What This Category’s Data Looks Like
The data for software development intelligent due diligence reports comes primarily from project code repository commit records, requirement specification documents, test defect reports, compliance audit working papers, and third-party code vulnerability scan results. Update frequency is adjusted alongside project iterations, typically after each version release or major requirement change.
Each individual document includes fields such as project unique identifier, function module name, code line count, vulnerability risk level, compliance check item number, and update timestamp. Code line count uses "lines" as the unit. Vulnerability levels use low, medium, high, and critical as grading units. The overall document combines structured metadata with code snippets and text descriptions.
What Constraints These Characteristics Impose on Knowledge Base Retrieval and Recall
Multi-source heterogeneous data sources require support for parsing and adapting multiple formats, including code files, markdown documents, structured tables, and more. The high-frequency update feature requires the retrieval link to support incremental synchronization, to avoid resource waste from full repeated parsing.
Content that includes code snippets requires retaining the integrity of code blocks during segment processing, to avoid splitting that breaks syntax logic. The presence of structured fields requires retrieval support for filtering by fields such as module name and vulnerability level, to improve the accuracy of recall results. Longer combined content requires reasonable control of single-segment text length, to avoid exceeding model context limits.
How to Configure Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_CHUNK_SIZE | 800–1200 characters | Software development due diligence reports include code snippets and structured text. Segments that are too long will lose contextual association, while segments that are too short will damage the syntax integrity of code blocks |
RECALL_TOP_K | Top 8–12 results | Retrieval requirements for due diligence reports usually cover compliance and vulnerability information across multiple modules. Too many recall results will increase the processing burden on model context |
SIMILARITY_THRESHOLD | 0.72–0.85 | Semantic similarity distinction between code and compliance text is relatively high. A threshold that is too low will introduce irrelevant results, while a threshold that is too high will miss relevant compliance or vulnerability information |
UPLOAD_INCREMENTAL_SYNC | Enabled | Software development projects iterate frequently. Incremental synchronization reduces the overhead of repeatedly parsing the same document and improves indexing efficiency |
PARSE_CODE_BLOCK_PRESERVE | Enabled | Code snippets need to retain complete context, to avoid splitting that causes syntax logic breaks and affects subsequent retrieval matching |
MAX_CONTEXT_LENGTH | 4000–6000 characters | Retrieval results of due diligence reports need to integrate information across multiple modules. An overly long context will exceed the input limits of most large language models |
The parameter values provided on this page are conventional recommendations used as starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require case-by-case analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Phenomenon: After uploading a single due diligence report, the initial segment count is displayed. After a period of time, the segment count increases and duplicate fragments appear. Cause: The
UPLOAD_INCREMENTAL_SYNCparameter is not enabled, and full parsing tasks are triggered repeatedly, resulting in the same document being segmented and indexed multiple times. - Phenomenon: When searching for due diligence content for a specified module, recall results include information from unrelated modules. Cause: No field filtering rules are configured, and the module name is not used as a retrieval filter condition, resulting in matching of irrelevant document fragments.
- Phenomenon: A timeout error is returned when parsing large code files. Cause: The
PARSE_FILE_TIMEOUT_SECONDSparameter is not adjusted, and the default timeout period is insufficient to process due diligence report documents containing large amounts of code.
How to Confirm Configurations Are Properly Set
- Upload a single typical software development due diligence report, view the segment preview interface, and confirm that code blocks are not split and the segment count meets expectations.
- Initiate a retrieval test, enter compliance item keywords for a specified module, check whether the recall results cover the target module, and adjust the similarity threshold to meet business requirements.
- Trigger an incremental synchronization task, view the index log, and confirm that only newly added or modified documents are parsed, with no duplicate indexing records.
- Call the multi-knowledge base retrieval function, enter bound variable parameters, and check whether specified multiple knowledge base contents can be recalled simultaneously.
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.