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➕ refactor: summarize error message without line number

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This commit is contained in:
Florian Hönicke
2023-05-31 10:28:35 +02:00
parent cc1ab36d6f
commit d1030f426b
3 changed files with 36 additions and 7 deletions
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38
test/unit/test_tools.py
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@@ -14,17 +14,17 @@ def test_no_search():
tool_lines = get_available_tools().split('\n')
assert len(tool_lines) == 1
def test_get_used_tools(tmpdir):
def test_get_used_apis(tmpdir):
os.environ['VERBOSE'] = 'true'
GPTSession(os.path.join(str(tmpdir), 'log.json'), model='gpt-3.5-turbo')
used_tools = PM.get_used_apis('''\
used_apis = PM.get_used_apis('''\
This microservice listens for incoming requests and generates a fixed output of "test" upon receiving a request. \
The response sent back to the requester includes the output as a string parameter. \
No specific request parameters are required, and the response always follows a fixed schema with a single "output" parameter.'''
)
assert used_tools == []
assert used_apis == []
def test_get_used_tools_2(tmpdir):
def test_get_used_apis_2(tmpdir):
os.environ['VERBOSE'] = 'true'
GPTSession(os.path.join(str(tmpdir), 'log.json'), model='gpt-3.5-turbo')
description = '''\
@@ -36,5 +36,31 @@ This microservice accepts a 1-minute WAV audio file of speech, encoded as a base
4. Encodes the resulting audio file as a base64 binary string.
The microservice returns the summarized text converted to audio and encoded as a base64 binary string.'''
used_tools = PM.get_used_apis(description)
assert used_tools == ['Whisper API', 'gpt_3_5_turbo', 'text-to-speech (TTS) library']
used_apis = PM.get_used_apis(description)
assert used_apis == ['Whisper API', 'gpt_3_5_turbo', 'text-to-speech (TTS) library']
def test_get_used_apis_3(tmpdir):
os.environ['VERBOSE'] = 'true'
GPTSession(os.path.join(str(tmpdir), 'log.json'), model='gpt-3.5-turbo')
description = '''\
This microservice takes a PDF file as input and returns a summarized text output. \
It uses PDF parsing and natural language processing tools to generate the summary, \
and applies post-processing techniques to improve its quality. \
The input parameter is the PDF file, \
and the output parameter is the summarized text.'''
used_apis = PM.get_used_apis(description)
assert used_apis == []
def test_get_used_apis_4(tmpdir):
os.environ['VERBOSE'] = 'true'
GPTSession(os.path.join(str(tmpdir), 'log.json'), model='gpt-3.5-turbo')
description = '''\
This microservice receives a tweet as input \
and identifies passive aggressive language using natural language processing techniques. \
It then generates a positive version of the tweet using a text processing tool such as GPT-3. \
The positive version of the tweet is returned as output. \
The input tweet should be provided as a base64 encoded string \
and the output positive tweet will also be returned as a base64 encoded string.'''
used_apis = PM.get_used_apis(description)
assert used_apis == ['GPT-3']