What the data for this category looks like
Energy storage-related marketing data for the financial, insurance, and wealth management industries. Sources include product specifications from equipment manufacturers, on-site operation logs, industry compliance certification documents, and supporting marketing materials such as product manuals, installation case videos, and certified scanned copies. Document structure is divided into three categories: professional parameter documents, project case documents, and marketing promotional materials. Fields include dedicated parameters such as rated energy storage capacity (unit: kWh), cycle life (unit: times), operating temperature range (unit: ℃), installation altitude (unit: m), and others. Update rhythm: product specifications are updated regularly alongside product line upgrades, project operation data is synchronized in real time, and marketing materials are updated according to marketing campaign cycles.
What constraints do these characteristics impose on the deployment and upgrade process
Dedicated energy storage parameters are numerous and use industry-specific units. Custom field parsing rules must be configured during deployment, and general-purpose text extraction templates cannot be reused directly. Real-time synchronized project operation data requires configuring an incremental synchronization trigger mechanism during upgrades to support real-time data access to the knowledge base. The presence of large numbers of long documents and high-definition images requires adjusting parsing timeout times and uploaded file size limits to accommodate processing of large-volume materials. The need to associate multi-source data requires configuring custom field mappings during deployment to ensure accurate association between professional parameters and marketing scenarios.
How to set the configurations
| Configuration Item | Recommended Value | Basis for This Setting |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Energy storage equipment manuals are mostly 10-20 page long documents, and OCR and text parsing take a long time |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Single files such as energy storage project case videos and high-definition installation drawings have large volumes |
chunk_size | 1000–1200 characters | Energy storage parameter fields are mostly short sentences; long document segmentation must retain the integrity of parameter associations |
vector_search_top_k | Top 8 entries | Energy storage marketing content must balance professional parameters and scenario cases; excessive recall will distract users |
RECALL_SIMILARITY_THRESHOLD | 0.75–0.85 | Many professional terms exist in energy storage, so low-relevance general documents need to be filtered |
ENABLE_IMAGE_PARSE | Enabled | Energy storage marketing materials include a large number of installation diagrams and qualification certificate images, and visual models are required to extract key information |
The parameter values provided on this page are all conventional recommendations used to determine the starting point for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require specific analysis, and it is recommended to conduct actual tests on your own samples before finalizing the values.
Three common mistakes
- Phenomenon: The SaaS version prompts no permission when attempting to add a custom model. Cause: An access application for the custom model was not submitted in the model management module of the console, and the qualification verification process was not completed.
- Phenomenon: After configuring the image parsing workflow, no parsing results are obtained when uploading energy storage installation images. Cause: An image-to-base64 conversion step was not added to the workflow, and the input format requirements of the visual model were not adapted.
- Phenomenon: Unable to execute SQL commands after entering the docker-deployed pgvector container. Cause: The postgres system user was not switched to, or the
CREATE EXTENSION vector;command to load the extension module was not executed.
How to confirm the configuration is complete
- Upload a single energy storage equipment manual document, check whether the parsed text retains the integrity of the association of dedicated parameters, and adjust the segmentation length parameter to a range suitable for the document structure.
- Initiate a model call test, check the relevance and number of returned results, and adjust the number of recalled entries and similarity threshold to standards matching business requirements.
- Upload energy storage-related image materials, check whether the visual parsing results extract key information, and confirm that the image parsing function has been normally enabled.
- Check the database operation log, confirm that the pgvector extension module has been loaded, and that the custom data field mapping configuration has taken effect.
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.