mirror of
https://github.com/trustgraph-ai/trustgraph.git
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feat: workspace-based multi-tenancy, replacing user as tenancy axis (#840)
Introduces `workspace` as the isolation boundary for config, flows,
library, and knowledge data. Removes `user` as a schema-level field
throughout the code, API specs, and tests; workspace provides the
same separation more cleanly at the trusted flow.workspace layer
rather than through client-supplied message fields.
Design
------
- IAM tech spec (docs/tech-specs/iam.md) documents current state,
proposed auth/access model, and migration direction.
- Data ownership model (docs/tech-specs/data-ownership-model.md)
captures the workspace/collection/flow hierarchy.
Schema + messaging
------------------
- Drop `user` field from AgentRequest/Step, GraphRagQuery,
DocumentRagQuery, Triples/Graph/Document/Row EmbeddingsRequest,
Sparql/Rows/Structured QueryRequest, ToolServiceRequest.
- Keep collection/workspace routing via flow.workspace at the
service layer.
- Translators updated to not serialise/deserialise user.
API specs
---------
- OpenAPI schemas and path examples cleaned of user fields.
- Websocket async-api messages updated.
- Removed the unused parameters/User.yaml.
Services + base
---------------
- Librarian, collection manager, knowledge, config: all operations
scoped by workspace. Config client API takes workspace as first
positional arg.
- `flow.workspace` set at flow start time by the infrastructure;
no longer pass-through from clients.
- Tool service drops user-personalisation passthrough.
CLI + SDK
---------
- tg-init-workspace and workspace-aware import/export.
- All tg-* commands drop user args; accept --workspace.
- Python API/SDK (flow, socket_client, async_*, explainability,
library) drop user kwargs from every method signature.
MCP server
----------
- All tool endpoints drop user parameters; socket_manager no longer
keyed per user.
Flow service
------------
- Closure-based topic cleanup on flow stop: only delete topics
whose blueprint template was parameterised AND no remaining
live flow (across all workspaces) still resolves to that topic.
Three scopes fall out naturally from template analysis:
* {id} -> per-flow, deleted on stop
* {blueprint} -> per-blueprint, kept while any flow of the
same blueprint exists
* {workspace} -> per-workspace, kept while any flow in the
workspace exists
* literal -> global, never deleted (e.g. tg.request.librarian)
Fixes a bug where stopping a flow silently destroyed the global
librarian exchange, wedging all library operations until manual
restart.
RabbitMQ backend
----------------
- heartbeat=60, blocked_connection_timeout=300. Catches silently
dead connections (broker restart, orphaned channels, network
partitions) within ~2 heartbeat windows, so the consumer
reconnects and re-binds its queue rather than sitting forever
on a zombie connection.
Tests
-----
- Full test refresh: unit, integration, contract, provenance.
- Dropped user-field assertions and constructor kwargs across
~100 test files.
- Renamed user-collection isolation tests to workspace-collection.
This commit is contained in:
parent
9332089b3d
commit
d35473f7f7
377 changed files with 6868 additions and 5785 deletions
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@ -10,11 +10,10 @@ post:
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Collections are organizational units for grouping:
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- Documents in the librarian
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- Knowledge cores
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- User data
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- Workspace data
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Each collection has:
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- **user**: Owner identifier
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- **collection**: Unique collection ID
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- **collection**: Unique collection ID (within the workspace)
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- **name**: Human-readable display name
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- **description**: Purpose and contents
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- **tags**: Labels for filtering and organization
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@ -22,7 +21,7 @@ post:
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## Operations
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### list-collections
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List all collections for a user. Optionally filter by tags and limit results.
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List all collections in the workspace. Optionally filter by tags and limit results.
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Returns array of collection metadata.
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### update-collection
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@ -30,7 +29,7 @@ post:
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If it exists, metadata is updated. Allows setting name, description, and tags.
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### delete-collection
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Delete a collection by user and collection ID. This removes the metadata but
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Delete a collection by collection ID. This removes the metadata but
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typically does not delete the associated data (documents, knowledge cores).
