Vector Models and Indexing for Optical Module Financing Daily Reports

Optical module financing daily report data comes from primary market financing information platforms, public bidding and cooperation announcements

What this category’s data looks like

Optical module financing daily report data comes from primary market financing information platforms, public bidding and cooperation announcements released by industry associations, regular financial reports of listed companies, and self-disclosed financing updates from enterprises. Update frequency is daily. Each daily report document contains one or more financing records. Standard fields for each record include full name of the financing subject, core model parameters of optical modules, financing amount, list of participating investors, financing round, and information release date. Financing amounts are marked in ten thousand yuan or hundred million yuan units. Optical module models use transmission rate parameters such as 100G, 800G as core identifiers.

What constraints do these characteristics impose on vector models and indexing

Daily updates require indexes to support incremental synchronization. This avoids computing resource consumption from full index rebuilding. Structured fields such as optical module models and financing amounts must be processed separately from unstructured text such as investor descriptions. This adapts to hybrid indexing rules. Each financing record is relatively short. When importing daily reports in batches, the shard size of single-batch indexing must be controlled. This prevents index queue blocking. Standardized parameter formats for optical module models can be used for targeted recall. Field standardization mapping must be completed in advance. This avoids vector matching deviations caused by differences in parameter expressions, such as "100G optical module" and "100Gb/s optical module".

How to set configurations

Configuration ItemRecommended ValueRationale
PARSE_CHUNK_SIZE800–1200 charactersAdapts to the semantic integrity of single financing records and associated context, avoids vector representation deviation caused by overly fragmented chunks, and complies with input length limits of mainstream vector models
EMBEDDING_MODELbge-large-zh-v1.5The optical module industry contains a large number of professional technical terms and investment and financing expressions. This model has more stable vector matching accuracy for text in the technology field
INDEX_INCREMENTALEnabledAdapts to the daily update characteristics of financing daily reports, avoids computing resource waste caused by full index rebuilding
RECALL_COUNTTop 8–12 resultsBalances the comprehensiveness of retrieval recall and result relevance, adapts to the multi-dimensional retrieval needs of financing information
PARSE_MAX_BATCH_SIZE50 records/batchControls the number of financing records imported in a single batch, prevents index blocking caused by excessive server memory usage by batch tasks
SIMILARITY_THRESHOLD0.72–0.78Filters low-similarity irrelevant financing information, retains results with high matching degree to retrieval intent

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 specific analysis. Testing on local samples is recommended before finalizing values.

Three common errors

  • Phenomenon: A 400 Bad Request error occurs when importing optical module financing daily report CSV files after upgrading the platform version. Cause: The default value range of PARSE_CHUNK_SIZE is adjusted in the new version. The chunk length of the old configuration exceeds the input limit of the new vector model, causing the parsing process to interrupt.
  • Phenomenon: The knowledge base indexing task continuously displays the "in progress" status, and no complete index result is generated. Cause: The daily report data volume imported in batches exceeds the configuration threshold of PARSE_MAX_BATCH_SIZE, and incremental indexing mode is not enabled. This triggers a resource exhaustion problem for full indexing.
  • Phenomenon: When retrieving optical module financing information, a large number of non-optical module field financing records are mixed in the recall results. Cause: No structured indexing rules are configured for the optical module model field. Only global vector matching is relied on, so irrelevant results cannot be filtered accurately through professional terms.

How to confirm configuration is complete

  • View the knowledge base parsing log. Confirm that the chunk length of each financing record matches the preset PARSE_CHUNK_SIZE value, and there are no abnormal chunk prompts.
  • Call the vector model test interface. Input combined text of optical module model and financing amount. Verify that the output result of vector representation meets expectations.
  • Submit a batch import test task. Query the task progress through the INDEX_STATUS interface. Confirm that the completion time of single-batch indexing does not exceed the preset threshold.
  • Retrieve keywords containing specific optical module models. Check whether the recall results include financing records of this model, and the proportion of irrelevant results meets business needs.

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.