What the data for this category looks like
Data sources for oil and gas extraction financial reports include domestic and overseas securities exchange disclosure platforms, official websites of industry regulators, and official corporate investor relations pages. Update cycles fall into two categories: fixed schedules and event triggers. Regular reports are disclosed quarterly and annually on a fixed basis. Temporary announcements such as major exploration discoveries or production fluctuation alerts are released alongside relevant events. Document structures typically include sections for operating performance, exploration and development, reserve evaluation, and more. Core fields cover oil and gas production, unit production costs, exploration capital expenditures, proven reserves, and others. Units vary by the disclosing entity’s region, with imperial barrels, cubic meters, metric tons, and other standards in use. Some fields require cross-region unit conversion.
What constraints these characteristics impose on model access and configuration
Multi-source heterogeneous data sources require model access to support parsing multiple formats including structured tables, unstructured PDFs, and plain text. Parsing parameters adapted to multiple formats must be configured. Regional unit differences require configuring field normalization mapping rules to avoid analysis errors caused by inconsistent units. Mixed update cycles of fixed schedules and event triggers require configuring both scheduled pull and event callback access nodes to ensure data timeliness and integrity. High density of domain-specific terminology in the oil and gas sector requires configuring custom vocabularies to enhance the semantic recognition capability of embedding models, improving retrieval and analysis accuracy.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
Chunk size | 800–1200 characters | Oil and gas financial reports contain long, specialized descriptions. Excessively long segments lose contextual connections, while excessively short segments disrupt the integrity of specialized terminology |
Similarity threshold | 0.75–0.85 | Semantic similarity of oil and gas specialized terminology is high. A higher threshold is needed to filter low-relevance retrieval results |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Parsing large exploration reports takes significant time. Extending the timeout period prevents task interruptions |
Recall count | Top 8 results | Relevant retrieval results for oil and gas financial reports need to cover multiple dimensions including production, costs, and reserves. Excessive results increase model inference load |
OPENAI_BASE_URL | Fill in the compliant proxy address based on actual deployment | Adapt to model access requirements across different regions, avoiding restrictions on interface calls |
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 individual analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Configuration Errors
- Symptom: When publishing a workflow via API call, no interactive interface for user selection or form input pops up, and expected input fields are missing from the returned results. Cause: The "Receive external form parameters" option was not enabled in the workflow's API release configuration, preventing API requests from passing parameters required for interaction.
- Symptom: An incorrect port number is entered when configuring
OPENAI_BASE_URL, but model calls still complete normally. Cause: Some proxy services do not strictly validate port legitimacy, or have a default port fallback matching logic that does not trigger a connection failure error. - Symptom: Semantic retrieval returns results with universally high similarity scores, and the issue persists after switching embedding models. Cause: No custom embedding vocabulary was configured for oil and gas extraction domain-specific terminology, causing the model to fail to distinguish highly similar specialized concepts, leading to overestimated semantic matching scores for retrieval.
How to Confirm Successful Configuration
- Upload a PDF of an oil and gas extraction company’s financial report, check if the parsed text fully extracts core fields including exploration and development, production, and costs, and verify the match between the parsed results and the original document.
- Submit a semantic retrieval request with an oil and gas specialized query term, check if the relevance of returned results meets business requirements, and adjust the similarity threshold or retrieval count to a reasonable range.
- Configure a scheduled pull task, verify whether the latest financial report data is automatically pulled at the specified time, and confirm that the task trigger logic works correctly.
- Call the API interface with preset form parameters, check if the workflow can correctly receive and use the passed parameters to complete inference, and confirm that the interactive configuration is effective.
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.