The original OpenAI chat completion request parameters.
Contains the complete request body that was sent to OpenAI's API, providing context for the response. This allows correlation between prompts and outputs, facilitating prompt engineering, debugging, and quality analysis of AI interactions.
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.
Aggregates the streaming response into a complete chat completion.
Utility method that consumes the entire stream and returns a unified response object. This is useful when batch processing is preferred over streaming, or when the complete response is needed for validation, storage, or further processing.
Promise resolving to the complete chat completion response
OptionaloptionsOptional request configuration used for the OpenAI API call.
Includes the settings that were applied during the request execution, such as timeout configurations and retry policies. This information helps in debugging and understanding the conditions under which the response was generated.
The origin point that triggered this AI response.
Identifies which specific agent operation initiated the AI request that resulted in this response. This source tracking maintains the connection between requests and responses, enabling end-to-end monitoring of AI interactions and performance analysis per operation type.
Async generator providing streaming response chunks from OpenAI.
Yields chat completion chunks as they are received from the AI vendor, enabling real-time processing of AI-generated content. Each chunk contains partial response data that can be immediately displayed or processed, improving perceived performance and user experience.
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 receiving a response from the AI vendor (OpenAI).
This event represents the AI vendor's response to a processing request from any agent in the AutoBE system. It captures both the original request context and the streaming response, enabling real-time processing and monitoring of AI-generated content as it's being produced.
The event provides access to the streaming response chunks, allowing consumers to process AI output progressively for better user experience. It also includes a utility method to aggregate the complete response when streaming is complete, supporting both real-time and batch processing scenarios.
This event is crucial for tracking AI response generation, monitoring completion rates, and analyzing the quality and characteristics of AI-generated content across different agent operations.
Author
Samchon