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96 lines
1.9 KiB
YAML
96 lines
1.9 KiB
YAML
# Vector DB 통합 시스템 설정
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# PostgreSQL (용어집)
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postgres:
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host: ${POSTGRES_HOST}
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port: ${POSTGRES_PORT}
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database: ${POSTGRES_DATABASE}
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user: ${POSTGRES_USER}
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password: ${POSTGRES_PASSWORD}
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pool_size: 10
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max_overflow: 20
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# Azure OpenAI (Embedding)
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azure_openai:
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api_key: ${AZURE_OPENAI_API_KEY}
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endpoint: ${AZURE_OPENAI_ENDPOINT}
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embedding_model: text-embedding-ada-002
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embedding_dimension: 1536
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api_version: "2023-05-15"
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# Azure AI Search (관련자료)
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azure_search:
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endpoint: ${AZURE_SEARCH_ENDPOINT}
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api_key: ${AZURE_SEARCH_API_KEY}
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index_name: meeting-minutes-index
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api_version: "2023-11-01"
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# Claude AI
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claude:
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api_key: ${CLAUDE_API_KEY}
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model: claude-3-5-sonnet-20241022
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max_tokens: 1024
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temperature: 0.3
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# Redis (캐싱)
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redis:
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host: redis
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port: 6379
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db: 0
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password: ${REDIS_PASSWORD}
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decode_responses: true
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# Azure Event Hub
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eventhub:
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connection_string: ${EVENTHUB_CONNECTION_STRING}
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name: ${EVENTHUB_NAME}
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consumer_group: ${AZURE_EVENTHUB_CONSUMER_GROUP}
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storage:
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connection_string: ${AZURE_STORAGE_CONNECTION_STRING}
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container_name: ${AZURE_STORAGE_CONTAINER_NAME}
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# Application Settings
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app:
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name: "Vector DB Service"
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version: "1.0.0"
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debug: true
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log_level: INFO
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# 용어집 설정
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term_glossary:
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# 검색 설정
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search:
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top_k: 5
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confidence_threshold: 0.7
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keyword_weight: 0.6
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vector_weight: 0.4
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# 캐싱 설정
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cache:
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ttl: 3600 # 1시간
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prefix: "term:"
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# 관련자료 설정
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related_documents:
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# 검색 설정
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search:
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top_k: 3
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relevance_threshold: 0.70
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folder_weight_boost: 0.20
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semantic_ranking: true
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# 캐싱 설정
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cache:
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ttl: 3600 # 1시간
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prefix: "doc:"
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# 데이터 로딩
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data:
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terms_dir: design/aidata
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terms_files:
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- terms-01.json
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- terms-02.json
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- terms-03.json
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- terms-04.json
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documents_file: design/aidata/meet-ref.json
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