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Remove LLM Fact Sheet requirement
Signed-off-by: David Weik <geekupyourlife@gmail.com>
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‎CHANGELOG.md‎

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@@ -2,6 +2,22 @@
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This changelog documents all the different updates that occur for this framework.
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## [0.1.29] - 2025-10-13
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No changes are requires at this time.
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### Added
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- None
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### Changed
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- The register-LLMs.py script does no longer require an entry in the LLM Fact Sheet.
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### Fixed
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- None
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## [0.1.29] - 2025-10-10
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No changes are requires at this time.

‎LLM-Definitions/register-LLMs.py‎

Lines changed: 65 additions & 71 deletions
Original file line numberDiff line numberDiff line change
@@ -93,80 +93,74 @@ def register_model(base_path):
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model_attributes = get_model_attributes(base_path)
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model_data = llm_fact_sheet[llm_fact_sheet['model_id'] == base_path]
9595
if model_data.empty:
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print(f"The selected LLM: {base_path} is not vailable in the llm_fact_sheet.csv. This is a required entry!")
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print(f"WARNING: The selected LLM: {base_path} is not vailable in the llm_fact_sheet.csv.")
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print('WARNING: This entry is required for the Logging/Monitoring to work properly!')
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# Add additional model metadata from the llm_fact_sheet.csv
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model_attributes['llmModelType'] = model_attributes.get('llmModelType', 'GPT')
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model_data_dict = model_data.to_dict('records')[0]
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model_attributes['provider'] = model_data_dict.get('provider', 'Unkown')
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model_attributes['endPoint'] = f"{args.scr_endpoint}/{base_path}/{base_path}"
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cost_estimation_type = model_data_dict.get('cost_type', 'Tokens')
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costPerCall = 0
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if (cost_estimation_type == 'Tokens'):
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costPerCall = (float(model_data_dict.get('input_token_price', '0')) + float(model_data_dict.get('output_token_price', '0'))) / 2
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elif (cost_estimation_type == 'Seconds'):
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costPerCall = float(model_data_dict.get('second_cost', '0'))
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else:
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# Add additional model metadata from the llm_fact_sheet.csv
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model_attributes['llmModelType'] = model_attributes.get('llmModelType', 'GPT')
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model_data_dict = model_data.to_dict('records')[0]
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model_attributes['provider'] = model_data_dict.get('provider', 'Unkown')
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model_attributes['endPoint'] = f"{args.scr_endpoint}/{base_path}/{base_path}"
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cost_estimation_type = model_data_dict.get('cost_type', 'Tokens')
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costPerCall = 0
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if (cost_estimation_type == 'Tokens'):
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costPerCall = (float(model_data_dict.get('input_token_price', '0')) + float(model_data_dict.get('output_token_price', '0'))) / 2
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elif (cost_estimation_type == 'Seconds'):
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costPerCall = float(model_data_dict.get('second_cost', '0'))
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else:
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print(f"The cost type for LLMs has to be either Tokens or Seconds, the value provided was: {cost_estimation_type} for {base_path}")
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model_attributes['costPerCall'] = costPerCall
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model_object = mr.create_model(model = model_attributes, project = project_attributes['project_name'])
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print(f"The cost type for LLMs has to be either Tokens or Seconds, the value provided was: {cost_estimation_type} for {base_path}")
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model_attributes['costPerCall'] = costPerCall
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model_object = mr.create_model(model = model_attributes, project = project_attributes['project_name'])
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time.sleep(1)
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# Score script
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file = open(f"{base_path}/{model_attributes['scoreCodeFile']}", 'rb')
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mr.add_model_content(model_object,
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file,
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name = model_attributes['name'] + '.py',
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role = 'score')
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file.close()
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# Dependencies
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file = open(f"{base_path}/requirements.json", 'rb')
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mr.add_model_content(model_object,
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file,
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name = 'requirements.json',
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role = 'python pickle')
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file.close()
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# Output variables
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file = open(f"{base_path}/outputVar.json", 'rb')
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mr.add_model_content(model_object, file, name = 'outputVar.json')
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file.close()
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time.sleep(1)
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# Score script
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file = open(f"{base_path}/{model_attributes['scoreCodeFile']}", 'rb')
