What Data for This Category Looks Like
Gas industry marketing content data mainly comes from internal enterprise marketing management systems, user gas usage profile databases, and offline promotion ledgers. Data update rhythms fall into two categories: marketing copy templates are updated quarterly or per campaign node, while user behavior data is synced daily. Each individual marketing document typically includes fields such as promotion region, target user age group, copy word count, and delivery channel. Units include people, square meters, yuan, and similar metrics. Document structure mostly combines structured tables and explanatory text. Some attachments containing user gas usage data use CSV format.
What Constraints Do These Characteristics Impose on Model Access and Configuration?
The structured user and regional data characteristics of the gas industry require clear field mapping rules during configuration, to map dedicated fields to model input parameters. Data with different update rhythms requires split synchronization cycle configurations. User behavior data is set to daily incremental synchronization, while marketing copy templates are set to quarterly full updates. For CSV-format gas usage data attachments, parsing parameters must be adjusted to fit table structures and avoid field misalignment. Context window parameters must also be configured based on copy lengths for different delivery channels, to adapt to long-text marketing content generation.
How to Set Configuration Values
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Gas marketing copy usually includes region descriptions and user profile-adapted content, so it needs to accommodate long-text input requirements |
field_mapping | Map "promotion region" to the {region} variable in prompt, map "target user age group" to the {age_group} variable | Gas marketing content requires precise matching of region and user characteristics, so fixed field correspondence is needed |
sync_interval | User data: 86400 seconds, marketing copy: 7776000 seconds | User behavior data requires timeliness, marketing copy update cycle is quarterly |
PARSE_CSV_HEADER_MODE | Automatically identify first row as header | Gas usage data attachments mostly use standard CSV format; automatic identification avoids field misalignment |
retrieval_top_k | Top 3 entries | Gas marketing content needs to match precise region and user data; too many retrievals will introduce irrelevant information |
prompt_template | Generate tailored community promotion copy adapted to the {region} area and {age_group} user group | Bind dedicated fields to generate customized marketing content |
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 case-by-case analysis. Testing on internal samples is recommended before finalizing settings.
Three Common Misconfigurations
- Phenomenon: After configuring
field_mapping, the copy generated by the model does not mention the target region, and the field is empty. Cause: The gas-specific "promotion region" field is not correctly bound to the prompt variable, so the model cannot obtain region information. - Phenomenon: When calling the debugging tool, the generated reply ends with an extra 0. Cause: The model's extra output switch is not turned off, or the configured
max_tokensparameter exceeds actual requirements, leading the model to generate redundant content. - Phenomenon: After uploading CSV-format gas usage data, a large number of invalid empty fields appear in the parsing result. Cause:
PARSE_CSV_HEADER_MODEis not configured to automatically identify headers, so data rows are mistakenly identified as headers, introducing invalid fields.
How to Confirm Successful Configuration
- Navigate to the knowledge base configuration page, review the field mapping list to confirm that gas-specific fields are correctly bound to prompt variables.
- Upload a single gas marketing copy and CSV-format gas usage data, verify that parsed result fields match the original document.
- Initiate a test call to check whether generated marketing copy includes content adapted to the target region and user group.
- Review the data synchronization log to confirm that update cycles for user data and marketing copy match preset configurations.
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.