12681022279

Committed 08 Jan 2025 11:43PM UTC coverage: 95.11% (+14.6%) from 80.557%

Build # 12681022279

Build Type

Pull #56

github

Specific Base da957e

Committed by

kevdevg

Commit Message

fix: add try catch to pillow images

Pull Request Pull Request #56: feat(huggingface): add support for image-to-image/ text-to-speech

Run Details

155 of 169 new or added lines in 7 files covered. (91.72%)

26 existing lines in 4 files now uncovered.

1770 of 1861 relevant lines covered (95.11%)

3.8 hits per line

Source File
Press 'n' to go to next uncovered line, 'b' for previous

94.59

/scope3ai/tracers/huggingface/speech_to_text.py

import time
from dataclasses import dataclass, asdict
from typing import Any, Callable, Optional, Union

from aiohttp import ClientResponse
from huggingface_hub import (
    AutomaticSpeechRecognitionOutput as _AutomaticSpeechRecognitionOutput,
)
from huggingface_hub import InferenceClient  # type: ignore[import-untyped]
from requests import Response

from scope3ai.api.types import Scope3AIContext, Model, ImpactRow
from scope3ai.api.typesgen import Task
from scope3ai.constants import PROVIDERS
from scope3ai.lib import Scope3AI
from scope3ai.response_interceptor.requests_interceptor import requests_response_capture

PROVIDER = PROVIDERS.HUGGINGFACE_HUB.value


@dataclass
class AutomaticSpeechRecognitionOutput(_AutomaticSpeechRecognitionOutput):
    scope3ai: Optional[Scope3AIContext] = None


def _hugging_face_automatic_recognition_wrapper(
    timer_start: Any,
    model: Any,
    response: Any,
    http_response: Union[ClientResponse, Response],
    args: Any,
    kwargs: Any,
) -> AutomaticSpeechRecognitionOutput:
    if http_response:
        compute_audio_length = http_response.headers.get("x-compute-audio-length")
        compute_time = http_response.headers.get("x-compute-time")
    else:
        compute_audio_length = 0
        compute_time = time.perf_counter() - timer_start

    scope3_row = ImpactRow(
        model=Model(id=model),
        task=Task.text_to_speech,
        input_audio_seconds=int(float(compute_audio_length)),
        request_duration_ms=float(compute_time) * 1000,
        managed_service_id=PROVIDER,
    )

    scope3_ctx = Scope3AI.get_instance().submit_impact(scope3_row)
    result = AutomaticSpeechRecognitionOutput(**asdict(response))
    result.scope3ai = scope3_ctx
    return result


def huggingface_automatic_recognition_output_wrapper(
    wrapped: Callable, instance: InferenceClient, args: Any, kwargs: Any
) -> AutomaticSpeechRecognitionOutput:
    timer_start = time.perf_counter()
    http_response: Response | None = None
    with requests_response_capture() as responses:
        response = wrapped(*args, **kwargs)
        http_responses = responses.get()
        if len(http_responses) > 0:
            http_response = http_responses[-1]
    model = kwargs.get("model") or instance.get_recommended_model(
        "automatic-speech-recognition"
    )
    return _hugging_face_automatic_recognition_wrapper(
        timer_start, model, response, http_response, args, kwargs
    )

1	import time	4✔
2	from dataclasses import dataclass, asdict	4✔
3	from typing import Any, Callable, Optional, Union	4✔
4
5	from aiohttp import ClientResponse	4✔
6	from huggingface_hub import (	4✔
7	AutomaticSpeechRecognitionOutput as _AutomaticSpeechRecognitionOutput,
8	)
9	from huggingface_hub import InferenceClient # type: ignore[import-untyped]	4✔
10	from requests import Response	4✔
11
12	from scope3ai.api.types import Scope3AIContext, Model, ImpactRow	4✔
13	from scope3ai.api.typesgen import Task	4✔
14	from scope3ai.constants import PROVIDERS	4✔
15	from scope3ai.lib import Scope3AI	4✔
16	from scope3ai.response_interceptor.requests_interceptor import requests_response_capture	4✔
17
18	PROVIDER = PROVIDERS.HUGGINGFACE_HUB.value	4✔
19
20
21	@dataclass	4✔
22	class AutomaticSpeechRecognitionOutput(_AutomaticSpeechRecognitionOutput):	4✔
23	scope3ai: Optional[Scope3AIContext] = None	4✔
24
25
26	def _hugging_face_automatic_recognition_wrapper(	4✔
27	timer_start: Any,
28	model: Any,
29	response: Any,
30	http_response: Union[ClientResponse, Response],
31	args: Any,
32	kwargs: Any,
33	) -> AutomaticSpeechRecognitionOutput:
34	if http_response:	4✔
35	compute_audio_length = http_response.headers.get("x-compute-audio-length")	4✔
36	compute_time = http_response.headers.get("x-compute-time")	4✔
37	else:
NEW 38	compute_audio_length = 0	×
NEW 39	compute_time = time.perf_counter() - timer_start	×
40
41	scope3_row = ImpactRow(	4✔
42	model=Model(id=model),
43	task=Task.text_to_speech,
44	input_audio_seconds=int(float(compute_audio_length)),
45	request_duration_ms=float(compute_time) * 1000,
46	managed_service_id=PROVIDER,
47	)
48
49	scope3_ctx = Scope3AI.get_instance().submit_impact(scope3_row)	4✔
50	result = AutomaticSpeechRecognitionOutput(**asdict(response))	4✔
51	result.scope3ai = scope3_ctx	4✔
52	return result	4✔
53
54
55	def huggingface_automatic_recognition_output_wrapper(	4✔
56	wrapped: Callable, instance: InferenceClient, args: Any, kwargs: Any
57	) -> AutomaticSpeechRecognitionOutput:
58	timer_start = time.perf_counter()	4✔
59	http_response: Response \| None = None	4✔
60	with requests_response_capture() as responses:	4✔
61	response = wrapped(args, *kwargs)	4✔
62	http_responses = responses.get()	4✔
63	if len(http_responses) > 0:	4✔
64	http_response = http_responses[-1]	4✔
65	model = kwargs.get("model") or instance.get_recommended_model(	4✔
66	"automatic-speech-recognition"
67	)
68	return _hugging_face_automatic_recognition_wrapper(	4✔
69	timer_start, model, response, http_response, args, kwargs
70	)

scope3data / scope3ai-py / 12681022279

Source File Press 'n' to go to next uncovered line, 'b' for previous

Source File
Press 'n' to go to next uncovered line, 'b' for previous