What the Data for This Category Looks Like
Ordnance equipment enterprise financial report data comes primarily from publicly listed company annual reports, specialized military industry disclosure documents, and public information from national defense science and technology industry authorities. Updates occur quarterly every 3 months, with annual updates once per year. Most documents are in PDF format, with structures including core operating data, R&D investment details, equipment type fielding progress, revenue by segment (such as defense equipment, civilian product trade) and other fields. Units are mostly ten thousand yuan and sets.
Constraints Imposed by These Characteristics During Deployment and Upgrade
The multi-source nature of ordnance equipment financial reports requires configuring multi-channel data access or batch import rules during deployment. Concentrated quarterly and annual report update periods create peak pressure for batch document processing, so sufficient server resources must be reserved. Large variations in financial report document structures and clear segment divisions require custom parsing rules to extract specific fields such as defense equipment and civilian product trade. Long text content increases vector database insertion and retrieval latency, so chunking and context window configurations must be adjusted. Some specialized disclosure documents use non-standard formats, so additional custom parsing template configurations are needed.
How to Set Configurations
| Config Item | Recommended Value | Basis for This Value |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 1000 MB | Annual financial report PDFs for ordnance equipment typically exceed 500 MB per file, so sufficient upload space must be reserved |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Long document parsing takes significant time, this avoids interrupting the parsing process due to timeout |
CHUNK_SIZE | 800–1000 characters | Balances financial report text splitting accuracy and retrieval efficiency, adapts to segment processing of multi-segment content |
maxContext | 8000–12000 characters | Covers complete business segment information from financial reports, supports comprehensive financial report analysis requests |
SIMILARITY_THRESHOLD | 0.72–0.78 | Distinguishes similar business data segments in financial reports, avoids redundant retrieval interfering with analysis results |
RECALL_TOP_N | Top 8–10 entries | Retrieves sufficient relevant financial report segments, supports generation of multi-dimensional analysis conclusions |
The parameter values provided on this page are conventional recommendations used as a starting point 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: A
401 Unauthorizederror is returned when deploying thetext-embedding-ada-002vector model. Cause: The model API key is not configured correctly, or the custom deployed vector model is not connected to a compatible channel. - Phenomenon: The chat page or knowledge base page becomes unresponsive and crashes when using version
4.8.20. Cause: The built-in memory usage threshold for the version has not been adjusted, or hardware resources are insufficient to support parsing and retrieval of batch financial report documents. - Phenomenon: After locally deploying the
deepseek-r1model, the<think>tags in the generated content are not processed correctly, causing abnormal page display. Cause: Custom templates for replacing tags are not configured, or model output format verification configuration is not enabled.
How to Confirm the Configuration Is Complete
- Upload a single annual financial report PDF for ordnance equipment, check if the parsed text covers core business segment fields, and confirm there are no timeout or parsing failure prompts.
- Initiate a financial report analysis query, check if the returned retrieval segments match specific segment content from the financial report, and confirm that retrieval configurations and similarity rules are working.
- Call the vector model interface, check if the returned vector data format meets expectations, and confirm that the model access channel and key configuration are correct.
- After upgrading the version, access the core function pages, confirm that page loading is normal, and check that the deployed version matches the target version.
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.