What this type of data looks like
Data sources for cybersecurity financial reports include three categories. These are publicly disclosed periodic reports of listed companies, industry operation documents from industry associations, and annual operation briefings published independently by vendors. Periodic reports are released quarterly. Annual reports are published after audit. Temporary announcements update alongside major corporate events. Document structures include several core sections. These are operating data, R&D investment details, security product iteration records, compliance rectification status, and customer cooperation scale data. Fields and units follow fixed rules. Revenue-related fields use RMB yuan. R&D investment uses ten thousand yuan. Product iteration versions use number-and-letter combinations for identification. Customer cooperation counts use integers.
Constraints on knowledge base retrieval and recall
Publicly disclosed cybersecurity financial reports can be lengthy. Some annual reports have very large character counts. The retrieval process must support intelligent splitting of long documents and segment association. Update schedules are uneven. Quarterly reports launch during fixed windows. Temporary announcements have no fixed release cycle. Knowledge base incremental sync must support on-demand triggering. It must also adapt to resource scheduling for batch sync operations. Documents contain dense technical terminology. Examples include CVE numbers, zero-trust solution revenue, and penetration test exercise revenue. A professional thesaurus must be used to improve recall accuracy. Some data has compliance disclosure requirements. Recall results must filter undisclosed internal operating data. Only publicly available disclosure content may be returned.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000-12000 characters | Core retrieval paragraphs of cybersecurity financial reports are mostly thousands of characters long. This range can accommodate multiple related segments without exceeding the context limit of general-purpose models |
segment_length | 1000-1500 characters | Financial report data often contains related fields. Excessive length will break data associations, while insufficient length will increase the number of retrieval shards |
similarity_threshold | 0.72-0.80 | Financial reports contain many technical terms. A higher similarity threshold is needed to filter irrelevant general documents and avoid recalling non-target financial report content |
recall_count | Top 6-10 results | Financial report data is scattered across multiple subsections. Too few results will miss key fields, while too many will increase the model's processing load |
reranked_return_count | Top 3-5 results | Reranking can further filter the most relevant paragraphs and improve the accuracy of generated results |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Parsing large annual financial report documents takes significant time. 300 seconds covers the parsing process for most single documents |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material format, data volume and business rules. Specific issues require specific analysis, and it is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Issue: After creating a global variable with the custom type set to Knowledge Base Selection, the variable cannot be selected as a judgment criterion in the judge's condition configuration. Cause: The judge only supports global variables of basic data types by default, and does not open the condition configuration entry for knowledge base selection type variables.
- Issue: When calling a regular conversation node, the system automatically introduces configured knowledge base retrieval results, causing the response to deviate from the preset general conversation logic. Cause: The option to automatically associate knowledge base was not turned off in the conversation node configuration, or the global default setting enabled full-process knowledge base association.
- Issue: The knowledge base Q&A return results do not include image association information from the original document, only returning text fragments. Cause: The image association extraction configuration during knowledge base parsing was not enabled, or the OCR association index rule was not configured.
How to Verify Proper Configuration
- Upload a single test cybersecurity financial report document, view the parsed segment results, and confirm the segment configuration meets expectations.
- Send a retrieval request targeting specific fields in the financial report, and check whether the number of returned results matches the preset recall count.
- After creating a global variable with the custom type set to Knowledge Base Selection, enter the judge configuration interface, and confirm the variable can be selected normally.
- Trigger a regular conversation node, confirm that knowledge base retrieval results are not automatically associated, and verify that the conversation node configuration takes effect.
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.