Vector Models and Indexing for Energy Metals Intelligent Due Diligence Reports

Data related to energy metals comes primarily from public market data of global commodity exchanges, monthly survey data from industry associations

What the Data for This Category Looks Like

Data related to energy metals comes primarily from public market data of global commodity exchanges, monthly survey data from industry associations, public disclosure documents from mining and smelting enterprises, and customs import and export statistics. Update frequencies cover three categories: daily (spot prices), monthly (industry supply and demand reports), and quarterly (corporate financial reports). Document formats include PDF deep research reports, structured Excel inventory tables, and web-based industrial policy documents. Fields include variety spot quotes (unit: USD/ton), production capacity (unit: 10,000 tons), transportation costs (unit: yuan/ton-kilometer), among others. Single due diligence report files often exceed 10 MB.

Constraints Imposed by These Characteristics on Vector Models and Indexing

Multi-source heterogeneous data formats (market tables, research report text, policy announcements) require vector models to adapt to inputs of different structures. Structured numerical fields need additional standardized extraction. Single due diligence reports often exceed 10 MB, leading to a large number of chunks after splitting. Reasonable chunk granularity must be controlled to avoid semantic fragmentation. Daily updated spot price and inventory data require indexes to support incremental updates, avoiding excessive time consumption from full index reconstruction. Quantitative attributes of different categories (such as production capacity, quotes) require hybrid vector indexes combined with numerical features. Relying only on text vectors will lose key quantitative information. Cross-category comparison content requires indexes to support multi-field joint recall, improving retrieval accuracy.

Configuration ItemRecommended ValueRationale
UPLOAD_FILE_MAX_SIZE15360 MBAdapts to the volume requirement that single energy metals due diligence reports often exceed 10 MB, preventing upload interception
CHUNK_SIZE800–1200 charactersBalances semantic integrity after splitting long documents and retrieval recall efficiency, avoiding overly fragmented or overly long chunks
VECTOR_MODELtext-embedding-3-largeAdapts to hybrid vector generation requirements for multi-source heterogeneous text and quantitative attributes, improving retrieval accuracy for cross-category content
INDEX_INCREMENTAL_UPDATEEnabledAdapts to daily updated market data, avoiding excessive resource consumption from full index reconstruction
RECALL_TOP_KTop 10 resultsCovers the result requirements of multi-dimensional retrieval in energy metals due diligence, avoiding missing key information due to too few recalls
PARSE_FILE_TIMEOUT_SECONDS1200 secondsAdapts to parsing time requirements for large-volume due diligence reports, avoiding parsing timeout interruptions

The parameter values provided on this page are common starting points for configuration. Actual values are affected by material formats, data volume and business rules. Specific issues require specific analysis, and it is recommended to test on your own samples before finalizing.

Three Common Mistakes

  • Phenomenon: Vectorization fails for some chunks after splitting a single due diligence report over 10 MB. The interface displays an embedding failed error, and normal operation resumes after repeatedly clicking retry. Cause: The number of chunks for large files exceeds the concurrent processing limit of the vector service, and some requests are temporarily discarded.
  • Phenomenon: Batch upload of multiple energy metals due diligence reports causes a server crash. After restart, the knowledge base status shows Not Ready, and index construction cannot be completed automatically. Cause: No breakpoint resume logic is configured for batch upload tasks, and unfinished index tasks are not resumed after service restart.
  • Phenomenon: After upgrading to version 4.9-4.10, the original energy metals knowledge base cannot return vector retrieval results, and search results are empty. Cause: The vector index format changes after the version update, and the original index is not automatically migrated. Index reconstruction is required.

How to Verify Correct Configuration

  • Upload an energy metals due diligence report larger than 10 MB, check if the number of chunks matches the preset CHUNK_SIZE configuration, and confirm there are no abnormal chunk errors.
  • Trigger an incremental index task, check that only new data is updated, and no full reconstruction is performed, which meets the configuration requirements of INDEX_INCREMENTAL_UPDATE.
  • Initiate a retrieval request containing quantitative attributes (such as production capacity, quotes), confirm that the returned results match the dual logic of vector recall and field matching.
  • View system operation logs, confirm there are no embedding failed or index timeout error messages.

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.