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info:
title: Scalable Graph ML Research API
description: |
REST API for interactively testing PhD research methods from
"Scalable Methods for Knowledge Graph Reasoning and Generation"
(Andrej Janchevski, EPFL, 2025).
Three research methods are exposed:
- **COINs**: Community-Informed Graph Embeddings for KG link prediction and query answering
- **MultiProxAn**: Discrete denoising diffusion for graph generation with MultiProx sampling
- **KG Anomaly Correction**: Diffusion-based knowledge graph subgraph correction
The API is stateless (no database). Model checkpoints are loaded in memory at startup.
A single inference queue ensures only one inference runs at a time (429 if busy).
version: 1.0.0
contact:
name: Andrej Janchevski
url: https://bani57.pythonanywhere.com
servers:
- url: /api/v1
description: API v1
tags:
- name: health
description: Server health and method discovery
- name: coins
description: COINs - Knowledge Graph Reasoning
- name: graph-generation
description: MultiProxAn - Graph Generation
- name: kg-anomaly
description: KG Anomaly Correction
paths:
# -- Health ----------------------------------------------------------
/health:
get:
operationId: getHealth
tags: [health]
summary: Server health check
description: Returns server status and which model groups are loaded.
responses:
"200":
description: Server is healthy
content:
application/json:
schema:
$ref: "#/components/schemas/HealthResponse"
/methods:
get:
operationId: getMethods
tags: [health]
summary: List research methods
description: Returns the three research methods available on this API.
responses:
"200":
description: List of methods
content:
application/json:
schema:
$ref: "#/components/schemas/MethodsResponse"
/debug/force-unlock:
post:
operationId: forceUnlockInferenceLock
tags: [health]
summary: Release a stuck inference lock (debug only)
description: |
Forcibly releases the global inference lock. Only available when
the server is running with `DJANGO_DEBUG=True`; returns `403` in
production. Use when a crashed request left the lock held and
subsequent requests are returning `429 INFERENCE_BUSY`.
responses:
"200":
description: Lock release result
content:
application/json:
schema:
type: object
required: [released]
properties:
released:
type: boolean
description: True if a held lock was released; false if the lock was already free.
example: true
"403":
description: Not available outside debug mode
content:
application/json:
schema:
type: object
properties:
error:
type: string
example: only available in debug mode
# -- COINs -----------------------------------------------------------
/coins/datasets:
get:
operationId: getCoinsDatasets
tags: [coins]
summary: List KG datasets
description: Returns available knowledge graph datasets with entity and relation counts.
responses:
"200":
description: Dataset list
content:
application/json:
schema:
$ref: "#/components/schemas/CoinsDatasetsResponse"
/coins/datasets/{dataset_id}/entities:
get:
operationId: getCoinsEntities
tags: [coins]
summary: List entities in a dataset
description: Paginated, searchable list of entities.
parameters:
- $ref: "#/components/parameters/CoinsDatasetId"
- $ref: "#/components/parameters/SearchQuery"
- $ref: "#/components/parameters/Page"
- $ref: "#/components/parameters/PageSize"
responses:
"200":
description: Paginated entity list
content:
application/json:
schema:
$ref: "#/components/schemas/CoinsEntitiesResponse"
"404":
$ref: "#/components/responses/NotFound"
/coins/datasets/{dataset_id}/relations:
get:
operationId: getCoinsRelations
tags: [coins]
summary: List relations in a dataset
description: Paginated, searchable list of relations.
parameters:
- $ref: "#/components/parameters/CoinsDatasetId"
- $ref: "#/components/parameters/SearchQuery"
- $ref: "#/components/parameters/Page"
- $ref: "#/components/parameters/PageSize"
responses:
"200":
description: Paginated relation list
content:
application/json:
schema:
$ref: "#/components/schemas/CoinsRelationsResponse"
"404":
$ref: "#/components/responses/NotFound"
/coins/datasets/{dataset_id}/sample-triples:
get:
operationId: getCoinsSampleTriples
tags: [coins]
summary: Random sample triples
description: Returns random triples from the dataset, useful for populating example queries.
parameters:
- $ref: "#/components/parameters/CoinsDatasetId"
- name: count
in: query
schema:
type: integer
minimum: 1
maximum: 50
default: 10
description: Number of random triples to return
- name: seed
in: query
required: false
schema:
type: string
description: |
Optional sampling seed. When provided, sampling is deterministic —
the same `(dataset_id, count, seed)` always yields the same triples.
Useful for day-stable "fact of the day" widgets (e.g. seed by the
ISO date). When omitted, sampling is fully random.
example: "2026-04-15"
responses:
"200":
description: Sample triples
content:
application/json:
schema:
$ref: "#/components/schemas/CoinsSampleTriplesResponse"
"404":
$ref: "#/components/responses/NotFound"
/coins/datasets/{dataset_id}/sample-query:
get:
operationId: getCoinsSampleQuery
tags: [coins]
summary: Sample a valid KG query
description: |
Walks the training knowledge graph to produce a structurally valid query
for the given query structure. Each returned query contains anchor entities,
relations, and a known target entity — guaranteed to form a real path or
intersection in the KG. This is the recommended way to populate the query
builder UI with meaningful defaults. For simple 1p (single-hop) queries the
result is equivalent to a random triple; for multi-hop and intersection
structures (2p, 3p, 2i, 3i, ip, pi) the sampler walks backward from a
random target through actual KG edges.
parameters:
- $ref: "#/components/parameters/CoinsDatasetId"
- name: query_structure
in: query
required: true
schema:
$ref: "#/components/schemas/CoinsQueryStructureEnum"
description: The query structure to sample for.
