What data looks like for this category
Energy storage marketing data for financial customers comes from product specifications, grid connection test reports, operation and maintenance logs, project investment return reports, and marketing material documents. Update cadences vary: product specifications are updated with model iterations, operation and maintenance logs are updated daily or in real time, project investment return reports are updated with project progress, and marketing materials are adjusted as needed. Most documents use structured parameter tables paired with technical descriptions and revenue analysis text. Fields include rated charge-discharge power (unit: kW), cycle life (unit: times), energy storage density (unit: Wh/kg), grid connection voltage (unit: V), payback period (unit: years), and other items. Each field is tied to a clear unit.
Constraints for multi-turn dialogue and prompt engineering
Parameters for energy storage products are tied to clear units, and include financial investment indicators. Multi-turn dialogue must retain context tags to avoid mixing parameters for residential, commercial and industrial, and grid-side energy storage, as well as revenue indicators for different financial scenarios. Long documents such as grid connection reports and investment analysis reports contain large amounts of content. Context length must be limited to prevent model overflow. Marketing scenarios vary widely. Multi-turn dialogue must gradually guide users to clarify their needs, such as whether they are targeting individual investors or institutional investors, to avoid incorrect parameter calls. Data update frequencies differ greatly. Prompt engineering must explicitly specify calling the latest data sources to prevent use of expired parameters or revenue data.
Configuration Settings
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Energy storage-related documents mostly use structured parameters paired with long technical descriptions and revenue analysis. Excessively long context can cause the model to confuse parameter units and scenarios |
tool_call_max_rounds | 3–5 rounds | Energy storage marketing requires gradual confirmation of user scenarios, parameter requirements, and investment goals. Multi-round tool calls help avoid missing key information |
RECALL_TOP_N | Top 6–8 entries | Energy storage parameters and financial indicator fields are numerous. Too many recalled entries cause context redundancy, while too few result in missing key units or revenue data |
PROMPT_TEMPLATE | First confirm user scenarios and requirements, then match corresponding energy storage parameters and financial indicators, and clearly mark units | Adapts to the characteristics of multiple energy storage scenarios and parameter-unit binding, improving the accuracy of marketing content generation |
PARSE_FILE_TIMEOUT_SECONDS | 120 seconds | Energy storage grid connection reports, operation and maintenance logs, and investment analysis reports have large file sizes, requiring extended parsing timeout periods |
empty_response_handle | Trigger fallback prompt | Adapts to scenarios where the model returns empty results, avoiding direct dialogue interruption |
The parameter values provided on this page are general recommendations for starting point configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Mistakes
- Blank return after chart tool call. Phenomenon: A chart tool is called to generate energy storage parameter or revenue comparison charts, but no content appears in the front-end display area. Cause: The prompt does not explicitly specify the energy storage parameter fields and corresponding units to call. The dataset field format generated by the model does not meet tool requirements.
- AI dialogue node returns empty content or an error and stops directly. Phenomenon: The dialogue node returns an empty string or error text, and the preset error prompt process is not triggered. Cause: The
empty_response_handleparameter is not configured, and no fallback logic is set for empty results or errors. - Dialogue records cannot be deleted. Phenomenon: A POST request is sent to delete dialogue records, but a 400 or 500 status code is returned, and the records remain. Cause: Permission verification parameters for dialogue deletion are not configured, resulting in insufficient interface call permissions.
How to Verify Proper Configuration
- Upload a single energy storage product specification or investment return report, initiate multi-turn queries, and verify that the parameters and indicators returned by the model match the fields and units in the document.
- Configure chart tool call parameters, initiate parameter or revenue comparison requests, and verify that the generated charts include expected energy storage-related data and financial indicators.
- Simulate a scenario where the model returns empty results, and confirm that the system triggers the preset error handling process and returns clear prompt information.
- Send a dialogue deletion request, and verify the interface return status and actual deletion result of the dialogue records.
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.