services:
  chunker:
    command:
    - chunker-token
    - -p
    - pulsar://pulsar:6650
    - --chunk-size
    - '150'
    - --chunk-overlap
    - '10'
    deploy:
      resources:
        limits:
          cpus: '0.5'
          memory: 128M
        reservations:
          cpus: '0.1'
          memory: 128M
    image: docker.io/trustgraph/trustgraph-flow:0.11.13
    restart: on-failure:100
  embeddings:
    command:
    - embeddings-hf
    - -p
    - pulsar://pulsar:6650
    - -m
    - all-MiniLM-L6-v2
    deploy:
      resources:
        limits:
          cpus: '1.0'
          memory: 400M
        reservations:
          cpus: '0.5'
          memory: 400M
    image: docker.io/trustgraph/trustgraph-flow:0.11.13
    restart: on-failure:100
  grafana:
    deploy:
      resources:
        limits:
          cpus: '1.0'
          memory: 256M
        reservations:
          cpus: '0.5'
          memory: 256M
    environment:
      GF_ORG_NAME: trustgraph.ai
    image: docker.io/grafana/grafana:11.1.4
    ports:
    - 3000:3000
    restart: on-failure:100
    volumes:
    - grafana-storage:/var/lib/grafana
    - ./grafana/provisioning/:/etc/grafana/provisioning/dashboards/
    - ./grafana/provisioning/:/etc/grafana/provisioning/datasources/
    - ./grafana/dashboards/:/var/lib/grafana/dashboards/
  graph-rag:
    command:
    - graph-rag
    - -p
    - pulsar://pulsar:6650
    - --prompt-request-queue
    - non-persistent://tg/request/prompt-rag
    - --prompt-response-queue
    - non-persistent://tg/response/prompt-rag-response
    - --entity-limit
    - '50'
    - --triple-limit
    - '30'
    - --max-subgraph-size
    - '3000'
    deploy:
      resources:
        limits:
          cpus: '0.5'
          memory: 128M
        reservations:
          cpus: '0.1'
          memory: 128M
    image: docker.io/trustgraph/trustgraph-flow:0.11.13
    restart: on-failure:100
  init-pulsar:
    command:
    - tg-init-pulsar
    - -p
    - http://pulsar:8080
    deploy:
      resources:
        limits:
          cpus: '1'
          memory: 128M
        reservations:
          cpus: '0.1'
          memory: 128M
    image: docker.io/trustgraph/trustgraph-flow:0.11.13
    restart: on-failure:100
  kg-extract-definitions:
    command:
    - kg-extract-definitions
    - -p
    - pulsar://pulsar:6650
    deploy:
      resources:
        limits:
          cpus: '0.5'
          memory: 128M
        reservations:
          cpus: '0.1'
          memory: 128M
    image: docker.io/trustgraph/trustgraph-flow:0.11.13
    restart: on-failure:100
  kg-extract-relationships:
    command:
    - kg-extract-relationships
    - -p
    - pulsar://pulsar:6650
    deploy:
      resources:
        limits:
          cpus: '0.5'
          memory: 128M
        reservations:
          cpus: '0.1'
          memory: 128M
    image: docker.io/trustgraph/trustgraph-flow:0.11.13
    restart: on-failure:100
  kg-extract-topics:
    command:
    - kg-extract-topics
    - -p
    - pulsar://pulsar:6650
    deploy:
      resources:
        limits:
          cpus: '0.5'
          memory: 128M
        reservations:
          cpus: '0.1'
          memory: 128M
    image: docker.io/trustgraph/trustgraph-flow:0.11.13
    restart: on-failure:100
  metering:
    command:
    - metering
    - -p
    - pulsar://pulsar:6650
    deploy:
      resources:
        limits:
          cpus: '0.5'
          memory: 128M
        reservations:
          cpus: '0.1'
          memory: 128M
    image: docker.io/trustgraph/trustgraph-flow:0.11.13
    restart: on-failure:100
  metering-rag:
    command:
    - metering
    - -p
    - pulsar://pulsar:6650
    - -i
    - non-persistent://tg/response/text-completion-rag-response
    deploy:
      resources:
        limits:
          cpus: '0.5'
          memory: 128M
        reservations:
          cpus: '0.1'
          memory: 128M
    image: docker.io/trustgraph/trustgraph-flow:0.11.13
    restart: on-failure:100
  neo4j:
    deploy:
      resources:
        limits:
          cpus: '1.0'
          memory: 768M
        reservations:
          cpus: '0.5'
          memory: 768M
    environment:
      NEO4J_AUTH: neo4j/password
    image: docker.io/neo4j:5.22.0-community-bullseye
    ports:
    - 7474:7474
    - 7687:7687
    restart: on-failure:100
    volumes:
    - neo4j:/data
  pdf-decoder:
    command:
    - pdf-decoder
    - -p
    - pulsar://pulsar:6650
    deploy:
      resources:
        limits:
          cpus: '0.5'
          memory: 128M
        reservations:
          cpus: '0.1'
          memory: 128M
    image: docker.io/trustgraph/trustgraph-flow:0.11.13
    restart: on-failure:100
  prometheus:
    deploy:
      resources:
        limits:
          cpus: '0.5'
          memory: 128M
        reservations:
          cpus: '0.1'
          memory: 128M
    image: docker.io/prom/prometheus:v2.53.2
    ports:
    - 9090:9090
    restart: on-failure:100
    volumes:
    - ./prometheus:/etc/prometheus/
    - prometheus-data:/prometheus
  prompt:
    command:
    - prompt-template
    - -p
    - pulsar://pulsar:6650
    - --text-completion-request-queue
    - non-persistent://tg/request/text-completion
    - --text-completion-response-queue
    - non-persistent://tg/response/text-completion-response
    - --definition-template
    - '<instructions>

