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https://github.com/trustgraph-ai/trustgraph.git
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Skeleton Bedrock support
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6 changed files with 401 additions and 0 deletions
261
docker-compose-bedrock.yaml
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261
docker-compose-bedrock.yaml
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volumes:
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cassandra:
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pulsar-conf:
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pulsar-data:
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etcd:
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minio-data:
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milvus:
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prometheus-data:
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grafana-storage:
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services:
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cassandra:
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image: docker.io/cassandra:4.1.5
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ports:
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- "9042:9042"
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volumes:
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- "cassandra:/var/lib/cassandra"
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restart: on-failure:100
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pulsar:
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image: docker.io/apachepulsar/pulsar:3.3.0
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command: bin/pulsar standalone
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ports:
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- "6650:6650"
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- "8080:8080"
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volumes:
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- "pulsar-conf:/pulsar/conf"
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- "pulsar-data:/pulsar/data"
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restart: on-failure:100
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init-pulsar:
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image: docker.io/apachepulsar/pulsar:3.3.0
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command:
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- "sh"
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- "-c"
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- "pulsar-admin --admin-url http://pulsar:8080 tenants create tg && pulsar-admin --admin-url http://pulsar:8080 namespaces create tg/flow && pulsar-admin --admin-url http://pulsar:8080 namespaces create tg/request && pulsar-admin --admin-url http://pulsar:8080 namespaces create tg/response && pulsar-admin --admin-url http://pulsar:8080 namespaces set-retention --size -1 --time 3m tg/response"
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depends_on:
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pulsar:
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condition: service_started
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restart: on-failure:100
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pulsar-manager:
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image: docker.io/apachepulsar/pulsar-manager:v0.3.0
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ports:
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- "9527:9527"
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- "7750:7750"
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environment:
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SPRING_CONFIGURATION_FILE: /pulsar-manager/pulsar-manager/application.properties
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restart: on-failure:100
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etcd:
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image: quay.io/coreos/etcd:v3.5.5
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command:
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- "etcd"
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- "-advertise-client-urls=http://127.0.0.1:2379"
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- "-listen-client-urls"
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- "http://0.0.0.0:2379"
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- "--data-dir"
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- "/etcd"
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environment:
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ETCD_AUTO_COMPACTION_MODE: revision
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ETCD_AUTO_COMPACTION_RETENTION: "1000"
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ETCD_QUOTA_BACKEND_BYTES: "4294967296"
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ETCD_SNAPSHOT_COUNT: "50000"
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ports:
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- "2379:2379"
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volumes:
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- "etcd:/etcd"
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restart: on-failure:100
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minio:
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image: docker.io/minio/minio:RELEASE.2024-07-04T14-25-45Z
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command:
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- "minio"
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- "server"
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- "/minio_data"
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- "--console-address"
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- ":9001"
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environment:
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MINIO_ROOT_USER: minioadmin
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MINIO_ROOT_PASSWORD: minioadmin
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ports:
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- "9001:9001"
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volumes:
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- "minio-data:/minio_data"
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restart: on-failure:100
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milvus:
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image: docker.io/milvusdb/milvus:v2.4.5
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command:
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- "milvus"
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- "run"
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- "standalone"
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environment:
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ETCD_ENDPOINTS: etcd:2379
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MINIO_ADDRESS: minio:9000
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ports:
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- "9091:9091"
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- "19530:19530"
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volumes:
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- "milvus:/var/lib/milvus"
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restart: on-failure:100
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prometheus:
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image: docker.io/prom/prometheus:v2.53.1
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ports:
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- "9090:9090"
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volumes:
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- "./prometheus:/etc/prometheus"
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- "prometheus-data:/prometheus"
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restart: on-failure:100
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grafana:
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image: docker.io/grafana/grafana:10.0.0
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ports:
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- "3000:3000"
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volumes:
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- "grafana-storage:/var/lib/grafana"
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- "./grafana/dashboard.yml:/etc/grafana/provisioning/dashboards/dashboard.yml"
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- "./grafana/datasource.yml:/etc/grafana/provisioning/datasources/datasource.yml"
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- "./grafana/dashboard.json:/var/lib/grafana/dashboards/dashboard.json"
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environment:
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# GF_AUTH_ANONYMOUS_ORG_ROLE: Admin
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# GF_AUTH_ANONYMOUS_ENABLED: true
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# GF_ORG_ROLE: Admin
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GF_ORG_NAME: trustgraph.ai
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# GF_SERVER_ROOT_URL: https://example.com
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restart: on-failure:100
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pdf-decoder:
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image: docker.io/trustgraph/trustgraph-flow:0.5.6
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command:
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- "pdf-decoder"
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- "-p"
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- "pulsar://pulsar:6650"
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restart: on-failure:100
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chunker:
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image: docker.io/trustgraph/trustgraph-flow:0.5.6
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command:
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- "chunker-recursive"
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- "-p"
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- "pulsar://pulsar:6650"
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- "--chunk-size"
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- "2000"
