What the data for this category looks like
Water industry research report data comes from three main sources: securities firm public utility industry research reports, publicly available operational data from urban water industry associations, and regular disclosure documents of listed water companies. Securities firm research reports update on the quarterly and semi-annual report release schedules. Industry operational data updates monthly or quarterly. Document structure includes research report title, publishing entity, release time, core operational data entries, business analysis content, and policy association notes. Fields include water treatment scale, total pipeline length, sewage treatment volume, project investment amount, and others. Corresponding units are ten thousand cubic meters per day, kilometers, ten thousand tons, and ten thousand yuan.
What constraints these characteristics impose on multi-turn dialogue and prompt engineering
Water industry research reports have concrete indicator attributes. Multi-turn dialogue must accurately anchor specific fields like water supply scale and pipeline length that users mention, to avoid information bias from generalized matching. High-frequency data updates require dialogue context to automatically filter expired data. This ensures referenced content timeliness aligns with industry data update cycles. Document structures with multiple policy associations require prompts to preset connection logic between policy orientation and specific project data. This supports cross-module information integration. Diverse unit types require prompts to clearly specify binding rules between indicators and their corresponding units. This prevents responses with mixed measurement dimensions.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
Recall count | Top 10-15 entries | Individual water industry research reports are lengthy. Recall enough relevant paragraphs to cover potential associated indicators for multi-turn queries, while avoiding interference from redundant information |
Similarity threshold | 0.75-0.85 | Water industry indicator fields have high distinctiveness. A threshold that is too low adds irrelevant research report paragraphs. A threshold that is too high may miss associated content in specific niche scenarios |
maxContext | Top 6 rounds of dialogue history | Multi-turn queries for water industry research reports often focus on multiple indicators within a single scenario. 6 rounds of context can cover complete query chains, while avoiding model inference delays caused by overly long context |
Chunk size | 800-1200 characters | Water industry research report indicator paragraphs are mostly compact structured content. This segment length preserves complete indicator-analysis associations, while adapting to model context window limits |
PARSE_FILE_TIMEOUT_SECONDS | 120 seconds | Individual water industry research report documents have large file sizes and contain multiple sets of structured indicator data. Sufficient parsing time is required to complete field extraction and segment processing |
Rerank result count | Top 5 entries | Re-ranking filters the most relevant research report fragments, adapting to the interactive logic where users gradually focus on specific indicators during multi-turn dialogue |
The parameter values provided on this page are conventional recommendations for establishing configuration baselines. Actual values are affected by material format, data volume, and business rules. Specific issues require specific analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Symptom: AI dialogue nodes added to the workflow append their output to the final reply. Cause: Workflow node output filtering rules are not configured, so temporary results from intermediate steps are not truncated.
- Symptom: API calls to the dialogue interface return redundant original research report document titles in results. Cause: Prompts do not specify that only indicator-related content should be returned, or knowledge base recall content filtering fields are not configured.
- Symptom: Multi-turn dialogue returns mixed units for the same indicator. Cause: Prompts do not bind mapping rules between indicators and their corresponding units, causing the model to match incorrect measurement methods.
How to Confirm Configurations Are Set Correctly
- Initiate consecutive queries that include multiple water industry indicators, verify that the reply only contains research report content related to the query, with no redundant intermediate step information.
- Check dialogue logs, confirm that all recalled research report paragraphs were updated within the last 7 days, with no expired data.
- Call the API interface, verify that returned result fields match preset indicator units, with no mixed units.
- Adjust the focus direction of a single query, confirm that multi-turn dialogue can coherently connect query logic for different indicators.
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.