What this category of data looks like
This category of data comes from the national unified construction project environmental impact assessment (EIA) declaration and approval system, ecological environment zoning control results, pollution discharge permit platform, and monitoring data. The update frequency is irregular. Daily processed documents include environmental impact assessment reports or report forms, approval applications, public participation explanations, technical assessment opinions, and EIA approvals. Document structures contain fields such as basic project information, category level judgment basis, pollution prevention measures, public participation status, and approval process nodes. Individual document lengths vary widely, and there is no unified fixed short-text format.
What constraints these characteristics impose on the knowledge base retrieval and recall link
Scattered data sources and non-fixed update cycles require the retrieval and recall link to support incremental synchronization and dynamic updates, to avoid using expired zoning control or monitoring data. Complex document structures and wide length differences require chunking strategies to adapt to long-text splitting, while retaining contextual integrity of key audit nodes. Errors made during EIA approval are directly tied to project construction and law enforcement accountability, so recall results must have high matching accuracy to avoid irrelevant documents interfering with approval decisions. Additionally, this category has overlapping terminology with adjacent categories such as pollution discharge permits, so the search scope must be strictly limited to the exclusive EIA knowledge base to prevent cross-category data confusion.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
similarity | 0.75–0.85 | EIA documents have high professional requirements, so low-match irrelevant content must be filtered to ensure the relevance of recall results |
limit | Top 8 entries | EIA approval requires checking multi-dimensional materials; an appropriate number of recall results can cover core audit points such as project category and pollution prevention measures |
searchMode | Semantic search | EIA terms have multiple expressions, so semantic matching can accurately target professional content better than pure keyword matching |
usingReRank | Enabled | Recall results from split long documents require secondary ranking to select fragments most relevant to approval questions |
datasetSearchUsingExtensionQuery | Enabled | EIA project names and categories have multiple expressions, so extended queries can cover more relevant documents |
collectionIds | Bind exclusive EIA knowledge base collection | Prevent mixing documents from other categories such as pollution discharge permits and environmental monitoring, avoiding cross-category data interference with approval processes |
Three common mistakes
- Phenomenon: Unexpected GPT-4o-mini call error logs appear during workflow runtime. Cause: The
collectionIdsbinding to the exclusive EIA knowledge base collection was not configured correctly, causing the system to trigger the default large model call logic. - Phenomenon: The uploaded EIA document directory structure is automatically deleted, and duplicate content is cleaned up without prompts. Cause: The automatic document cleaning rule of the knowledge base was not turned off; the default rule removes directories and merges duplicate text.
- Phenomenon: The question-and-answer pair extraction task is stuck in training, and no relevant records appear in the call logs. Cause: EIA documents were not correctly imported into the bound knowledge base collection, or the imported documents have no extractable fragments that meet requirements.
How to confirm the configuration is correct
- Check the knowledge base collection configuration in FastGPT v4.17.0, confirm that only EIA-related document collection IDs are included.
- Initiate a test query, enter a question related to EIA project categories, and verify that the
similarityscore of the returned results falls within the preset 0.75–0.85 range. - View the workflow runtime logs, confirm that only knowledge base retrieval operations are triggered, with no additional large model call records.
- Upload a standard EIA document fragment, verify that the question-and-answer pair extraction task starts normally and generates viewable extraction results.
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.