What the data for this category looks like
Gas industry data primarily comes from internal business systems of gas operation enterprises, with four core source types: user gas usage profiles, payment records, maintenance work orders, and marketing activity ledgers. Update schedules vary by data type:
- User basic profiles are synchronized and updated quarterly
- Monthly gas usage is generated daily
- Real-time payment records are updated immediately
- Marketing activity data is adjusted along with activity cycles
Single user data documents include fields such as user ID, account opening address, gas usage type, monthly cumulative gas usage (unit: cubic meters), payment status, and historical activity participation records. Field formats use a mixed structure of structured text and numerical values.
What Constraints Do These Data Characteristics Impose on Multi-turn Dialogues and Prompt Engineering
Gas industry multi-turn dialogue and prompt configuration must match constraints imposed by data characteristics: First, user data is bound to a unique identity identifier. Prompts must explicitly extract the user ID or account opening address provided by the user to avoid confusion across user data. Second, differences in data update rhythms require distinguishing between real-time and offline data sources when calling dialogue tools. Real-time payment records must pull the latest data with each dialogue, while monthly gas usage can be cached for 24 hours. Field units must be mandatory verified in prompts to avoid generating incorrect gas usage or payment amount values. Marketing activity data is adjusted along with cycles, so prompts must limit calls to only currently active activity content and exclude expired activity records.
How to Set Configurations
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Gas user data includes multi-dimensional content such as gas usage profiles, payment records, and activity records. Sufficient context must be retained to avoid truncation of critical information |
similarityTopK | Top 6–8 entries | Gas data fields have relatively high complexity. Too many recalled entries will cause context overload, while too few will fail to cover the complete user profile |
promptTemplate | Fixed template: Extract the identity identifier provided by the user, combine with gas usage data in cubic meters, payment records in yuan, and currently active marketing activities to generate targeted content, only call records within the activity cycle | Clearly constrain data scope, unit verification, and identity matching rules to avoid generating incorrect or expired marketing content |
recallThreshold | 0.75–0.85 | The field similarity of gas user data is relatively high. Low-match redundant content must be filtered to improve dialogue accuracy |
apiKeyIsolation | Enable user-level key isolation | Prevent sharing of dialogue data and call records across different users, which complies with user privacy protection requirements of gas enterprises |
toolCallRetryTimes | 2 times | Gas data calls may fail due to system synchronization delays. Limited retries can improve tool call success rates |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require case-by-case analysis. It is recommended to run tests on relevant samples before finalizing the settings.
Three Common Configuration Mistakes
- Phenomenon: Dialogue answers tested within the platform do not match results returned by API calls. Cause: User-level key isolation configuration is not enabled, or the corresponding user identity parameter is not passed in API requests, causing different call scenarios to use different knowledge base recall datasets.
- Phenomenon: Marketing content generated in multi-turn dialogues references expired gas marketing activities. Cause: The prompt template does not limit calls to only activity data within the current active cycle, causing the model to incorrectly use historical activity records.
- Phenomenon: API calls return empty results or throw a
400 Bad Requesterror. Cause: A reasonable similarity threshold is not set, or the format of the passed user identity identifier does not meet system requirements, causing knowledge base recall failure.
How to Confirm Configurations Are Correctly Set
- Initiate two API calls with an interval of more than 24 hours, verify that gas usage data is updated to the latest version, and confirm that the cache configuration matches the data update rhythm.
- Pass different user identity identifiers to initiate API calls, verify that returned marketing content only corresponds to the user's gas usage data and activity records, and confirm that key isolation configuration is effective.
- Edit the prompt template and trigger a test dialogue, verify that generated content clearly marks the units of gas usage and payment amount, and confirm that template constraints are effective.
- Simulate a scenario of tool call delay, verify that the system initiates retries according to configured retry times, and confirm that tool call parameter configuration is correct.
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.