What This Category’s Data Looks Like
Data related to coal chemical industry business process handling comes mainly from internal enterprise business manuals, window service guidelines, safety and environmental approval process documents, and qualification application guidelines. Updates follow internal enterprise process optimization and local regulatory policy adjustments, with a typical cycle of 1 to 3 months. Documents include structured tables such as approval node lists and material lists, plus unstructured paragraph text. Fields include processing item name, approval department, required materials, processing time limit, contact number, and more. Units for time limit fields are mostly working days or hours, while material fields note units like quantity and specification.
Constraints on Knowledge Base Retrieval and Recall
Coal chemical business process data has a high proportion of structured tables, and includes fields with specific units. This requires the retrieval link to retain table structure information and avoid breaking table content into scattered pieces. Business process questions often point to specific approval nodes or material requirements, requiring precise matching of field keywords to avoid unit confusion. Data has a fixed update cycle, so recall must prioritize the latest version of process documents to avoid returning outdated handling rules. In addition, coal chemical business involves hazardous chemical approval, and data accuracy directly affects handling compliance, imposing high constraints on retrieval and recall precision.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
similarity | 0.72–0.78 | Coal chemical business process questions are mostly precise step queries. This range balances recall coverage and precision, avoiding irrelevant processes from appearing in results |
limit | Top 8 entries | Relevant nodes for business process guidance usually do not exceed 7. Taking the top 8 entries covers the full process without introducing redundant information |
searchMode | keyword + vector | Balances keyword matching (such as "pollution discharge permit") and semantic matching (such as "how to collect the approval form"), adapting to scenarios where both fixed keywords and colloquial questions exist in coal chemical business |
usingReRank | Enabled | Performs secondary sorting on recall results to filter semantically similar but irrelevant process descriptions, improving result accuracy in coal chemical business process scenarios |
datasetSearchUsingExtensionQuery | Disabled | Coal chemical business process questions mostly target specific items. Expanding queries will easily introduce irrelevant general process content and reduce precision |
collectionIds | Bind to the dedicated knowledge base collection for coal chemical business process handling | Avoid recalling process documents of other categories, ensuring results only target the coal chemical business scenario |
Three Common Errors
- When retrieving tabular data for coal chemical business, only scattered cell text is returned, and the corresponding relationship of approval nodes cannot be restored. Cause: Multi-vector support for table data is not enabled, so the structural association information of the table is not correctly encoded, and key context is lost during retrieval.
- When calling the API to pull trained knowledge base documents, the returned content does not match the latest process in the business system. Cause: The FastGPT official knowledge base API interface is not used, and internal business interfaces are mistakenly called, pulling raw data that has not been cleaned and indexed.
- After configuring chunking-related parameters, redundant content across processing links appears in retrieval results, and target steps cannot be accurately matched. Cause: Chunking parameters are not adjusted based on the paragraph length of coal chemical business documents, leading to over-splitting or merging of long paragraphs, and irrelevant process descriptions are spliced during recall.
How to Verify Correct Configuration
- Upload a coal chemical business approval node table document, perform a simulated query, check if the returned results retain the table structure and field correspondence, and confirm that the multi-vector support configuration is effective.
- Initiate a query targeting a specific processing item, verify that the number of returned results matches the value of the configured
limitparameter, and confirm that the number of recalled entries meets expectations. - Check the knowledge base index logs, confirm that only the dedicated knowledge base collection for coal chemical business process handling is bound, and no documents from other categories are mixed in.
- Perform a re-ranking function test, compare the retrieval results with
usingReRankenabled and disabled, and confirm that redundant content is filtered out after enabling, making the results more precise.
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.