Dialogue Logging and Auditing for E-commerce Service

What This Category of Data Looks Like

E-commerce service investment research data comes from real-time or near-real-time sources: public e-commerce platform product pages, user reviews, search hot terms, and third-party monitoring tools. Data includes structured fields and unstructured content. Structured fields include product SKU, category ID, selling price, sales volume, UV, PV, with units of pieces, yuan, and times respectively. Unstructured content includes product detail descriptions and user review texts. Basic product information updates daily. Comments and search hot terms update in real time. Industry category data updates weekly. A single product document typically contains dozens of structured fields and approximately 1,000 words of unstructured content.

Constraints on Dialogue Logging and Auditing

E-commerce service investment research data’s multi-dimensional, high-frequency update characteristics create multiple requirements for dialogue logging and auditing. First, data volume is large. Split logs by session subject to prevent single log files from growing too large and slowing retrieval. Second, data update frequencies vary significantly. Link knowledge base update times to conversation initiation times during audits to ensure accurate traceability. Third, mixed structured and unstructured data requires logs to record user questions, recalled product information, and original data source links. This supports subsequent compliance checks. Fourth, e-commerce conversations may cover sensitive content such as competitor comparisons and pricing strategies. Enforce strict access permissions for logs.

Configuration Settings

Configuration Item	Recommended Value	Rationale
`customUid`	Bind e-commerce store ID, member ID, or customer service employee ID	Conversations in e-commerce services center on stores, users, or service personnel. Grouping logs by this field allows quick filtering of logs for a specific subject
`LOG_RETENTION_DAYS`	90-180 days	E-commerce investment research auditing requires reviewing quarterly-level conversation records. This duration balances storage costs and auditing needs
`RECALL_SOURCE_TRACK`	Enabled	E-commerce data includes many unique identifiers such as product SKUs and links. Enabling this option records specific recalled data sources in logs to facilitate traceability
`SESSION_MAX_HISTORY`	First 20 conversation entries	E-commerce user consultation sessions focus on recent interactions. Limiting historical conversation entries reduces retrieval and context stitching load
`LOG_EXPORT_FIELDS`	Include `query`, `recall_items`, `customUid`, `create_time`	Covers all information required for auditing: question content, recalled data, operating subject, and timestamp
`DOWNLOAD_LOG_SIGN`	Enabled	E-commerce conversations may contain sensitive content such as member information and pricing. Enabling this option verifies download permissions to prevent data leaks

The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require individual analysis. It is recommended to test against deployment-specific samples before finalizing settings.

Three Common Misconfigurations

Phenomenon: Passing the customUid parameter when calling the conversation history interface returns session records for non-target subjects. Cause: The SESSION_SPLIT_BY_CUSTOM_UID parameter is not configured correctly, so conversations are not stored grouped by customUid.
Phenomenon: Calling the historical record interface in a workflow node returns an empty array. Cause: The ENABLE_SESSION_HISTORY switch is not enabled in workflow configuration, or the current session’s customUid parameter is not bound in the request.
Phenomenon: A 403 status code is returned after clicking a knowledge base original text download link. Cause: The nginx proxy is not configured with correct request header forwarding rules, so FastGPT cannot verify download permissions, or the access port for the log download interface is not opened.

How to Verify Correct Configuration

Call the /api/v1/chat/message/list interface, pass a test customUid, and confirm the returned results only include conversation records bound to that customUid.
Initiate a conversation that includes product information recall, view the conversation log details, and confirm the log contains specific product SKUs and source links from the recall_items field.
Export the conversation log file, and confirm the exported fields include the preset content required for auditing.
After configuring the nginx proxy, access the knowledge base original text download link, and confirm the link redirects normally and no permission error is returned.

Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.