What the Data for This Category Looks Like
Data for logistics financial reports comes from two primary sources. Publicly disclosed annual and quarterly regular reports of listed logistics enterprises. Industry operation reference data released by industry associations. Data updates follow a fixed quarterly and annual cycle. No temporary real-time update channels exist. Document structures typically include core fields. These fields cover revenue breakdown (express freight, delivery, supply chain segments, etc.), operating costs (fuel, labor, yard rental, etc.), freight volume, revenue per shipment, cost per shipment, and turnover volume. Field units include 100 million yuan, pieces, ton-kilometers, yuan per shipment, and other standard logistics finance units.
Constraints for Multi-turn Conversation and Prompting
The fixed update rhythm imposes a key constraint. Unreported real-time data cannot be requested during multi-turn conversations. The data disclosure cycle must be clearly communicated to users. The long text structure of reports requires retaining sufficient context during multi-turn conversations. Split parsing can lose cross-field associations, so context must be preserved. The variety of professional fields and units requires pre-calibrating unit rules in prompts. This prevents confusion between the statistical calibers of freight volume and turnover volume, revenue per shipment and cost per shipment.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Single parsed logistics financial report text is relatively long. Context for multi-turn conversations must be retained to link cross-field information such as freight volume and costs |
UPLOAD_FILE_MAX_SIZE | 500 MB | Complete annual financial report PDFs often exceed 200 MB. Supporting large file uploads avoids parsing interruptions |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Long financial report parsing requires significant preprocessing time. This prevents timeout termination of the parsing process |
recall_top_k | Top 6–8 entries | Logistics financial reports have many core fields. Sufficient associated data must be recalled to support multi-turn follow-up questions |
similarity_threshold | 0.75–0.85 | Logistics industry fields are highly professional. A high similarity threshold is needed to filter irrelevant recalled content |
stream_response | Enabled | Long responses during multi-turn conversations require streaming output to improve interaction smoothness |
The parameter values provided on this page are common recommended starting points for configuration setup. Actual values are affected by material format, data volume and business rules, and specific issues require case-by-case analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Mistakes
- After enabling streaming output for the conversation API, links cannot jump to new pages and only overwrite the current page. The cause is that front-end route jump logic is not configured, and only the default streaming output rendering method is used.
- In version v4.8.10, the conversation log details do not match the actual response content. The cause is that persistent storage of context cache is not enabled, causing the log to read the initial context instead of the complete conversation chain.
- It is impossible to link the change trends of freight volume and cost per shipment during multi-turn conversations. The cause is that the prompt does not explicitly require retaining context association for historical fields, and only generates responses for individual single questions.
How to Confirm Configuration Is Correct
- Upload a complete logistics financial report PDF, check if the parsed text fields include core fields such as freight volume and cost per shipment, to confirm that the parsing configuration takes effect.
- Initiate a multi-turn conversation, sequentially ask "Year-over-year change in this quarter's freight volume" and "Corresponding change in cost per shipment", check if the response links the context of the two questions, to confirm that the context window configuration is reasonable.
- Call the conversation API to initiate a streaming output request, check if the front-end rendered response supports custom jump logic, to confirm that the streaming output configuration is correct.
- View the conversation log in version v4.8.10, check if the log details match the latest response content, to confirm that the context cache configuration is correct.
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.