What the data for this category looks like
Plastics and rubber investment research data primarily comes from industry associations, futures exchanges, the General Administration of Customs, spot price platforms, and professional research report institutions. Spot data is updated daily, including same-day spot prices, regional inventory, and trading activity. Monthly supply and demand reports are split into sub-categories such as PE, PP, and natural rubber, with fields covering output, import volume, and consumption. Units are ten thousand tons and yuan per ton. Industrial chain association data mostly exists as structured tables and graphs, while some research reports use long document formats.
What constraints these characteristics impose on model access and configuration
Daily spot data updates, fixed monthly report cycles, and large format differences require incremental recall rules triggered by data type. Structured fields have clear units and value ranges, so the model must support unit-aware numerical parsing and cross-field comparison. A high share of long-document research reports requires adjusting segment length to fit the model's context window. Inconsistent formats across multiple data sources require preset data cleaning mapping rules to prevent the model from confusing statistical standards across different categories.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
CHUNK_SIZE | 800–1200 characters | Fits the long-document structure of plastics and rubber research reports, avoids context breaks after segmentation |
maxContext | 12000–16000 characters | Accommodates structured data and long document content across multiple categories |
RECALL_TOP_N | Top 10–15 entries | Covers multi-dimensional data such as supply and demand and prices across different sub-categories |
SIMILARITY_THRESHOLD | 0.75–0.85 | Ensures matching accuracy between recalled data and investment research queries, filters irrelevant content |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Matches the parsing time required for large monthly supply and demand reports |
UPLOAD_FILE_MAX_SIZE | 500 MB | Supports batch uploading of industrial chain graphs and bulk research report files |
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. Each situation requires specific analysis. It is recommended to run tests using local test samples before finalizing settings.
Three common configuration errors
- Symptom: Model inference takes longer than 3 minutes, and the interface displays a loading timeout. Cause: Model quantization was not enabled for low video memory graphics cards, and the
max_batch_sizeparameter was not adjusted to match hardware performance. - Symptom: Workflow conversation returns a failure, but complete response logs are visible in the model backend, with a 504 status code returned by the interface. Cause: The workflow's model call timeout parameter was not configured, and the frontend disconnected after waiting for a timeout.
- Symptom: Multiple accounts cannot call the same model simultaneously, only a single account can initiate requests normally. Cause: Multi-channel key mapping was not added in the model configuration, and the multi-account polling scheduling strategy was not enabled.
How to confirm the configuration is complete
- Upload a typical plastics and rubber monthly supply and demand report, check that the parsed segments are complete with no obvious content breaks.
- Initiate a query covering specific category prices and supply and demand data, verify that the number and matching accuracy of recalled results match the preset rules.
- Call the model to generate investment research analysis content, check that response time and output length meet business requirements.
- After configuring multi-channel keys, initiate multiple queries to confirm that call requests from different accounts are scheduled normally.
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.