      Study the following text and derive definitions for any discovered entities.

      Do not provide definitions for entities whose definitions are incomplete

      or unknown.

      Output relationships in JSON format as an arary of objects with fields:

      - entity: the name of the entity

      - definition: English text which defines the entity

      </instructions>


      <text>

      {text}

      </text>


      <requirements>

      You will respond only with raw JSON format data. Do not provide

      explanations. Do not use special characters in the abstract text. The

      abstract will be written as plain text.  Do not add markdown formatting

      or headers or prefixes.  Do not include null or unknown definitions.

      </requirements>'
    - --relationship-template
    - '<instructions>

      Study the following text and derive entity relationships.  For each

      relationship, derive the subject, predicate and object of the relationship.

      Output relationships in JSON format as an arary of objects with fields:

      - subject: the subject of the relationship

      - predicate: the predicate

      - object: the object of the relationship

      - object-entity: false if the object is a simple data type: name, value or date.  true
      if it is an entity.

      </instructions>


      <text>

      {text}

      </text>


      <requirements>

      You will respond only with raw JSON format data. Do not provide

      explanations. Do not use special characters in the abstract text. The

      abstract must be written as plain text.  Do not add markdown formatting

      or headers or prefixes.

      </requirements>'
    - --topic-template
    - "You are a helpful assistant that performs information extraction tasks for\
      \ a provided text.\nRead the provided text. You will identify topics and their\
      \ definitions in JSON.\n\nReading Instructions:\n- Ignore document formatting\
      \ in the provided text.\n- Study the provided text carefully.\n\nHere is the\
      \ text:\n{text}\n\nResponse Instructions: \n- Do not respond with special characters.\n\
      - Return only topics that are concepts and unique to the provided text.\n- Respond\
      \ only with well-formed JSON.\n- The JSON response shall be an array of objects\
      \ with keys \"topic\" and \"definition\". \n- The JSON response shall use the\
      \ following structure:\n\n```json\n[{{\"topic\": string, \"definition\": string}}]\n\
      ```\n\n- Do not write any additional text or explanations."
    - --knowledge-query-template
    - 'Study the following set of knowledge statements. The statements are written
      in Cypher format that has been extracted from a knowledge graph. Use only the
      provided set of knowledge statements in your response. Do not speculate if the
      answer is not found in the provided set of knowledge statements.


      Here''s the knowledge statements:

      {graph}


      Use only the provided knowledge statements to respond to the following:

      {query}

      '
    - --document-query-template
    - 'Study the following context. Use only the information provided in the context
      in your response. Do not speculate if the answer is not found in the provided
      set of knowledge statements.


      Here is the context:

      {documents}


      Use only the provided knowledge statements to respond to the following:

      {query}

      '
    - --rows-template
    - '<instructions>

      Study the following text and derive objects which match the schema provided.


      You must output an array of JSON objects for each object you discover

      which matches the schema.  For each object, output a JSON object whose fields

      carry the name field specified in the schema.

      </instructions>


      <schema>

      {schema}

      </schema>


      <text>

      {text}

      </text>


      <requirements>

      You will respond only with raw JSON format data. Do not provide

      explanations. Do not add markdown formatting or headers or prefixes.

