import os import pytest from src.options.generate.generator import Generator # The cognitive difficulty level is determined by the number of requirements the microservice has. def test_generation_level_0(tmpdir): """ Requirements: coding challenge: ❌ pip packages: ❌ environment: ❌ GPT-3.5-turbo: ❌ APIs: ❌ Databases: ❌ """ os.environ['VERBOSE'] = 'true' generator = Generator( "The microservice is very simple, it does not take anything as input and only outputs the word 'test'", str(tmpdir) + 'microservice', 'gpt-3.5-turbo' ) assert generator.generate() == 0 # fixture @pytest.fixture def tmpdir(): return 'microservice' def test_generation_level_1(tmpdir): """ Requirements: coding challenge: ❌ pip packages: ❌ environment: ❌ GPT-3.5-turbo: ✅ (for summarizing the text) APIs: ❌ Databases: ❌ """ os.environ['VERBOSE'] = 'true' generator = Generator( '''Input is a tweet that might contain passive aggressive language. The output is the positive version of that tweet. Example tweet: \'When your coworker microwaves fish in the break room... AGAIN. 🐟🤢 But hey, at least SOMEONE's enjoying their lunch. #officelife\'''', str(tmpdir) + 'microservice', 'gpt-3.5-turbo' ) assert generator.generate() == 0 def test_generation_level_2(tmpdir): """ Requirements: coding challenge: ❌ pip packages: ✅ (pdf parser) environment: ❌ GPT-3.5-turbo: ✅ (for summarizing the text) APIs: ❌ Databases: ❌ """ os.environ['VERBOSE'] = 'true' generator = Generator( "The input is a PDF like https://www.africau.edu/images/default/sample.pdf and the output the summarized text (50 words).", str(tmpdir) + 'microservice', 'gpt-3.5-turbo' ) assert generator.generate() == 0 #Create a wrapper around google called Joogle. It modifies the page summary preview text of the search results to insert the word Jina as much as possible. @pytest.mark.skip(reason="not possible") def test_generation_level_3(tmpdir): """ Requirements: coding challenge: ❌ pip packages: ✅ (text to speech) environment: ❌ GPT-3.5-turbo: ✅ (summarizing the text) APIs: ✅ (whisper for speech to text) Databases: ❌ """ os.environ['VERBOSE'] = 'true' generator = Generator( 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" headers = {{ 'Authorization': 'Bearer {os.environ['WHISPER_API_KEY']}' }} data = {{ "url": "URL_OF_STORED_AUDIO_FILE" }} 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' ) assert generator.generate() == 0 @pytest.mark.skip(reason="not possible") def test_generation_level_4(tmpdir): """ Requirements: coding challenge: ✅ (putting text on the image) pip packages: ✅ (Pillow for image processing) environment: ❌ GPT-3.5-turbo: ✅ (for writing the joke) APIs: ✅ (scenex for image description) Databases: ❌ """ os.environ['VERBOSE'] = 'true' generator = Generator(f''' 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" \\ --data '{{"data":[ {{"image": "", "features": []}} ]}}' Result format: {{ "result": [ {{ "text": "" }} ] }} The description is then used to generate a joke. The joke is the put on the image. The output is the image with the joke on it.''', str(tmpdir) + 'microservice', 'gpt-3.5-turbo' ) assert generator.generate() == 0