What data for this use case looks like
Code security auditing data typically comes from source code repositories, dependency lists, static code scanning tools, and public vulnerability databases. It updates with each project version or iteration cycle. Daily produced documents include code audit reports, vulnerability proof materials, remediation recommendation documents, and retest records. Common data fields include vulnerability location information, risk level tags, associated code snippets, repair solutions, and verification results. There is no unified mandatory format, and it is adjusted based on service provider or team requirements.
Constraints imposed by these characteristics on multi-turn dialogue and prompt engineering
Since code security auditing data updates with project version iterations, multi-turn dialogue must support dynamic loading of audit documents for the corresponding project. This prevents context mixing of vulnerability information across different versions. Data sources include manually reviewed business logic and attack paths. Prompts must clearly distinguish between static scanning results and manual review conclusions to avoid confusion in risk level determination. Daily document structures are inconsistent. Prompts must accommodate audit reports, remediation recommendations, and other content in multiple formats. General document parsing adaptation rules must be configured. Additionally, dialogue must be linked to retest records. This ensures that each round of Q&A can trace the verification status of vulnerability repairs, and avoids repeated answers to the same question.
How to set up configurations
This configuration applies to FastGPT v4.17.0.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
chatId | Bind to the project's unique identifier | Distinguish audit dialogue contexts for different projects, avoid cross-project data mixing |
messages | Filter historical messages by project version | Ensure multi-turn dialogue only loads audit documents and Q&A records for the current version |
variables | Pass the current project's audit document path | Dynamically load code audit reports, retest records, and other data for the corresponding project |
| Context window size | 8000–12000 token | Adapt to the long text content of code audit documents, avoid truncation of critical vulnerability information |
| Historical conversation recall limit | Top 10 entries | Control context redundancy, focus on recent Q&A and audit data |
| Code snippet matching threshold | 0.7–0.9 | Adapt to the recognition accuracy of vulnerability code snippets in code security auditing scenarios |
Three common misconfigurations
- Symptom: The runtime data field in the conversation log is empty after calling the interface. Cause: The current project's code audit data source path was not passed in
variables. The system cannot load audit documents and operation records for the corresponding project. - Symptom: When passing an any parameter to the text content extraction module to extract code blocks, the complete response indicates the code block is undefined. Cause: The prompt did not clearly define extraction rules for code blocks, and did not adapt to the vulnerability code snippet format in code security auditing scenarios.
- Symptom: After manually deleting a single conversation record, associated log data disappears synchronously. Cause: The binding logic between conversations and logs did not implement project-level isolation based on
chatId. The accidental deletion affected all associated data under the same project.
How to confirm correct configuration
- Initiate a test conversation, enter keywords from the current project's audit document, and verify that the dialogue context only loads audit data for the current version.
- Review the filtering logic of the
messagesparameter, confirm that historical messages only retain Q&A and audit records for the current project, with no cross-project data included. - Trigger a code block extraction operation, verify that the response correctly identifies vulnerability code snippets in the audit document, with no undefined prompts.
- Manually delete a test conversation, confirm that only the target conversation record is deleted, and conversations and logs for other projects are not affected.
The values provided are common starting points, and should be evaluated against the reader's own 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.