Model Access and Configuration for Refinery Investment

What this category of data looks like

Refinery investment research data primarily comes from production plant DCS systems, ERP production ledgers, crude oil quality inspection reports, industry capacity monitoring documents, and compliance announcements. Production operation logs are updated hourly. Ledger documents are updated daily. Industry research reports and policy documents are updated weekly or monthly. Individual documents mostly combine structured tables and long text, including fields such as plant number, operating temperature, pressure, raw material ratio, product yield, and more. Units include industrial standard units such as degrees Celsius, megapascals, cubic meters per hour, tons, and others.

What constraints do these characteristics impose on model access and configuration

Refinery investment research data has numerous structured fields and diverse units. This requires model access to support joint retrieval of multiple fields and unit standardization matching. Hourly updated operation logs and daily updated ledger data require configuring incremental synchronization trigger thresholds and recall priorities for different data sources. Documents combining long text and structured tables occupy significant context quota. The segment length of individual documents must be limited to avoid exceeding the model context window. Format differences across multiple data sources require configuring unified field mapping rules to ensure information consistency during retrieval.

How to set configurations

Configuration Item	Recommended Value	Rationale
`maxContext`	`8000–12000 characters`	Individual refinery documents mostly combine long text and structured tables. This range covers valid information after typical document segmentation and avoids truncating core data
`recall_top_k`	`Top 10–15 entries`	Refinery investment research needs to cover associated data across multiple plants and raw materials. 10-15 recall entries balance information comprehensiveness and retrieval efficiency
`rerank_enable`	`Enabled`	There are many structured fields, and similarity judgments are prone to errors. Enabling reranking improves the relevance matching of retrieval results
`rerank_top_n`	`Top 5–8 entries`	Core decision-making basis for refinery investment research focuses on key plant parameters. 5-8 reranked results focus on valid information
`UPLOAD_FILE_MAX_SIZE`	`200 MB`	Single plant operation log or quality inspection report files in the refinery industry are large. This value meets conventional file upload requirements
`PARSE_FILE_TIMEOUT_SECONDS`	`600 seconds`	Parsing large-volume structured documents takes a long time. 600 seconds avoids parsing timeout interruptions

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 targeted analysis, and it is recommended to test on your own samples before finalizing settings.

Three common mistakes

Phenomenon: Model response delay exceeds 30 seconds after invocation, and logs show excessive time spent in the retrieval phase. Cause: No reasonable recall threshold is configured for multi-source incremental refinery data, resulting in full historical data being pulled for each retrieval.
Phenomenon: Reranking model deployment passes testing, but reranked results returned by each retrieval are marked false. Cause: The rerank_trigger_threshold parameter is not configured, or the threshold is set too high, causing the system to not trigger the reranking logic.
Phenomenon: Reranking model is not invoked after knowledge base retrieval content exceeds 8000 characters. Cause: The maxContext parameter is not adjusted to adapt to long document segmentation, and the reranking pre-check is not triggered after the system automatically truncates content.

How to confirm the configuration is complete

Upload 1 to 2 typical refinery documents, check if the parsed segment length matches the maxContext setting, and confirm no core information is truncated.
Send a simulated retrieval request, check if the number of retrieved results matches the recall_top_k configuration, and verify that the return marker for reranked results is normal.
Adjust the size of test documents, verify that the UPLOAD_FILE_MAX_SIZE and PARSE_FILE_TIMEOUT_SECONDS configurations can cover the upload and parsing of conventional files.
Simulate incremental data updates, check if the system automatically synchronizes new refinery operation logs according to the configured trigger threshold, and confirm that the latest data can be obtained during retrieval.

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.