- name: count
in: query
schema:
type: integer
minimum: 1
maximum: 10
default: 1
description: Number of sample queries to return.
- name: seed
in: query
required: false
schema:
type: string
description: |
Optional sampling seed for deterministic results. Same
`(dataset_id, query_structure, count, seed)` always yields the
same queries. Useful for day-stable prefills (e.g. seed by ISO date).
example: "2026-04-17"
responses:
"200":
description: Sampled queries
content:
application/json:
schema:
$ref: "#/components/schemas/CoinsSampleQueryResponse"
"400":
$ref: "#/components/responses/InvalidRequest"
"404":
$ref: "#/components/responses/NotFound"
/coins/models:
get:
operationId: getCoinsModels
tags: [coins]
summary: List embedding algorithms
description: |
Returns available embedding algorithms with their supported query structures
and datasets. TransE, DistMult, ComplEx, RotatE support 1p only.
Q2B supports all query structures (1p, 2p, 3p, 2i, 3i, ip, pi).
TransE, DistMult, ComplEx, RotatE, and KBGAT support 1p only.
responses:
"200":
description: Algorithm list
content:
application/json:
schema:
$ref: "#/components/schemas/CoinsModelsResponse"
/coins/query-structures:
get:
operationId: getCoinsQueryStructures
tags: [coins]
summary: Query structure graph templates
description: |
Returns a graph template per query structure. Each template defines nodes
(anchor, variable, target) and edges that the frontend renders as a small
interactive graph with entity dropdowns on anchor nodes and relation
dropdowns on edges.
responses:
"200":
description: Query structure templates
content:
application/json:
schema:
$ref: "#/components/schemas/CoinsQueryStructuresResponse"
/coins/predict:
post:
operationId: coinsPredict
tags: [coins]
summary: Run link prediction / query answering
description: |
Submit a filled-in query graph and get ranked entity predictions for the
target node. The `anchors` and `relations` keys must match the node and
edge IDs from the query structure template.
The response includes per-step timing (Step 1: community detection +
localized embedding, Step 2: link prediction) and a simulated baseline
estimate showing the COINs speedup.
requestBody:
required: true
content:
application/json:
schema:
$ref: "#/components/schemas/CoinsPredictRequest"
examples:
single_hop:
summary: "1p - single hop"
value:
dataset_id: wordnet
algorithm: rotate
query_structure: "1p"
anchors: { "a": 11754 }
relations: { "r1": 3 }
top_k: 10
two_intersection:
summary: "2i - two-way intersection"
value:
dataset_id: wordnet
algorithm: q2b
query_structure: "2i"
anchors: { "a1": 11754, "a2": 5142 }
relations: { "r1": 3, "r2": 1 }
top_k: 10
intersection_projection:
summary: "ip - intersection then projection"
value:
dataset_id: wordnet
algorithm: q2b
query_structure: ip
anchors: { "a1": 11754, "a2": 5142 }
relations: { "r1": 3, "r2": 1, "r3": 2 }
top_k: 10
responses:
"200":
description: Ranked predictions
content:
application/json:
schema:
$ref: "#/components/schemas/CoinsPredictResponse"
"400":
$ref: "#/components/responses/InvalidRequest"
"404":
$ref: "#/components/responses/NotFound"
"422":
$ref: "#/components/responses/InferenceError"
"429":
$ref: "#/components/responses/InferenceBusy"
"503":
$ref: "#/components/responses/ModelUnavailable"
# -- Graph Generation ------------------------------------------------
/graph-generation/datasets:
get:
operationId: getGraphGenDatasets
tags: [graph-generation]
summary: List graph generation datasets
description: Returns available graph types with node/edge type info and model availability.
responses:
"200":
description: Dataset list
content:
application/json:
schema:
$ref: "#/components/schemas/GraphGenDatasetsResponse"
/graph-generation/sampling-modes:
get:
operationId: getGraphGenSamplingModes
tags: [graph-generation]
summary: List sampling strategies
description: Returns available sampling modes (standard, multiprox) with parameter specs.
responses:
"200":
description: Sampling mode list
content:
application/json:
schema:
$ref: "#/components/schemas/GraphGenSamplingModesResponse"
/graph-generation/generate:
post:
operationId: graphGenGenerate
tags: [graph-generation]
summary: Generate a graph (SSE streaming)
description: |
Server-Sent Events stream (`text/event-stream`). Emits `progress`
events during diffusion, optional `preview` events with intermediate
PNGs, and a terminal `result` event whose `data` payload is the JSON
described below.
**Standard mode**: runs full diffusion (T->0); terminal `result`
payload conforms to `GraphGenStandardResponse` (animated GIF + final PNG).
**MultiProx mode**: runs the first Gibbs iteration; terminal `result`
payload conforms to `GraphGenMultiProxResponse` and includes an opaque
`state` blob to be passed to `/graph-generation/continue`.
requestBody:
required: true
content:
application/json:
schema:
$ref: "#/components/schemas/GraphGenGenerateRequest"
examples:
standard_qm9:
summary: Standard QM9 molecule generation
value:
dataset_id: qm9
model_type: discrete
sampling_mode: standard
num_nodes: null
diffusion_steps: 500
chain_frames: 20
multiprox_comm20:
summary: MultiProx Community20 generation
value:
dataset_id: comm20
model_type: discrete
sampling_mode: multiprox
num_nodes: null
diffusion_steps: 500
multiprox_params:
m: 10
t: 0.5
t_prime: 0.1
responses:
"200":
description: SSE stream of progress/preview events terminated by a result event
content:
text/event-stream:
schema:
$ref: "#/components/schemas/GraphGenSseStream"
"400":
$ref: "#/components/responses/InvalidRequest"
"429":
$ref: "#/components/responses/InferenceBusy"
"503":
$ref: "#/components/responses/ModelUnavailable"
/graph-generation/continue:
post:
operationId: graphGenContinue
tags: [graph-generation]
summary: Advance MultiProx generation by one step (SSE streaming)
description: |
SSE stream (`text/event-stream`). Advances the MultiProx
multi-measurement chain by one Gibbs iteration. The client must send
back the opaque `state` from the previous step's `result` event.
