What the data for this category looks like
Oilfield service engineering yield rate and market data is primarily sourced from internal enterprise production scheduling systems, ERP accounting modules, and public industry block quotation databases. Data syncs complete daily at midnight for full previous day's data. The document structure follows a standardized format, with each record corresponding to a single oilfield service project. Fields include project unique identifier, service type, operation block, operation cycle, direct revenue amount, direct cost amount, and additional relevant fields. All field units adhere to general metrology standards: operation cycle is measured in days, revenue and cost are measured in yuan, and no percentage-based statistical fields are included.
What constraints do these characteristics impose on multi-turn dialogue and prompting?
The structured, multi-entry nature of oilfield service engineering data requires multi-turn dialogue to support precise filtering by project identifier, block, or service type. Prompts must explicitly define query scopes to prevent the model from generating unsubstantiated generic responses. The daily update rhythm requires prompts to specify the data time range explicitly, to avoid the model using expired historical data. The detailed multi-field structure requires dialogue contexts to retain sufficient historical filtering conditions, to prevent query logic from being lost due to context truncation. Additionally, daily reports contain a large number of projects, so the number of recalled results must be limited to avoid excessive token consumption or information redundancy.
How to configure the settings
| Configuration Key | Recommended Setting | Rationale |
|---|---|---|
maxContext | 12000–15000 characters | Multi-turn dialogue for oilfield service engineering needs to retain project filtering conditions and historical query logic, to avoid losing critical information due to context truncation |
Recall count | Top 8–12 entries | Daily reports contain dozens to hundreds of oilfield service projects. Too many recalled results increase token consumption, while too few miss target projects |
Similarity threshold | 0.75–0.85 | Structured field matching requires high precision to avoid including unrelated projects in responses |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Oilfield service engineering data files contain detailed multi-field information, so parsing takes longer than generic documents |
PROMPT_TEMPLATE | Fixed prefix: "Please respond based on the same-day structured oilfield service engineering yield rate and market data. Filter results according to the project ID, block, or service type specified by the user, and clearly mark the referenced field information." | Explicitly define the data scope and response format to prevent the model from generating unsubstantiated content |
Rerank result count | Top 4–6 entries | Reranked results need to retain the most relevant project data to avoid redundant information interfering with responses |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require specific analysis, and it is recommended to test on your own samples before finalizing settings.
Three common configuration errors
- The symptom is an API Key invalid error during post-configuration calls, or only two entries appearing in the global variable list. The cause is mistakenly using an application-specific API Key as a global universal key, without distinguishing the usage scenarios of the two types of API Keys.
- The symptom is a
Cannot read properties of null (reading 'q')error triggered during dialogue. The cause is insufficient context length configuration for multi-turn dialogue, leading to null value fields in the historical message queue. - The symptom is being unable to configure independent upload entrances for different types of oilfield service data in the same scenario, and only being able to receive files of a single format. The cause is incorrect configuration of multi-file upload trigger rules, without dividing upload entrances by data type.
How to confirm configuration is complete
- Enter the application configuration page, verify that the
maxContextparameter value matches the context requirements of the current scenario. Initiate multiple consecutive queries to confirm that context is not truncated. - Upload a standard oilfield service engineering data file, verify that the parsing process completes normally, and confirm that parsing time does not exceed the configured
PARSE_FILE_TIMEOUT_SECONDSthreshold. - Initiate a query with explicit filtering conditions, verify that the number of recalled results matches the setting of
Recall count, and confirm that results follow the expected filtering logic. - Test upload requests for different types of data, confirm that corresponding data parsing and import processes are triggered according to preset rules.
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.