      </requirements>'
    deploy:
      resources:
        limits:
          cpus: '0.5'
          memory: 128M
        reservations:
          cpus: '0.1'
          memory: 128M
    image: docker.io/trustgraph/trustgraph-flow:0.11.13
    restart: on-failure:100
  prompt-rag:
    command:
    - prompt-template
    - -p
    - pulsar://pulsar:6650
    - -i
    - non-persistent://tg/request/prompt-rag
    - -o
    - non-persistent://tg/response/prompt-rag-response
    - --text-completion-request-queue
    - non-persistent://tg/request/text-completion-rag
    - --text-completion-response-queue
    - non-persistent://tg/response/text-completion-rag-response
    - --definition-template
    - '<instructions>

      Study the following text and derive definitions for any discovered entities.

      Do not provide definitions for entities whose definitions are incomplete

      or unknown.

      Output relationships in JSON format as an arary of objects with fields:

      - entity: the name of the entity

      - definition: English text which defines the entity

      </instructions>


      <text>

      {text}

      </text>


      <requirements>

      You will respond only with raw JSON format data. Do not provide

      explanations. Do not use special characters in the abstract text. The

      abstract will be written as plain text.  Do not add markdown formatting

      or headers or prefixes.  Do not include null or unknown definitions.

      </requirements>'
    - --relationship-template
    - '<instructions>

      Study the following text and derive entity relationships.  For each

      relationship, derive the subject, predicate and object of the relationship.

      Output relationships in JSON format as an arary of objects with fields:

      - subject: the subject of the relationship

      - predicate: the predicate

      - object: the object of the relationship

      - object-entity: false if the object is a simple data type: name, value or date.  true
      if it is an entity.

      </instructions>


      <text>

      {text}

      </text>


      <requirements>

      You will respond only with raw JSON format data. Do not provide

      explanations. Do not use special characters in the abstract text. The

      abstract must be written as plain text.  Do not add markdown formatting

      or headers or prefixes.

      </requirements>'
    - --topic-template
    - "You are a helpful assistant that performs information extraction tasks for\
      \ a provided text.\nRead the provided text. You will identify topics and their\
      \ definitions in JSON.\n\nReading Instructions:\n- Ignore document formatting\
      \ in the provided text.\n- Study the provided text carefully.\n\nHere is the\
      \ text:\n{text}\n\nResponse Instructions: \n- Do not respond with special characters.\n\
      - Return only topics that are concepts and unique to the provided text.\n- Respond\
      \ only with well-formed JSON.\n- The JSON response shall be an array of objects\
      \ with keys \"topic\" and \"definition\". \n- The JSON response shall use the\
      \ following structure:\n\n```json\n[{{\"topic\": string, \"definition\": string}}]\n\
      ```\n\n- Do not write any additional text or explanations."
    - --knowledge-query-template
    - 'Study the following set of knowledge statements. The statements are written
      in Cypher format that has been extracted from a knowledge graph. Use only the
      provided set of knowledge statements in your response. Do not speculate if the
      answer is not found in the provided set of knowledge statements.


      Here''s the knowledge statements:

      {graph}


      Use only the provided knowledge statements to respond to the following:

      {query}

      '
    - --document-query-template
    - 'Study the following context. Use only the information provided in the context
      in your response. Do not speculate if the answer is not found in the provided
      set of knowledge statements.


      Here is the context:

      {documents}


      Use only the provided knowledge statements to respond to the following:

      {query}

      '
    - --rows-template
    - '<instructions>

      Study the following text and derive objects which match the schema provided.


      You must output an array of JSON objects for each object you discover

      which matches the schema.  For each object, output a JSON object whose fields

      carry the name field specified in the schema.

      </instructions>


      <schema>

      {schema}

      </schema>


      <text>

      {text}

      </text>


      <requirements>

      You will respond only with raw JSON format data. Do not provide

      explanations. Do not add markdown formatting or headers or prefixes.

