Base Models¶

Fundamental dataclasses used by all processors and API routes.

BaseResponse¶

Base class for all API responses with standardized format.

Fields¶

Field	Type	Description
`status`	`ProcessingStatus`	Status of the processing (SUCCESS, ERROR, PENDING)
`request`	`RequestInfo`	Information about the request
`process`	`Optional[ProcessInfo]`	Information about the processing process
`error`	`Optional[ErrorInfo]`	Error information (if status is ERROR)
`data`	`Any`	Processor-specific data

Example¶

from src.core.models.base import BaseResponse, RequestInfo, ProcessInfo
from src.core.models.enums import ProcessingStatus

response = BaseResponse(
    status=ProcessingStatus.SUCCESS,
    request=RequestInfo(
        processor="audio",
        timestamp="2024-01-01T00:00:00Z"
    ),
    process=ProcessInfo(
        id="process-123",
        main_processor="audio",
        started="2024-01-01T00:00:00Z"
    ),
    data={"transcription": "..."}
)

ErrorInfo¶

Structured error information for API responses.

Fields¶

Field	Type	Description
`code`	`str`	Error code identifier
`message`	`str`	Human-readable error message
`details`	`Dict[str, Any]`	Additional error details

Example¶

from src.core.models.base import ErrorInfo

error = ErrorInfo(
    code="INVALID_FORMAT",
    message="The format 'xyz' is not supported",
    details={"supported_formats": ["mp3", "wav"]}
)

RequestInfo¶

Information about a processing request.

Fields¶

Field	Type	Description
`processor`	`str`	Name of the processor
`timestamp`	`str`	ISO 8601 timestamp of the request
`parameters`	`Dict[str, Any]`	Request parameters

ProcessInfo¶

Information about a processing process, including LLM tracking.

Fields¶

Field	Type	Description
`id`	`str`	Unique process identifier
`main_processor`	`str`	Name of the main processor
`started`	`str`	ISO 8601 timestamp when processing started
`sub_processors`	`List[str]`	List of sub-processors used
`completed`	`Optional[str]`	ISO 8601 timestamp when processing completed
`duration`	`Optional[float]`	Processing duration in milliseconds
`llm_info`	`Optional[LLMInfo]`	LLM usage tracking information
`is_from_cache`	`bool`	Whether result was loaded from cache
`cache_key`	`Optional[str]`	Cache key used

Example¶

from src.core.models.base import ProcessInfo
from src.core.models.llm import LLMInfo, LLMRequest

process_info = ProcessInfo(
    id="process-123",
    main_processor="audio",
    started="2024-01-01T00:00:00Z",
    completed="2024-01-01T00:05:00Z",
    duration=300000.0,
    llm_info=LLMInfo(requests=[
        LLMRequest(
            model="whisper-1",
            purpose="transcription",
            tokens=1500,
            duration=4500.0,
            processor="audio"
        )
    ]),
    is_from_cache=False
)

ProcessingLogger¶

Protocol for logger interface.

Methods¶

debug(message: str, **kwargs: Any) -> None
info(message: str, **kwargs: Any) -> None
warning(message: str, **kwargs: Any) -> None
error(message: str, **kwargs: Any) -> None