Emits `progress` and `preview` events, then a terminal `result` event
with the `GraphGenMultiProxResponse` payload (including the updated
`state`). The API remains fully stateless -- no server-side sessions.
requestBody:
required: true
content:
application/json:
schema:
$ref: "#/components/schemas/GraphGenContinueRequest"
responses:
"200":
description: SSE stream of progress/preview events terminated by a result event
content:
text/event-stream:
schema:
$ref: "#/components/schemas/GraphGenSseStream"
"400":
$ref: "#/components/responses/InvalidRequest"
"429":
$ref: "#/components/responses/InferenceBusy"
# -- KG Anomaly Correction ------------------------------------------
/kg-anomaly/datasets:
get:
operationId: getKgAnomalyDatasets
tags: [kg-anomaly]
summary: List KG anomaly correction datasets
description: Returns datasets for which correction models are available.
responses:
"200":
description: Dataset list
content:
application/json:
schema:
$ref: "#/components/schemas/KgAnomalyDatasetsResponse"
/kg-anomaly/datasets/{dataset_id}/sample-subgraphs:
get:
operationId: getKgAnomalySampleSubgraphs
tags: [kg-anomaly]
summary: Get example subgraphs for correction
description: |
Returns pre-computed example subgraphs from the test set. When
`noise_level` is supplied, the model's forward diffusion is applied
to each subgraph's edges so the caller receives a corrupted input
ready for `/kg-anomaly/correct`. For `task=correct` only the edges
inside the inpaint mask (second half of nodes) are noised; for
`task=generate` every edge is noised.
parameters:
- $ref: "#/components/parameters/KgAnomalyDatasetId"
- name: count
in: query
schema:
type: integer
minimum: 1
maximum: 10
default: 5
description: Number of sample subgraphs to return
- name: noise_level
in: query
required: false
schema:
type: number
minimum: 0.0
exclusiveMinimum: true
maximum: 1.0
description: |
Fraction of the full diffusion horizon T at which to sample
noised edges (e.g. 0.4 for moderate corruption). Omit to receive
the clean subgraphs.
- name: task
in: query
required: false
schema:
type: string
enum: [correct, generate]
default: correct
description: Task the noise should align with. Ignored if noise_level is not set.
- name: seed
in: query
required: false
schema:
type: integer
description: Optional RNG seed for reproducible noise.
responses:
"200":
description: Sample subgraphs
content:
application/json:
schema:
$ref: "#/components/schemas/KgAnomalySampleSubgraphsResponse"
"404":
$ref: "#/components/responses/NotFound"
/kg-anomaly/correct:
post:
operationId: kgAnomalyCorrect
tags: [kg-anomaly]
summary: Correct a KG subgraph (SSE streaming)
description: |
Server-Sent Events stream (`text/event-stream`). Emits `progress`
events during diffusion, optional `preview` events with intermediate
PNGs, and a terminal `result` event whose `data` payload is the JSON
described below.
**Standard mode**: runs full diffusion correction; terminal `result`
payload conforms to `KgAnomalyStandardResponse`.
**MultiProx mode**: runs the first Gibbs iteration; terminal `result`
payload conforms to `KgAnomalyMultiProxResponse` and includes an
opaque `state` blob to be passed to `/kg-anomaly/continue`.
requestBody:
required: true
content:
application/json:
schema:
$ref: "#/components/schemas/KgAnomalyCorrectRequest"
examples:
standard:
summary: Standard correction
value:
dataset_id: wordnet
sampling_mode: standard
subgraph:
nodes:
- entity_id: 11754
type_id: 3
- entity_id: 5142
type_id: 3
- entity_id: 8142
type_id: 3
edges:
- source_idx: 0
target_idx: 1
relation_id: 3
- source_idx: 1
target_idx: 2
relation_id: 1
chain_frames: 20
multiprox:
summary: MultiProx correction (future)
value:
dataset_id: wordnet
sampling_mode: multiprox
subgraph:
nodes:
- entity_id: 11754
type_id: 3
- entity_id: 5142
type_id: 3
edges:
- source_idx: 0
target_idx: 1
relation_id: 3
multiprox_params:
m: 10
t: 0.5
t_prime: 0.1
responses:
"200":
description: SSE stream of progress/preview events terminated by a result event
content:
text/event-stream:
schema:
$ref: "#/components/schemas/KgAnomalySseStream"
"400":
$ref: "#/components/responses/InvalidRequest"
"404":
$ref: "#/components/responses/NotFound"
"422":
$ref: "#/components/responses/InferenceError"
"429":
$ref: "#/components/responses/InferenceBusy"
"503":
$ref: "#/components/responses/ModelUnavailable"
/kg-anomaly/continue:
post:
operationId: kgAnomalyContinue
tags: [kg-anomaly]
summary: Advance MultiProx correction by one step (SSE streaming)
description: |
SSE stream (`text/event-stream`). Advances the MultiProx correction
chain by one Gibbs iteration. The client must send back the opaque
`state` from the previous step's `result` event. Emits `progress`
and `preview` events, then a terminal `result` event with the
`KgAnomalyMultiProxResponse` payload (including the updated `state`).
