What the data for this category looks like
Data is primarily sourced from drilling logs, reserve assessment reports, environmental impact assessment approval files, and approval registration ledgers for oil and gas exploration projects. Update frequency is adjusted based on project progress. New or revised entries are added when new drilling is completed or reserve data is updated. Most documents are multi-chapter structured files, with dedicated fields including well number, formation depth, recoverable reserves, and approval document number. Units mostly use industry-standard oil and gas measurement methods such as meters, cubic meters, and tons.
Constraints on Multi-turn Dialogue and Prompt Engineering
There are numerous dedicated fields with strong professional specificity. Multi-turn dialogue must clearly distinguish contextual connections between fields such as well numbers and reserve parameters, to prevent the large language model from confusing references. Individual files or declaration materials have lengthy content. The context length of multi-turn dialogue must be limited to a reasonable range to avoid exceeding the model's processing limit. Industry terms have dedicated abbreviations. Prompt templates must include industry term specifications upfront, to ensure the large language model accurately understands professional expressions. Data update frequency is not fixed. The multi-turn dialogue data source must support quickly switching to the latest version of files using the session identifier, to avoid calling outdated information.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Maximum context length | 8000–12000 characters | Individual oil and gas files have lengthy content. Sufficient context must be retained to connect professional fields across multiple turn questions, and this aligns with the model processing limit of FastGPT v4.17.0 |
variables variable binding | Bind dedicated fields such as well number and approval document number | Helps the large language model accurately locate core information for the corresponding file, and prevents cross-session confusion of review data from different projects |
chatId session isolation setting | Isolate sessions by project number | Multiple oil and gas exploration projects run in parallel. Isolating sessions prevents cross-use of file data across different projects, and complies with FastGPT v4.17.0 session management specifications |
messages historical message truncation threshold | Retain the most recent 20 dialogue messages | Excessively long history consumes model processing space. 20 messages covers the context requirements of conventional multi-turn review workflows |
| Timeout setting | 600 seconds | Loading file data and running model inference take significant time. This prevents interruptions to the review process due to timeout |
| Prompt template preamble | Include oil and gas industry file review term specifications | Unify the large language model's understanding standards for professional expressions, and reduce reference errors |
Three Common Configuration Mistakes
- Symptom: A connection error is prompted after submitting a review request using a Qianwen large language model, and recovery fails after enabling a network proxy. Cause: The network proxy binding parameter for the session is not configured correctly, or the
messageshistory is too long, causing the request body to exceed the interface limit. - Symptom: The dialogue icon does not update as required, and custom settings cannot be saved. Cause: The custom icon parameter is not bound in the
variablesvariables, or the configuration item is not associated with the correspondingchatIdsession identifier. - Symptom: File images returned by the knowledge base cannot be displayed in the dialogue, and the prompt engineering does not take effect. Cause: The prompt template does not explicitly require the large language model to convert image links into displayable formats, and the image pending verification field is not bound in
variables.
How to Verify Configuration Completion
- Initiate a single-turn query, enter a specific well number, and verify that the file information returned by the large language model matches the dedicated data for that well number, to confirm that the
variablesbinding is active. - Initiate more than 5 consecutive professional queries, verify that the dialogue context retains previous field references, to confirm that the
messagestruncation threshold setting is reasonable. - Simulate a parallel multi-project scenario, create multiple
chatIdsessions, verify that file data from different sessions is not displayed crosswise, to confirm that the session isolation configuration is active. - Trigger a timeout scenario, submit a request after waiting longer than the preset duration, and verify that the system returns a corresponding prompt or completes inference normally per the configuration, to confirm that the timeout setting is active.
The values provided are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.