What This Category of Data Looks Like
The main subjects of this category of data include ecological environment authorities’ EIA departments, administrative examination and approval bureaus, construction units, and EIA institutions. Daily documents include environmental impact statements, environmental impact report forms, approval applications, public participation descriptions, technical assessment opinions, EIA approval decisions, and similar materials. Data sources include the national unified EIA declaration and approval system for construction projects, ecological environment zoning control results, pollution discharge permission platforms, and environmental monitoring data. The data update frequency is irregular, with no fixed cycle. Most documents combine structured fill-in content and long-text reports, including core fields such as project category, EIA level, pollution prevention measures, and public participation status. There is no unified fixed unit; field units vary depending on the document type.
What Constraints Do These Characteristics Impose on the Knowledge Base Retrieval and Recall Link
The data characteristics of this category impose clear constraints on the knowledge base retrieval and recall link. Data sources across multiple systems require limiting the retrieval scope to avoid interference from irrelevant data. Long-text documents such as environmental impact statements need to adapt to chunking rules to avoid splitting that damages the integrity of business logic. Irregularly updated data needs to support incremental indexing, eliminating the need for full reconstruction each time. Core fields such as project category and EIA level are critical for approval decisions. Retrieval must prioritize matching highly relevant content. Severe potential consequences require retrieval results to have stable confidence levels to prevent incorrect matches from disrupting the approval process.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
similarity | 0.72–0.80 | EIA approval-related content requires a high matching degree to avoid low-relevance results interfering with approval judgments |
limit | Top 8 entries | After matching core business fields, a small number of highly relevant results can support technical assessment and responses. Excessive results increase context pressure |
searchMode | vector+keyword | Balances retrieval needs for structured fields and long-text content, matching structured information such as project category and EIA level, as well as text content such as pollution prevention measures |
usingReRank | Enabled | Local matching deviations may occur after long-text chunking; re-ranking optimizes result sorting and improves the priority of core content |
datasetSearchUsingExtensionQuery | Enabled | Expands the retrieval scope to cover cross-system associated EIA data, supplementing business content not covered by a single data source |
collectionIds | Bind dedicated EIA approval dataset ID | Limits the retrieval scope to data exclusive to this category, avoiding mixing in irrelevant content from other domains |
Three Common Mistakes
- Phenomenon: When uploading EIA report files larger than 10MB, after being split into more than 1000 chunks, some chunks experience vectorization anomalies, and the interface displays abnormal chunking status. Cause: Chunking parameters were not adjusted for long-text EIA reports, leading to chunking boundaries damaging business logic and triggering vectorization verification failures.
- Phenomenon: After uploading multiple batches of EIA approval-related documents, the server restarts, the knowledge base does not automatically complete indexing, and the interface displays the knowledge base as unready with no automatic retry prompt. Cause: Automatic index triggering rules were not configured, relying only on manual triggering, and incremental indexing tasks were not restored after server restart.
- Phenomenon: When calling knowledge base retrieval, the number of returned results does not match the configuration of the
limitparameter, with either too many or too few results. Cause: The retrieval mode was not adjusted based on the mixed characteristics of structured and long-text EIA documents, leading to a mismatch between retrieval logic and data characteristics.
How to Confirm Proper Configuration
- View the retrieval configuration panel to confirm that the values of
similarity,limit,searchModeand other parameters comply with preset rules. - Upload a single typical EIA document, and check that there are no abnormal prompts for chunking status and vectorization results.
- Initiate a test retrieval targeting core business fields such as project category and EIA level, and verify that the relevance of returned results meets expectations.
- Simulate a server restart scenario to verify whether the knowledge base automatically triggers incremental indexing tasks without manual operation.
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.