What the data for this category looks like
Data for IT service category research reports comes primarily from industry association public reports, monthly updates from third-party research institutions, annual and half-year financial reports of listed IT service enterprises, and technical implementation research reports released independently by vendors. Update cycles follow monthly and quarterly schedules, with some emerging technology tracks receiving weekly dynamic updates. Document structures usually include overall industry scale, segmented track proportions, leading vendor competition patterns, core technical parameters, and implementation case details. Fields include revenue units, time cycles, technical indicator units, and other relevant metrics.
What constraints do these characteristics impose on document parsing and chunking
The structured, nested nature of IT service research reports requires the document parsing stage to retain hierarchical association information for tables and charts, to avoid losing business logic connections after chunking. High-frequency updated, large-volume research reports can total dozens of pages per document. This requires chunking strategies to adapt to long document processing, and avoid truncating core argument paragraphs across chapters. Fields with mixed units, such as revenue and computing power parameters, require parsing to bind values to their corresponding units, to prevent values and units from being separated after chunking. The large number of technical implementation cases requires chunking to retain the contextual association of cases, to ensure that complete application scenario descriptions can be obtained during retrieval.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | IT service research reports have large individual volumes. The parsing process includes multi-page text and table extraction. 600 seconds covers the full parsing cycle for most large files |
chunk_size | 800–1200 characters | Research reports contain professional technical terms and long argument paragraphs. This range retains complete business logic while adapting to the context window limits of most large models |
chunk_overlap | 100–150 characters | Prevents chunking from truncating core arguments across paragraphs, ensuring that contextual information from adjacent paragraphs can be obtained during retrieval |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Some large industry research reports include multiple appendix sections. This threshold covers the file volume requirements for most compliant uploads |
enable_structured_parse | Enabled | IT service research reports contain a large number of structured tables and data fields. Enabling this option retains hierarchical and associated table information, improving retrieval accuracy |
max_context | 8192 tokens | Adapts to the context windows of most mainstream large models, preventing chunked content from exceeding the model's processing range |
The parameter values provided on this page are common starting points for configuration setup. Actual values are affected by material format, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.
Three common errors
- Phenomenon: In the locally deployed FastGPT 4.8.22 version, the file parsing function cannot be triggered normally, and the interface shows stalled parsing status. Cause: Local parsing service port mapping is not configured correctly, causing the main program to fail to connect to the parsing node.
- Phenomenon: A
500 Internal Server Erroris returned when parsing research reports online. The log contains error fields for JSON parsing failure. Cause: Special characters in the research report are not properly escaped, causing a format error in the parsing module when generating structured JSON. - Phenomenon: After uploading a large-volume research report, the system waits continuously for parsing results and eventually triggers a timeout error. Cause: No parsing task queuing mechanism is configured. A single large file occupies parsing resources for too long, causing subsequent tasks to fail to process in a timely manner.
How to confirm the configuration is properly set
- Upload a typical-volume IT service research report, check the number of parsed text blocks, and verify that the chunk length matches the preset chunking configuration range.
- Check the parsing log to confirm that the parsing timeout configuration is not triggered, and the parsing process completes fully with no abnormal error fields.
- Upload a research report containing structured tables, check the parsing results to confirm that the hierarchical and associated information of the tables is fully retained.
- Test the multi-file upload scenario to confirm that the upload threshold configuration allows files of the target volume to be submitted normally.
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.