Knowledge Base Retrieval and Recall for Optical Module

What data for this category looks like

Optical module investment research data originates from communication industry standard documents, official manufacturer specifications, third-party test reports, quarterly supply chain quotation data, and brokerage industry research reports. The update rhythm shifts irregularly alongside manufacturer new product launches, industry standard iterations, and supply chain price fluctuations. Single documents mostly combine structured parameter tables and paragraph descriptions. Core fields include wavelength, transmission rate, operating power consumption, mass production capacity, and delivery cycle. Their units are nanometers, Gbps, watts, units, and days respectively.

Constraints on knowledge base retrieval and recall

Optical module data has a high proportion of structured parameters and multiple unit types. Retrieval must support field-level precise matching and unit normalization processing to avoid recall failure caused by inconsistent units. Data update frequency fluctuates with industry dynamics. Deploy an incremental update mechanism to ensure knowledge base content timeliness. Single documents contain both short parameter entries and long-text analysis content. Balance short-snippet precise recall and long-text context association to avoid losing key parameter information due to unbalanced segmentation strategies.

How to set configurations

Configuration Item	Recommended Value	Rationale
`segment length`	`800–1200 characters`	Optical module documents contain both short parameter entries and long-text analysis. This range balances fragment integrity and context association
`recall count`	`top 8–12 results`	Investment research needs to cover multi-dimensional parameters. Too many will introduce redundancy, too few will fail to cover all relevant information
`similarity threshold`	`0.72–0.85`	Structured parameters have high requirements for semantic matching accuracy, and low-match irrelevant documents need to be filtered
`re-ranked return count`	`top 4–6 results`	Investment research decisions need to focus on core parameters and analysis conclusions, reducing user screening costs
`incremental update interval`	`every 12 hours`	Supply chain and new product information updates for optical modules have no fixed cycle. This interval balances timeliness and system load
`text understanding model`	`calibrated based on actual testing`	Optical module data mainly consists of structured parameters. A model that supports field-level semantic understanding needs to be selected, adapting to the parameter matching capability of the deepseekR1 series models

The parameter values provided on this page are all conventional recommendations used as starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require specific analysis, and it is recommended to test on your own samples before finalizing the settings.

Three common errors

Phenomenon: No retrieval results appear after enabling the enable re-ranking model function on the application side, but results are normal in the knowledge base test link. Cause: The re-ranking model's interface configuration was not synchronized to the application deployment environment, or the application side did not correctly load the re-ranking model's associated parameters.
Phenomenon: After upgrading to version 4.8.16, clicking the knowledge base page returns a 404 status code. Cause: The knowledge base's routing configuration file was not correctly overwritten during the upgrade process, resulting in invalid path mapping.
Phenomenon: The knowledge base retrieval result is empty, and no relevant logs display in the console. Cause: The DEBUG log level is not enabled, so key logs during the retrieval process fail to output normally.

How to confirm correct configuration

Upload a standard optical module specification document, trigger knowledge base parsing, and check whether parsed fields include core parameters such as wavelength and transmission rate, and whether field units are unified.
Initiate a retrieval test, enter keywords containing specific parameters, and check whether the number of recall results matches the configured recall count.
Enable the re-ranking model and initiate retrieval again, and check whether the sorting logic of returned results conforms to core parameter matching degree.
View system logs to confirm whether the incremental update task runs regularly according to the configured incremental update interval.

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.