative indicators. This requires workflow nodes to accurately extract and verify field formats. The length of single documents varies widely. Workflows must support long text chunking to avoid exceeding large model context limits. Policy update frequency is irregular, and timeliness must be ensured. Workflows must include configured nodes for timed synchronization of data sources. Applicable scenarios differ significantly across policies. Workflows must support triggering corresponding policy query nodes based on variables such as equipment model and applicable region to ensure query accuracy.
How to set the configuration
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Matches the average length of single clauses of power generation equipment policies, avoiding overly fragmented chunks or exceeding large model processing limits |
| Maximum Single Search Results | Top 5 entries | Aligns with the common number of query entries for power generation equipment manufacturing policies, avoiding redundant returned content |
| Context Window | 16000 token | Adapts to the context quota of most mainstream large models, supporting full loading of single special policy document content |
| Variable Validation | Validate equipment model and emission limit fields | Ensures extracted policy fields meet the professional format requirements of power generation equipment manufacturing |
| Node Timeout | 600 seconds | Covers the time requirements of long text parsing and multi-round policy queries |
| Timed Synchronization | Every 7 days | Matches the regular update cycle of power generation equipment policies, ensuring knowledge base content timeliness |
Three Common Mistakes
- Phenomenon: When calling the workflow via a channel link, the interface prompts "undefined" is not valid JSON. Cause: The
variablesandnodeIdin the workflow are not correctly bound to fields such as the document number and effective date of power generation policies, resulting in empty node output and failure to generate valid JSON format. - Phenomenon: When orchestrating multiple large model dialogue nodes in the workflow, total token consumption exceeds expectations. Cause: The context window parameter is not configured, multiple nodes share the global token quota, and token usage is not managed independently per node.
- Phenomenon: Workflow functions do not match expected behavior. Post-investigation reveals that workflow nodes were mistakenly used as plugins. Cause: The applicable boundaries between workflows and plugins are not clearly defined. Workflows support chaining multiple nodes into a logical sequence, while plugins only implement a single independent function.
How to Confirm the Configuration Is Correct
- Manually trigger the workflow, check the output content of each node, and confirm that expected fields such as the document number, effective date, and quantitative indicators of power generation policies are included.
- Copy the channel link to a testing tool, verify that the JSON format of the returned results meets expectations, with no empty values or syntax errors.
- Adjust the maximum single search results parameter, observe whether the number of search results matches the configured value.
- View the timed synchronization logs of the workflow, confirm that the data source has completed updates according to the set cycle.
- Check the binding configuration of
variablesin the workflow, confirm that core fields of power generation policies have been associated.
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.