What the documents look like
Category access review happens before listing or onboarding. The work centers on entity qualifications and the authorization chain, and the material set includes business licenses, trademark registration certificates, brand authorization chains, and industry permits. For cross-border submission, a reviewer needs to confirm that an original and its translation describe the same material, and must retain the language, the entity, and the scope of authorization. Materials are collected again at each onboarding, and update frequency does not replace version verification.
The access step also depends on the model layer. FastGPT relies on AI Proxy, and both the App service and an Admin service that reuses App/Service configuration must set AIPROXY_API_ENDPOINT and a non-empty AIPROXY_API_TOKEN; a missing value fails startup validation. Legacy OpenAI environment variables or a single-model custom request address do not substitute for these two settings. The system needs at least one language model and one index model to operate. Multilingual capability is checked against the selected model and the actual language pair, not assumed from the model family.
Constraints at the model connections step
Model mapping connects the identifier FastGPT requests to the identifier the upstream provider receives. The documented example maps gpt-4o-test to gpt-4o: FastGPT sends gpt-4o-test, and AI Proxy sends gpt-4o upstream. Whether the two identifiers differ does not by itself determine whether the mapping is correct; the configured rule and the actual request log are what a reviewer compares.
Automatic model probing covers only models currently enabled in the system. Disabled models do not participate and produce no history. A probe request that fails is retried up to three times, so a single round makes at most four attempts; one success marks the round valid, and only four failed attempts produce an abnormal result. A successful test with latency at or below 30 seconds is normal, and a successful test above 30 seconds is high latency. Model availability and retrieval content quality are separate checks.
Retrieval is not authorization. A similarity score does not filter by business category, entity, or permission, and a retrieval result cannot stand in for an authorization review. Vector libraries that use different embedding models cannot be associated together; the reviewer checks identifiers and excludes non-matching libraries rather than running a cross-model search to compare recall. Image retrieval requires an image input and a model that supports it, and reranking requires a rerank model that is enabled. The overall flow diagram lists optional paths, and not every request executes all of them.
Configuration and implementation checks
The table below covers settings and implementation checks that bear directly on model connections for cross-border material and multilingual retrieval. Values are official documented settings or explicit review items.
| Configuration item | Use on this page | How to check |
|---|---|---|
AIPROXY_API_ENDPOINT | AI Proxy service root address, with no /v1 appended | Compare the value against the documented example format, such as http://aiproxy:3000, and confirm no extra path |
AIPROXY_API_TOKEN | AI Proxy administrator token, non-empty | Compare against the server-side configuration and confirm it matches and is not empty |
| Model channel protocol type | Protocol matching the model provider | On the admin model provider page, compare the channel protocol type against the provider |
| Model mapping | Maps the FastGPT request model to the upstream model | Compare the key-value pair, for example gpt-4o-test mapped to gpt-4o, against the configured rule and the request log |
| Index model | Indexes text chunks for related-text retrieval | Confirm at least one index model is enabled and check its documented multilingual handling against the selected model |
| Model status probe | Periodically tests availability of enabled models | Confirm the probe scope covers only enabled models and that a single round makes one to four attempts |
Hypothetical paper exercise sample. A cross-border merchant intends to submit one brand authorization chain document to a platform. The source text has three sentences. Sentence one: "Authorizing party: Sample Brand Management Co., Ltd.; authorized party: Sample Trading Co., Ltd.; authorized brand: ABC; authorization period: January 1, 2025 to December 31, 2026." Sentence two: "This authorization is limited to online sales channels in mainland China." Sentence three: "This authorization takes effect on the date both parties affix their seals." The draft sentence to be judged is: "This authorization covers online sales in the target market and remains valid until December 31, 2026." The review compares "target market" in the draft against "mainland China" in sentence two, and compares "remains valid until" in the draft against the "authorization period" field in sentence one. The sample does not define a target market, so territorial coverage remains to be verified. The stated period can be quoted. The fact of both parties affixing seals is not provided, so whether the authorization has taken effect remains to be verified. The multilingual handling of the index model is checked against the model actually selected; no assumption is made that all index models perform identically for Chinese and the target-market language.
Three common errors
- Entering
AIPROXY_API_ENDPOINTas a full request address that includes/v1or/chat/completions. The environment variable document states this value is the service root address, for examplehttp://aiproxy:3000, with no/v1appended. Check by taking the variable value, comparing it against the documented example format, and confirming the path portion is only the root address. The presence of/v1or/chat/completionsfails the condition. - Mixing the FastGPT request model identifier with the upstream model identifier in a model mapping. Model mapping maps the FastGPT request model to the model actually provided, for example
gpt-4o-testtogpt-4o. Check by taking the mapping key-value pair, comparing whether the key is the model ID used in FastGPT and whether the value is the upstream model ID, and judging against the configured rule. Different names alone do not determine whether the mapping is wrong. - Treating an abnormal model status probe result as equivalent to an empty retrieval result or a failed qualification document. The documented abnormal condition is four consecutive failed requests, which is unrelated to retrieval content. Check by taking the retry count and judgment condition in the probe configuration, comparing them against the attempt count and error information in the actual probe record, and confirming the abnormal judgment concerns only model request failure, not retrieval results or document content.
How to verify the setup
- Input the three-sentence authorization source and the draft sentence, then check territory, period, and effective condition separately. The target market is undefined, so only "online sales channels in mainland China" can be retained from the source. The end date of December 31, 2026 is the stated period. The seal fact is missing, so no statement can be made that the authorization is currently effective.
- Input the mapping configuration and the actual request log, then check whether the FastGPT model identifier points to the upstream target according to the configured rule. Identical or different key and value names cannot alone be judged wrong. Without a log, the execution result remains to be verified.
- Input the selected index model and the original and translated samples of the same authorization material, then check language support and whether the returned fragments correspond to the same entity and scope. When the translation, the capability statement, or the returned record is missing, each remains to be verified rather than presumed empty or certain to match.
The above is a paper review. Status alerts, material review, and authorization effectiveness are recorded independently, and a retrieval score does not replace permission or entity verification.