requestBody:
required: true
content:
application/json:
schema:
$ref: "#/components/schemas/KgAnomalyContinueRequest"
responses:
"200":
description: SSE stream of progress/preview events terminated by a result event
content:
text/event-stream:
schema:
$ref: "#/components/schemas/KgAnomalySseStream"
"400":
$ref: "#/components/responses/InvalidRequest"
"429":
$ref: "#/components/responses/InferenceBusy"
# ========================================================================
components:
# -- Parameters ----------------------------------------------------
parameters:
CoinsDatasetId:
name: dataset_id
in: path
required: true
schema:
$ref: "#/components/schemas/CoinsDatasetIdEnum"
description: Knowledge graph dataset identifier
KgAnomalyDatasetId:
name: dataset_id
in: path
required: true
schema:
$ref: "#/components/schemas/KgAnomalyDatasetIdEnum"
description: KG anomaly correction dataset identifier
SearchQuery:
name: q
in: query
schema:
type: string
description: Substring search filter
Page:
name: page
in: query
schema:
type: integer
minimum: 1
default: 1
description: Page number (1-indexed)
PageSize:
name: page_size
in: query
schema:
type: integer
minimum: 1
maximum: 200
default: 50
description: Items per page
# -- Responses (errors) --------------------------------------------
responses:
InvalidRequest:
description: Malformed input
content:
application/json:
schema:
$ref: "#/components/schemas/ErrorResponse"
example:
error:
code: INVALID_REQUEST
message: "Anchor keys {a1} do not match template anchors {a} for query structure 1p"
details: {}
NotFound:
description: Resource not found
content:
application/json:
schema:
$ref: "#/components/schemas/ErrorResponse"
example:
error:
code: NOT_FOUND
message: "Dataset 'unknown' not found"
details: {}
InferenceError:
description: Model inference failed
content:
application/json:
schema:
$ref: "#/components/schemas/ErrorResponse"
example:
error:
code: INFERENCE_ERROR
message: "Inference failed: entity_id 99999 out of range for dataset wordnet"
details: {}
InferenceBusy:
description: Another inference is already running
content:
application/json:
schema:
$ref: "#/components/schemas/ErrorResponse"
example:
error:
code: INFERENCE_BUSY
message: "Another inference is in progress. Please wait and try again."
details: {}
ModelUnavailable:
description: Model checkpoint not loaded
content:
application/json:
schema:
$ref: "#/components/schemas/ErrorResponse"
example:
error:
code: MODEL_UNAVAILABLE
message: "Model for dataset wordnet with algorithm rotate is not loaded"
details: {}
# -- Schemas -------------------------------------------------------
schemas:
# -- Enums --
CoinsDatasetIdEnum:
type: string
enum: [freebase, wordnet, nell]
CoinsAlgorithmEnum:
type: string
enum: [transe, distmult, complex, rotate, q2b, kbgat]
CoinsQueryStructureEnum:
type: string
enum: ["1p", "2p", "3p", "2i", "3i", ip, pi]
GraphGenDatasetIdEnum:
type: string
enum: [qm9, comm20]
GraphGenModelTypeEnum:
type: string
enum: [discrete, continuous]
SamplingModeEnum:
type: string
enum: [standard, multiprox]
KgAnomalyDatasetIdEnum:
type: string
enum: [freebase, wordnet, nell]
QueryNodeTypeEnum:
type: string
enum: [anchor, variable, target]
EdgeChangeStatusEnum:
type: string
enum: [unchanged, modified, added, removed]
# -- Error --
ErrorResponse:
type: object
required: [error]
properties:
error:
type: object
required: [code, message]
properties:
code:
type: string
message:
type: string
details:
type: object
additionalProperties: true
# -- Health --
HealthResponse:
type: object
required: [status, models_loaded]
properties:
status:
type: string
example: ok
models_loaded:
type: object
required: [coins, multiproxan, kg_anomaly]
properties:
coins:
type: boolean
multiproxan:
type: boolean
kg_anomaly:
type: boolean
MethodsResponse:
type: object
required: [methods]
properties:
methods:
type: array
items:
type: object
required: [id, name, thesis_section, description]
properties:
id:
type: string
example: coins
name:
type: string
example: COINs - Knowledge Graph Reasoning
thesis_section:
type: string
example: "3.1"
description:
type: string
# -- COINs: Discovery --
CoinsDatasetsResponse:
type: object
required: [datasets]
properties:
datasets:
type: array
items:
$ref: "#/components/schemas/CoinsDataset"
CoinsDataset:
type: object
required: [id, name, num_entities, num_relations, description]
properties:
id:
$ref: "#/components/schemas/CoinsDatasetIdEnum"
name:
type: string
example: WN18RR
num_entities:
type: integer
example: 41105
num_relations:
type: integer
example: 11
description:
type: string
example: Subset of WordNet lexical database with 11 relation types
CoinsEntitiesResponse:
type: object
required: [dataset_id, total, page, page_size, entities]
properties:
dataset_id:
$ref: "#/components/schemas/CoinsDatasetIdEnum"
total:
type: integer
page:
type: integer
page_size:
type: integer
entities:
type: array
items:
$ref: "#/components/schemas/CoinsEntity"
CoinsEntity:
type: object
required: [id, name]
properties:
id:
type: integer
example: 0
name:
type: string
example: dog's_breakfast.n.01
label:
type: string
description: Dataset-specific short, display-friendly form of `name`. Only present on sample-triples responses.
