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https://github.com/lightbroker/llmsecops-research.git
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Adam Wilson
86 lines
3.3 KiB
Python
86 lines
3.3 KiB
Python
from dependency_injector import containers, providers
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from src.text_generation.adapters.embedding_model import EmbeddingModel
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from src.text_generation.adapters.text_generation_foundation_model import TextGenerationFoundationModel
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from src.text_generation.entrypoints.http_api_controller import HttpApiController
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from src.text_generation.entrypoints.server import RestApiServer
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from src.text_generation.services.logging.json_web_traffic_logging_service import JSONWebTrafficLoggingService
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from src.text_generation.services.nlp.semantic_similarity_service import SemanticSimilarityService
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from src.text_generation.services.nlp.text_generation_completion_service import TextGenerationCompletionService
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from src.text_generation.services.nlp.retrieval_augmented_generation_completion_service import RetrievalAugmentedGenerationCompletionService
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from src.text_generation.services.guardrails.generated_text_guardrail_service import GeneratedTextGuardrailService
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from src.text_generation.services.guidelines.rag_guidelines_service import RetrievalAugmentedGenerationGuidelinesService
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from src.text_generation.services.utilities.response_processing_service import ResponseProcessingService
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class DependencyInjectionContainer(containers.DeclarativeContainer):
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wiring_config = containers.WiringConfiguration(modules=['src.text_generation'])
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config = providers.Configuration(yaml_files=['config.yml'])
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logging_service = providers.Singleton(
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JSONWebTrafficLoggingService
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)
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foundation_model = providers.Singleton(
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TextGenerationFoundationModel
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)
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embedding_model = providers.Singleton(
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EmbeddingModel
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)
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rag_guidelines_service = providers.Factory(
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RetrievalAugmentedGenerationGuidelinesService,
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embedding_model=embedding_model
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)
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response_processing_service = providers.Factory(
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ResponseProcessingService
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)
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rag_response_service = providers.Factory(
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RetrievalAugmentedGenerationCompletionService,
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foundation_model=foundation_model,
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embedding_model=embedding_model,
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rag_guidelines_service=rag_guidelines_service,
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response_processing_service=response_processing_service
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)
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# add / implement guidelines svc
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# TODO placeholder; replace with responses from garak runs
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comparison_texts = [
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'something here',
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'another example'
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]
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semantic_similarity_service = providers.Factory(
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SemanticSimilarityService,
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embedding_model=embedding_model
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)
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generated_text_guardrail_service = providers.Factory(
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GeneratedTextGuardrailService,
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semantic_similarity_service=semantic_similarity_service,
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comparison_texts=comparison_texts
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)
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text_generation_response_service = providers.Factory(
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TextGenerationCompletionService,
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foundation_model
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)
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api_controller = providers.Factory(
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HttpApiController,
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logging_service=logging_service,
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text_generation_response_service=text_generation_response_service,
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rag_response_service=rag_response_service,
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generated_text_guardrail_service=generated_text_guardrail_service
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)
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rest_api_server = providers.Factory(
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RestApiServer,
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listening_port=9999, # config.server.port,
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api_controller=api_controller
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) |