What This Category of Data Looks Like
Data related to industrial metal financial reports mainly comes from annual and semi-annual reports of corresponding enterprises, announcements from the Shanghai Futures Exchange and London Metal Exchange, and monthly statistical reports from the China Nonferrous Metals Industry Association. Update cycles follow fixed schedules: enterprise financial reports are released quarterly and annually, while industry statistical data is updated monthly. Document structures include modules such as structured data tables, industry trend analysis text, and associated enterprise operating data. Fields and units are tailored to specific metal categories. For example, the unit of "electrolytic aluminum output" for electrolytic aluminum is ten thousand tons, the unit of "spot average price" is yuan per ton, and the unit of "inventory level" is ten thousand tons. Some documents include converted import and export amounts, with units in ten thousand US dollars.
Constraints Imposed by These Characteristics on Knowledge Base Retrieval and Recall
The multi-source and multi-update rhythm characteristics of industrial metal financial reports require retrieval systems to distinguish between historical data and newly released documents, to avoid recalling expired data. The large number of structured tables and precise fields in documents require retrieval systems to support field-level matching, rather than relying solely on fuzzy text matching, to prevent recall results where indicators are disconnected from analysis. The strong correlation between fields and corresponding analysis text in documents requires retaining the binding relationship between fields and text during chunking, to avoid failing to accurately associate data and analysis content after chunking.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
Chunk Length | 800–1200 characters | Industrial metal financial reports include long-form analysis and compact structured tables. This range retains the binding relationship between fields and corresponding analysis, avoiding chunking that breaks field associations |
Recall Count | Top 8–12 entries | Industrial metal financial report data comes from multiple sources. A sufficient number of documents must be recalled to cover indicators and analysis across different dimensions, while avoiding redundant results |
Similarity Threshold | 0.72–0.80 | Structured numeric field matching for industrial metal financial reports has higher precision requirements than general text. This threshold filters low-relevance non-target documents while retaining valid matching results |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Large industrial metal financial report documents contain multiple tables and long text, with long parsing times. This duration avoids timeout interruptions |
ENABLE_STRUCTURED_PARSE | Enabled | Industrial metal financial reports contain large amounts of structured table data. Enabling structured parsing retains precise associations between fields and values, improving retrieval matching accuracy |
The parameter values provided on this page are general recommendations used as a starting point for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require specific analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Phenomenon: Knowledge base recall results do not include metal price charts or inventory data table images from the original document. Cause: Document multimedia element extraction configuration is not enabled, and the association between images and corresponding text chunks is not retained during chunking.
- Phenomenon: When calling the
/api/v1/chat/completionsinterface, the returned results do not mark the document sources corresponding to the response content. Cause: Document source tracking is not enabled in the knowledge base configuration, or the request parameter does not carry thewithReferenceparameter and set it to a valid value. - Phenomenon: Knowledge base retrieval results do not match the uploaded industrial metal financial report documents. Cause: Structured parsing configuration is not enabled, causing fields and values in the document to not be correctly identified, preventing precise keyword matching during retrieval.
How to Confirm Configuration Is Correct
- Upload a test industrial metal financial report document, check if the parsed structured data retains the field and value correspondence from the original document, to confirm the configuration is active.
- Initiate a query targeting the price or inventory of a specific metal category, verify that the returned results include source information from the original document, to confirm document source tracking configuration is correct.
- Call the
/api/v1/chat/completionsinterface, pass the test question and theappIdof the corresponding knowledge base, check if the returned results include matching financial report content, to confirm knowledge base association is working properly. - Upload an industrial metal financial report document containing images, initiate a query, and check if the recall results include references or displays of the original images, to confirm multimedia extraction configuration is active.
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.