What the Data for This Category Looks Like
Marketing content data for general equipment primarily comes from manufacturers’ public product manuals, technical specification documents, industry standard documents, and after-sales operation and maintenance records. The data update rhythm adjusts with new product launches and standard iterations, usually updated quarterly or annually. The page count of individual documents varies widely. It is recommended to count or measure using locally collected samples before confirming a value. Most content is structured text, including fields such as equipment model, rated power, maximum flow rate, external dimensions, applicable media, and maintenance cycle. Most fields are accompanied by standard industrial units such as kW, m³/h, mm, etc.
Constraints Imposed by These Characteristics on Multi-turn Dialogue and Prompt Engineering
The multi-field structured data of general equipment requires multi-turn dialogue to gradually clarify the user's core demand dimensions, avoiding requesting too many parameters at once. Document lengths can be significant, so prompts need to limit the scope of retrieved document fragments to prevent redundant information from interfering with dialogue logic. Standard industrial units attached to fields must be explicitly required in prompts to avoid parameter confusion. There are logical relationships between equipment parameters, so multi-turn dialogue must support gradual verification of parameter matching to ensure generated marketing content aligns with actual performance boundaries of the equipment.
How to Set Configurations
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
maxContext | First 8000–12000 characters | General equipment parameters are closely related; overly long context can introduce irrelevant parameters, so limiting the scope improves dialogue logic accuracy |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Large equipment manuals have significant length, so sufficient time is needed for structured splitting and field extraction |
UPLOAD_FILE_MAX_SIZE | 500 MB | General equipment product manuals and industry standard documents are often uploaded in batches; this value covers most bulk scenarios |
Recall count | Top 3–5 results | General equipment has concentrated parameter dimensions; a small number of retrievals can cover core needs and avoid redundant information |
Similarity threshold | 0.75–0.85 | Achieve precise matching of equipment models and parameters, avoiding interference from low-relevance documents in dialogue |
Rerank result count | Top 2 results | Focus on core parameter-related content and simplify information input for multi-turn dialogue |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require specific analysis, and it is recommended to test using locally collected samples before confirming final values.
Three Common Mistakes
- Parsing results are empty after uploading general equipment product manuals. This occurs because structured parsing rules for industrial documents have not been configured. Most parameter fields of general equipment use standardized formats, so valid content cannot be automatically extracted without specifying rules.
- Parameter unit confusion occurs during multi-turn dialogue. This happens because the prompt does not explicitly require retaining original industrial units, and the model may arbitrarily convert units leading to parameter matching discrepancies.
- Application internal call records are not displayed in the conversation details page. This is because the full-link conversation log switch has not been enabled. Parameter verification for general equipment marketing conversations relies on log troubleshooting, so parameter matching errors cannot be located without enabling this switch.
How to Verify Successful Configuration
- Upload a standard general equipment product manual and check if core fields such as equipment model and rated power are extracted in the parsing results.
- Initiate a test conversation involving multiple associated parameters, such as "Recommend a 10kW flow pump suitable for conveying clean water", and check if the reply links to parameter matching logic.
- Enter the conversation details page and confirm that complete context calls, document retrievals, and parameter verification records are displayed.
- Adjust the similarity threshold, initiate a repeated query, and check if retrieved documents match accurately as the threshold changes.
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.