What the data for this category looks like
Sources of optical module research reports mainly include communication industry broker research reports, public industry association materials, and technical white papers from optical module manufacturers. Update cycles are adjusted alongside industry new product launches, standard iterations, and quarterly supply chain trends, with no fixed schedule.
Document structures include core parameter sections, technical test data, application scenario analysis, vendor pricing, and supply chain information. Fields cover professional details such as optical module model, transmission rate (unit: Gbps), operating wavelength (unit: nm), power consumption (unit: W), and packaging form. Some documents also include competitor comparison content.
What constraints do these characteristics impose on the model access and configuration workflow
Optical module research reports contain a large number of professional technical parameters and units. This requires models to accurately identify and associate corresponding semantics. Therefore, embedding models must adapt to communication domain-specific terminology to avoid parameter matching errors.
The non-fixed update cycle of research report content requires the vector database to support incremental updates, rather than fixed-cycle full refreshes, to accommodate sudden new product research report data.
Documents also include both long technical analysis sections and short parameter entries. This requires balancing context recall and precise field matching. Therefore, recall and reranking configurations must balance coverage and precision.
The presence of multi-dimensional fields requires retaining original field information during indexing, to avoid parameter confusion caused by normalization processing.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
embedding_model | bge-large-zh-v1.5 | Strong semantic understanding ability for professional technical texts, can accurately match professional terms such as optical module rate and wavelength |
chunk_size | 800–1200 characters | Optical module research reports contain both long technical analysis sections and short parameter entries. This length balances context integrity and recall precision |
recall_top_k | Top 10–15 results | Research report content involves multi-dimensional parameters. A sufficient number of relevant segments must be recalled before reranking and filtering |
similarity_threshold | 0.72–0.78 | Queries for optical module parameters have high requirements for semantic matching accuracy. This range effectively filters low-relevance recall results |
rerank_top_n | Top 3–5 results | Final returned results must focus on core parameters and conclusions, to avoid redundant content interfering with user queries |
api_timeout | 600 seconds | Optical module research reports may contain a large amount of long text content. The parsing and embedding process takes a long time, so this duration must be supported |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require specific analysis. It is recommended to test on your own samples before finalizing values.
Three common configuration mistakes
- Phenomenon: Insufficient matching accuracy of optical module parameters in retrieval results. Cause: A general embedding model was selected, without adaptation to communication domain-specific terminology. The model cannot accurately associate core fields such as optical module rate and wavelength.
- Phenomenon:
504 Gateway Timeouterror is returned when calling the large model. Cause: Theapi_timeoutconfiguration was not adjusted. The long text parsing and embedding time of optical module research reports exceeds the default timeout threshold. - Phenomenon: Detailed logs for large model calls via OneAPI cannot be viewed. Cause: The debug log switch for FastGPT was not enabled, or the log storage path was not configured.
How to confirm the configuration is complete
- Upload a public optical module research report document, and check whether the parsed segments retain the parameter fields and unit information from the original document.
- Initiate a query including "100G optical module power consumption", and verify whether the returned results include accurate parameter matching content and relevant research report segments.
- Enter the model management interface, and confirm that the API configuration of the target model has been saved and the status is normal.
- Call the official provided knowledge base question and answer interface, and verify that the custom interface can normally initiate requests and obtain matching results.
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.