What the data for this category looks like
Data for minor metals financial report analysis primarily comes from listed companies’ annual/quarterly reports, public announcements from domestic compliant commodity trading platforms, and publicly available statistical documents from industry associations. Data updates follow fixed quarterly and annual cycles, with temporary announcements released alongside market fluctuations. Single financial report documents are mostly structured, containing fields such as primary mineral output, terminal consumption volume, spot average price, and import/export volume. Most units use tons, yuan per ton, and ten thousand USD. Some segmented categories use minor units such as grams and kilograms.
What constraints do these characteristics impose on deployment and upgrade?
The multi-field and multi-unit characteristics of minor metals financial reports require configuring adaptive field extraction rules during deployment to avoid unit parsing errors. Fixed quarterly and annual update cycles require configuring scheduling parameters for timed synchronization tasks to ensure the knowledge base refreshes data on schedule. Multi-format financial report documents (PDF, Excel) need compatible dedicated parsing engines to prevent loss of critical data during parsing. During upgrades, synchronously update knowledge base mappings for industry-specific fields to support new segmented category statistical indicators, and adjust recall thresholds to meet precise matching requirements for multi-field data.
How to Set Configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 1000 MB | Minor metals financial report single PDF/Excel files usually do not exceed 800 MB, reserve reasonable buffer space |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Long-document financial report parsing requires longer processing time to avoid mid-parsing timeout interruptions |
rerank_top_n | top 8 entries | Minor metals financial reports have a large number of fields. Use the reranking model to filter highly relevant content; 8 entries cover core indicators |
SYNC_CRON_EXPR | 0 0 2 1 1,4,7,10 * | Adapts to the quarterly update cycle of minor metals financial reports, executes synchronization tasks at 2:00 AM on the first day of each quarterly month |
MAX_CONTEXT | 8000–12000 characters | Minor metals financial reports include multiple sets of core indicators, require sufficient context length to fully extract key data |
FE_DOMAIN | Public IP or bound domain of the locally deployed server | Used to configure the callback address after file upload, ensuring the locally deployed environment can normally read uploaded files |
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 Mistakes
- Phenomenon: When starting the WSL2 container, an error like
mkdir /run/desktop/mnt/host/wsl/dockerappears, and the service cannot start normally. Cause: WSL2 shared disk permissions are not configured correctly, so FastGPT cannot read locally uploaded minor metals financial report files. - Phenomenon: After executing
docker-compose up -d, an ERRO-level log is returned, and the service fails to start. Cause: TheUPLOAD_FILE_MAX_SIZEparameter is not set correctly, or the local deployment directory has insufficient remaining storage space to load large-volume financial report parsing dependency packages. - Phenomenon: Core indicators (such as unit price per ton, import/export volume) fields are empty after financial report parsing, and the number of recall results is abnormal. Cause: Field extraction rules adapted to multiple units are not configured, so the parsing engine cannot recognize measurement units exclusive to minor metals.
How to Confirm Configuration Is Correct
- Upload a PDF or Excel file of a minor metals financial report, check if the parsed fields include exclusive indicators such as primary mineral output and spot average price, and verify that unit parsing is correct.
- Execute the
docker pscommand, confirm that all FastGPT-related containers are in normal running status, with no abnormally exited logs. - View the execution logs of the timed synchronization task, confirm that the refresh is triggered normally according to the configured scheduling cycle.
- Call the financial report analysis interface, check if the relevance of the returned results meets expectations, and verify that the reranking model configuration takes effect.
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.