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chore: import upstream snapshot with attribution
2026-07-13 13:36:38 +08:00

58 lines
1.7 KiB
Python

import instructor
from pydantic import BaseModel
import os
class Description(BaseModel):
relevant_speakers: list[str]
summary: str
curr_file = os.path.dirname(__file__)
file_path = os.path.join(curr_file, "./test_files/sample.mp3")
MODEL = os.getenv("GOOGLE_GENAI_MODEL", "google/gemini-pro")
def test_audio_compatability_list():
client = instructor.from_provider(
model=MODEL, mode=instructor.Mode.GENAI_STRUCTURED_OUTPUTS
)
# For now, we'll skip file operations since the new API might handle them differently
# This test might need to be updated based on the new google-genai file upload API
content = "Please transcribe this recording: [audio file would go here]"
result = client.chat.completions.create(
response_model=Description,
messages=[
{"role": "user", "content": content},
],
)
assert isinstance(result, Description), (
"Result should be an instance of Description"
)
def test_audio_compatability_multiple_messages():
client = instructor.from_provider(
model=MODEL, mode=instructor.Mode.GENAI_STRUCTURED_OUTPUTS
)
# For now, we'll skip file operations since the new API might handle them differently
# This test might need to be updated based on the new google-genai file upload API
result = client.chat.completions.create(
response_model=Description,
messages=[
{
"role": "user",
"content": "Please transcribe this recording: [audio file would go here]",
},
],
)
assert isinstance(result, Description), (
"Result should be an instance of Description"
)