What the data for this category looks like
Financial scenario oilfield services engineering research report sources include internal oilfield service industry research databases from financial institutions, public industry research materials, and publicly available operational documents related to oil and gas services. Regular research reports are released quarterly, with temporary analysis content updated synchronously when major industry events occur such as new technology implementation or changes in market supply and demand. Each single document usually includes four core modules: industry trend judgment, key project breakdown, cost composition details, and technology iteration progress. Some in-depth research reports include equipment parameter tables and operating process descriptions. Common fields include drilling depth (unit: meter), single-well operating cycle (unit: day), single-well service cost (unit: ten thousand yuan), equipment rated power (unit: kilowatt), and operating volume (unit: well).
What constraints these characteristics impose on multi-turn dialogue and prompting
Single oilfield services engineering research reports in financial scenarios have relatively long lengths and multiple sets of professional numerical fields. This leads to high token usage for single-round recalled context. It is necessary to limit the number of documents recalled in a single pass and the length of single extracted segments to avoid exceeding the model context window. Research reports contain a large number of professional parameters with specific units. The prompt must clearly specify the standard unit corresponding to the field to prevent the model from confusing the meaning of numerical values in different scenarios and affecting the accuracy of financial analysis. Regular research reports are updated quarterly and temporary emergency documents exist. Multi-turn dialogue needs to support dynamic association with the latest updated knowledge base entries, while retaining key identifiers such as project numbers and regions mentioned by users in context management. This facilitates accurate matching of corresponding content during subsequent follow-up questions and meets the needs of financial analysts to gradually decompose industry data. Technical details and cost data in research reports are strongly correlated. Multi-turn dialogue needs to allow users to decompose questions step by step without repeatedly providing initial background information.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Single oilfield services research report has long content, reserve sufficient space to accommodate recalled report fragments and dialogue history |
recallTopK | Top 3–5 entries | Single research report has large content volume, excessive recall will lead to token overflow, while ensuring coverage of core analysis content |
similarityThreshold | 0.72–0.85 | Professional terminology in the oilfield services industry has high recognition, too low a threshold will introduce irrelevant documents, too high a threshold may miss segmented related content |
rerankTopN | Top 2–3 entries | The re-ranking step needs to filter redundant content in the recall results and focus on the most relevant report fragments |
promptTemplate | Match unit instructions according to the question scenario, first reference the report fragment then answer the question | Oilfield services research reports contain multiple sets of professional data with specific units, clarifying units can avoid model ambiguity |
knowledgeBaseSyncInterval | Sync once per hour | Major industry events may quickly update research reports, short interval synchronization ensures the timeliness of knowledge base content |
The parameter values provided on this page are conventional recommendations used as a starting point for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require specific analysis. It is recommended to test on your own samples before finalizing.
Three common mistakes
- Symptom: When calling the dialogue interface, newly created knowledge base cannot be associated, and the error "No bound knowledge base found" is returned. Cause: The
kbIdsparameter is not correctly passed in theparamsfield of the dialogue request, or the parameter format is a string instead of an array type. - Symptom: The recalled report fragments are not correctly embedded in the answer, only general content is generated. Cause: The configuration logic of
promptTemplateandreferenceTemplateis confused, the instruction to reference recalled content is not added in the main prompt, or the output variable ofreferenceTemplateis not correctly inserted into the main prompt. - Symptom: There is a large difference between the results returned by the API call and the online dialogue. When the API is set to
stream=falseanddetail=true, the returned results lack the details of the report reference. Cause: The detailed mode of knowledge base recall is not enabled in the API request, or the value logic of thedetailparameter is not correctly configured, causing the API to not return the complete recalled context.
How to confirm that the configuration is set correctly
- Initiate a single-round test dialogue, ask a question containing oilfield services engineering professional terminology, and check whether the returned result includes the fragment reference of the corresponding research report.
- Initiate multi-round continuous dialogue, successively ask for data of different dimensions of the same project, and check whether the context retains the project number and region information mentioned in the previous round.
- Call the API interface to initiate a test request, and check whether the
kbIdsandrecallDocsfields in the returned result contain valid content. - For the open-source version v4.9.14, view the concurrent request count through the system monitoring interface to verify whether it meets the concurrent upper limit of the current configuration.
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.