What the data for this category looks like
Water treatment investment research data sources include real-time sensor data from water monitoring stations, industry process manuals, national standard compliance documents, operation logs, and environmental impact assessment reports. Real-time monitoring data is updated from second to hourly level. Process manuals and standard documents are updated quarterly or annually.
Document structures include structured monitoring data tables (including monitoring points, time, parameter values), long-text process descriptions, compliance clause documents, and equipment operation records. Fields and units include COD (mg/L), turbidity (NTU), flow rate (m³/h), pH (dimensionless), equipment operating pressure (kPa), and other multi-dimensional standardized parameters.
What constraints these characteristics impose on multi-turn dialogue and prompt engineering
High-frequency updates of real-time monitoring data require multi-turn dialogue to retain recent context, to avoid using expired data that disrupts investment research judgments. Mixed structured data and long-text documents require prompt engineering to distinguish between different types of knowledge base content, to avoid confusing parameters and descriptions.
Multi-dimensional fields and units require prompt engineering to enforce consistent units in responses, to prevent mismatched parameter units. The need for comparison of continuous monitoring data requires multi-turn dialogue to retain sufficient historical context to support trend analysis.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
maxContext | Last 8 turns of dialogue context | Water treatment investment research often involves comparison of continuous monitoring data. Excessive old context will interfere with current parameter judgment |
recall_top_k | Top 6-8 recall results | Water treatment data includes multi-dimensional monitoring parameters. Excessive recall will cause context overload |
similarity_threshold | 0.75-0.85 | Water treatment monitoring data has relatively high feature similarity. Too low a threshold will introduce irrelevant data, while too high a threshold will miss valid results |
prompt_template | Must include "Responses must indicate the corresponding parameter units, and only use water treatment industry data from 2024 or later in the knowledge base" | Avoid unit errors and outdated information, and comply with investment research compliance requirements |
context_refresh_interval | Refresh real-time monitoring data context every 15 minutes | Real-time monitoring data has a high update frequency, and old data will affect the accuracy of investment research |
parse_chunk_size | 800-1200 characters | Water treatment process documents include long paragraphs and tables. Too large chunks will lose context, while too small chunks will break parameter associations |
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, and it is recommended to test on your own samples before finalizing settings.
Three Common Mistakes
- The dialogue interface cannot display process flowcharts or monitoring data charts from the knowledge base. Cause: Non-text file parsing configuration is not enabled, so the system cannot load and render associated visual resources.
- The model responds with content outside the scope of the knowledge base, without citing sources. Cause: The prompt template does not clearly limit the use of only recalled knowledge base content, and no mandatory verification rules are added.
- When only the most recent 1 turn of context is called in multi-turn dialogue, it is impossible to associate changes in water quality monitoring data across time periods. Cause: The
maxContextparameter is not adjusted according to the continuity of water treatment data, resulting in missing key comparison information in the context.
How to Confirm Proper Configuration
- Initiate a multi-turn dialogue involving comparison of continuous water quality parameters, check whether the response indicates the standard units of the corresponding parameters and does not introduce content outside the knowledge base.
- Upload water treatment process flowcharts and monitoring data tables, confirm that the dialogue interface can normally display associated visual resources.
- Initiate the same query in both the dialogue area and the simple application workspace, verify that the number and content of recalled knowledge base entries are consistent.
- Modify the
maxContextparameter to different values, test whether the multi-turn dialogue can correctly associate changes in monitoring data across time periods.
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.