diff --git a/test/test_generator.py b/test/test_generator.py index b54d3c3..7b39dbe 100644 --- a/test/test_generator.py +++ b/test/test_generator.py @@ -8,7 +8,7 @@ from src.options.generate.generator import Generator def test_generation_level_0(tmpdir): """ Requirements: - coding: ❌ + coding challenge: ❌ pip packages: ❌ environment: ❌ GPT-3.5-turbo: ❌ @@ -27,16 +27,78 @@ def test_generation_level_0(tmpdir): def test_generation_level_1(tmpdir): """ Requirements: - coding: ❌ - pip packages: ✅ (pdf parser) + coding challenge: ❌ + pip packages: ❌ environment: ❌ - GPT-3.5-turbo: ❌ + 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 parsed text", + ''' +Input is a tweet that might contain passive aggressive language like: +'When your coworker microwaves fish in the break room... AGAIN. 🐟🤢 But hey, at least SOMEONE's enjoying their lunch. #officelife' +The output is a tweet that is not passive aggressive like: +'Hi coworker, +I hope you're having an amazing day! +Just a quick note: sometimes microwaving fish can create an interesting aroma in the break room. +If you're up for trying different lunch options, that could be a fun way to mix things up. +Enjoy your day! #variety' +''', + str(tmpdir) + 'microservice', + 'gpt-3.5-turbo' + ) + generator.generate() + + +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.", + str(tmpdir) + 'microservice', + 'gpt-3.5-turbo' + ) + generator.generate() + + +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' ) @@ -46,7 +108,7 @@ def test_generation_level_1(tmpdir): def test_generation_level_4(tmpdir): """ Requirements: - coding: ✅ (putting text on the image) + coding challenge: ✅ (putting text on the image) pip packages: ✅ (Pillow for image processing) environment: ❌ GPT-3.5-turbo: ✅ (for writing the joke)