What this category of data looks like
Data for this category comes from advertising platform backends, the National Enterprise Credit Information Publicity System, customer-submitted materials, and industry access rules. Daily processed documents include account opening applications, business licenses, industry qualifications, and account opening audit records. Data updates occur daily or synchronize with each account opening application. Data fields include the main body’s unified social credit identifier, industry qualification number, application submission time, audit status, and other fields. Only full original records of the entire application and audit process are retained, with no additional custom statistical fields.
What constraints these characteristics impose on the conversation logs and auditing workflow
Data sources are scattered. Auditing requires associating log entries from multiple platforms. Conversation logs must support cross-data source associated queries. Updates synchronize with individual account opening applications. Auditing must support full process retrieval for each application sheet, rather than only time-based filtering. Document structures are fixed. Logs must retain complete mapping of original material fields. Field names cannot be arbitrarily truncated or modified. Error consequences are clearly defined. Auditing must retain complete audit operation logs to quickly locate issues in qualification verification and access judgment links.
How to configure settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
| Session log storage duration | 180 days | Aligns with regular archive cycle requirements for compliance auditing |
| Log association identifier | Bind chatId and account opening application number | Ensures full-process conversations for each account opening application can be uniquely retrieved by application number |
| Detail display field | Fully load detail field content | Retains all details of original audit interactions, matches field mapping rules for business documents |
| Cross-source log association | Associate multi-data source logs by responseChatItemId | Uniformly displays audit process data from advertising platforms and enterprise credit systems |
| Exception log trigger threshold | 300-600 second timeout | Covers regular audit operation durations, avoids false triggering of exception alerts |
Three common misconfigurations
- Session logs display blank content or return an "invalid chatId" error. Account opening application numbers are not correctly bound to
chatId, causing logs to fail association with corresponding application sheets and preventing retrieval by application dimension. - Uploaded business licenses, industry qualifications, and other materials are not included in large language model audit statistics. Log and uploaded data association rules are not configured. Uploaded material data is not loaded into the
detailfield of the conversation context. - Calling the multimodal API to review image-based qualifications returns a 400 invalid image status code. Image format and size parameters are not verified during the log auditing phase, causing materials that do not meet interface requirements to be directly submitted to the audit process.
How to confirm proper configuration
- The FastGPT v4.17.0 retrieval function is used to enter any account opening application number, retrieve the corresponding session log, and confirm that complete conversation interactions and associated material fields are displayed.
- A test qualification material is uploaded to trigger an audit conversation, and confirmation is made that the material content appears in the log details of the
detailfield. - An image material that does not meet interface requirements is submitted, and confirmation is made that the log records format verification exception information.
- An audit operation exceeding 300 seconds is simulated, and confirmation is made that a corresponding timeout exception record is generated in the log.
The values provided here are common starting points, and should be evaluated against the samples relevant to the specific deployment.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-10-19.