Dialogue Logging and Audit for Optical Module Investment Research Knowledge Base Construction

Optical module investment research data comes from three main sources: official specification documents of communication equipment manufacturers, test

What the data for this category looks like

Optical module investment research data comes from three main sources: official specification documents of communication equipment manufacturers, test specifications released by industry associations, and parameter documents published in carrier centralized procurement announcements. Updates occur irregularly, following manufacturer new product launches and industry standard iterations. A single update package may contain multiple structured parameter tables. Each single document includes fields such as model identifier, transmission rate, operating wavelength, power consumption, interface type, compliance certification, and application scenarios. Some documents include additional test data tables. Units follow standard communications industry units: Gbps for transmission rate, km for transmission distance, W for power consumption.

What constraints do these characteristics impose on the dialogue logging and audit workflow

Optical module documents are mostly structured long tables with lengthy single-document content. Dialogue logs must fully record the parameter dimensions of user queries and matched document fragments to avoid missing key information during audits. Updates occur irregularly and document batch imports are frequent. The audit process must trace the import time and version information of documents to ensure sessions call the latest version of documents. There are many parameter fields with subtle differences in units. Logs must record the original document fields and unit conversion processes to facilitate verification of data accuracy during audits. Investment research scenarios have strict requirements for session traceability, requiring complete records of each conversation’s call chain, matching results, and modification records.

How to set configurations

Configuration ItemRecommended ValueRationale
maxContext8000–12000 charactersOptical module specification documents are mostly structured long texts, adapted for long document parsing and model context limits
PARSE_FILE_TIMEOUT_SECONDS300 secondsOptical module documents include multi-page parameter tables, with higher parsing time than general documents
UPLOAD_FILE_MAX_SIZE2000 MBSupports batch import of full-series optical module specification document packages released by manufacturers
Recall countTop 8 entriesOptical modules have many parameter dimensions, requiring sufficient recalled relevant document fragments to cover query needs
Similarity threshold0.75Optical module parameters have high precision requirements, filtering irrelevant documents with low matching degrees
LOG_EXPORT_RETENTION_DAYS180 daysMeets audit retention requirements for financial investment research scenarios

Three common configuration mistakes

  • Symptom: After importing optical module documents, indexing takes an excessively long time, and logs indicate that the context length exceeds the limit. Cause: The maxContext parameter is not adjusted to adapt to the parsing requirements of long optical module documents.
  • Symptom: The conversation details page does not display complete internal application call records. Cause: The ENABLE_DETAILED_LOG configuration item is not enabled, and only basic session information is recorded.
  • Symptom: No conversation history records appear in the MongoDB database. Cause: The storage path corresponding to MONGO_LOG_COLLECTION is not configured, or the session log writing switch is not enabled.

How to confirm configurations are properly set

  • Upload a single 10-page optical module specification document, wait for parsing to complete, check the indexing status, and confirm no timeout errors occur.
  • Initiate a conversation containing an optical module parameter query, enter the session details page, and confirm that the complete model call context, matched document fragments, and return results are visible.
  • Log in to the MongoDB database, check whether complete records of this session exist in the corresponding log collection, including query keywords, matched document IDs, and audit fields.
  • Trigger a batch document import operation, check whether the system logs record the import time, number of documents, and parsing results.

The parameter values provided on this page are common starting points for configuration. Actual values are affected by material format, data volume and business rules. Specific issues require on-site analysis, and testing against local samples is recommended before finalizing.

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.