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Merge branch 'main' into feature/test-gitflow
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0.71.0
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0.71.0

llm-complete-guide/configs/dev/rag.yaml

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- rerankers
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- pygithub
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- rerankers[flashrank]
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- matplotlib
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- elasticsearch
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environment:
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ZENML_PROJECT_SECRET_NAME: llm_complete
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ZENML_ENABLE_RICH_TRACEBACK: FALSE

llm-complete-guide/configs/dev/rag_eval.yaml

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- psycopg2-binary
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- tiktoken
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- pygithub
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- elasticsearch
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python_package_installer: "uv"

llm-complete-guide/configs/production/eval.yaml

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- matplotlib
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- pillow
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- pygithub
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- elasticsearch
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environment:
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ZENML_PROJECT_SECRET_NAME: llm_complete
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ZENML_ENABLE_RICH_TRACEBACK: FALSE

llm-complete-guide/configs/production/rag.yaml

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enable_cache: True
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enable_cache: False
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# environment configuration
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settings:
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- rerankers
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- pygithub
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- rerankers[flashrank]
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- matplotlib
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- elasticsearch
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environment:
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ZENML_PROJECT_SECRET_NAME: llm_complete
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ZENML_ENABLE_RICH_TRACEBACK: FALSE
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parameters:
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docs_url: https://docs.zenml.io
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use_dev_set: false
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enable_cache: true
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# generate_embeddings:
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# step_operator: "sagemaker"
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# settings:

llm-complete-guide/configs/staging/embeddings.yaml

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# enable_cache: False
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enable_cache: False
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# environment configuration
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settings:

llm-complete-guide/configs/staging/eval.yaml

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- matplotlib
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- pillow
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- pygithub
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- elasticsearch
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environment:
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ZENML_PROJECT_SECRET_NAME: llm_complete
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ZENML_ENABLE_RICH_TRACEBACK: FALSE

llm-complete-guide/configs/staging/rag.yaml

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- rerankers
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- pygithub
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- rerankers[flashrank]
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- matplotlib
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- elasticsearch
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environment:
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ZENML_PROJECT_SECRET_NAME: llm_complete
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ZENML_ENABLE_RICH_TRACEBACK: FALSE
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parameters:
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docs_url: https://docs.zenml.io
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use_dev_set: false
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enable_cache: true

llm-complete-guide/constants.py

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384 # Update this to match the dimensionality of the new model
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)
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# ZenML constants
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ZENML_CHATBOT_MODEL = "zenml-docs-qa-chatbot"
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# Scraping constants
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RATE_LIMIT = 5 # Maximum number of requests per second
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USE_ARGILLA_ANNOTATIONS = False
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SECRET_NAME = os.getenv("ZENML_PROJECT_SECRET_NAME", "llm-complete")
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SECRET_NAME_ELASTICSEARCH = "elasticsearch-zenml"

llm-complete-guide/gh_action_rag.py

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zenml_model_name (str): The ZenML model name.
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zenml_model_version (str): The ZenML model version.
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"""
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pipeline_args = {"enable_cache": not no_cache}
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client = Client()
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config_path = Path(__file__).parent / "configs" / config
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