Citation Source and Traceability for Steel Trade Investment

What this category of data looks like

Steel trade investment research data primarily comes from industry association monthly analysis reports, steel mill ex-factory price ledgers, port inventory weekly reports, commodity exchange market data, and trader transaction records. Update cycles cover daily (spot prices, same-day transactions), weekly (port inventory, regional supply and demand), and monthly (industry production capacity, annual outlook) updates. Most documents are structured tables, with fields including steel mill name, steel product specification, price per ton, inventory tonnage, transaction amount, and more. Units are uniformly ton, yuan, and yuan/ton. Some research reports are semi-structured industry trend analysis documents.

How these characteristics impose constraints on citation source and traceability

The multi-field structured nature of steel trade data requires precise matching of dimensions such as steel product specification and transaction date during traceability, to avoid cross-category data confusion. High-frequency daily and weekly updates require the traceability chain to link data update timestamps, to ensure referenced information is the latest valid version. For multi-product parallel business scenarios, separate index groups must be created for each steel product, to prevent cross-category interference in recall results. For citations of semi-structured industry research reports, specific paragraphs must be targeted instead of using the entire document as the target, to ensure traceability accuracy.

How to set configurations

Configuration Item	Recommended Value	Rationale
`recall count`	`Top 8-12`	Steel trade data has many fields and scattered product categories. Sufficient candidate results must be covered to match precise needs and avoid missing key category information.
`similarity threshold`	`0.75-0.85`	Steel trade data requires precise matching of product category and date fields. A threshold that is too low will introduce cross-category or outdated recall results, affecting traceability accuracy.
`PARSE_FILE_TIMEOUT_SECONDS`	`300 seconds`	Parsing large structured inventory tables or semi-structured industry research report documents takes a long time. Sufficient time must be reserved for complete parsing to avoid mid-process interruptions.
`chunk length`	`800-1000 characters`	Steel trade data has dense field combinations. Chunks that are too long will damage the integrity of associated fields such as product category and date. Chunks that are too short will split complete business information units.
`maxContext`	`8000-12000 characters`	Paragraphs in steel trade industry research reports are relatively long. Sufficient context must be retained to support precise paragraph traceability and avoid truncation of key information.
`reranked return count`	`Top 3-5`	The most matching steel trade data must be displayed first, to reduce interference from redundant results on traceability judgment and improve citation efficiency.

The parameter values provided on this page are common starting points for configuration. Actual values are affected by material format, data volume and business rules. Specific issues require specific analysis, and it is recommended to test on your own samples before finalizing settings.

Three common mistakes

The symptom is service unresponsiveness during knowledge base index construction, with a 504 status code returned. The cause is failure to adjust the PARSE_FILE_TIMEOUT_SECONDS parameter for large structured documents in steel trade, leading to parsing timeout without triggering retries.
The symptom is that the generated answer does not strictly reuse the original text from the knowledge base Q&A pairs, with AI rewritten content present. The cause is failure to enable the "force use of knowledge base original text for answers" switch, or failure to restrict the model's context rewriting permissions.
The symptom is that the workflow code node cannot select the knowledge base citation variable, and the first search result cannot be output. The cause is failure to configure the knowledge base retrieval node in the workflow, or failure to correctly bind the output variable of the retrieval node to the parameter list of the code node.

How to confirm the configuration is correct

Upload a structured steel trade inventory table, check if the parsed chunked content retains core fields such as steel mill name, steel product specification, and date, with no obvious truncation or incorrect splitting.
Initiate a query targeting a specific steel product and transaction date, verify that the source fields of the returned results include the document name and update timestamp, and match the precise dimensions of the query.
Adjust the similarity threshold and recall count, verify that the number and relevance of returned results meet business expectations, with no cross-category irrelevant data mixed in.
Enter the workflow debugging page, confirm that the output variable of the knowledge base retrieval node has been correctly bound to the downstream code node, and the first search result can be selected 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.