aljaz/dev-gpt
1
0
Fork 0
mirror of https://github.com/aljazceru/dev-gpt.git synced 2025-12-19 14:44:20 +01:00
Code Issues Packages Projects Releases Wiki Activity

refactor: cleanup

Browse Source
This commit is contained in:
Florian Hönicke
2023-05-10 01:02:12 +02:00
parent 8c37158c02
commit b0e6b85ce5
2 changed files with 23 additions and 15 deletions
Download Patch File Download Diff File Expand all files Collapse all files

2
dev_gpt/options/generate/pm/pm.py
View File

@@ -60,7 +60,7 @@ Description of the microservice:
context,
microservice_description,
condition_question='Does the microservice send requests to an API?',
question_gen='Generate a question that asks for the endpoint and an example of a request and response when interacting with the api.',
question_gen='Generate a question that asks for the endpoint and an example of a request and response when interacting with the external API.',
extension_name='Example of API usage',
)
# database missing

36
test/integration/test_generator.py
View File

@@ -70,7 +70,7 @@ def test_generation_level_2(microservice_dir, mock_input_sequence):
)
assert generator.generate() == 0
@pytest.mark.parametrize('mock_input_sequence', [['y']], indirect=True)
@pytest.mark.parametrize('mock_input_sequence', [['y', 'yfinance.Ticker("MSFT").info']], indirect=True)
def test_generation_level_3(microservice_dir, mock_input_sequence):
"""
Requirements:
@@ -95,7 +95,27 @@ Example input: 'AAPL'
)
assert generator.generate() == 0
@pytest.mark.parametrize('mock_input_sequence', [['y', 'https://www.signalogic.com/melp/EngSamples/Orig/ENG_M.wav']], indirect=True)
@pytest.mark.parametrize(
'mock_input_sequence', [
[
'y',
'https://www.signalogic.com/melp/EngSamples/Orig/ENG_M.wav',
'''\
import requests
url = "https://transcribe.whisperapi.com"
headers = {{
'Authorization': 'Bearer {os.environ['WHISPER_API_KEY']}'
}}
data = {{
"url": "URL_OF_STORED_AUDIO_FILE"
}}
response = requests.post(url, headers=headers, data=data)
assert response.status_code == 200
print('This is the text from the audio file:', response.json()['text'])'''
]
],
indirect=True
)
def test_generation_level_4(microservice_dir, mock_input_sequence):
"""
Requirements:
@@ -110,18 +130,6 @@ def test_generation_level_4(microservice_dir, mock_input_sequence):
generator = Generator(
f'''Given an audio file (1min wav) of speech,
1. convert it to text using the Whisper API.
Here is the documentation on how to use the API:
import requests
url = "https://transcribe.whisperapi.com"
headers = {{
'Authorization': 'Bearer {os.environ['WHISPER_API_KEY']}'
}}
data = {{
"url": "URL_OF_STORED_AUDIO_FILE"
}}
response = requests.post(url, headers=headers, data=data)
assert response.status_code == 200
print('This is the text from the audio file:', response.json()['text'])
2. Summarize the text (~50 words) while still maintaining the key facts.
3. Create an audio file of the summarized text using a tts library.
4. Return the the audio file as base64 encoded binary.