What this category of data looks like
Data for iron ore financial report analysis comes primarily from listed company public financial report announcements, commodity industry association reports, and exchange spot price databases. Update cycles fall into two categories: fixed schedule and real-time. Quarterly financial report announcements are released within 10 business days after the end of the reporting quarter. Spot price data updates daily. Industry supply and demand reports update on a monthly or quarterly basis. Document structure includes structured and unstructured data. Structured data is stored in CSV or JSON format, with fields including reporting period, port inventory, average grade, and FOB price. Unstructured text takes the form of full PDF financial reports, containing content such as revenue breakdowns, cost analysis, and price fluctuation explanations. Field units cover multiple types including RMB, USD, dry ton, and ten thousand tons.
Constraints on HTTP Interfaces and External Systems
The multi-type, multi-update-cycle, and multi-unit characteristics of iron ore financial report data create multiple constraints for HTTP interface and external system integration. Fixed-schedule quarterly financial report announcements require interfaces to support scheduled batch pull tasks. High-frequency updated spot price data requires interfaces to support multiple real-time requests per minute. Multiple format data sources (full PDF financial reports, structured CSV/JSON datasets) require interfaces to support parsing and parameterized pulling of multiple file types, reducing adaptation costs for external systems. Multi-unit fields require interfaces to provide unit specification parameters to ensure error-free cross-system data conversion. Long PDF financial reports require interfaces to support segmented pulling and context truncation configuration, preventing single request timeouts or overloaded return content.
Configuration Settings
| Configuration Item | Recommended Value | Basis for This Setting |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | A single iron ore financial report PDF typically contains dozens of pages of industry data and price tables. Full parsing requires significant time, and 600 seconds covers conventional parsing requirements |
UPLOAD_FILE_MAX_SIZE | 500 MB | Iron ore industry supporting reports often include massive historical spot price datasets. Single file sizes are typically large, and 500 MB meets conventional upload requirements |
Recall count | Top 10 entries | Core associated information for iron ore financial report analysis is typically concentrated in the top 10 announcements and price data. Excessive recall increases context redundancy |
Similarity threshold | 0.75–0.85 | The correlation between iron ore price fluctuations and financial report revenue is high. This range filters low-correlation irrelevant data and retains valid associated information |
maxContext | 10000–12000 characters | The core analysis paragraphs of a single long financial report typically do not exceed 12000 characters. This range ensures that key information is fully included in the context |
api_request_rate_limit | 10 requests per minute | Iron ore spot price data updates daily. High-frequency pulling requires limiting request frequency to avoid triggering rate limiting rules from external data sources |
The parameter values provided on this page are common recommended starting points. 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 local samples before finalizing settings.
Three Common Misconfigurations
- Calling the chat interface to upload iron ore financial report attachments returns a
413 Request Entity Too Largeerror. The cause is failure to adjust theUPLOAD_FILE_MAX_SIZEconfiguration item. The default limit is smaller than the actual size of industry reports. - Calling the knowledge base API fails to correctly handle coreference resolution. For example, when asking "What is the year-over-year change of this data", the context's financial report period cannot be associated. The cause is failure to enable historical context splicing configuration, or the
maxContextparameter is set too small to accommodate the full context. - After configuring external API integration, model parameters still need to be repeatedly configured in the interface, resulting in a
model not founderror. The cause is that the FastGPT model configuration does not fully match the model name configured in the external system, causing the interface to fail to recognize the available model.
How to Verify Successful Configuration
- Upload a standard iron ore financial report PDF file, check whether the parsing result includes core fields such as reporting period, grade, and FOB price, and confirm that the parsing process does not trigger a timeout.
- Call the chat interface to upload an iron ore industry report with a volume conforming to industry conventions, check whether the interface return status is normal, and confirm that the upload limit configuration meets the file volume requirements.
- First upload iron ore financial report data via the API, then initiate a query containing coreference, check whether the interface can correctly associate context information, and confirm that the context configuration takes effect.
- Initiate consecutive request tests, check whether external system rate limiting rules are triggered, and confirm that the request frequency configuration is reasonable.
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.