init
Browse files- backend.py +59 -13
backend.py
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@@ -16,15 +16,9 @@ def clean_test_case_output(text):
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"""
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Cleans the output to handle HTML characters and unwanted tags.
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"""
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# Unescape HTML entities
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# Use BeautifulSoup to handle HTML tags more comprehensively
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soup = BeautifulSoup(text, 'html.parser')
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# Convert <br> tags to newlines and remove all other tags
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cleaned_text = soup.get_text(separator="\n").strip()
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return cleaned_text
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def generate_testcases(user_story):
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@@ -36,12 +30,65 @@ def generate_testcases(user_story):
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:param user_story: A string representing the user story for which to generate test cases.
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:return: A list of test cases in the form of dictionaries.
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"""
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try:
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#
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completion = client.chat.completions.create(
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model="nv-mistralai/mistral-nemo-12b-instruct", # Using Mistral model
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messages=[
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{"role": "user", "content":
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],
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temperature=0.06, # Further lowering temperature for precise and deterministic output
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top_p=0.5, # Prioritize high-probability tokens even more
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@@ -81,6 +128,7 @@ def generate_testcases(user_story):
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except requests.exceptions.RequestException as e:
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print(f"API request failed: {str(e)}")
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return []
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# Add options for multiple test case formats
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def export_test_cases(test_cases, format='json'):
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if not test_cases:
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@@ -93,7 +141,6 @@ def export_test_cases(test_cases, format='json'):
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# Improve JSON export to be line-by-line formatted
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return json.dumps(test_cases, indent=4, separators=(',', ': ')) # More readable format
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elif format == 'csv':
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# Check if test_cases is a list of dicts
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if isinstance(test_cases, list) and isinstance(test_cases[0], dict):
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output = io.StringIO()
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csv_writer = csv.DictWriter(output, fieldnames=test_cases[0].keys(), quoting=csv.QUOTE_ALL)
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@@ -119,4 +166,3 @@ def save_test_cases_as_file(test_cases, format='json'):
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else:
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return f"Unsupported format: {format}"
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return f'{format} file saved'
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"""
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Cleans the output to handle HTML characters and unwanted tags.
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"""
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text = html.unescape(text) # Unescape HTML entities
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soup = BeautifulSoup(text, 'html.parser') # Use BeautifulSoup to handle HTML tags
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cleaned_text = soup.get_text(separator="\n").strip() # Remove tags and handle newlines
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return cleaned_text
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def generate_testcases(user_story):
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:param user_story: A string representing the user story for which to generate test cases.
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:return: A list of test cases in the form of dictionaries.
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"""
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# Few-shot learning examples to guide the model
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few_shot_examples = """
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Example 1:
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User Story:
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Ensure the "Key Details" feature is enabled in the backend.
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1. Open the Tech 360 app.
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2. Click on the Search tab.
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3. Enter the account number and click on Enter.
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4. Choose the account from the Search result.
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5. Verify that the "Key Details" button is displayed under the recommendation section.
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6. Clicking on "Key Details" should navigate to the key details screen.
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Test Case:
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Test Case: Verify "Key Details" Feature in Tech 360 App
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Steps:
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1. Launch the Tech 360 app.
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2. Go to the Search tab.
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3. Enter a valid account number and click Enter.
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4. Select an account from the search results.
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5. Ensure the "Key Details" button is displayed under the recommendation section.
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6. Click on "Key Details" and verify that it navigates to the Key Details screen.
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Expected Result: User is navigated to the Key Details screen successfully.
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Example 2:
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User Story:
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Open the Tech 360 app. Go On-Job on a Wi-Fi Ready Preinstall Job. Wait for PHT to finish. Go to the Device Details Page for XB7 and ONU.
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Test Case:
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Test Case: Verify Device Details Page for XB7 and ONU in Wi-Fi Ready Preinstall Job
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Steps:
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1. Launch the Tech 360 app.
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2. Go On-Job on a Wi-Fi Ready Preinstall Job.
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3. Wait for PHT to finish.
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4. Navigate to the Device Details Page for XB7 and ONU.
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Expected Result: Device details for XB7 and ONU are displayed correctly.
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Example 3:
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User Story:
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Open the Tech 360 app. Go On-Job on a Wi-Fi Ready Preinstall Job. Initiate Add/Remove/Swap Flows for ONU and XB7.
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Test Case:
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Test Case: Verify Add/Remove/Swap Flows for ONU and XB7 in Wi-Fi Ready Preinstall Job
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Steps:
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1. Launch the Tech 360 app.
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2. Go On-Job on a Wi-Fi Ready Preinstall Job.
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3. Initiate Add/Remove/Swap flows for ONU and XB7.
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Expected Result: Add/Remove/Swap flows for ONU and XB7 are initiated and processed successfully.
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"""
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# Combine the few-shot examples with the user story for the model to process
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prompt = few_shot_examples + f"\nUser Story: {user_story}\n"
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try:
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# Call the Nvidia Mistral API with the refined prompt
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completion = client.chat.completions.create(
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model="nv-mistralai/mistral-nemo-12b-instruct", # Using Mistral model
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messages=[
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{"role": "user", "content": prompt}
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],
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temperature=0.06, # Further lowering temperature for precise and deterministic output
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top_p=0.5, # Prioritize high-probability tokens even more
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except requests.exceptions.RequestException as e:
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print(f"API request failed: {str(e)}")
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return []
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# Add options for multiple test case formats
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def export_test_cases(test_cases, format='json'):
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if not test_cases:
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# Improve JSON export to be line-by-line formatted
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return json.dumps(test_cases, indent=4, separators=(',', ': ')) # More readable format
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elif format == 'csv':
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if isinstance(test_cases, list) and isinstance(test_cases[0], dict):
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output = io.StringIO()
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csv_writer = csv.DictWriter(output, fieldnames=test_cases[0].keys(), quoting=csv.QUOTE_ALL)
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else:
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return f"Unsupported format: {format}"
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return f'{format} file saved'
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