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operationId: collectionManagementService
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@ -44,22 +43,19 @@ post:
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$ref: '../components/schemas/collection/CollectionRequest.yaml'
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examples:
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listCollections:
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summary: List all collections for user
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summary: List all collections in workspace
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value:
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operation: list-collections
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user: alice
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listCollectionsFiltered:
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summary: List collections filtered by tags
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value:
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operation: list-collections
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user: alice
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tag-filter: ["research", "AI"]
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limit: 50
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updateCollection:
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summary: Create/update collection
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value:
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operation: update-collection
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user: alice
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collection: research
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name: Research Papers
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description: Academic research papers on AI and ML
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summary: Delete collection
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value:
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operation: delete-collection
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user: alice
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collection: research
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responses:
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'200':
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@ -84,13 +79,11 @@ post:
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value:
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timestamp: "2024-01-15T10:30:00Z"
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collections:
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- user: alice
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collection: research
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- collection: research
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name: Research Papers
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description: Academic research papers on AI and ML
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tags: ["research", "AI", "academic"]
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- user: alice
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collection: personal
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- collection: personal
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name: Personal Documents
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description: Personal notes and documents
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tags: ["personal"]
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@ -8,7 +8,6 @@ get:
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## Parameters
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- `user`: User identifier (required)
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- `document-id`: Document IRI to retrieve (required)
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- `chunk-size`: Size of each response chunk in bytes (optional, default: 1MB)
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security:
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- bearerAuth: []
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parameters:
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- name: user
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in: query
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required: true
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schema:
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type: string
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description: User identifier
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example: trustgraph
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- name: document-id
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in: query
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required: true
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@ -23,7 +23,6 @@ get:
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"m": { // Metadata
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"i": "core-id", // Knowledge core ID
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"m": [...], // Metadata triples array
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"u": "user", // User
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"c": "collection" // Collection
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},
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"t": [...] // Triples array
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"m": { // Metadata
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"i": "core-id",
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"m": [...],
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"u": "user",
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"c": "collection"
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},
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"e": [ // Entities array
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## Query Parameters
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- **id**: Knowledge core ID to export
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- **user**: User identifier
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## Streaming
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type: string
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description: Knowledge core ID to export
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example: core-123
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- name: user
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in: query
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required: true
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schema:
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type: string
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description: User identifier
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example: alice
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responses:
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'200':
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description: Export stream
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summary: Simple question
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value:
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question: What is the capital of France?
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user: alice
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streamingQuestion:
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summary: Question with streaming enabled
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value:
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question: Explain quantum computing
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user: alice
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streaming: true
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conversationWithHistory:
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summary: Multi-turn conversation
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value:
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question: And what about its population?
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user: alice
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history:
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- thought: User is asking about the capital of France
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action: search
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arguments:
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query: "capital of France"
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observation: "Paris is the capital of France"
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user: alice
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responses:
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'200':
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description: Successful response
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value:
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vectors: [0.023, -0.142, 0.089, 0.234, -0.067, 0.156, 0.201, -0.178]
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limit: 10
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user: alice
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collection: research
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largeQuery:
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summary: Larger result set
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value:
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data: JVBERi0xLjQKJeLjz9MKMSAwIG9iago8PC9UeXBlL0NhdGFsb2cvUGFnZXMgMiAwIFI+PmVuZG9iagoyIDAgb2JqCjw8L1R5cGUvUGFnZXMvS2lkc1szIDAgUl0vQ291bnQgMT4+ZW5kb2JqCg==
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id: doc-789
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user: alice
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collection: research
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withMetadata:
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summary: Load with metadata
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value:
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data: JVBERi0xLjQKJeLjz9MK...
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id: doc-101112
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user: bob
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collection: papers
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metadata:
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- s: {v: "doc-101112", e: false}
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- Higher = more context but slower
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- Lower = faster but may miss relevant info
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- **collection**: Target specific document collection
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- **user**: Multi-tenant isolation
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operationId: documentRagService
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security:
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summary: Basic document query
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value:
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query: What are the key findings in the research papers?
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user: alice
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collection: research
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streamingQuery:
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summary: Streaming query
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value:
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query: Summarize the main conclusions
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user: alice
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collection: research
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doc-limit: 15
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streaming: true
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value:
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vectors: [0.023, -0.142, 0.089, 0.234, -0.067, 0.156, 0.201, -0.178]
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limit: 10
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user: alice
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collection: research
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largeQuery:
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summary: Larger result set
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summary: Basic graph query
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value:
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query: What connections exist between quantum physics and computer science?
