What the data for this category looks like
Data for listed companies in the coal chemical industry is primarily sourced from regular reports disclosed by stock exchanges and operation briefs released by industry associations. Quarterly reports are updated within 30 days after the end of each quarter. Annual reports are released collectively by the end of April each year. Temporary announcements are updated as needed.
Document structures include consolidated financial statements, coal chemical business segment details, raw material and production-sales inventory ledgers, and cost and expense breakdowns. Core fields include designed production capacity, actual output, average raw material purchase price, product ex-factory price, unit production cost, operating revenue, and attributable net profit. Common units are ten thousand tons, yuan/ton, and hundred million yuan.
Constraints on model access and configuration
The long text and multi-field characteristics of coal chemical financial reports create multiple constraints for model access and configuration. A single financial report document can reach tens of thousands of characters and include multiple segment details. Model access configuration must adapt to long context input to avoid truncation of core business data.
Fields mix multiple units and segmented business dimensions. Precise field mapping rules must be configured to prevent unit identification and business classification errors.
Fixed disclosure schedules and unstructured temporary announcements require configuring trigger parameters for scheduled synchronization and incremental pulling. This ensures data timeliness.
How to set configuration parameters
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
maxContext | 128000–200000 characters | A single coal chemical financial report document can reach tens of thousands of characters. A long context can fully carry segment details and business ledger content |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | A single financial report requires parsing multiple tables and long text paragraphs. The timeout threshold must adapt to the parsing time of complex documents |
recall count | Top 8–12 entries | Coal chemical financial reports have more than ten core business fields. Accurate recall of core fields can improve extraction accuracy |
similarity threshold | 0.75–0.85 | Semantic similarity between different business fields of the same category must be distinguished to avoid field confusion and extraction errors |
UPLOAD_FILE_MAX_SIZE | 200 MB | The PDF or Excel file size of a single annual financial report can reach tens to over one hundred megabytes, adapting to large file upload requirements |
rerank return count | Top 5 entries | Core business fields are concentrated in the early recall results. Reranking can further filter redundant information and improve result quality |
The parameter values provided on this page are all conventional recommendations used as a starting point for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require specific analysis. It is recommended to conduct tests on your own samples before finalizing the configuration.
Three common configuration errors
- Phenomenon: An empty response is returned after calling the rerank model, and the log shows a
204 No Contentstatus code. Cause: The correct request header parameters for the rerank model are not configured, or the input text array length exceeds the upper limit supported by the model. - Phenomenon: A request failure occurs when configuring the Deepseek model with
https://api.deepseek.com, returning a404 Not Founderror. Cause: The dedicated path suffix for the model, such as/v1/chat/completions, is not added, resulting in an incomplete request address. - Phenomenon: After the external search tool in the workflow returns
array<object>format data, the generated financial report analysis text field is missing. Cause: The field mapping rules of the format conversion node are not configured, so the structured array cannot be converted into natural language text recognizable by the model.
How to verify successful configuration
- Upload a single coal chemical financial report sample, check the field integrity and unit accuracy of the parsed text, and verify whether the field mapping rules meet the requirements of the category.
- Initiate a single model call, check whether the returned financial report analysis results cover the core data of the coal chemical business segment, and adjust relevant parameters to a range suitable for the current document length.
- Simulate incremental pulling of temporary announcements, check whether the scheduled synchronization task is triggered according to the disclosure schedule, and verify the update logic of the data source configuration.
- Trigger a rerank model call, check the number and relevance of the returned results, and adjust the similarity threshold and rerank return count to a range that meets business requirements.
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.