What Data Looks Like for This Category
Data for this category primarily comes from pressure testing platforms, APM monitoring systems, database slow logs, and production traffic baselines. Regularly produced documents include pressure testing plans, capacity assessment reports, pressure testing data records, and optimization suggestion sheets. Update frequency is monthly or during major version iterations. Document fields include core metrics such as throughput, response latency, and resource occupancy rate, with units mostly tps, milliseconds, percentage, or GB. Some reports include structured bottleneck analysis tables and resource configuration lists.
Constraints on Document Parsing and Chunking
Data sources for this category include structured tables, time-series monitoring data, and analytical text, with significant differences in content format across sources. Document update frequency is low, but batch updates occur during version iterations. Parsing must retain the binding relationship between metrics and units to avoid losing association with core performance indicators after chunking. Since documents focus on bottleneck identification and capacity conclusions, chunking must balance the contextual integrity of long-text analytical paragraphs and structured tables. Do not split cross-page bottleneck analysis and corresponding data into different chunks, as this will affect the accuracy of subsequent Q&A associations.
Configuration Settings
This document applies to FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | This category of documents includes long-text analytical paragraphs and structured tables. This range balances the integrity of single-block information and retrieval granularity |
chunkSplitter | Split by paragraph + heading | Adapts to the chapter structure of pressure testing plans and assessment reports, retaining contextual association of analytical logic |
customPdfParse | Enabled | Used to parse PDF-format pressure testing reports that support external resources, preventing the default parser from losing image links and table formats |
PARSE_FILE_TIMEOUT_SECONDS | 300–600 seconds | Large pressure testing data record files have more content, requiring sufficient parsing time |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Adapts to the upload needs of batch pressure testing data, preventing interception due to oversized files |
chunkSettingMode | Manual configuration | Allows adjusting chunking parameters for different document types (such as plan-type and data-type documents) to adapt to the multi-format documents in this category |
Three Common Misconfigurations
- Phenomenon: After uploading a pressure testing report PDF that includes external image links, the parsed result has no image-related content or prompts a file parsing failure. Cause: The
customPdfParseconfiguration is not enabled, and the default parsing engine cannot handle embedded content with external image links. - Phenomenon: After locally deploying MinerU, enabling enhanced PDF parsing still fails to call the service. Cause: FastGPT's parsing port is not aligned with MinerU's local Docker port, or the corresponding port is not opened in the firewall.
- Phenomenon: After enabling table multi-vector support, the retrieval result does not include complete table field information. Cause: The chunking configuration is not adapted to structured tables, splitting the table into multiple independent chunks and destroying the contextual integrity of the table.
How to Verify Proper Configuration
- Upload a standard pressure testing plan PDF, check whether the parsed text retains the association between metric units and chapter headings.
- View the parsing status log in the knowledge base settings, confirm that the
customPdfParseoption is checked, and no timeout errors appear in the parsing task. - Upload a pressure testing data record file larger than 500 MB, confirm that the upload and parsing process is not interrupted.
- Test retrieval of specific bottleneck indicators in the pressure testing report, confirm that the retrieval result can associate with the complete contextual content of the corresponding chunk.
Note: The values provided are common starting points and should be evaluated 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 2026-10-19.