What the Data for This Category Looks Like
This category’s data is generated across the full ad account opening process. Daily documents include account opening application forms, business license scans, corresponding industry operation qualification documents, and audit record ledgers for account opening. Data sources include account application records from ad platform backends, entity verification data from public enterprise credit information systems, paper or electronic materials submitted by customers, and public industry access rules. Data update frequency follows individual account opening application progress: updates are made after each application node is completed. Multi-round verification data is generated during entity qualification verification and industry access judgment stages.
Constraints Imposed on Multi-turn Dialogue and Prompt Word Configuration
The above data characteristics impose clear constraints on multi-turn dialogue and prompt word configuration. First, data sources are scattered and include unstructured materials, requiring multi-turn dialogue to support information retrieval and verification across multiple data sources. Second, update frequency changes with application nodes, so prompt words must adapt to context binding for a single session to avoid information confusion across different applications. Third, the entity qualification verification stage accounts for a high proportion of time, so multi-turn dialogue must support process guidance for segmented verification while retaining audit records from each round. Fourth, the dynamic nature of industry access rules requires prompt words to call the latest rule library in real time and distinguish access differences across industries. Finally, the high frequency of material correction communication requires multi-turn dialogue to automatically identify missing material fields and trigger targeted correction reminders.
Configuration Specifications
This configuration applies to FastGPT v4.17.0. Details are as follows:
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chatId | Bind to the unique identifier of a single account opening application | Prevent confusion of dialogue contexts across different account opening applications, ensure one-to-one correspondence between session logs and application records |
messages | Limit the context window to the first 15 rounds of dialogue | Multi-turn communication for account opening audits usually focuses on qualification correction and rule explanation. 15 rounds are sufficient to cover the complete application process and avoid context overload |
variables | Bind qualification field variables submitted by customers | Automatically call submitted data such as business license registration numbers and industry qualification numbers during dialogue, reducing repeated data entry |
| Maximum Context | 8000–12000 characters | The total sum of materials and communication content for a single account opening application usually falls within this range, avoiding exceeding the model’s processing limit |
| Question Optimization | Enabled, calibrated based on actual testing | Convert colloquial correction requests from customers into standardized qualification field verification items, improving audit efficiency |
Three Common Misconfigurations
- Phenomenon: After passing the
chatIdparameter when calling the API, the parameter value is not displayed in the dialogue log. Cause: The session initialization logic does not associatechatIdwith the unique identifier of the account opening application, resulting in the parameter not being correctly written to the log field. - Phenomenon: Users accessing via login-free links delete dialogue content, and background audit logs are also cleared. Cause: Independent storage logic for dialogue content and audit records is not configured, and session storage is mistakenly used as the only data source for audit logs.
- Phenomenon: Inconsistent audit results are returned when calling industry access rules during dialogue. Cause: The prompt word does not limit the use of only the industry access rule library bound to the current session, resulting in calls to expired or irrelevant rule data.
How to Verify Successful Configuration
- A simulated account opening application dialogue can be initiated, with the preset
chatIdparameter passed, and the background logs can be checked to confirm whether the parameter value is displayed. - A login-free link can be generated and a dialogue initiated. After manually deleting the dialogue content, the background audit records can be checked to confirm whether complete communication logs are retained.
- A historical variable loading node can be configured in the workflow. After initiating a new dialogue, it can be verified that qualification field variables saved in previous sessions can be retrieved.
- A simulated dialogue with more than 15 rounds can be initiated. It can be verified whether the context is automatically truncated to the most recent 15 rounds of content to avoid interference from redundant information.
The values provided are common starting points and should be measured against the applicable samples.
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.