What data for this category looks like
Data related to chemical raw material financial reports comes from three sources: periodic reports of listed companies disclosed by the Shanghai and Shenzhen Stock Exchanges, operation data released by industry associations, and import and export trade data publicly available from the General Administration of Customs. Update cycles vary across sources:
- Periodic reports of listed companies are updated quarterly and annually
- Industry operation data is updated monthly
- Import and export data is updated weekly
Each single document typically includes modules such as business overview, core operating data, cost structure, and upstream and downstream supply and demand conditions. Each module contains structured numerical fields and qualitative descriptive text. Units for numerical fields include tons, RMB yuan, and others.
Constraints on knowledge base retrieval and recall
The characteristics of this data create specific constraints for the retrieval and recall workflow:
- Large format differences across multi-source data. Sources include PDF annual reports, Excel structured reports, and web-based industry briefings. Parsing requires adaptation to different document types, and unified field mapping rules are needed during recall.
- Differentiated update cycles across data sources. Full data updates consume excessive resources. Configure differentiated incremental update trigger logic.
- Documents contain mixed structured numerical and qualitative text content. Retrieval must balance precise matching of numerical conditions and semantic matching of business descriptions. This requires weight configuration for hybrid retrieval.
- Single financial report documents are lengthy. Splitting them easily breaks the contextual integrity of business modules. Adjust the splitting logic to retain associated data.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
segment length | 800–1200 characters | Chemical raw material financial report documents are lengthy. This segment length can retain the context of associated business modules such as production capacity and revenue, and avoid losing core data associations after splitting |
recall count | Top 6–8 results | Financial report data includes multi-dimensional operating indicators. A recall volume of 6-8 results can cover core analysis dimensions such as supply and demand, costs, and production capacity, and avoid interference from redundant information |
similarity threshold | 0.72–0.8 | Financial reports contain structured numerical values and qualitative text. This threshold can filter low-correlation results while retaining valid content for semantic matching |
PARSE_FILE_TIMEOUT_SECONDS | 900 seconds | Parsing a single large annual report PDF takes a long time. 900 seconds can cover the complete parsing process and avoid mid-process timeout interruptions |
incremental update trigger method | Trigger based on file modification time | The update cycles of financial report data from different sources are differentiated. Triggering based on modification time can only update newly added or modified documents, improving retrieval efficiency |
rerank return count | Top 3–4 results | The large model context window has limited capacity. Returning 3-4 most relevant results after reranking can optimize the accuracy of responses |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require case-by-case analysis. Testing on local samples is recommended before finalizing settings.
Three Common Errors
- Phenomenon: After migrating a knowledge base, all document text is visible on the knowledge base management page, but the model prompts that no available content exists in the knowledge base during conversations. Cause: The current conversation application is not bound to the target knowledge base, or the knowledge base retrieval function is not enabled.
- Phenomenon: A single large financial report document is automatically split into more than 3000 text chunks. Associated data across segments cannot be retrieved during retrieval. Cause: The
segment lengthparameter is not adjusted. An excessively small segment length destroys the contextual integrity of business modules. - Phenomenon: Uploaded financial report images containing tables and charts cannot be correctly parsed and recalled. Cause: The knowledge base image OCR parsing configuration is not enabled. Only basic image metadata is extracted, and text content within the image is not recognized.
How to Confirm Proper Configuration
- Enter the knowledge base management page, upload a test financial report document, and verify that the number of parsed text chunks matches the currently configured segment length.
- Launch a test conversation containing specific operating indicator keywords, and check that recall results include relevant content from the target document.
- Enter the tool call configuration page, confirm that the target knowledge base is bound, and that the knowledge base can be selected during calls.
- View the knowledge base parsing logs to confirm that no parsing timeout or truncation occurs for large financial report documents.
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.