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docs/build/mapping-creator/index.md

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## Configuration Info
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A specific configuration is require to activate this feature.
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Furthermore, for best experience an LLM provider configuration is also needed.
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A specific configuration is required to activate this feature.
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Furthermore, for the best experience, an LLM provider configuration is also needed.
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See the link in the info box for details.
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!!! info "Configuration"
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## Usage
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The Mapping Creator is a feature of BUILD transformation tasks (_BUILD_> _Project_> (_Workflow_>) _Transformation_> _Mapping Creator_).
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The Mapping Creator is a feature of BUILD transformation tasks (_BUILD_ > _Project_ > (_Workflow_ >) _Transformation_ > _Mapping Creator_).
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!!! question "Help"
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Access help and a feature tour via the help menu :eccenca-item-question:.
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Use the Mapping Creator to connect your data to semantic models.
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Using visual tools, drag-and-drop, and suggestions, you are able to create mappings between your source data and knowledge graph classes as well as their properties.
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Using visual tools, drag-and-drop, and suggestions, you can create mappings between your source data and knowledge graph classes as well as their properties.
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![Mapping Creator](mapping-creator.png){ class="bordered" }
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### Manual creation
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To start a mapping you need to select or define a target class first.
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The target class defines where your data will be be mapped in the knowledge graph.
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The target class defines where your data will be mapped in the knowledge graph.
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#### Add properties
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![Resource edit actions](mapping-creator-edit-actions.png){ class="bordered" width="40%" }
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To complete a mapping properties need to be added to complete your desired target schema (i.e. the graph fragment that your transformation shall yield).
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To complete a mapping, properties need to be added to complete your desired target schema (i.e. the graph fragment that your transformation shall yield).
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There are two options to add properties:
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In the _add target class_ dialog you may select different kind of properties:
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- class properties - properties defined in the domain of the selected class or its super-classes
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- default properties - typical well knows like `rdfs:label` or `rdfs:comment`
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- default properties - typical well-known properties like `rdfs:label` or `rdfs:comment`
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- generic properties - properties defined with no explicit domain (or in domain of `owl:Thing`)
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The property preview helps to confirm your choice.
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![Adding a property from your vocabulary](mapping-creator-property-selection.png){ class="bordered" width="80%" }
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The _add property from vocabularies_ dialog allows to search and select a property and to configure it in the desired way:
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The _add property from vocabularies_ dialog allows you to search and select a property and to configure it in the desired way:
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- redefine the role of a property, to use a DatatypeProperty in the role of an ObjectProperty, or vice versa
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- define the _direction_ an ObjectProperty should be used in
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![Smart Property Suggestions](smart-suggestions.png){ class="bordered" }
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Once the smart suggestions have been generated, you need do two steps:
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Once the smart suggestions have been generated, you need to perform two steps:
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1. For each property, decide whether to accept or reject the AI-generated mapping.
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Click :octicons-thumbsup-16: Confirm to accept or :octicons-thumbsdown-16: Decline to reject.

