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75 lines
3.0 KiB
Plaintext
75 lines
3.0 KiB
Plaintext
Instructions:
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We are writing a feature computation framework.
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It will mainly consist of FeatureBuilder classes.
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Each Feature Builder will have the methods:
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- get(key, context, cache): To first check cache, and then go on to call dependencies to compute the feature. Returns value and hash of value.
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- dry_run(key, context): To check that "type" of key will match input requirements of features
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- input_type(context): That explains what dimensions key is applying to
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- output_type(context): That explains what type the output is
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It will have the class attr:
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- deps: list of FeatureBuilder classes
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Where it is unclear, please make assumptions and add a commend in the code about it
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Here is an example of Builders we want:
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ProductEmbeddingString: takes product_id, queries the product_db and gets the title as a string
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ProductEmbedding: takes string and returns and embedding
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ProductEmbeddingDB: takes just `merchant` name, uses all product_ids and returns the blob that is a database of embeddings
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ProductEmbeddingSearcher: takes a string, constructs embeddingDB feature (note: all features are cached), embeds the string and searches the db
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LLMProductPrompt: queries the ProductEmbeddingString, and formats a template that says "get recommendations for {title}"
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LLMSuggestions: Takes product_id, looks up prompts and gets list of suggestions of product descriptions
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LLMLogic: Takes the product_id, gets the LLM suggestions, embeds the suggestions, does a search, and returns a list of product_ids
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The LLMLogic is the logic_builder in a file such as this one:
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```
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def main(merchant, market):
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cache = get_cache()
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interaction_data_db = get_interaction_data_db()
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product_db = get_product_db()
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merchant_config = get_merchant_config(merchant)[merchant]
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context = Context(
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interaction_data_db=interaction_data_db,
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product_db=product_db,
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merchant_config=merchant_config,
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)
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product_ids = cache(ProductIds.get)(
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key=(merchant, market),
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context=context,
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cache=cache,
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)
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for logic_builder in merchant_config['logic_builders']:
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for product_id in product_ids:
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key = (merchant, market, product_id)
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p2p_recs = cache(logic_builder.get)(key, cache, context)
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redis.set(key, p2p_recs)
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```
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API to product_db:
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```
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async def get_product_attribute_dimensions(
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self,
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) -> dict[AttributeId, Dimension]:
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return await self.repository.get_product_attribute_dimensions(self.merchant)
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async def get_products(
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self,
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attribute_ids: set[AttributeId],
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product_ids: set[ProductId] | None = None,
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) -> dict[ProductId, dict[AttributeId, dict[IngestionDimensionKey, Any]]]:
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return await self.repository.get_products_dict(
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self.merchant, attribute_ids, product_ids
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)
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```
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(note, dimensions are not so important. They related to information that varies by: locale, warehouse, pricelist etc)
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Remember to read the Instructions carefully. |