The complete OpenAI chat completion request parameters.
Contains the full request body including messages, model selection, temperature settings, and streaming configuration that will be sent to OpenAI's API. This streaming-enabled request allows real-time processing of AI responses for improved user experience and progressive output generation.
Timestamp when the event was created.
ISO 8601 formatted date-time string indicating when this event was emitted by the system. This timestamp is crucial for event ordering, performance analysis, and debugging the agent workflow execution timeline.
Format: "YYYY-MM-DDTHH:mm:ss.sssZ" (e.g., "2024-01-15T14:30:45.123Z")
A unique identifier for the event.
OptionaloptionsOptional request configuration for the OpenAI API call.
Includes additional settings such as timeout configurations, retry policies, and custom headers that control how the request is executed. These options ensure reliable AI interactions even under varying network conditions or API availability scenarios.
The origin point that triggered this AI request.
Identifies which specific agent operation initiated this AI request, such as "analyzeWrite", "prismaSchemas", or "testCorrect". This source tracking enables precise attribution of AI usage to specific workflow steps, facilitating cost allocation and performance analysis per operation.
Unique identifier for the event type.
A literal string that discriminates between different event types in the AutoBE system. This field enables TypeScript's discriminated union feature, allowing type-safe event handling through switch statements or conditional checks.
Examples: "analyzeWrite", "prismaSchemas", "interfaceOperations", "testScenarios"
Event emitted when sending a request to the AI vendor (OpenAI).
This event represents the initiation of an AI processing request from any agent in the AutoBE system. It captures the exact moment when a specific operation (identified by the source) requires AI assistance, such as generating code, reviewing schemas, or creating specifications.
The event includes the complete request payload that will be sent to OpenAI's API, enabling comprehensive tracking of AI interactions. This allows for monitoring which agent operations are actively consuming AI resources, debugging prompt effectiveness, and analyzing the flow of AI requests throughout the backend generation pipeline.
Author
Samchon