example: dog's_breakfast
CoinsRelationsResponse:
type: object
required: [dataset_id, total, page, page_size, relations]
properties:
dataset_id:
$ref: "#/components/schemas/CoinsDatasetIdEnum"
total:
type: integer
page:
type: integer
page_size:
type: integer
relations:
type: array
items:
$ref: "#/components/schemas/CoinsRelation"
CoinsRelation:
type: object
required: [id, name]
properties:
id:
type: integer
example: 0
name:
type: string
example: _hypernym
label:
type: string
description: Dataset-specific short, display-friendly form of `name`. Only present on sample-triples responses.
example: hypernym
CoinsSampleTriplesResponse:
type: object
required: [dataset_id, triples]
properties:
dataset_id:
$ref: "#/components/schemas/CoinsDatasetIdEnum"
triples:
type: array
items:
$ref: "#/components/schemas/CoinsTriple"
CoinsTriple:
type: object
required: [head, relation, tail]
properties:
head:
$ref: "#/components/schemas/CoinsEntity"
relation:
$ref: "#/components/schemas/CoinsRelation"
tail:
$ref: "#/components/schemas/CoinsEntity"
CoinsSampleQueryResponse:
type: object
required: [dataset_id, query_structure, queries]
properties:
dataset_id:
$ref: "#/components/schemas/CoinsDatasetIdEnum"
query_structure:
$ref: "#/components/schemas/CoinsQueryStructureEnum"
queries:
type: array
description: |
Sampled queries. Each query is a valid walk through the training KG.
May return fewer than `count` if the graph is too sparse for the
requested structure (e.g. 3i requires a target with at least 3 in-edges).
items:
$ref: "#/components/schemas/CoinsSampledQuery"
CoinsSampledQuery:
type: object
required: [anchors, relations, target]
description: |
A structurally valid query instance. `anchors` and `relations` keys match the
node/edge IDs from `GET /coins/query-structures` for the given structure.
The `target` is the known answer entity.
properties:
anchors:
type: object
additionalProperties:
$ref: "#/components/schemas/CoinsEntity"
description: "Anchor entities keyed by node ID (e.g. `a`, `a1`, `a2`, `a3`)."
example:
a1: { id: 123, name: "/m/06thjt", label: "06thjt" }
a2: { id: 456, name: "/m/0d_kd", label: "0d_kd" }
relations:
type: object
additionalProperties:
$ref: "#/components/schemas/CoinsRelation"
description: "Relations keyed by edge ID (e.g. `r1`, `r2`, `r3`)."
example:
r1: { id: 7, name: "/people/person/nationality", label: "person nationality" }
r2: { id: 12, name: "/location/country/capital", label: "country capital" }
target:
$ref: "#/components/schemas/CoinsEntity"
CoinsModelsResponse:
type: object
required: [models]
properties:
models:
type: array
items:
$ref: "#/components/schemas/CoinsModel"
CoinsModel:
type: object
required: [algorithm, name, description, supported_query_structures, available_datasets]
properties:
algorithm:
$ref: "#/components/schemas/CoinsAlgorithmEnum"
name:
type: string
example: TransE
description:
type: string
example: Translation-based embedding model
supported_query_structures:
type: array
items:
$ref: "#/components/schemas/CoinsQueryStructureEnum"
example: ["1p"]
available_datasets:
type: array
items:
$ref: "#/components/schemas/CoinsDatasetIdEnum"
example: [freebase, wordnet, nell]
# -- COINs: Query Structures --
CoinsQueryStructuresResponse:
type: object
required: [query_structures]
properties:
query_structures:
type: array
items:
$ref: "#/components/schemas/CoinsQueryStructure"
CoinsQueryStructure:
type: object
required: [id, name, description, nodes, edges]
properties:
id:
$ref: "#/components/schemas/CoinsQueryStructureEnum"
name:
type: string
example: Single Hop
description:
type: string
example: "Direct link prediction: who/what is connected to the anchor via this relation?"
nodes:
type: array
items:
$ref: "#/components/schemas/QueryNode"
edges:
type: array
items:
$ref: "#/components/schemas/QueryEdge"
QueryNode:
type: object
required: [id, type, label]
properties:
id:
type: string
description: Node identifier referenced by edges and the predict request
example: a
type:
$ref: "#/components/schemas/QueryNodeTypeEnum"
label:
type: string
description: Display label for the frontend
example: Anchor
QueryEdge:
type: object
required: [id, source, target, label]
properties:
id:
type: string
description: Edge identifier referenced by the predict request
example: r1
source:
type: string
description: Source node id
example: a
target:
type: string
description: Target node id
example: t
label:
type: string
description: Display label for the frontend
example: Relation
# -- COINs: Predict --
CoinsPredictRequest:
type: object
required: [dataset_id, algorithm, query_structure, anchors, relations]
properties:
dataset_id:
$ref: "#/components/schemas/CoinsDatasetIdEnum"
algorithm:
$ref: "#/components/schemas/CoinsAlgorithmEnum"
query_structure:
$ref: "#/components/schemas/CoinsQueryStructureEnum"
anchors:
type: object
additionalProperties:
type: integer
description: |
Map of anchor node id -> entity id. Keys must match all anchor nodes
in the query structure template.
example: { "a": 11754 }
variables:
type: object
additionalProperties:
type: integer
description: |
Optional map of variable node id -> entity id. Keys must be a subset
of the variable nodes in the query structure template. Omitted variable
nodes are sampled automatically from the graph given the anchors and relations.
