Marketplace category access: conversation logs for operations handover

What the documents look like

Marketplace category access happens before listing or store onboarding. The core materials are the business license, trademark registration certificate, brand authorization chain, and industry permits. These come from marketplace recruitment pages, the national enterprise credit information publicity system, trademark office data, and permit systems. Updates are irregular, and each onboarding round collects them again. Recruitment operations staff, store onboarding specialists, and brand-side channel managers need to confirm whether a given material is being collected, pending correction, submitted, or rejected. Conversation logs and audit records document this communication: who submitted which material in which conversation, which request is pending review, and which correction is complete. The logs themselves do not change a material's authorization status; they retain an operational trail.

Two features of this category shape the task. First, every onboarding round is a fresh collection, so the log must tie a specific submission to a specific round rather than assume continuity across rounds. Second, authorization status is a business fact held in the materials and approval workflow, not something the conversation interface produces. A retrieved passage or a filled form field records what was said or entered; it does not establish that a permit is valid or that a category is approved.

Constraints at the conversation logs step

In the conversation interface, chatId determines which session is taken from the FastGPT database, and dataId identifies one conversation under a session. During handover, verifying a target conversation requires combining chatId with the business record; sessions from different entry points must not be counted together. When run details are needed, set detail=true per the official contract and inspect module status and complete results in responseData; with detail=false only the final answer appears, and intermediate states are not returned. Which fields the interface actually returns depends on the response, and business data that is not returned cannot be presumed to be fully retained. Identity fields in test mode and production calls may differ, so inputs, history, and returned content are checked separately. Reconciliation, retention, and compliance requirements are implemented by the complete business solution; the existence of a log does not equal a completed compliance audit.

Hypothetical drill sample: a brand-side channel manager submits a scanned trademark registration certificate to a store onboarding specialist. The draft sentence under review reads: "This trademark registration certificate already covers Class 35, the authorization chain is complete, and the category access can be submitted." The material text provided for comparison reads: "Trademark Registration Certificate No. XXXX, registrant: a certain food company; approved goods/services: Class 30, coffee, tea; valid until a date in 2029." A separate handover request reads: "Please confirm whether the dealer tier in this brand's authorization chain has provided a second-level authorization letter." The material text contains no Class 35 and no second-level authorization letter content.

Configuration and implementation checks

Three common errors

1. Treating a detail=false response as a complete run record. In that mode only the final answer appears, responseData is absent, and module status and intermediate results cannot be obtained from that response. To check, compare the fields returned by the same request under detail=true and detail=false, and observe whether responseData is present.
2. Assuming identical business records because chatId matches. chatId identifies only the session; different dataId values under one session correspond to different conversations. To check the draft sentence, input that chatId with the target dataId, compare the returned obj and value against the material name and submission time in the business record, and observe whether they point to the same conversation.
3. Treating a retrieval result or a filled form as completed authorization. The quoteList and score returned by retrieval indicate recalled content and similarity only; they do not indicate that a material passed review or that authorization took effect. To check, input "already covers Class 35" from the draft sentence, compare it with the approved goods/services in the material text, and observe whether Class 35 appears. When it does not appear, record it as unsupported and retain the evidence gap.

How to verify the setup

1. Input the material text and the draft sentence from the sample, and compare the draft sentence "already covers Class 35" with the original "Class 30, coffee, tea." Expected observation: the original does not contain Class 35, the sentence is unsupported by the material, and it is recorded as pending verification. No claim is made that this was actually tested.
2. Input the handover request "whether the dealer tier has provided a second-level authorization letter," and compare it against whether second-level authorization letter content appears in the material text. Expected observation: the original does not state a second-level authorization letter, the completeness of the authorization chain for that request is unsupported, and the gap is retained.
3. Input query requests for two different dataId values under the same chatId, and compare whether the two returned value fields correspond to different conversation content. Expected observation: the two returns differ, confirming that dataId distinguishes single conversations; if the returns are identical, record as pending verification and do not infer a cause for the duplication.

Related reading

• openapi/chat
• FastGPT conversation logs