What the Data for This Category Looks Like
Data for water treatment intelligent due diligence reports primarily comes from real-time monitoring systems of water utility operators, operation logs of water treatment plants, environmental impact assessment (EIA) filing documents, and laboratory reports from third-party testing institutions. Two update cadences apply: real-time monitoring parameters are updated minute-by-minute, while logs and filing documents are updated on a fixed daily or weekly schedule. A single report document typically includes modules such as influent water quality parameters, treatment process operation parameters, effluent compliance verification data, equipment operation duration, and periodic maintenance records. Fields include pH value, chemical oxygen demand (COD), ammonia nitrogen concentration, treatment flow rate, total equipment operating hours, and more, with corresponding units: dimensionless, mg/L, mg/L, m³/h, and hours respectively.
Constraints Imposed on Multi-turn Dialogue and Prompt Engineering by These Data Characteristics
The data characteristics of water treatment due diligence reports impose multiple constraints on multi-turn dialogue and prompt configuration. The mixed presence of real-time and archived data requires multi-turn dialogue to clearly distinguish whether the current query relates to real-time monitoring data or historical logs, and prompts must limit context to only retain associations with the same type of data. The multi-field, multi-unit parameter system requires prompts to mandate that corresponding units are included in queries to avoid confusion between different indicators. The fixed document module structure requires multi-turn dialogue to accurately recall data by modules such as influent, treatment, effluent, and equipment, to avoid calling mismatched parameters across modules. Compliance verification requirements require multi-turn dialogue to associate data from at least two modules to complete validation, and conclusions cannot be drawn based solely on a single parameter.
How to Configure the Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Water treatment due diligence reports contain multi-module data, and complete parameter context for 3 or more rounds of queries must be retained to avoid losing indicator associations across rounds |
RECALL_TOP_N | Top 3–5 entries | Core analysis for water treatment due diligence relies on only 3-5 key water quality indicators; excessive recall will introduce non-core data that interferes with accurate judgment |
SIMILARITY_THRESHOLD | 0.75–0.85 | Water treatment parameters are strongly bound to their indicators and units, so a high matching threshold is required to avoid recalling incorrect indicators or unit types |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | A complete single water treatment due diligence report contains multiple pages of monitoring logs and operation records, so sufficient time is needed to complete full document parsing |
CHUNK_SIZE | 800–1200 characters | Segmenting water treatment data by module facilitates associated queries, and segment length is matched to the parameter count and document layout of a single module |
PROMPT_TEMPLATE | Mandate matching units and recall data by module classification | Water treatment parameters have a one-to-one correspondence with their units, so prompts must explicitly require returned results to match the queried units and indicator modules |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require on-site analysis, and it is recommended to test on your own samples before finalizing settings.
Three Common Configuration Mistakes
- Phenomenon: Unintentionally introducing knowledge base content related to water treatment due diligence reports when calling the multi-turn dialogue interface. Cause: The association switch for irrelevant knowledge bases is not disabled in dialogue configuration, or prompts do not explicitly limit usage to current interaction context data.
- Phenomenon: A
408 Request Timeouterror code is returned during dialogue. Cause: The setPARSE_FILE_TIMEOUT_SECONDSparameter value is shorter than the actual time required for document parsing, causing queries to trigger before full document loading is complete. - Phenomenon: After selecting a general-purpose dialogue model, the model fails to accurately identify unit differences between water treatment parameters. Cause: A text understanding model adapted for multi-unit parameter scenarios is not selected, or unit matching is not mandated in prompts.
How to Verify Proper Configuration
- Single-indicator queries are initiated, returned results are verified to include the corresponding unit, and
SIMILARITY_THRESHOLDis adjusted until matching results meet expectations. - Cross-round associated queries are initiated, context is verified to retain indicator parameters from the previous round, and
maxContextis adjusted until context associations are correct. - Complete water treatment due diligence reports are uploaded, parsing duration is verified to be less than the set
PARSE_FILE_TIMEOUT_SECONDS, and the timeout parameter is adjusted to match actual parsing duration. - Multi-module combined queries are initiated, recalled parameters are verified to originate from the corresponding modules, and
RECALL_TOP_Nis adjusted until only core indicator data is returned.
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.