Execute Public Retriever

Authorizations

Authorization

string

header

required

Bearer authentication header of the form Bearer <token>, where <token> is your auth token.

Headers

X-Public-API-Key

string | null

X-Retriever-Password

string | null

Path Parameters

public_name

string

required

Public name of the published retriever

Query Parameters

return_presigned_urls

boolean

default:true

Generate fresh presigned download URLs for all blobs with S3 storage. Default: True for public retrievers to enable media rendering. Set to False if you only need metadata without URLs.

Body

application/json

Request payload for executing a retriever.

Executes a predefined retriever with runtime inputs. The retriever uses the collections it was created with - collection overrides are not supported at execution time to ensure feature_uri and schema validation integrity.

All filtering, pagination, and result shaping is handled by the individual stages based on the inputs provided.

Use Cases: - Execute retriever with its configured collections - Pass inputs that stages use to determine filtering/pagination behavior

Design Philosophy: - Retrievers are validated at creation time against their collections - Feature URIs, input schemas, and stage configs are tightly coupled to collections - Filters, limits, and offsets are NOT top-level request fields - These are handled by stages when they receive inputs - Example: A stage might read {INPUT.top_k} to determine result limit

Examples: Simple query: {"inputs": {"query": "AI", "top_k": 50}}

Different inputs for stage behavior:
    {"inputs": {
        "query": "machine learning",
        "top_k": 100,
        "min_score": 0.7,
        "published_after": "2024-01-01"
     }}

inputs

Inputs · object

Runtime inputs for the retriever mapped to the input schema. Keys must match the retriever's input_schema field names. Values depend on field types (text, vector, filters, etc.). REQUIRED unless all retriever inputs have defaults.

Common input keys:

'query': Text search query
'embedding': Pre-computed vector for search
'top_k': Number of results to return
'min_score': Minimum relevance threshold
Any custom fields defined in input_schema

Template Syntax (Jinja2):

Namespaces (uppercase or lowercase):

INPUT / input: Query inputs (e.g., {{INPUT.query}})
DOC / doc: Document fields (e.g., {{DOC.payload.title}})
CONTEXT / context: Execution context
STAGE / stage: Stage configuration
SECRET / secret: Vault secrets (e.g., {{SECRET.api_key}})

Accessing Data:

Dot notation: {{DOC.payload.metadata.title}}
Bracket notation: {{DOC.payload['special-key']}}
Array index: {{DOC.items[0]}}, {{DOC.tags[2]}}
Array first/last: {{DOC.items | first}}, {{DOC.items | last}}

Array Operations:

Iterate: {% for item in DOC.tags %}{{item}}{% endfor %}
Extract key: {{DOC.items | map(attribute='name') | list}}
Join: {{DOC.tags | join(', ')}}
Length: {{DOC.items | length}}
Slice: {{DOC.items[:5]}}

Conditionals:

If: {% if DOC.status == 'active' %}...{% endif %}
If-else: {% if DOC.score > 0.8 %}high{% else %}low{% endif %}
Ternary: {{'yes' if DOC.enabled else 'no'}}

Built-in Functions: max, min, abs, round, ceil, floor Custom Filters: slugify (URL-safe), bool (truthy coercion), tojson (JSON encode)

S3 URLs: Internal S3 URLs (s3://bucket/key) are automatically presigned when accessed via DOC namespace.

Examples:

{
  "query": "artificial intelligence",
  "top_k": 25
}

{
  "min_score": 0.7,
  "query": "customer feedback",
  "top_k": 50
}

{
  "category": "blog",
  "embedding": [0.1, 0.2, 0.3],
  "top_k": 10
}

filters

Filters · object

Optional ad-hoc filters applied at execution time. Merged (AND) with any filters already defined in the retriever's stages. Uses the standard LogicalOperator format: {"AND": [{"field": "brand", "operator": "eq", "value": "Acme"}]}. Supports operators: eq, ne, in, nin, gt, gte, lt, lte, contains, exists, is_null.

Example:

{
  "AND": [
    {
      "field": "brand",
      "operator": "eq",
      "value": "Acme"
    }
  ]
}

pagination

OffsetPaginationParams · object

Offset-based pagination using page number sizing.

Best for: Traditional page UIs with page number navigation

How it works:

Uses page numbers (1, 2, 3...) and page size
Calculates offset as: (page_number - 1) * page_size
Simple and familiar for users
Can jump to any page directly

Tradeoffs:

Can have "page drift" if data changes between requests
Example: Items added/deleted causes duplicates or gaps
Less efficient for large offsets (database must skip N rows)

Use when:

Building traditional page-numbered UIs
Users need to jump to specific pages
Result set is relatively stable
Working with smaller datasets

Example: Page 1: {"method": "offset", "page_size": 25, "page_number": 1} Page 2: {"method": "offset", "page_size": 25, "page_number": 2}

OffsetPaginationParams
CursorPaginationParams
ScrollPaginationParams
KeysetPaginationParams

Show child attributes

stream

boolean

default:false

Enable streaming execution to receive real-time stage updates via Server-Sent Events (SSE). NOT REQUIRED - defaults to False for standard execution.

When stream=True:

Response uses text/event-stream content type
Each stage completion emits a StreamStageEvent
Events include: stage_start, stage_complete, stage_error, execution_complete
Clients receive intermediate results and statistics as stages execute
Useful for progress tracking, debugging, and partial result display

When stream=False (default):

Response returns after all stages complete
Returns a single RetrieverExecutionResponse with final results
Lower overhead for simple queries

Use streaming when:

You want to show real-time progress to users
You need to display intermediate results
Pipeline has many stages or long-running operations
Debugging or monitoring pipeline performance

Example streaming client (JavaScript):

const eventSource = new EventSource('/v1/retrievers/ret_123/execute?stream=true');
eventSource.onmessage = (event) => {
  const stageEvent = JSON.parse(event.data);
  if (stageEvent.event_type === 'stage_complete') {
    console.log(`Stage ${stageEvent.stage_name} completed`);
    console.log(`Documents: ${stageEvent.documents.length}`);
  }
};

Example streaming client (Python):

import requests
response = requests.post('/v1/retrievers/ret_123/execute',
                        json={'inputs': {...}, 'stream': True},
                        stream=True)
for line in response.iter_lines():
    if line.startswith(b'data: '):
        event = json.loads(line[6:])
        print(f"Stage {event['stage_name']}: {event['event_type']}")

Examples:

false

true

expand

string[] | null

OPTIONAL. List of fields containing document IDs to resolve inline. Referenced documents are fetched and attached under an '_expanded' key in each result document. Supports dot-notation for nested fields (e.g., 'items.product_id'). Max 50 unique references per request. Depth is limited to 1 (no recursive expansion).

Example:

["customer_id"]

skip_cache

boolean

default:false

OPTIONAL. Bypass stage result cache for this execution. When True, all stages execute fresh without cache lookup. Useful after corpus updates, retriever config changes, or engine deploys. Results are still written to cache for future requests.

Examples:

false

true

return_presigned_urls

boolean

default:false

Generate presigned URLs for S3-backed blobs and url-shaped fields in result documents. Also accepted as a return_presigned_urls query parameter; if either source is true, presigning is enabled.

Examples:

false

true

return_vectors

boolean

default:false

Include vector embeddings in result documents. Also accepted as a return_vectors query parameter; if either source is true, vectors are returned.

Examples:

false

true

Response

Successful Response