example: { "v1": 5432 }
relations:
type: object
additionalProperties:
type: integer
description: |
Map of edge id -> relation id. Keys must match all edges in the
query structure template.
example: { "r1": 3 }
top_k:
type: integer
minimum: 1
maximum: 10
default: 10
description: Number of top predictions to return
CoinsPredictResponse:
type: object
required: [dataset_id, algorithm, query_structure, query_description, predictions, timing]
properties:
dataset_id:
$ref: "#/components/schemas/CoinsDatasetIdEnum"
algorithm:
$ref: "#/components/schemas/CoinsAlgorithmEnum"
query_structure:
$ref: "#/components/schemas/CoinsQueryStructureEnum"
query_description:
type: string
description: Human-readable rendering of the query with entity/relation names
example: "dog's_breakfast.n.01 --[_hypernym]--> ?"
predictions:
type: array
items:
$ref: "#/components/schemas/CoinsPrediction"
timing:
$ref: "#/components/schemas/CoinsTiming"
CoinsPrediction:
type: object
required: [rank, intra_community_rank, entity_id, entity_name, score, is_valid_answer]
properties:
rank:
type: integer
minimum: 1
description: |
COINs aggregate rank from rank_samples: rank = c_err + intra_community_rank.
Sum of all entity counts in communities with better step-1 score, plus the
rank of this prediction within its community.
example: 14
intra_community_rank:
type: integer
minimum: 1
description: Rank of this prediction within the hit community (intra_community_rank in rank_samples)
example: 1
entity_id:
type: integer
example: 12045
entity_name:
type: string
example: dish.n.02
score:
type: number
format: float
example: 0.923
is_valid_answer:
type: boolean
description: |
True if this entity actually satisfies the query in the KG (i.e. is a member of
`get_all_answers`). Step 2 scores every entity in the hit community, so any
prediction may be a non-answer the model surfaced — the flag lets the frontend
mark the genuine hits.
example: true
CoinsTiming:
type: object
required: [step1_ms, step1_label, step2_ms, step2_label, total_ms, rank_c, baseline_estimate_ms, baseline_label, speedup]
properties:
step1_ms:
type: number
format: float
description: "Time for Step 1: community detection + localized embedding"
example: 12
step1_label:
type: string
example: Community detection + localized embedding
step2_ms:
type: number
format: float
description: "Time for Step 2: community search + link prediction (covers all communities tried)"
example: 33
step2_label:
type: string
example: Link prediction
total_ms:
type: number
format: float
description: Total COINs inference time (step1 + step2)
example: 45
rank_c:
type: integer
minimum: 0
description: |
Step-1 rank of the community where predictions were found (rank_c in rank_samples).
1 = top-ranked community was a hit. >1 = had to search deeper.
0 = no predictions found in any community.
example: 1
baseline_estimate_ms:
type: number
format: float
description: Simulated estimate of full-graph inference without COINs
example: 320
baseline_label:
type: string
example: Estimated baseline (without COINs)
speedup:
type: number
format: float
description: "Proposition 3.1 speedup: V / (K + c_err + |C_{rank_c}|)"
example: 7.1
# -- Graph Generation: Discovery --
GraphGenDatasetsResponse:
type: object
required: [datasets]
properties:
datasets:
type: array
items:
$ref: "#/components/schemas/GraphGenDataset"
GraphGenDataset:
type: object
required: [id, name, type, description, node_types, edge_types, max_nodes, available_model_types]
properties:
id:
$ref: "#/components/schemas/GraphGenDatasetIdEnum"
name:
type: string
example: QM9
type:
type: string
enum: [molecular, synthetic]
example: molecular
description:
type: string
example: Small organic molecules with up to 9 heavy atoms (C, N, O, F)
node_types:
type: array
items:
type: string
example: [C, N, O, F]
edge_types:
type: array
items:
type: string
example: [none, single, double, triple, aromatic]
max_nodes:
type: integer
example: 9
available_model_types:
type: array
items:
$ref: "#/components/schemas/GraphGenModelTypeEnum"
example: [discrete, continuous]
GraphGenSamplingModesResponse:
type: object
required: [sampling_modes]
properties:
sampling_modes:
type: array
items:
$ref: "#/components/schemas/GraphGenSamplingMode"
GraphGenSamplingMode:
type: object
required: [id, name, description]
properties:
id:
$ref: "#/components/schemas/SamplingModeEnum"
name:
type: string
example: Standard Denoising
description:
type: string
example: "Iterative denoising from T to 0. Full quality, slower."
parameters:
type: array
description: |
Configurable parameters for this sampling mode.
Standard mode: T (diffusion steps).
MultiProx mode: T (diffusion steps), m (parallel samples), t (noise level), t_prime (noise level).
items:
$ref: "#/components/schemas/SamplingParameter"
SamplingParameter:
type: object
required: [name, type, description, default, min, max]
properties:
name:
type: string
example: m
type:
type: string
enum: [integer, float]
description:
type: string
example: Number of parallel samples per multi-measurement step
default:
type: number
min:
type: number
max:
type: number
# -- Graph Generation: Generate --
GraphGenGenerateRequest:
type: object
required: [dataset_id, model_type, sampling_mode]
properties:
dataset_id:
$ref: "#/components/schemas/GraphGenDatasetIdEnum"
model_type:
$ref: "#/components/schemas/GraphGenModelTypeEnum"
sampling_mode:
$ref: "#/components/schemas/SamplingModeEnum"
num_nodes:
type: integer
nullable: true
description: "Number of nodes. null = sampled from learned distribution."
example: null
diffusion_steps:
type: integer
minimum: 50
maximum: 1000
default: 500
description: Number of diffusion steps T (both standard and multiprox modes)
chain_frames:
type: integer
minimum: 10
maximum: 30
default: 20
description: Number of denoising snapshots in the GIF (standard mode only)
multiprox_params:
$ref: "#/components/schemas/MultiProxParams"
MultiProxParams:
type: object
nullable: true
description: |
Required when sampling_mode is multiprox, null otherwise.