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mr.add_model_content(model_object, file, name = model_attributes['name'] + '.py', role = 'score')
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file.close()
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# Dependencies
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file = open(f"{base_path}/requirements.json", 'rb')
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mr.add_model_content(model_object, file, name = 'requirements.json', role = 'python pickle')
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file.close()
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# Output variables
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file = open(f"{base_path}/outputVar.json", 'rb')
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mr.add_model_content(model_object, file, name = 'outputVar.json')
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file.close()
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# Input variables
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file = open(f"{base_path}/inputVar.json", 'rb')
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mr.add_model_content(model_object, file, name = 'inputVar.json')
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file.close()
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# Options information
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file = open(f"{base_path}/options.json", 'rb')
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mr.add_model_content(model_object, file, name = 'options.json', role='documentation')
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file.close()
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# Upload the optional model card
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if os.path.exists(f"{base_path}/Model-Card.pdf"):
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file = open(f"{base_path}/Model-Card.pdf", 'rb')
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mr.add_model_content(model_object, file, name = 'Model-Card.pdf', role = 'documentation')
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elif os.path.exists(f"{base_path}/Model-Card.md"):
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file = open(f"{base_path}/Model-Card.md", 'rb')
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mr.add_model_content(model_object, file, name = 'Model-Card.md', role = 'documentation')
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else:
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print(f"No model card added for {base_path}")
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# Upload toknizer filesif they exist
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if os.path.exists(f"{base_path}/tokenizer_config.json"):
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file = open(f"{base_path}/tokenizer_config.json", 'rb')
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mr.add_model_content(model_object, file, name = 'tokenizer_config.json', role = 'documentation')
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if os.path.exists(f"{base_path}/special_tokens_map.json"):
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file = open(f"{base_path}/special_tokens_map.json", 'rb')
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mr.add_model_content(model_object, file, name = 'special_tokens_map.json', role = 'documentation')
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if os.path.exists(f"{base_path}/tokenizer.json"):
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file = open(f"{base_path}/tokenizer.json", 'rb')
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mr.add_model_content(model_object, file, name = 'tokenizer.json', role = 'documentation')
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update_model_tags(model_attributes, model_object.id)
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print(f"Link to the model in SAS Model Manager: {args.viya_server}/SASModelManager/models/{model_object.id}")
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return model_object
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# Input variables
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file = open(f"{base_path}/inputVar.json", 'rb')
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mr.add_model_content(model_object, file, name = 'inputVar.json')
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file.close()
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# Options information
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file = open(f"{base_path}/options.json", 'rb')
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mr.add_model_content(model_object, file, name = 'options.json', role='documentation')
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file.close()
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# Upload the optional model card
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if os.path.exists(f"{base_path}/Model-Card.pdf"):
142+
file = open(f"{base_path}/Model-Card.pdf", 'rb')
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mr.add_model_content(model_object, file, name = 'Model-Card.pdf', role = 'documentation')
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elif os.path.exists(f"{base_path}/Model-Card.md"):
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file = open(f"{base_path}/Model-Card.md", 'rb')
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mr.add_model_content(model_object, file, name = 'Model-Card.md', role = 'documentation')
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else:
148+
print(f"No model card added for {base_path}")
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# Upload toknizer filesif they exist
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if os.path.exists(f"{base_path}/tokenizer_config.json"):
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file = open(f"{base_path}/tokenizer_config.json", 'rb')
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mr.add_model_content(model_object, file, name = 'tokenizer_config.json', role = 'documentation')
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if os.path.exists(f"{base_path}/special_tokens_map.json"):
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file = open(f"{base_path}/special_tokens_map.json", 'rb')
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mr.add_model_content(model_object, file, name = 'special_tokens_map.json', role = 'documentation')
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if os.path.exists(f"{base_path}/tokenizer.json"):
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file = open(f"{base_path}/tokenizer.json", 'rb')
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mr.add_model_content(model_object, file, name = 'tokenizer.json', role = 'documentation')
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update_model_tags(model_attributes, model_object.id)
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print(f"Link to the model in SAS Model Manager: {args.viya_server}/SASModelManager/models/{model_object.id}")
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return model_object
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# Establish a session
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try:

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