What the Data for This Category Looks Like
Data sources for water industry research reports include public documents from the China Urban Water Supply and Drainage Association, research reports from securities firms’ public utility teams, annual reports from local water utility groups, and water industry statistical bulletins from the Ministry of Housing and Urban-Rural Development.
There are three update schedules:
- In-depth industry research reports are updated quarterly
- Dynamic documents such as project bids and price adjustments are updated immediately when events occur
- Policy documents are updated synchronously upon release
Most documents consist of multi-paragraph body text paired with embedded operational data tables. Core fields include water treatment volume, total pipe network length, project investment amount, policy document number, and release date, with corresponding units being ten thousand cubic meters, kilometers, ten thousand yuan, no unit, and date respectively.
Constraints on Knowledge Base Retrieval and Recall
Dispersed, multi-source data requires compatibility with multiple upload formats including PDF, Word, and Excel, while supporting unified field mapping across documents from different sources. The presence of embedded operational tables requires the retrieval link to extract structured professional data from tables, preventing information loss from only recognizing plain text. Differentiated update frequencies require configuring batch incremental synchronization strategies, balancing the timeliness of industry dynamics and the stability of in-depth research reports. Extensive use of specialized terminology requires the retrieval link to support custom term mapping, reducing semantic recognition errors. The high proportion of long documents requires setting reasonable text chunking rules, avoiding context overflow that impacts recall accuracy.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Water industry research reports contain large numbers of specialized terms and table fragments. This chunk length covers core business descriptions in a single segment, avoiding disruption to term relevance and contextual logic |
recallTopK | Top 6–8 results | The number of relevant research reports in water industry specific use cases is moderate. This value balances contextual redundancy and information completeness |
similarityThreshold | 0.72–0.8 | Terminology in the water industry has high recognition accuracy. This threshold filters irrelevant public utility research reports while retaining weakly related but core policy documents |
PARSE_TABLE_ENABLE | Enabled | Water industry research reports contain large numbers of operational data tables. Enabling this setting extracts structured table fields, improving retrieval precision |
UPLOAD_FILE_MAX_SIZE | 1000 MB | A single in-depth water industry research report PDF may include multi-chapter charts. This size supports complete upload of full documents |
incrementalSyncInterval | 2 times daily | Balances the timeliness of industry dynamics and resource consumption, adapting to the update frequencies of different types of research reports |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require case-by-case analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Mistakes
- A knowledge base query API call returns the
403 Forbiddenerror code with a permission denied prompt. The cause is that an application secret was used when initiating the request, instead of a knowledge base-specific API key, and no interface access whitelist was configured. - Embedded research report screenshots in question-and-answer results fail to render, returning the
[Image failed to load]placeholder. The cause is that the image structured parsing switch for knowledge base files was not enabled, or uploaded research report images were not embedded in the document body and thus cannot be extracted. - Knowledge base retrieval response time exceeds business expectations, resulting in timeout prompts. The cause is that the number of recalled entries was set too high, or full retrieval of all documents was performed without enabling incremental synchronization, and no sharded retrieval strategy was configured.
How to Verify Proper Configuration
- Upload a water industry research report document that includes operational data tables, and check whether the parsed text extracts the core fields from the table to confirm that the table parsing configuration is active.
- Initiate a retrieval request containing water industry specialized terms, and check whether the number of returned results matches the preset recall top K configuration to confirm that the recall parameters are set correctly.
- Initiate a query API call using a knowledge base-specific API key, and check whether normal retrieval results are returned to confirm that the interface permission configuration is correct.
- Initiate multiple identical retrieval requests consecutively, and check whether the response time meets the threshold required by business needs to confirm that the synchronization and sharding configurations are reasonable.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.