- Adding specialist configuration information to be added as arguments for retrievers.
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@@ -1,31 +0,0 @@
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version: "1.0.0"
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name: "Retrieves vacancy text for a specific role"
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configuration:
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es_k:
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name: "es_k"
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type: "integer"
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description: "K-value to retrieve embeddings (max embeddings retrieved)"
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required: true
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default: 8
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es_similarity_threshold:
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name: "es_similarity_threshold"
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type: "float"
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description: "Similarity threshold for retrieving embeddings"
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required: true
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default: 0.3
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arguments:
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query:
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name: "query"
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type: "string"
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description: "Query to retrieve embeddings"
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required: true
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role_reference:
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name: "Role Reference"
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type: "string"
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description: "The role information needs to be retrieved for"
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required: true
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metadata:
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author: "Josako"
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date_added: "2025-07-07"
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changes: "Initial version"
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description: "Retrieves vacancy text for a specific role"
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@@ -15,10 +15,4 @@ RETRIEVER_TYPES = {
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"partner": "traicie",
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"valid_catalog_types": ["TRAICIE_ROLE_DEFINITION_CATALOG"]
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},
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"TRAICIE_ROLE_DEFINITION_VACANCY_TEXT": {
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"name": "Traicie Role Definition Vacancy Text Retriever",
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"description": "Retrieves vacancy text for a given role",
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"partner": "traicie",
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"valid_catalog_types": ["TRAICIE_ROLE_DEFINITION_CATALOG"]
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}
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}
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@@ -181,6 +181,15 @@ def prepare_arguments(specialist: Any, arguments: Dict[str, Any]) -> Dict[str, A
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inherited_args['type'] = retriever.type
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inherited_args['type_version'] = retriever.type_version
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# Get arguments that are required from the specialist configuration
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retriever_config = cache_manager.retrievers_config_cache.get_config(retriever.type, retriever.type_version)
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retriever_required_args = retriever_config.get('arguments', {})
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for req_arg_name, req_arg_config in retriever_required_args.items():
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specialist_config_val = specialist.configuration.get(req_arg_name, None)
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if specialist_config_val is not None:
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inherited_args[req_arg_name] = specialist_config_val
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# Validate the combined arguments
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validate_retriever_arguments(
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retriever.type, retriever.type_version,
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