From 28b604afb5189f49ed71b52ae276097e8cc1ff4c Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Florian=20Ho=CC=88nicke?= Date: Sat, 29 Apr 2023 02:34:05 +0200 Subject: [PATCH] =?UTF-8?q?=F0=9F=A7=AA=20test:=20level=204?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- test/test_generator.py | 9 ++++----- 1 file changed, 4 insertions(+), 5 deletions(-) diff --git a/test/test_generator.py b/test/test_generator.py index 7b39dbe..1d95177 100644 --- a/test/test_generator.py +++ b/test/test_generator.py @@ -83,7 +83,7 @@ def test_generation_level_3(tmpdir): """ os.environ['VERBOSE'] = 'true' generator = Generator( - F'''Given an audio file of speech like https://www.signalogic.com/melp/EngSamples/Orig/ENG_M.wav, + f'''Given an audio file of speech like https://www.signalogic.com/melp/EngSamples/Orig/ENG_M.wav, get convert it to text using the following api: import requests url = "https://transcribe.whisperapi.com" @@ -97,7 +97,6 @@ response = requests.post(url, headers=headers, files=file, data=data) print(response.text) Summarize the text. Create an audio file of the summarized text. - ''', str(tmpdir) + 'microservice', 'gpt-3.5-turbo' @@ -120,9 +119,9 @@ def test_generation_level_4(tmpdir): The input is an image like this: https://upload.wikimedia.org/wikipedia/commons/thumb/4/47/PNG_transparency_demonstration_1.png/560px-PNG_transparency_demonstration_1.png. Use the following api to get the description of the image: Request: -curl "https://us-central1-causal-diffusion.cloudfunctions.net/describe" \ - -H "x-api-key: token {os.environ['SCENEX_API_KEY']}" \ - -H "content-type: application/json" \ +curl "https://us-central1-causal-diffusion.cloudfunctions.net/describe" \\ + -H "x-api-key: token {os.environ['SCENEX_API_KEY']}" \\ + -H "content-type: application/json" \\ --data '{{"data":[ {{"image": "", "features": []}} ]}}'