What the data for this category looks like
White goods investment research data is sourced from public reports of industry monitoring institutions, public brand financial reports, e-commerce platform sales data, offline terminal retail monitoring, upstream raw material supply chain data, and patent technical documents. Data update cycles differ:
- E-commerce sales data is updated hourly
- Offline terminal retail data is updated weekly
- Industry reports and financial reports are updated monthly, quarterly, or annually
Document structures include structured tables, long-text analysis, supply chain quotation details, and more. Fields include sales volume, average price, inventory turnover days, and raw material purchase prices, with corresponding units of 10,000 units, yuan per unit, days, and yuan per ton respectively.
Constraints imposed on model access and configuration
Multi-source data with uneven update frequencies requires timed synchronization rules grouped by data source type. This prevents excessive resource consumption from high-frequency data syncs and avoids delayed updates for low-frequency data. Documents with varying structures need flexible segmentation strategies to prevent semantic fragmentation in long-text analysis and prevent loss of structured data fields. Multi-dimensional business fields require metadata mapping rules to ensure the model can accurately identify and link different types of business data. High-frequency sales and terminal data needs a near-real-time vector update mechanism to maintain the timeliness of investment research results.
How to set configurations
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
PARSE_FILE_SEGMENT_SIZE | 800–1200 characters | Adapts to the mixed format of long text and structured content in white goods industry reports and financial reports, avoiding semantic fragmentation |
RECALL_TOP_K | Top 6–8 entries | Covers the multi-dimensional data required for white goods investment research, avoiding excessive recall results interfering with model judgment |
SIMILARITY_THRESHOLD | 0.72–0.78 | Filters low-relevance content outside the white goods field, retaining data sources strongly matched to the investment research theme |
SYNC_TASK_CRON | 0 2 * | Synchronizes and updates high-frequency data such as e-commerce and terminal retail data daily at 2 AM, avoiding peak business hours |
maxContext | 12000–16000 characters | Adapts to the context requirements of long documents, supporting complete reading of a single industry report or financial report |
VECTOR_BATCH_REBUILD | Enabled | Supports batch retraining of vector models, replacing inefficient single-file adjustment operations |
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 case-by-case analysis. It is recommended to test on your own samples before finalizing the configuration.
Three common errors
- Phenomenon: When deploying version V4.9.3 on Ubuntu Server 24.04 and configuring
qwen-maxand an Alibaba Cloud API key, the large model does not reference web search results in non-tool call mode, while the web search node function operates normally. Cause: The network authorization switch for non-tool mode is not enabled in the model access configuration, or the search node is not bound to the current model's call chain. - Phenomenon: After uploading files in simple mode of V4.8.9, some models automatically parse the files while others do not trigger parsing. Cause: The trigger rules for
PARSE_FILE_AUTO_TRIGGERare not clearly configured, or default parsing thresholds vary across different models. - Phenomenon: The vector model only supports adjusting training parameters for a single file and cannot perform batch retraining. Cause: The
VECTOR_BATCH_REBUILDparameter is not enabled, or the trigger conditions and data source scope for batch tasks are not configured.
How to verify successful configuration
- Check the API key configuration items in the model access interface, confirm the key is correctly filled and has not expired.
- Upload a single white goods industry document, verify that the parsed segment length matches the configured
PARSE_FILE_SEGMENT_SIZE. - Initiate a simulated investment research query, confirm that the number of returned recall results matches the
RECALL_TOP_Kconfiguration. - Trigger a batch vector update task, check that the task log shows the expected number of files being processed in batch.
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.