What the documents look like
Channel receivables collection happens after credit sales, and the work centers on credit limits and cash recovery. Brand finance staff, sales back-office staff, and dealer owners handle several document types together: the accounts receivable aging table, collection letters, credit agreements, and shipment freeze notices. The underlying records come from the financial system, bank receipts, dealer orders, and sales contracts. A product question and selection assistant reads these materials and drafts answers for human review. Automatic write-back or shipment freezing requires separate implementation and authorization checks.
For this category, an answer is only usable when it keeps the counterparty, the period, the amount, and the credit scope intact. A draft that drops the as-of date or merges two periods can look correct while pointing to the wrong collection stage. Model connection and configuration therefore matter less for fluency and more for whether the retrieved material and the drafted sentence line up on the same subject, period, and field.
Update frequency does not change the model connection step described here, so it is not treated as a configuration input.
Constraints at the model connections step
FastGPT connects to model providers through AI Proxy. From V4.17.0, AI Proxy is a required dependency. Both the App and any Admin service that reuses App/Service configuration must set AIPROXY_API_ENDPOINT and a non-empty AIPROXY_API_TOKEN. Missing either one causes startup validation to fail. Legacy OpenAI environment variables or a single-model custom request address cannot replace these two settings.
The system needs at least one language model and one index model to work normally. Language model fields include maxContext, maxResponse, quoteMaxToken, maxTemperature, vision, toolChoice, and functionCall. Index model fields include defaultToken and maxToken. These fields are defined in model configuration, while application or node parameters are set during orchestration. A same-named field on a chat interface does not override orchestration settings.
Retrieval and relevance scores do not perform permission or entity isolation. Whether a retrieved passage may be shown to a particular user depends on the business-side authorization decision, not on the similarity score. Retrieval is not authorization.
Hypothetical paper exercise sample. A brand finance staff member submits an excerpt from a Credit Agreement reading: "Dealer A, credit limit eight hundred thousand yuan, payment term sixty days, agreement effective from March 1, 2025." The same person submits an excerpt from an Accounts Receivable Aging Table reading: "Dealer A, as of June 30, 2025, overdue amount one hundred twenty thousand yuan, aging over ninety days." The draft sentence to be checked is: "Dealer A currently has an overdue amount of one hundred twenty thousand yuan." This sample is for paper review only. It does not represent any real customer or any business event that has occurred.
Configuration and implementation checks
The table below lists check items for this hypothetical exercise. The starting values are exercise starting points for comparison against the documentation or against observed values. They are not official defaults.
| Check item | Hypothetical starting value | Comparison method and basis |
|---|---|---|
AIPROXY_API_ENDPOINT | A value entered as the AI Proxy service root address | Compare against the documentation: the root address does not append /v1. Compare against startup validation result. |
AIPROXY_API_TOKEN | A non-empty token entered to match the server side | Compare against the AI Proxy administrator token; confirm non-empty and consistent. |
| Language model | One model enabled that supports text dialogue | Compare maxContext and maxResponse against the expected question-and-answer length. |
| Index model | One index model enabled | Compare defaultToken and maxToken against the intended document splitting approach. |
| Model test | One test round initiated in channel testing for the configured model | Observe the test result and request duration. A failed result is recorded as pending investigation. |
| Retrieval scope | Limited to the document set containing the credit agreement and aging table | Check whether returned passages come from that scope. Missing coverage is recorded as an evidence gap. |
Three common errors
- Treating
AIPROXY_API_TOKENas optional. The documentation states this item is required and must not be empty; missing it causes startup validation to fail. Input: the environment variable configuration. Comparison: the required-field statement in the documentation. Observable result: whether startup validation passes. - Using an application API key in place of the AI Proxy administrator token. The documentation states the two serve different purposes. Input: the credential actually entered. Comparison: the AI Proxy server-side configuration. Observable result: whether the model call succeeds.
- Treating a retrieved passage as an already-verified fact. In the sample, the aging table states an overdue amount only as of June 30, 2025. If the draft sentence says "currently," check whether a newer source exists. Input: the draft sentence and the two source excerpts. Comparison: subject, period, and field. Observable result: whether the draft matches the source on all three.
How to verify the setup
- Verification one: check
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKEN. Input: the address and token entered in this hypothetical exercise. Comparison: the documentation statements that the root address does not append/v1, and that the token is non-empty and consistent with the server side. Observable result: whether startup validation passes and whether the model test returns a result. A failed result is recorded as pending investigation; no specific failure cause is inferred. - Verification two: check the draft sentence "Dealer A currently has an overdue amount of one hundred twenty thousand yuan." Input: this sentence and the aging table excerpt "as of June 30, 2025, overdue amount one hundred twenty thousand yuan." Comparison: subject, period, and field. Observable result: the aging table supports "overdue one hundred twenty thousand yuan as of that date." Whether "currently" holds requires additional material; if absent, record an evidence gap.
- Verification three: with both excerpts as input, check that the subject is Dealer A in each, then separately check the agreement effective date and the aging table as-of date. The same subject does not remove the period difference. If multiple knowledge bases are searched together, separately check that their vector models are consistent. Actual citation behavior remains untested; no guarantee of a first-hit result or full recall is made.