What This Type of Data Looks Like
Data for water treatment financing daily reports originates primarily from environmental protection project declaration ledgers, local water industry public disclosure materials, and project filing documents from financing institutions. Updates are delivered daily, covering new water treatment project financing updates from the current day and the past seven days. Most documents are delivered in Excel format. Headers include fields such as project name, water treatment type, financing subject, financing amount, fund arrival date, daily treatment scale, and project location. The daily treatment scale uses cubic meters per day as the unit. Financing amount uses ten thousand RMB as the unit.
Constraints on Document Parsing and Chunking
Mass daily Excel data (single files can exceed 10,000 rows) requires the parsing process to support large file handling, to avoid timeouts or data truncation. Fields include numeric data with units, such as daily treatment scale measured in cubic meters per day. Parsing must retain the association between fields and their units to prevent information loss. Each financing project in a single file is an independent business unit. Chunking must use individual projects as the minimum granularity, to avoid splicing information across projects. It must also adapt to project information blocks of varying lengths, to prevent individual blocks from becoming too long and exceeding context limits. Mixed multi-type fields require the parsing process to accurately distinguish text, numeric, and date formats, to ensure post-chunking information can be correctly identified by subsequent steps.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 2000 MB | Accommodates Excel files with 10,000+ rows, reserves sufficient space for upload and parsing |
PARSE_EXCEL_HEADER_ROW | 1 | The header for water treatment financing daily reports is fixed in the first row, ensuring accurate field recognition |
maxChunkSize | 800–1200 characters | Matches the information length of individual financing projects, adapts to context window limits |
chunkOverlap | 100–150 characters | Retains associated information between adjacent projects, avoids context breaks |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Large file parsing requires extended processing time, prevents mid-process interruptions |
enableFieldUnitRecognition | Enabled | Retains unit information for daily treatment scale and financing amount, ensures complete data parsing |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, 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 Misconfigurations
- Symptom: Incomplete command-style prompts are returned when parsing Excel documents. Cause: The
maxChunkSizeparameter is not adjusted. Excess rows included in a single block exceed context limits, triggering abnormal model responses. - Symptom: Fields and their units are lost after chunking. For example, daily treatment scale only displays the numeric value without the "cubic meters per day" unit. Cause: The
enableFieldUnitRecognitionconfiguration is not enabled, so the parsing process fails to associate fields with their unit information. - Symptom: Single file parsing times out or is truncated. Cause:
PARSE_FILE_TIMEOUT_SECONDSis set too short, failing to match the processing time required for 10,000+ row Excel files.
How to Verify Correct Configuration
- Upload a single test Excel file with 10,000+ rows. Check that parsing completion status codes show no abnormalities and no timeout errors occur.
- Randomly select multiple financing projects. Confirm chunked content includes complete project information and corresponding units, with no missing fields.
- Review the number of chunked results. Verify each project corresponds to one independent chunk, with no cross-project splicing.
- Initiate a test conversation. Confirm the model can accurately extract fields such as financing amount and treatment scale from chunked content, with no information omitted.
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.