docs/explore-and-author/companion/index.md

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## Configuration Info
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A specific configuration is require to activate this feature.
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Our deployment templates (helm charts and docker-compose configurations) provide testes configuration profiles for different LLM providers.
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A specific configuration is required to activate this feature.
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Our deployment templates (helm charts and docker-compose configurations) provide tested configuration profiles for different LLM providers.
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See the link in the info box for details.
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!!! info "Configuration"
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See [`spring.ai.*` configuration properties in _Configuration of Servlet Container_](../../deploy-and-configure/configuration/explore/dataplatform/application-full.md#configuration-of-servlet-container) to learn how to enable and configure this feature.
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Explore uses _Spring AI_ to connect and configure LLM provider, as such the [Spring AI Chat Model API Configuration Reference](https://docs.spring.io/spring-ai/reference/api/chatmodel.html) applies.
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For optimal results, we recommend using Anthropic or OpenAI frontier-level models configured through the native Spring AI provider setup.
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## Usage
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![Companion Menu Button](companion-button.png){ class="bordered" width="40%" }
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You can open the _Chat with Companion_ from any explore module via the :eccenca-application-ai-suggestion: Companion button the top right of the application header, next to the :eccenca-application-useraccount: user menu.
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You can open the _Chat with Companion_ from any explore module via the :eccenca-application-ai-suggestion: Companion button in the top right of the application header, next to the :eccenca-application-useraccount: user menu.
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![Companion Chat](companion-anatomy.jpg){ class="bordered" width="60%" }
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- :eccenca-toggler-maximize: to increase the size of the sidebar
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- :eccenca-toggler-minimize: to decrease the size of the sidebar
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- :eccenca-item-add-artefact: to start a new conversation
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- the dropdown menu to select or search for a conversation
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- :octicons-triangle-down-24: the dropdown menu to select or search for a conversation
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- :eccenca-item-upload: to add documents as context to the chat (supported formats include `pdf`, `txt` and `md`)
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- :eccenca-item-wrench: to configure the tools that the LLM can use to answer.
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- :eccenca-item-wrench: to use your microphone to dictate your questions
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- :eccenca-item-microphone: to use your microphone to dictate your questions
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- :material-send-variant-outline: to submit your question
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To maximise the relevance and accuracy of the generated answer, your question is automatically enriched based on the context of the current view (e.g. the query text, the graph and the resource IRI).
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To maximize the relevance and accuracy of the generated answer, your question is automatically enriched based on the context of the current view (e.g. the query text, the graph and the resource IRI).
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### Tool selection
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`query_execute_saved`
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: Executes a saved SPARQL query on this corporate memory instance.
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The query is identified by it's IRI.
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The query is identified by its IRI.
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- Query related:
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`vocabularies_property_list`
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: All Properties defined in this knowledge graph by installed vocabularies.
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While all properties are returned, they can easy be grouped by either their explicit association with an ontology in the isDefinedBy (`rdfs:isDefinedBy`) field, or by the sourceGraph field, which contains the names of the graphs from which the type statements were loaded from.
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While all properties are returned, they can easily be grouped by either their explicit association with an ontology in the isDefinedBy (`rdfs:isDefinedBy`) field, or by the sourceGraph field, which contains the names of the graphs from which the type statements were loaded.
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`vocabularies_class_list`
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: All Classes defined in this knowledge graph by installed vocabularies.
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While all classes are returned, they can easy be grouped by either their explicit association with an ontology in the isDefinedBy (`rdfs:isDefinedBy`) field, or by the sourceGraph field, which contains the names of the graphs from which the type statements were loaded from.
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While all classes are returned, they can easily be grouped by either their explicit association with an ontology in the isDefinedBy (`rdfs:isDefinedBy`) field, or by the sourceGraph field, which contains the names of the graphs from which the type statements were loaded.
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- Resource related
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`resource_search`
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: Performs a lucene syntax full text search of labels and descriptions for 'searchTerm' and retrieve list of best matches.
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The context graph will restrict the search to it includes, or search the full graph. Pattern allows to define a `SPARQL WHERE` clause snippet, which defaults to `{GRAPH ?contextGraph {?resource ?p ?o}}`.
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The context graph will restrict the search to its includes, or search the full graph. Pattern allows to define a `SPARQL WHERE` clause snippet, which defaults to `{GRAPH ?contextGraph {?resource ?p ?o}}`.
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Search will always be on the `?resource`, so adjust the pattern, if needed.
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`resource_get`
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docs/explore-and-author/graph-exploration/graph-insights/index.md

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# Graph Insights
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![Explore - Graph Insights](explore-graph-insights.png "Explore - Graph Insights"){ class="bordered" }
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## Introduction
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...
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Graph Insights allows you to explore your knowledge graph through grouped nodes and aggregated relations to keep the view readable.
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Expansions are data-guided to avoid dead ends, while on-demand details give you context without clutter.
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Interactive filters help you shape the exploration, building query paths with class, attribute, and relation filters along the way.
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Each exploration can be converted to SPARQL, effectively serving as a no-code query builder. This also provides table-like views for users less familiar with graphs.
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## Configuration Info
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A specific configuration is required to activate this feature.
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!!! info "Configuration"
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See [Graph Insights Configuration](../../../deploy-and-configure/configuration/graphinsights/index.md) to learn how to enable and configure this feature.
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<!--
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## Usage
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...
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-->
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## Management
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In order to manage Graph Insights snapshots, you can use the
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[`graph insights`](../../../automate/cmemc-command-line-interface/command-reference/graph/insights/index.md)
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command group of cmemc.
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With this command group, you can list, create, delete and inspect graph insight snapshots.
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With this command group, you can list, create, delete, and inspect graph insight snapshots.
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## Automation
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To automate re-creation of Graph Insights snapshots, you can use the
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[Update Snapshots](../../../build/reference/customtask/cmem_plugin_graph_insights-Update.md)
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task in your workflows.
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This tasks allows for updating snapshots based on the specification of an
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affected graph.
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This task allows for updating snapshots based on the specification of an affected graph.

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