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- "--chunk-overlap"
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- "100"
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restart: on-failure:100
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vectorize:
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image: docker.io/trustgraph/trustgraph-flow:0.5.6
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command:
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- "embeddings-vectorize"
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- "-p"
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- "pulsar://pulsar:6650"
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restart: on-failure:100
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embeddings:
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image: docker.io/trustgraph/trustgraph-flow:0.5.6
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command:
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- "embeddings-hf"
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- "-p"
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- "pulsar://pulsar:6650"
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# - "-m"
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# - "mixedbread-ai/mxbai-embed-large-v1"
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restart: on-failure:100
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kg-extract-definitions:
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image: docker.io/trustgraph/trustgraph-flow:0.5.6
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command:
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- "kg-extract-definitions"
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- "-p"
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- "pulsar://pulsar:6650"
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restart: on-failure:100
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kg-extract-relationships:
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image: docker.io/trustgraph/trustgraph-flow:0.5.6
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command:
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- "kg-extract-relationships"
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- "-p"
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- "pulsar://pulsar:6650"
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restart: on-failure:100
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store-graph-embeddings:
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image: docker.io/trustgraph/trustgraph-flow:0.5.6
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command:
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- "ge-write-milvus"
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- "-p"
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- "pulsar://pulsar:6650"
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- "-t"
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- "http://milvus:19530"
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restart: on-failure:100
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store-triples:
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image: docker.io/trustgraph/trustgraph-flow:0.5.6
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command:
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- "triples-write-cassandra"
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- "-p"
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- "pulsar://pulsar:6650"
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- "-g"
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- "cassandra"
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restart: on-failure:100
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text-completion:
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image: docker.io/trustgraph/trustgraph-flow:0.5.6
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command:
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- "text-completion-bedrock"
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- "-p"
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- "pulsar://pulsar:6650"
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# - "-k"
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# - ${COHERE_KEY}
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- "-m"
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- "c4ai-aya-23-35b"
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restart: on-failure:100
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text-completion-rag:
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image: docker.io/trustgraph/trustgraph-flow:0.5.6
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command:
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- "text-completion-bedrock"
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- "-p"
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- "pulsar://pulsar:6650"
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# - "-k"
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# - ${COHERE_KEY}
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- "-m"
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- "c4ai-aya-23-8b"
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- "-i"
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- "non-persistent://tg/request/text-completion-rag"
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- "-o"
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- "non-persistent://tg/response/text-completion-rag-response"
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restart: on-failure:100
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#text-completion-rag:
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# image: docker.io/trustgraph/trustgraph-flow:0.5.6
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# command:
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# - "text-completion-ollama"
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# - "-p"
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# - "pulsar://pulsar:6650"
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# - "-r"
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# - "http://${OLLAMA_HOST}:11434/"
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# - "-i"
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# - "non-persistent://tg/request/text-completion-rag"
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# - "-o"
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# - "non-persistent://tg/response/text-completion-rag-response"
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# - "-m"
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# - "gemma2:2b"
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# restart: on-failure:100
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graph-rag:
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image: docker.io/trustgraph/trustgraph-flow:0.5.6
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command:
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- "graph-rag"
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- "-p"
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- "pulsar://pulsar:6650"
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- "--text-completion-request-queue"
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- "non-persistent://tg/request/text-completion-rag"
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- "--text-completion-response-queue"
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- "non-persistent://tg/response/text-completion-rag-response"
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restart: on-failure:100
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6
scripts/text-completion-bedrock
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6
scripts/text-completion-bedrock
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#!/usr/bin/env python3
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from trustgraph.model.text_completion.bedrock import run
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run()
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2
setup.py
2
setup.py
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@ -46,6 +46,7 @@ setuptools.setup(
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"prometheus-client",
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"pyarrow",
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"cohere",
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"boto3",
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],
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scripts=[
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"scripts/chunker-recursive",
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@ -69,6 +70,7 @@ setuptools.setup(
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"scripts/query",
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"scripts/run-processing",
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"scripts/text-completion-azure",
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"scripts/text-completion-bedrock",
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"scripts/text-completion-claude",
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"scripts/text-completion-ollama",
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"scripts/text-completion-vertexai",
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3
trustgraph/model/text_completion/bedrock/__init__.py
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3
trustgraph/model/text_completion/bedrock/__init__.py
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from . llm import *
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7
trustgraph/model/text_completion/bedrock/__main__.py
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7
trustgraph/model/text_completion/bedrock/__main__.py
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#!/usr/bin/env python3
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from . llm import run
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if __name__ == '__main__':
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run()
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122
trustgraph/model/text_completion/bedrock/llm.py
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122
trustgraph/model/text_completion/bedrock/llm.py
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"""
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Simple LLM service, performs text prompt completion using AWS Bedrock.
