Extend repository schema to include sentence embedder #15
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tiadams
requested changes
Aug 19, 2024
datastew/embedding.py
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| class MPNetAdapter(EmbeddingModel): | ||
| def __init__(self, model="sentence-transformers/all-mpnet-base-v2"): | ||
| logging.getLogger().setLevel(logging.INFO) | ||
| self.mpnet_model = SentenceTransformer(model) | ||
| self.model = SentenceTransformer(model) |
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Model property is a str in GPT4 and an object in MPNet, that shouldnt be the case if it is implementing the same class
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Addressed the issue by renaming the model attribute of GPT4Adapter to model_name.
datastew/repository/model.py
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| @@ -18,6 +17,15 @@ def __init__(self, name: str, id: str) -> object: | |||
| self.id = id | |||
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| class SentenceEmbedder(Base): | |||
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We dont need a seperate Table for a single string property
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The embedding model can just be a single string property in the embedding class.
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Refactored the code accordingly.
tiadams
reviewed
Aug 21, 2024
datastew/repository/weaviate.py
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| for item in result['data']['Get']['Mapping']: | ||
| sentence_embedders.add(item["hasSentenceEmbedder"]) | ||
| except Exception as e: | ||
| raise RuntimeError(f"Failed to fetch terminologies: {e}") |
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Why is it failed to fetch terminologies here?
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A typo on my side, sorry. Fixed in the latest push.
tiadams
approved these changes
Aug 21, 2024
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Extended both SQL and Weaviate repository schemas to include sentence embedders.
Made necessary changes to functions utilizing these classes.
Added a new function allowing the user to filter based on the terminology and model.
Added new tests for each repository for the function retrieving all the stored sentence embedders.