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user: alice
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collection: research
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streamingQuery:
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summary: Streaming query with custom limits
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value:
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query: Trace the historical development of AI from Turing to modern LLMs
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user: alice
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collection: research
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entity-limit: 40
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triple-limit: 25
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vectors: [0.023, -0.142, 0.089, 0.234, -0.067, 0.156, 0.201, -0.178]
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schema_name: customers
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limit: 10
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user: alice
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collection: sales
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filteredQuery:
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summary: Search specific index
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email
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}
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}
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user: alice
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collection: research
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queryWithVariables:
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summary: Query with variables
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query:
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type: string
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description: SPARQL 1.1 query string
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user:
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type: string
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default: trustgraph
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description: User/keyspace identifier
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collection:
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type: string
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default: default
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summary: SELECT query
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value:
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query: "SELECT ?s ?p ?o WHERE { ?s ?p ?o } LIMIT 10"
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user: trustgraph
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collection: default
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askQuery:
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summary: ASK query
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summary: Simple relationship question
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value:
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question: Who does Alice know?
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user: alice
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collection: research
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complexQuestion:
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summary: Complex multi-hop question
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value:
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question: What companies employ engineers that Bob collaborates with?
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user: bob
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collection: work
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filterQuestion:
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summary: Question with implicit filters
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value:
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text: This is the document text...
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id: doc-123
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user: alice
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collection: research
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withMetadata:
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summary: Load with RDF metadata using base64 text
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value:
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text: UXVhbnR1bSBjb21wdXRpbmcgdXNlcyBxdWFudHVtIG1lY2hhbmljcyBwcmluY2lwbGVzLi4u
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id: doc-456
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user: alice
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collection: research
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metadata:
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- s: {v: "doc-456", e: false}
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s:
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v: https://example.com/person/alice
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e: true
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user: alice
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collection: research
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limit: 100
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allInstancesOfType:
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p:
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v: https://example.com/knows
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e: true
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user: alice
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limit: 200
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responses:
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'200':
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"m": { // Metadata
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"i": "core-id", // Knowledge core ID
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"m": [...], // Metadata triples array
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"u": "user", // User
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"c": "collection" // Collection
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},
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"t": [...] // Triples array
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"m": { // Metadata
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"i": "core-id",
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"m": [...],
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"u": "user",
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"c": "collection"
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},
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"e": [ // Entities array
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## Query Parameters
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- **id**: Knowledge core ID
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- **user**: User identifier
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## Streaming
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type: string
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description: Knowledge core ID to import
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example: core-123
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- name: user
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in: query
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required: true
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schema:
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type: string
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description: User identifier
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example: alice
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requestBody:
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required: true
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content:
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- **Graph Embeddings**: Vector embeddings for entities
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- **Metadata**: Descriptive information about the knowledge
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Each core has an ID, user, and collection for organization.
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Each core has an ID and collection for organization (within the workspace).
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## Operations
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### list-kg-cores
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List all knowledge cores for a user. Returns array of core IDs.
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List all knowledge cores in the workspace. Returns array of core IDs.
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### get-kg-core
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Retrieve a knowledge core by ID. Returns triples and/or graph embeddings.
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summary: List knowledge cores
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value:
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operation: list-kg-cores
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user: alice
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getKnowledgeCore:
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summary: Get knowledge core
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value:
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triples:
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metadata:
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id: core-123
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user: alice
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collection: default
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metadata:
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- s: {v: "https://example.com/core-123", e: true}
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graph-embeddings:
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metadata:
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id: core-123
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user: alice
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collection: default
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metadata: []
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entities:
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triples:
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metadata:
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id: core-456
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user: bob
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collection: research
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metadata: []
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triples:
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graph-embeddings:
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metadata:
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id: core-456
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user: bob
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collection: research
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metadata: []
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entities:
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value:
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operation: delete-kg-core
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id: core-123
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user: alice
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loadKnowledgeCore:
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summary: Load core into flow
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value:
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triples:
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metadata:
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id: core-123
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user: alice
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collection: default
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metadata:
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- s: {v: "https://example.com/core-123", e: true}
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graph-embeddings:
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metadata:
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id: core-123
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user: alice
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collection: default
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metadata: []
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entities:
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