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Input is prompt, output is response. Mistral is default.
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"""
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import boto3
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import json
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from .... schema import TextCompletionRequest, TextCompletionResponse
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from .... schema import text_completion_request_queue
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from .... schema import text_completion_response_queue
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from .... log_level import LogLevel
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from .... base import ConsumerProducer
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module = ".".join(__name__.split(".")[1:-1])
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default_input_queue = text_completion_request_queue
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default_output_queue = text_completion_response_queue
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default_subscriber = module
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default_model = 'mistral.mistral-large-2407-v1:0'
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class Processor(ConsumerProducer):
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def __init__(self, **params):
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input_queue = params.get("input_queue", default_input_queue)
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output_queue = params.get("output_queue", default_output_queue)
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subscriber = params.get("subscriber", default_subscriber)
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model = params.get("model", default_model)
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api_key = params.get("api_key")
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super(Processor, self).__init__(
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**params | {
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"input_queue": input_queue,
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"output_queue": output_queue,
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"subscriber": subscriber,
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"input_schema": TextCompletionRequest,
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"output_schema": TextCompletionResponse,
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"model": model,
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}
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)
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self.model = model
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self.bedrock = boto3.client(service_name='bedrock-runtime', region_name="us-west-2")
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print("Initialised", flush=True)
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def handle(self, msg):
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v = msg.value()
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# Sender-produced ID
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id = msg.properties()["id"]
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print(f"Handling prompt {id}...", flush=True)
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prompt = v.prompt
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promptbody = json.dumps({
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"prompt": prompt,
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"max_tokens": 8192,
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"temperature": 0.0,
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"top_p": 0.99,
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"top_k": 40
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})
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accept = 'application/json'
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contentType = 'application/json'
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response = self.bedrock.invoke_model(body=promptbody, modelId=self.model, accept=accept, contentType=contentType)
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# Mistral Response Structure
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if self.model.startswith("mistral"):
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response_body = json.loads(response.get("body").read())
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outputtext = response_body['outputs'][0]['text']
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# Claude Response Structure
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elif self.model.startswith("anthropic"):
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model_response = json.loads(response["body"].read())
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outputtext = model_response['content'][0]['text']
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# Llama 3.1 Response Structure
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elif self.model.startswith("meta"):
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model_response = json.loads(response["body"].read())
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outputtext = model_response["generation"]
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# Use Mistral as default
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else:
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response_body = json.loads(response.get("body").read())
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outputtext = response_body['outputs'][0]['text']
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resp = outputtext
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print(resp, flush=True)
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print("Send response...", flush=True)
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r = TextCompletionResponse(response=resp)
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self.send(r, properties={"id": id})
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print("Done.", flush=True)
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@staticmethod
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def add_args(parser):
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ConsumerProducer.add_args(
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parser, default_input_queue, default_subscriber,
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default_output_queue,
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)
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parser.add_argument(
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'-m', '--model',
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default="mistral.mistral-large-2407-v1:0",
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help=f'Bedrock model (default: Mistral-Large-2407)'
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)
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def run():
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Processor.start(module, __doc__)
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