What the data for this category looks like
Cement investment research data is mainly sourced from monthly operation briefs released by the China Building Materials Federation, annual reports publicly released by cement production enterprises, daily quotation data from commodity spot trading platforms, and infrastructure policy documents issued by the Ministry of Housing and Urban-Rural Development and local governments. Update cycles cover daily (spot prices), monthly (industry operation data), annual (enterprise annual reports), and irregular (policy documents). Documents include structured tables of production capacity, inventory and prices, unstructured text for industry supply-demand analysis and policy interpretations, and some documents contain technical fields such as energy consumption indicators and kiln operating parameters. Units include ten thousand tons, yuan/ton, kWh/ton, and others.
What constraints do these characteristics impose on the document parsing and chunking process?
The multi-source, multi-update-cycle and complex structure of cement investment research data imposes clear constraints on the document parsing and chunking process. A high proportion of structured tables requires accurate identification of cell associations to avoid cross-row and cross-column data misalignment. Data with different update frequencies coexist in the same document. Timestamp associations must be retained during chunking to avoid mixing old and new data during retrieval. Technical and financial fields are mixed. Field context associations must be retained to avoid losing the correspondence between ton cost and production capacity after chunking. A high proportion of long documents requires precise segmentation to preserve complete supply-demand analysis logic.
How to Configure
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
PARSE_TABLE_ENABLE | Enabled | Cement investment research data contains a large number of structured production capacity, price and inventory tables. Enabling this option preserves cell-to-cell associations and avoids data misalignment |
PARSE_MAX_CHUNK_SIZE | 800–1200 characters | Cement industry documents include both long supply-demand analysis passages and dense monthly data tables. This range balances context completeness and retrieval accuracy |
PARSE_FILE_TIMEOUT_SECONDS | 300–600 seconds | A single annual industry report or enterprise annual report may contain dozens of pages. An overly short timeout will cause large document parsing to fail |
UPLOAD_FILE_MAX_SIZE | 500 MB | Meets the upload requirements for single large industry reports and enterprise annual reports, preventing file interception |
PARSE_USE_MARKER | Enabled for v4.9.0 and above | Cement industry PDF documents often have nested tables and multi-column layouts. Marker parsing can restore document structure more accurately |
PARSE_PARALLEL_WORKERS | 2–4 | Balances parsing speed and server resource usage, avoiding parsing failures caused by too many parallel workers |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material format, data volume and business rules. Specific issues require targeted analysis, and it is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Scenario: Calling the FastGPT file parsing interface returns a
403 Forbiddenstatus code, or the interface prompts that the parsing function is unauthorized. Cause: Commercial edition permissions have not been activated. Enhanced parsing functions in v4.9.0 and above are only available for commercial editions. - Scenario: Using the v4.9.0 enhanced parsing function to parse cement PDF documents results in lost table structures and messy text layout. Switching to v4.8.20 with Marker parsing restores normal functionality. Cause: Some versions of v4.9.0 have nested table parsing compatibility issues, and do not adapt to multi-column PDF layout formats common in the cement industry.
- Scenario: The file parsing tool does not trigger during a chat, and uploaded cement documents are not correctly indexed. Cause:
PARSE_TABLE_ENABLEis not enabled in system configuration, so structured table data in documents is not extracted, and valid retrieval chunks cannot be generated.
How to Verify Successful Configuration
- Upload a cement industry monthly brief containing structured tables, review parsed text content to confirm no table cell misalignment or data loss.
- Upload a large annual industry report, check the parsing task duration to confirm it does not exceed the set
PARSE_FILE_TIMEOUT_SECONDSvalue. - Call the file parsing tool in the chat interface, upload a cement enterprise annual report, confirm the tool triggers successfully and generated retrieval blocks include core business fields.
- Check system operation logs to confirm parsing tasks return no abnormal status codes, verifying permissions and timeout configurations are effective.
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.