What the data for this category looks like
Marketing content data for optoelectronics used in finance, insurance, or wealth management comes from multiple sources: internal enterprise device specification documents, device procurement requirement documents from financial institutions, industry technical standard files, and public whitepapers on financial scenario application cases. Data update rhythm adjusts based on product iterations or financial scenario needs. Updates trigger when new products launch or core parameters change, with no fixed cycle. Document structures typically include fields such as product model identifiers, optical performance parameters, electrical performance parameters, financial scenario adaptation notes, and compliance certification information. Each field uses clear professional units. For example, resolution uses pixels, frame rate uses fps, and power consumption uses watts.
What constraints these characteristics impose on deployment and upgrade
Multi-source data with no fixed update cycle requires custom data source access and incremental sync configuration during deployment. This avoids full syncs consuming excessive resources, and adapts to rapid update requirements in financial scenarios. Fields with professional units and complex document structures require custom field mapping rules during deployment. This ensures core parameters are accurately identified and extracted, meeting the strict device parameter requirements of financial customers. Large average document sizes require adjustments to file parsing timeout and size limits during upgrades. This prevents parsing failures from disrupting delivery of financial marketing content. Significant differences in parameter requirements across financial scenarios require support for knowledge base multi-version management during upgrades. This ensures marketing content from different branches calls the corresponding version of product data.
How to Set Configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Optoelectronic product documents often contain long sections of professional parameters, so parsing takes longer than general documents |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Single files such as device test reports and technical whitepapers from some financial institutions can exceed 1 GB, so upload limits need to be relaxed |
maxContext | 8000–12000 characters | Marketing content needs to integrate multiple sets of product parameters and financial scenario adaptation notes, so the context length must cover complete technical paragraphs |
Recall count | top 8 entries | Core parameters of optoelectronic marketing content are concentrated, excessive recall will introduce unnecessary information |
Similarity threshold | 0.75–0.85 | Professional parameter matching requires strict standards to avoid incorrect associations with low matching degrees |
Rerank result count | top 5 entries | Core marketing content needs to prioritize the most relevant product parameters, so only the most accurate results after reranking should be retained |
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 individual analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Mistakes
- Phenomenon: After starting a Docker container, the image shows an Up status, but port 3000 cannot be accessed. The log prompts
mongo connection failed. Manual verification of the MongoDB account password fails. Cause: TheMONGO_INITDB_ROOT_USERNAMEandMONGO_INITDB_ROOT_PASSWORDparameters are not configured correctly, or the deployment package does not match the image version, resulting in database connection authentication failure. - Phenomenon: Accessing the
grok-3model in version4.8.20, an error is prompted when clicking test after configuration is complete, but the model runs normally when actually used to generate content. Cause: The test request does not carry complete authentication context, while the reference request automatically inherits the knowledge base configuration information, resulting in an exception in the test link. - Phenomenon: Dependent packages cannot be loaded during offline deployment, and service startup fails. Cause: The official Docker offline package was not used, and online images were pulled directly, resulting in missing dependencies in the intranet environment.
How to Confirm Proper Configuration
- Upload a copy of the optoelectronic product specification document, check whether the parsing result contains preset professional fields, and verify whether the field units comply with industry specifications.
- Trigger a manual sync task, check whether newly added product documents are automatically synced to the knowledge base, and whether the update time matches the actual document release time.
- Initiate a marketing content generation request, check whether the returned result contains complete product parameters and financial scenario adaptation notes, and has no redundant irrelevant information.
- View system operation logs, confirm that the
PARSE_FILE_TIMEOUT_SECONDSparameter does not trigger timeout alarms, and the database connection status is normal.
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.