Knowledge Base Retrieval and Recall for Energy Metals Marketing Content

Marketing-related data for energy metals primarily comes from public statistics from industry associations, quoted prices from global metal exchanges

What the data for this category looks like

Marketing-related data for energy metals primarily comes from public statistics from industry associations, quoted prices from global metal exchanges, publicly disclosed information from leading mining and smelting enterprises, and reports from third-party industry consulting institutions. It also includes marketing copy for institutional clients, product manuals, and industry educational materials. The data update rhythm is tiered: spot transaction prices are updated daily, weekly industry dynamic reports are released each week, monthly supply and demand balance sheets and capacity utilization data are updated each month, quarterly capacity planning adjustment announcements are updated each quarter, and annual industry development white papers are released each year.

Documents are divided into two categories: standardized reports and non-standardized analysis. Standardized reports include fields such as product name, delivery location, pricing unit, latest price, and month-on-month change. Non-standardized content includes policy interpretations, supply and demand trend judgments, and marketing copy. Field units mostly use bulk commodity pricing units such as ton, ten thousand tons, yuan/ton, and US dollar/ton.

The diversity of content and tiered update characteristics in marketing scenarios require the knowledge base to support unified retrieval and precise recall of multiple types of documents. The tiered update feature requires a strategy combining incremental synchronization and scheduled full updates, to avoid resource waste and delays caused by full retransmissions, and ensure the timeliness of marketing content. The precise fields and units of standardized reports require the retrieval link to support field-level matching. Pricing units and product specifications must be used as retrieval filter conditions, to avoid confusion between results with different pricing units or segmented categories, which would affect the accuracy of marketing communications. A non-negligible proportion of long-text analysis documents requires the retrieval system to support long-text segment recall. It is also necessary to set recall weights for data with different update frequencies. For example, spot price data has a higher weight than annual analysis reports, to ensure the timeliness of marketing content. The characteristics of multiple segmented categories require category filtering before recall, to reduce the number of invalid recall results and improve the efficiency of marketing communications.

How to set the configurations

Configuration ItemRecommended ValueRationale
UPLOAD_FILE_MAX_SIZE1024 MBAdapts to the common file size of single marketing reports and industry reports in the energy metals industry, and avoids out-of-bounds upload errors
PARSE_FILE_TIMEOUT_SECONDS600 secondsCovers the parsing time requirements for long-cycle industry reports and multi-category summary reports
PARSE_CHUNK_SIZE1500–2000 charactersMatches the business unit length of energy metals documents, and retains the complete logic of standardized reports and marketing paragraphs
Similarity Threshold0.75–0.85Adapts to the precise matching requirements of marketing scenarios, filters cross-category and low-relevance recall results, and balances precision and recall coverage
Number of Recalled EntriesTop 8–12 entriesAdapts to the marketing information requirements of multiple segmented categories in the energy metals industry, and avoids response delays caused by excessive recall
RECALL_RERANK_TOP_NTop 3–5 entriesRemoves duplicate or highly similar recall results, and optimizes the information purity of marketing output

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, and it is recommended to test on your own samples before finalizing the configuration.

Three Common Mistakes

  • Symptom: In the FastGPT Community Edition v4.9.1-fix2 version, an offset is out of bounds error occurs when uploading a 190MB energy metals industry report. Cause: The UPLOAD_FILE_MAX_SIZE configuration was not adjusted, and the default value is too small, causing large file uploads to be interrupted.
  • Symptom: After associating the knowledge base, the response speed drops significantly, and output delay increases noticeably. Cause: The number of recalled entries is set too high, and reranking filtering is not enabled, causing a large number of irrelevant documents to participate in subsequent processing workflows.
  • Symptom: The accuracy of knowledge base recall results in marketing scenarios is low, and confusion occurs between results with different pricing units or segmented categories. Cause: The Similarity Threshold is not set or is set too low, and field-level matching filtering is not enabled, causing documents from non-target categories to be recalled.

How to Confirm the Configuration Is Correct

  • Upload a typical energy metals industry marketing report, check the upload progress and background error logs, and confirm that the UPLOAD_FILE_MAX_SIZE configuration adapts to the file size.
  • Initiate a keyword search for marketing scenarios, check the number of returned results and response duration, and confirm that the number of recalled entries and reranking configuration meet business requirements.
  • Compare search results for different pricing units and segmented categories, and confirm that the Similarity Threshold and field matching rules filter out irrelevant content.
  • Manually trigger an incremental synchronization, check whether updated data appears normally in recall results, and confirm that the tiered update 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.