What the data for this category looks like
Heating industry investment research data sources include public heating industry operation reports, internal ledgers of heating enterprises, municipal pipe network monitoring data, and pricing announcement documents from relevant national pricing authorities. Update cycles include quarterly financial report releases, monthly operation report updates, daily pipe network monitoring data synchronization, and some policy documents released irregularly. Documents include structured energy consumption and cost tables, pipe network operation time-series records, and policy interpretation texts. Fields include total heating area, unit heating cost, and heating cycle duration, with units of ten thousand square meters, yuan/gigajoule, and days respectively.
Constraints Imposed by These Characteristics on Document Parsing and Chunking
Thermal investment research documents contain large volumes of structured tables and time-series data. Direct use of generic chunking will break field correspondence. This prevents subsequent retrieval from matching the association between cost and heating area. Daily monitoring data has strong time-series requirements. Chunking must retain timestamp context, otherwise specific time period pipe network abnormality records cannot be located. Policy texts with dense professional terms require controlled chunk lengths to avoid term splitting. This also balances context integrity for retrieval. When documents with different update frequencies are mixed, distinct chunking rules must be applied to long-cycle financial reports and short-cycle monitoring data. This avoids semantic breaks across different data types.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
PARSE_TABLE_STRUCTURE | Enabled | Thermal documents contain a large number of structured tables. Retaining structure avoids field confusion and information loss |
CHUNK_SIZE | 800–1000 characters | Balances retrieval granularity for long-text analysis and table fragments in thermal documents, avoiding term splitting |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Adapts to the upload requirements of large-volume PDF and CSV collections from annual operation ledgers of heating enterprises |
PARSE_FILE_TIMEOUT_SECONDS | 900 seconds | Meets the full parsing duration requirements for large-volume thermal ledgers |
CUSTOM_PARSE_HOOK | Bound to thermal industry term dictionary | Prevents professional terms such as "heating coal consumption" and "pipe network hydraulic condition" from being split |
AUTO_CHUNK_OVERLAP | 100–150 characters | Retains context association for time-series data, avoiding time period information breaks after chunking |
The parameter values provided on this page are common starting points for configuration setup. 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 values.
Three Common Configuration Mistakes
- Symptom: When uploading a heating operation ledger PDF that exceeds the default threshold, an "offset out of range" error appears at 90% parsing progress. Cause: The
UPLOAD_FILE_MAX_SIZEparameter was not adjusted to a value suitable for large-volume files. The system default threshold cannot load complete heating ledger data. - Symptom: Thermal documents uploaded via the
create_file_collectionAPI have inconsistent chunking results with the same documents uploaded directly through the platform. Cause: The API call did not specify theCHUNK_SIZEandAUTO_CHUNK_OVERLAPparameters, using the system default configuration. Platform uploads use industry-adapted configurations by default. - Symptom: After configuring
CUSTOM_PARSE_HOOKto bind the heating industry term dictionary, policy documents imported via a custom URL have no parsing results. Cause: ThePARSE_TABLE_STRUCTUREswitch was not enabled in the custom URL configuration. This prevents professional terms and table structures from being correctly identified.
How to Verify Correct Configuration
- Upload a typical heating operation PDF, check that the parsed tables have complete row and column structures, with no garbled characters or field misalignment.
- Compare the chunk count of the same document uploaded via API and through the platform, confirming that parameter configurations are consistent.
- View system parsing logs, confirming that trigger records exist for
PARSE_TABLE_STRUCTUREandCUSTOM_PARSE_HOOK. - Test heating policy documents imported via a custom URL, confirming that professional terms are fully retained with no splitting or breaks.
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.