Constraint: t_prime <= t (the second noise level must not exceed the first).
Returns 400 INVALID_REQUEST if violated.
required: [m, t, t_prime]
properties:
m:
type: integer
minimum: 2
maximum: 100
description: Number of parallel samples per multi-measurement step
example: 10
t:
type: number
format: float
minimum: 0.0
maximum: 1.0
description: First noise level (normalized, 0-1)
example: 0.5
t_prime:
type: number
format: float
minimum: 0.0
maximum: 1.0
description: "Second noise level (normalized, 0-1). Must satisfy t_prime <= t."
example: 0.1
GraphGenStandardResponse:
type: object
required: [dataset_id, model_type, sampling_mode, image, chain_gif, inference_time_ms]
properties:
dataset_id:
$ref: "#/components/schemas/GraphGenDatasetIdEnum"
model_type:
$ref: "#/components/schemas/GraphGenModelTypeEnum"
sampling_mode:
type: string
enum: [standard]
image:
type: string
format: byte
description: Final generated graph as base64 PNG (data URI)
example: "data:image/png;base64,iVBORw0KGgo..."
chain_gif:
type: string
format: byte
description: Animated GIF of the denoising process (data URI), played once by frontend
example: "data:image/gif;base64,R0lGODlh..."
inference_time_ms:
type: number
format: float
example: 3200
GraphGenContinueRequest:
type: object
required: [state]
properties:
state:
type: string
format: byte
description: |
Opaque base64 blob containing the serialized diffusion state from
the previous step's response. Must be passed back unchanged.
GraphGenMultiProxResponse:
type: object
required: [step, image, state, inference_time_ms]
properties:
step:
type: integer
minimum: 0
description: Current Gibbs iteration number (0-indexed)
example: 0
image:
type: string
format: byte
description: Current graph state as base64 PNG (data URI)
example: "data:image/png;base64,iVBORw0KGgo..."
state:
type: string
format: byte
description: |
Opaque base64 blob containing the serialized diffusion state.
Pass this back to the continue endpoint for the next step.
example: "base64-encoded-diffusion-state..."
inference_time_ms:
type: number
format: float
example: 800
# -- Graph Generation SSE stream ----------------------------------
GraphGenSseStream:
type: string
description: |
SSE text stream. Each event is `event: <name>\ndata: <payload>\n\n`.
* `event: progress` -- payload is `GraphGenProgressEvent` JSON.
* `event: preview` -- payload is a raw `data:image/png;base64,...` data URI
(intermediate graph snapshot; not JSON).
* `event: result` -- payload is a `GraphGenStandardResponse` (standard mode)
or `GraphGenMultiProxResponse` (multiprox mode / continue) JSON.
* `event: error` -- payload is an error object with `code` and `message`.
GraphGenProgressEvent:
type: object
required: [type, stage]
properties:
type:
type: string
enum: [progress]
stage:
type: string
description: Current phase (e.g. "denoise", "noise", "refine")
step:
type: integer
description: Current step within the stage
total:
type: integer
description: Total steps in the stage
# -- KG Anomaly Correction: Discovery --
KgAnomalyDatasetsResponse:
type: object
required: [datasets]
properties:
datasets:
type: array
items:
$ref: "#/components/schemas/KgAnomalyDataset"
KgAnomalyDataset:
type: object
required: [id, name, description]
properties:
id:
$ref: "#/components/schemas/KgAnomalyDatasetIdEnum"
name:
type: string
example: WN18RR
description:
type: string
example: Diffusion model trained on WordNet subgraphs
KgAnomalySampleSubgraphsResponse:
type: object
required: [dataset_id, subgraphs]
properties:
dataset_id:
$ref: "#/components/schemas/KgAnomalyDatasetIdEnum"
subgraphs:
type: array
items:
$ref: "#/components/schemas/KgAnomalySampleSubgraph"
KgAnomalySampleSubgraph:
type: object
required: [id, num_nodes, num_edges, nodes, edges]
properties:
id:
type: string
example: sample_1
num_nodes:
type: integer
example: 6
num_edges:
type: integer
example: 8
nodes:
type: array
items:
$ref: "#/components/schemas/SubgraphNode"
edges:
type: array
items:
$ref: "#/components/schemas/SubgraphEdgeWithNames"
SubgraphNode:
type: object
required: [entity_id, type_id]
properties:
entity_id:
type: integer
example: 11754
entity_name:
type: string
description: Present in responses, not required in requests
example: dog's_breakfast.n.01
type_id:
type: integer
example: 3
SubgraphEdge:
type: object
required: [source_idx, target_idx, relation_id]
properties:
source_idx:
type: integer
description: Index into the nodes array
example: 0
target_idx:
type: integer
description: Index into the nodes array
example: 1
relation_id:
type: integer
example: 3
SubgraphEdgeWithNames:
allOf:
- $ref: "#/components/schemas/SubgraphEdge"
- type: object
properties:
entity_name_source:
type: string
example: dog's_breakfast.n.01
entity_name_target:
type: string
example: bulldog.v.01
relation_name:
type: string
example: _hypernym
# -- KG Anomaly Correction: Correct --
KgAnomalyTaskEnum:
type: string
enum: [generate, correct]
description: |
"generate" = generate all edges from scratch (no masking).