      </requirements>'
    deploy:
      resources:
        limits:
          cpus: '0.5'
          memory: 128M
        reservations:
          cpus: '0.1'
          memory: 128M
    image: docker.io/trustgraph/trustgraph-flow:0.11.13
    restart: on-failure:100
  pulsar:
    command:
    - bin/pulsar
    - standalone
    deploy:
      resources:
        limits:
          cpus: '2.0'
          memory: 1500M
        reservations:
          cpus: '1.0'
          memory: 1500M
    environment:
      PULSAR_MEM: -Xms600M -Xmx600M
    image: docker.io/apachepulsar/pulsar:3.3.1
    ports:
    - 6650:6650
    - 8080:8080
    restart: on-failure:100
    volumes:
    - pulsar-data:/pulsar/data
  qdrant:
    deploy:
      resources:
        limits:
          cpus: '1.0'
          memory: 256M
        reservations:
          cpus: '0.5'
          memory: 256M
    image: docker.io/qdrant/qdrant:v1.11.1
    ports:
    - 6333:6333
    - 6334:6334
    restart: on-failure:100
    volumes:
    - qdrant:/qdrant/storage
  query-doc-embeddings:
    command:
    - de-query-qdrant
    - -p
    - pulsar://pulsar:6650
    - -t
    - http://qdrant:6333
    deploy:
      resources:
        limits:
          cpus: '0.5'
          memory: 128M
        reservations:
          cpus: '0.1'
          memory: 128M
    image: docker.io/trustgraph/trustgraph-flow:0.11.13
    restart: on-failure:100
  query-graph-embeddings:
    command:
    - ge-query-qdrant
    - -p
    - pulsar://pulsar:6650
    - -t
    - http://qdrant:6333
    deploy:
      resources:
        limits:
          cpus: '0.5'
          memory: 128M
        reservations:
          cpus: '0.1'
          memory: 128M
    image: docker.io/trustgraph/trustgraph-flow:0.11.13
    restart: on-failure:100
  query-triples:
    command:
    - triples-query-neo4j
    - -p
    - pulsar://pulsar:6650
    - -g
    - bolt://neo4j:7687
    deploy:
      resources:
        limits:
          cpus: '0.5'
          memory: 128M
        reservations:
          cpus: '0.1'
          memory: 128M
    image: docker.io/trustgraph/trustgraph-flow:0.11.13
    restart: on-failure:100
  store-doc-embeddings:
    command:
    - de-write-qdrant
    - -p
    - pulsar://pulsar:6650
    - -t
    - http://qdrant:6333
    deploy:
      resources:
        limits:
          cpus: '0.5'
          memory: 128M
        reservations:
          cpus: '0.1'
          memory: 128M
    image: docker.io/trustgraph/trustgraph-flow:0.11.13
    restart: on-failure:100
  store-graph-embeddings:
    command:
    - ge-write-qdrant
    - -p
    - pulsar://pulsar:6650
    - -t
    - http://qdrant:6333
    deploy:
      resources:
        limits:
          cpus: '0.5'
          memory: 128M
        reservations:
          cpus: '0.1'
          memory: 128M
    image: docker.io/trustgraph/trustgraph-flow:0.11.13
    restart: on-failure:100
  store-triples:
    command:
    - triples-write-neo4j
    - -p
    - pulsar://pulsar:6650
    - -g
    - bolt://neo4j:7687
    deploy:
      resources:
        limits:
          cpus: '0.5'
          memory: 128M
        reservations:
          cpus: '0.1'
          memory: 128M
    image: docker.io/trustgraph/trustgraph-flow:0.11.13
    restart: on-failure:100
  text-completion:
    command:
    - text-completion-cohere
    - -p
    - pulsar://pulsar:6650
    - -k
    - ${COHERE_KEY}
    - -t
    - '0'
    deploy:
      resources:
        limits:
          cpus: '0.5'
          memory: 128M
        reservations:
          cpus: '0.1'
          memory: 128M
    image: docker.io/trustgraph/trustgraph-flow:0.11.13
    restart: on-failure:100
  text-completion-rag:
    command:
    - text-completion-cohere
    - -p
    - pulsar://pulsar:6650
    - -k
    - ${COHERE_KEY}
    - -t
    - '0'
    - -i
    - non-persistent://tg/request/text-completion-rag
    - -o
    - non-persistent://tg/response/text-completion-rag-response
    deploy:
      resources:
        limits:
          cpus: '0.5'
          memory: 128M
        reservations:
          cpus: '0.1'
          memory: 128M
    image: docker.io/trustgraph/trustgraph-flow:0.11.13
    restart: on-failure:100
  vectorize:
    command:
    - embeddings-vectorize
    - -p
    - pulsar://pulsar:6650
    deploy:
      resources:
        limits:
          cpus: '1.0'
          memory: 512M
        reservations:
          cpus: '0.5'
          memory: 512M
    image: docker.io/trustgraph/trustgraph-flow:0.11.13
    restart: on-failure:100
volumes:
  grafana-storage: {}
  neo4j: {}
  prometheus-data: {}
  pulsar-data: {}
  qdrant: {}