What the data for this category looks like
Data sources for shipping port financial reports include public operation announcements from port management authorities, periodic reports of listed companies, and industry statistical publications. Update cycles fall into three categories: monthly operation bulletins, quarterly operation summaries, and annual full financial reports. Disclosure frequency and level of detail vary across cycles.
Document structure typically includes four core sections: core operation indicators, detailed financial revenue and expenditure, infrastructure usage, and business situation analysis. Core fields cover container throughput, bulk cargo throughput, total cargo throughput, revenue, berth operation volume, and more. Corresponding units are TEU, ten thousand tons, natural tons, RMB yuan, and operation hours respectively.
What constraints do these characteristics impose on model access and configuration
First, multi-cycle disclosure data requires the model to support filtering and recalling knowledge base fragments by time range during calls. Corresponding retrieval parameters must be configured to achieve precise matching. Second, exclusive fields and units require configuring entity mapping rules during model access to prevent the model from confusing semantic and unit differences between indicators such as different types of throughput and revenue. Third, financial report documents are lengthy; annual financial reports may contain dozens of pages. Reasonable text segmentation and context window parameters must be configured to avoid exceeding the model's token processing limit. Fourth, multi-source data requires configuring differentiated indexing rules to ensure the recall priority of public operation data and financial data aligns with analysis needs.
Overall, data analysis for this category places higher demands on the model's professional field recognition and context processing capabilities. Parameters must be adjusted specifically during the configuration phase.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
apiBaseUrl | http://{your-oneapi-domain}/v1 | Most open-source large model APIs follow the OpenAI-compatible format. The /v1 path must be added to adapt to calling specifications, which conforms to community general configuration practices |
requestTimeout | 300 seconds | Shipping port financial report documents are lengthy. The model requires a long time to process complete fragments, to avoid task interruption due to timeout midway |
chunkSize | 1000–1500 characters | Port financial reports contain a large number of professional terms and long sentences. Excessively long segmentation will exceed the model's token limit, while excessively short segmentation will destroy the integrity of professional terms |
recallTopK | Top 6–8 entries | Core operation data of port financial reports is distributed across multiple paragraphs. Too few recalls will miss key indicators, while too many will increase the model's inference burden |
similarityThreshold | 0.75–0.85 | Port financial report fields are highly professional. A high similarity threshold is required to ensure recalled data matches query needs and avoids interference from irrelevant content |
chunkOverlap | 200 characters | Ensure continuity of professional terms between segments, preventing semantic breaks caused by truncated long sentences |
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, and it is recommended to conduct tests on your own samples before finalizing the configuration.
Three Common Misconfigurations
- The phenomenon is that the model call returns a 404 error. The cause is that the
/v1path is not added at the end of the AI model API address, which does not conform to the calling format of OpenAI-compatible APIs. - The phenomenon is that the financial report data returned by the model has mixed units. For example, the values of container throughput and bulk cargo throughput are confused. The cause is that entity mapping rules for professional fields are not configured, and the model cannot recognize semantic differences between exclusive units such as TEU and ten thousand tons.
- The phenomenon is that the workflow triggers the retrieval link and reports an error when the knowledge base is empty. The cause is that the branch jump logic for empty knowledge bases is not configured, and the workflow directly calls the large model without skipping the retrieval step.
How to Confirm Successful Configuration
- Test a single port financial report document, check whether the throughput data returned by the model includes the corresponding exclusive unit, and verify that the field mapping takes effect.
- Upload an extremely long annual port financial report, observe the time consumed by the model processing process, and adjust the
requestTimeoutparameter to match the actual processing duration. - Trigger a workflow test with an empty knowledge base, confirm that the system skips the retrieval step and directly calls the large model, with no abnormal errors.
- Check the API call log, confirm that the request address includes the
/v1path, the return status code is 200, there are no format errors, and the deployed version meets the requirements of v4.8.21-fix or higher.
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.