What the Data for This Use Case Looks Like
Data sources for urban gas ledger summary and report generation primarily include daily inspection records, pipeline network operation and maintenance reports, station operation logs, and user account opening and payment archives. Update cycles cover daily inspection ledgers, weekly operation reports, monthly operation reports, and annual summary reports. Daily inspection ledgers are updated daily per point. Report-type documents update on fixed cycles. Most documents use PDF format, and primarily contain structured tables with fields including inspection date, pipeline point number, pressure value, leak concentration, processing result, rectification measures, and handler. Pressure values use kilopascals as the unit. Leak concentrations use ppm as the unit. Point numbers are fixed-format strings. Dates use the YYYY-MM-DD format.
Constraints on Document Parsing and Chunking
Structured tables with unified fields make up a high proportion of documents. The parsing process must retain table structure and field correspondence. It must avoid splitting content from a single record across multiple chunks, which causes field misalignment during subsequent retrieval. Single monthly operation reports may contain dozens of pages of multi-row tables. These documents have large file sizes and high update frequencies. The parsing process must allow sufficient processing time to prevent timeout interruptions. Field names and units are consistent across different ledgers. Chunking processes must ensure complete associated field content within each chunk. Incomplete association prevents accurate matching of retrieval requests.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | The content length of a single record in urban gas ledgers is moderate. This range ensures a single chunk contains complete content for a single record or associated fields, preventing split of a single record across multiple chunks |
chunkSplitter | Paragraph + table recognition | Ledger documents primarily consist of tables and paragraph descriptions. This configuration retains table structure and paragraph logic, ensuring field association |
customPdfParse | Enabled | Preserves table formatting and field correspondence within PDF files |
UPLOAD_FILE_MAX_SIZE | 100–200 MB | Single monthly operation report PDFs have large file sizes. This range covers the size of most ledger documents |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Large ledger documents have many pages. 600 seconds ensures complete parsing |
chunkSettingMode | Manual configuration | Allows adjustment of chunking logic to match the structured characteristics of ledgers |
Three Common Misconfigurations
- After a single annual inspection ledger PDF is uploaded, search tests return no results. Cause:
customPdfParseis not enabled, causing table structures within the PDF to be flattened and field information lost. - After local deployment, data processing fails during knowledge base training. Cause: The
UPLOAD_FILE_MAX_SIZEconfiguration value is smaller than the size of the uploaded ledger PDF, so the file is truncated and not fully parsed. - Parsing timeout errors occur during training. Cause:
PARSE_FILE_TIMEOUT_SECONDSis set to the default 300 seconds, which cannot complete parsing of large ledger documents, leading to timeout interruptions.
How to Confirm Configurations Are Properly Set
- A single monthly inspection ledger PDF is uploaded, and the parsing log is checked for the presence of ledger fields such as point number and pressure value.
- A search test is run, and returned results are confirmed to include specific record content from the ledger, with no field misalignment or missing content.
- A large quarterly operation report PDF is uploaded, and the parsing process is confirmed to have no timeout errors.
- The
chunkSettingModeconfiguration is checked, and the manually configured chunking logic is confirmed to match the structured characteristics of the ledger.
The values listed above are common starting points and should be evaluated against local sample documents.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.