46 lines
1.9 KiB
Properties
46 lines
1.9 KiB
Properties
spring.application.name=rag-service
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# --- LLM Provider: Groq (OpenAI-compatible API) ---
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spring.ai.openai.base-url=${SPRING_AI_OPENAI_BASE_URL:https://api.groq.com/openai/v1}
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spring.ai.openai.api-key=${SPRING_AI_OPENAI_API_KEY:}
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spring.ai.openai.chat.model=${SPRING_AI_OPENAI_CHAT_MODEL:llama-3.3-70b-versatile}
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# --- Embedding model: use local pgvector with a lightweight model ---
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# Groq does not provide an embedding endpoint, so we disable OpenAI embedding auto-config
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# and rely on the pgvector store's existing embedding setup
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spring.ai.openai.embedding.enabled=false
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jwt.secret=${JWT_SECRET:ywfI6dBznYmHbokihB/OBzZz6E0Fj+6PiqrM8dQ5c3t0HeYarblCbOGM8vQtOt472AtQ+MsCH7OVIKHOzjrPsQ==}
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jwt.expiration=103600000
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spring.datasource.url=${SPRING_DATASOURCE_URL:jdbc:postgresql://localhost:5432/ragdb}
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spring.datasource.username=${SPRING_DATASOURCE_USERNAME:postgres}
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spring.datasource.password=${SPRING_DATASOURCE_PASSWORD:postgres}
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logging.level.org.springframework.ai.chat.client.advisor=DEBUG
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logging.level.org.springframework.web.servlet.mvc.method.annotation.RequestMappingHandlerMapping=DEBUG
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logging.level.org.springframework.web=DEBUG
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logging.level.org.flywaydb=DEBUG
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logging.level.com.balex.rag.controller=DEBUG
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app.document.chunk-size=200
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server.compression.enabled=false
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server.tomcat.connection-timeout=60000
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spring.mvc.async.request-timeout=60000
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end.points.users=/users
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end.points.id=/{id}
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end.points.all=/all
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end.points.create=/create
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end.points.userinfo=/userinfo
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end.points.refresh.token=/refresh/token
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end.points.auth=/auth
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end.points.login=/login
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end.points.register=/register
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end.points.chat=/chat
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end.points.entry=/entry
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end.points.document=/documents
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rag.rerank-fetch-multiplier=2
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#Swagger
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swagger.servers.first=http://localhost:8080
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springdoc.swagger-ui.path=/swagger-ui.html
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springdoc.api-docs.path=/v3/api-docs
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#Kafka
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spring.kafka.bootstrap-servers=${KAFKA_BOOTSTRAP_SERVERS:localhost:9092}
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analytics.kafka.topic=user-events |