"correct" = keep fixed edges unchanged, only correct the masked edges.
KgAnomalyCorrectRequest:
type: object
required: [dataset_id, sampling_mode, subgraph]
properties:
dataset_id:
$ref: "#/components/schemas/KgAnomalyDatasetIdEnum"
sampling_mode:
$ref: "#/components/schemas/SamplingModeEnum"
task:
$ref: "#/components/schemas/KgAnomalyTaskEnum"
default: correct
description: |
"generate" = ignore the input subgraph edges and generate a new subgraph from scratch.
"correct" (default) = keep fixed edges unchanged, only correct the masked (anomalous) edges.
The mask is computed automatically based on the subgraph structure.
subgraph:
$ref: "#/components/schemas/InputSubgraph"
diffusion_steps:
type: integer
minimum: 50
maximum: 1000
default: 500
description: Number of diffusion steps T (both standard and multiprox modes)
chain_frames:
type: integer
minimum: 10
maximum: 30
default: 20
description: Number of denoising snapshots in the GIF (standard mode only)
multiprox_params:
$ref: "#/components/schemas/MultiProxParams"
InputSubgraph:
type: object
required: [nodes, edges]
description: "Subgraph to correct. Maximum ~20 nodes."
properties:
nodes:
type: array
maxItems: 20
items:
type: object
required: [entity_id, type_id]
properties:
entity_id:
type: integer
type_id:
type: integer
edges:
type: array
items:
$ref: "#/components/schemas/SubgraphEdge"
KgAnomalyStandardResponse:
type: object
required: [dataset_id, original_image, corrected_image, chain_gif, changes, inference_time_ms]
properties:
dataset_id:
$ref: "#/components/schemas/KgAnomalyDatasetIdEnum"
original_image:
type: string
format: byte
description: Before-correction subgraph as base64 PNG (data URI)
example: "data:image/png;base64,..."
corrected_image:
type: string
format: byte
description: After-correction subgraph as base64 PNG with color-coded edges (data URI)
example: "data:image/png;base64,..."
chain_gif:
type: string
format: byte
description: Animated GIF of the correction diffusion process (data URI)
example: "data:image/gif;base64,..."
changes:
$ref: "#/components/schemas/CorrectionChanges"
inference_time_ms:
type: number
format: float
example: 5100
KgAnomalyContinueRequest:
type: object
required: [state]
properties:
state:
type: string
format: byte
description: |
Opaque base64 blob containing the serialized diffusion state from
the previous step's response. Must be passed back unchanged.
KgAnomalyMultiProxResponse:
type: object
required: [step, image, state, changes, inference_time_ms]
properties:
step:
type: integer
minimum: 0
example: 0
image:
type: string
format: byte
description: Current subgraph state as base64 PNG (data URI)
example: "data:image/png;base64,..."
state:
type: string
format: byte
description: |
Opaque base64 blob containing the serialized diffusion state.
Pass this back to the continue endpoint for the next step.
example: "base64-encoded-diffusion-state..."
changes:
$ref: "#/components/schemas/CorrectionChanges"
inference_time_ms:
type: number
format: float
example: 900
CorrectionChanges:
type: object
required: [edges, summary]
properties:
edges:
type: array
items:
$ref: "#/components/schemas/CorrectedEdge"
summary:
$ref: "#/components/schemas/CorrectionSummary"
CorrectedEdge:
type: object
required: [source_idx, target_idx, relation_id, relation_name, status]
properties:
source_idx:
type: integer
example: 0
target_idx:
type: integer
example: 1
relation_id:
type: integer
example: 3
relation_name:
type: string
example: _hypernym
status:
$ref: "#/components/schemas/EdgeChangeStatusEnum"
original_relation_id:
type: integer
description: Only present when status is "modified"
example: 99
CorrectionSummary:
type: object
required: [unchanged, modified, added, removed]
properties:
unchanged:
type: integer
example: 2
modified:
type: integer
example: 1
added:
type: integer
example: 0
removed:
type: integer
example: 0
# -- KG Anomaly SSE stream ----------------------------------------
KgAnomalySseStream:
type: string
description: |
SSE text stream. Each event is `event: <name>\ndata: <payload>\n\n`.
* `event: progress` -- payload is `KgAnomalyProgressEvent` JSON.
* `event: preview` -- payload is a raw `data:image/png;base64,...` data URI
(intermediate subgraph snapshot; not JSON).
* `event: result` -- payload is a `KgAnomalyStandardResponse` (standard mode)
or `KgAnomalyMultiProxResponse` (multiprox mode / continue) JSON.
* `event: error` -- payload is an error object with `code` and `message`.
KgAnomalyProgressEvent:
type: object
required: [type, stage]
properties:
type:
type: string
enum: [progress]
stage:
type: string
description: Current phase (e.g. "denoise", "noise", "refine")
step:
type: integer
description: Current step within the stage
total:
type: integer
description: Total steps in the stage
kg_log_likelihood:
type: number
nullable: true
description: >
Mean log-sigmoid score from the frozen KG embedder + link ranker
applied to the edges currently present in the argmax reconstruction.
Higher = cleaner. Present only on frame-boundary events.
kg_log_likelihood_step:
type: integer
nullable: true
description: Step index that `kg_log_likelihood` corresponds to.
|