What the documents look like
Letter-of-credit document examination serves the bank's payment conditions. The central question is documentary consistency rather than tax matching, which separates this category from export tax rebate filing. The working materials are the issuing bank's advice, UCP600 clauses, the freight forwarder's bill of lading, bank presentation records, the credit itself, the commercial invoice, the bill of lading, the insurance policy and the draft. Each transaction produces a fresh combination of clauses and documents, so any drafting aid is checked against per-transaction texts rather than a stable template. Marketing copy drafted for a credit-related product therefore has to be traced back to the specific credit, invoice, bill of lading, insurance policy or draft under review.
The practical consequence for model connection is that the copy being drafted is judged against named source sentences in those documents. A claim about certification, quality or ranking has no support unless a source sentence carries the same subject, the same object and the same state. Common industry practice in one document type does not establish the state of another document type.
Constraints at the model connections step
FastGPT connects to model providers through the AI Proxy service. From V4.17.0, AI Proxy is a required dependency. Both the App service and any Admin service that reuses App/Service configuration must set AIPROXY_API_ENDPOINT to the AI Proxy service root address without appending /v1, and must set a non-empty AIPROXY_API_TOKEN. Missing either one causes startup validation to fail. Older OpenAI variables or a single-model custom request address do not replace these two settings.
Channel configuration and model configuration are checked separately. A channel carries a channel name, a protocol type, a model list, model mapping, a proxy address entered as a BaseUrl, and an API key. Model mapping translates a FastGPT model ID to the upstream model, as in mapping gpt-4o-test to gpt-4o. Model capability is verified per input type: vision, toolChoice and functionCall are separate declarations, and a completed channel does not by itself show that a needed capability is present.
Application parameters are set in the application or node configuration. A compatible chat interface field of the same name is not assumed to override orchestration settings. Retrieval is a recall process and does not perform permission or entity isolation. A relevance score is not a category, entity or permission filter, and a similarity setting does not exclude unrelated businesses or unauthorized records. Datasets built on different vector models cannot be associated together; identifiers are checked first and non-matching datasets are excluded.
Hypothetical paper exercise sample. A draft marketing sentence is being prepared for a commercial invoice under a letter of credit. The source sentences available for comparison are: "This credit requires the invoice to state the goods description consistent with the credit terms." and "The invoice shall show the beneficiary name, the invoice number and the amount." The draft sentence under review is: "This product has obtained international certification and leads in quality." The certification and quality statements in the draft sentence have no corresponding record in the source sentences. This is a paper exercise only; no test, deployment or approval has occurred.
Configuration and implementation checks
| Configuration item | Hypothetical starting value for this exercise | Reason and comparison method |
|---|---|---|
| AIPROXYAPIENDPOINT | AI Proxy service root address | Documented requirement to omit /v1; compare against the deployed root address |
| AIPROXYAPITOKEN | Non-empty administrator token | Documented requirement to match the server side; compare against the channel configuration |
| Model channel | Protocol type selected per provider | Documented guidance to match the provider; compare against the model list |
| Model capability | Verified per input type | Documented requirement to verify vision and tool calling separately; compare against the intended input |
| Application parameters | Set in the application or node configuration | Documented statement that same-named compatible interface fields do not override orchestration; compare against actual node values |
| Retrieval association | Identifiers checked, non-matching datasets excluded | Documented statement that datasets on different vector models cannot be associated; compare against dataset identifiers |
Three common errors
- Treating a completed model channel as proof that model capability is satisfied. Input is the channel list, comparison is between the channel protocol and the intended input type, and the observable result is a missing capability declaration for that input.
- Treating a similarity setting as a permission or entity filter. Input is the retrieval configuration, comparison is between the retrieval scope and the ownership of the target record, and the observable result is an unauthorized record appearing in the result set.
- Treating a certification statement in the draft sentence as supported by the source material. Input is the source sentences and the draft sentence, comparison is subject, object and state, and the observable result is the absence of that certification record in the material.
How to verify the setup
- Input the source sentences and the draft sentence from the hypothetical sample above. Compare whether the certification and quality statements in the draft sentence appear in the source material. When the material does not carry them, record the result as unsupported rather than as a denial or a conflict.
- Input the channel configuration and the intended input type. Compare the declared model capability against the actual input requirement, and observe whether vision or tool calling capability is missing.
- Input the dataset identifiers and the ownership of the target record. Compare whether the dataset identifiers match, exclude non-matching datasets and record the actual observation. An empty result can be checked against the downstream design using an explicit paper input of
[]; no claim is made that a fictional rule search must return an empty result.