What This Category of Data Looks Like
The core data sources for this category include engineering orders, sand, cement and admixture inspection records, moisture content test reports, mixing plant control systems, and project laboratories. Data updates follow three rhythms: per vehicle production task, per batch of raw material delivery, and daily summary statistics.
Daily documents include mix proportion notices, opening identifications, production and transport slips, raw material inspection reports, test block records, and strength reports. Document fields cover mix proportion usage, slump, strength grade, transport order numbers, test block age, and more. Most fields use dedicated units, and some documents include original inspection tables in scanned format.
Constraints on Document Parsing and Chunking
The data characteristics of this category impose multiple constraints on document parsing and chunking. High-frequency single-vehicle production and transport slips are short documents, so avoid splitting professional field combinations across chunks. Batch daily summary documents are long documents, so control single chunk length to avoid exceeding model context limits.
Different document types have distinct structural differences: mix proportion notices and test block records use different layout logic, so structured separation rules must be adapted. Original reports in scanned format must retain table structures to avoid losing field associations after parsing. High-frequency updated data requires the parsing process to have sufficient timeout fault tolerance to prevent task interruptions from excessive processing time.
Configuration Settings
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the average length of a single ledger document, avoids splitting professional field combinations |
chunkSplitter | Custom delimiter (line break + keywords "order number", "date") | Matches the structured layout of ready-mixed concrete documents, avoids merging production and transport content across separate slips |
customPdfParse | Enable Marker parsing mode | Adapts to opening identifications and test block reports with scanned content, retains text and table structures |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Accommodates single-batch raw material inspection summary documents, avoids upload limit errors |
PARSE_FILE_TIMEOUT_SECONDS | 300–600 seconds | Adapts to parsing time for large-volume summary documents, avoids task interruptions due to timeout |
chunkSettingMode | Manual mode | Adjusts chunking parameters for different document types (transport slips, inspection slips) to avoid automatic chunking breaking professional field associations |
Three Common Misconfigurations
- Uploading a 3MB PDF ledger summary file triggers an upload error | The
UPLOAD_FILE_MAX_SIZEparameter was not adjusted, the default threshold is lower than the actual file size, causing upload failure - After setting the custom delimiter only to line breaks, the chunking result still merges multiple independent production and transport slips | Structured keywords such as "order number" and "date" were not used as separation criteria; only using line breaks cannot distinguish individual vehicle transport ledgers
- An error occurs when parsing scanned-format opening identifications after deploying Marker via Docker | Environment variables were not correctly configured to point to the local parsing service, causing a failure when calling third-party parsing tools
How to Verify Correct Configuration
Executable verification actions compatible with FastGPT v4.17.0 are as follows:
- Upload a single production and transport slip PDF, check if the chunking result retains complete professional field combinations such as slump and mix proportion usage
- Upload a batch of raw material inspection summary documents, verify that the parsing progress completes within the
PARSE_FILE_TIMEOUT_SECONDSrange - Check system logs to confirm that no upload limit errors related to
UPLOAD_FILE_MAX_SIZEappear - For scanned-format opening identifications, confirm that the parsed result retains the original table field layout
The values listed here are common starting points and should be evaluated against the reader's own samples.