What the documents look like
Channel receivables collection happens after credit sales, and the work centers on credit limits and cash recovery. The material comes from finance systems, bank receipts, distributor orders, and sales contracts. The documents handled day to day include the receivables aging table, the dunning letter, the credit agreement, and the shipment freeze notice. These documents update mainly by week and by month, and their field definitions shift as the aging period rolls forward. When drafting product and marketing copy in this category, the amounts, aging periods, freeze status, and agreement clauses in the draft must match the retrieved source text. The knowledge base retrieval and recall step determines which document fragments are available at drafting time and whether those fragments cover the fields a judgment needs.
Constraints at the retrieval step
The knowledge base search node can associate one or more knowledge bases that use the same vector model. Semantic retrieval relies on vector distance to compute similarity. Full-text retrieval suits precise lookup of numbers, models, and proper nouns. Hybrid retrieval merges the two paths through RRF. A ReRank model reorders candidate text a second time and returns a 0-1 score. The minimum relevance value takes effect only under semantic retrieval or when result reordering is used. The reference limit is measured in tokens. Question optimization performs coreference resolution and question expansion and adds an extra model call. Reference content is output as an array, and its length can be 0, so the output path still runs when nothing is found. Retrieval results do not perform permission filtering or entity isolation, and a similarity score does not distinguish authorization scope.
Hypothetical exercise sample: a brand finance staff member drafts a channel collection message and needs to check the source text. Material one is an excerpt from the credit agreement: "The credit limit under this agreement is RMB 800,000, and the credit validity period runs from January 1, 2025 to December 31, 2025." Material two is an excerpt from the receivables aging table: "Distributor A has an outstanding receivable balance of RMB 920,000 as of June 30, 2025, of which RMB 120,000 is overdue by 31 to 60 days." The draft sentence to be judged is: "Distributor A has exceeded the credit limit; please arrange repayment within this week." This sentence involves a subject, an object, an amount, and a status, and each item must be compared against the two materials.
Configuration and implementation checks
Configuration here follows the sample on this page for retrieval and checking. It lists only settings the official documents describe, or implementation check items. The values are hypothetical starting points for this exercise, used to compare against another value, and they are not official defaults.
| Configuration item | Hypothetical starting point for this exercise | Reason for the choice and comparison method |
|---|---|---|
| Associated knowledge bases | Associate only the same-vector-model base holding the credit agreement and the aging table | First check whether the vector model identifiers match, exclude bases with different models, and do not run cross-model retrieval |
| Search mode | Test the draft sentence with semantic retrieval first | Compare semantic results against full-text results and observe whether amount and date fields are recalled |
| Reference limit | Hypothetical starting point of 2000 tokens | Test with aging table fragments of different lengths, compare whether fragments are truncated, then adjust the value |
| Minimum relevance | Hypothetical starting point of 0.5 | Label relevant and irrelevant samples first, then compare whether irrelevant fragments are filtered at different values |
| Question optimization | Off at first, retrieving with the complete draft sentence | Compare the original question with the optimized question and check whether subject and amount were altered |
| Result reordering | Not enabled at first | Enable it when candidates are numerous, and compare ordering and scores before and after reordering |
Three common errors
- Treating a similarity score as an authorization filter. Input the draft sentence to retrieve the credit agreement. If a returned fragment contains another distributor's credit limit, a high score does not make that fragment usable for this sample. Compare the subject name in the fragment against the sample, and mark fragments with a different subject as inapplicable.
- Treating a pending-review status as already effective. Assume material three is a draft shipment freeze notice marked "pending review by the finance lead." A draft sentence reading "shipment has been frozen" does not match the draft status. Compare the status field on the notice; pending review does not equal an executed freeze.
- Treating an unstated field as a denial. The aging table lists only the amount overdue by 31 to 60 days and does not state the total credit limit used. A draft sentence reading "has exceeded the credit limit" lacks a same-period, same-field comparison between the credit limit and the receivable balance, so it is unsupported, and the evidence gap should be recorded.
How to verify the setup
- Input the draft sentence "Distributor A has exceeded the credit limit; please arrange repayment within this week" and retrieve the credit agreement and the aging table. Compare the subject, amount, and date fields in the returned fragments. If the credit limit of RMB 800,000 and the receivable balance of RMB 920,000 exist for the same period and the fragments fully cover both fields, the checking condition is met; if only one field is recalled, record the gap.
- Input material three, the freeze notice draft marked "pending review by the finance lead," and retrieve its status field. Compare the freeze wording in the draft sentence against the draft status. If the draft status is pending review, a draft sentence reading "has been frozen" does not meet the condition; revise it to match the draft status or mark it as pending verification.
- Input a short question containing no amount and no subject, and observe the reference content output. Compare the output array length against the retrieval log. If the output is an empty array, the documented behavior is that the path still runs, so the downstream drafting step should be designed to handle an empty result; do not claim that an empty result is necessarily produced by a particular rule.