Collections in Tallyfy Answers are organizational structures that group similar objects together like database tables and provide features for searching filtering and managing data with automatic schema detection and complete CRUD operations.
Find similar objects
The recommendation endpoint allows you to discover objects similar to a specified reference object.
This similarity search uses vector embeddings to find objects with related characteristics, which is useful for recommendation systems, content discovery, and finding related items.
Tallyfy Answers uses semantic similarity to find related objects through this process:
- Each object’s text content is converted into vector embeddings (numerical representations)
- When searching for similar objects, Tallyfy compares vector distances
- Objects with closer vector distances are considered more similar
- Results are ranked by similarity score from most to least similar
GET /collections/{collection_name}/recommend/{object_id}
Parameter | Type | Required | Description |
---|---|---|---|
collection_name | string | Yes | Name of the collection to search in |
object_id | string | Yes | ID of the reference object to find similar objects to |
Parameter | Type | Required | Default | Description |
---|---|---|---|---|
limit | integer | No | 4 | Maximum number of similar objects to return (1-20) |
A successful similarity search request returns a 200 OK
status code and a JSON response containing:
{ "results": [ { "id": "product-456", "score": 0.89, "document": { "name": "Bluetooth Speaker", "description": "Portable waterproof speaker with 20-hour battery life", "price": 129.99, "categories": ["electronics", "audio"] } }, { "id": "product-789", "score": 0.72, "document": { "name": "Wireless Earbuds", "description": "Premium noise-canceling earbuds with charging case", "price": 99.99, "categories": ["electronics", "audio"] } } ], "meta": { "limit": 10, "found": 2 }}
Field | Type | Description |
---|---|---|
results | array | List of similar objects with similarity scores |
results[].id | string | Unique identifier of the similar object |
results[].score | float | Similarity score (0.0-1.0)1 where higher is more similar |
results[].document | object | Full content of the similar object |
meta.limit | integer | Maximum number of results requested |
meta.found | integer | Total number of similar objects found |
Status | Description |
---|---|
404 | Collection or reference object not found |
400 | Invalid parameters or filter syntax |
# Find objects similar to article-123, limit to 5 resultscurl -X GET "https://answers.tallyfy.com/collections/docs/recommend/article-123?limit=5" \ -H "Authorization: Bearer your_api_key"
- Product recommendations: “Customers who viewed this also viewed…”
- Content discovery: Finding related articles or documentation
- Similarity matching: Identifying near-duplicate content
- Alternative suggestions: Offering similar options when an item is unavailable
- Start with a lower
min_score
threshold and adjust based on result quality - Use the
filter
parameter to combine similarity with business rules - For better recommendations, ensure your objects contain rich, descriptive text
- Include diverse object attributes to improve similarity matching accuracy
The Tallyfy Answers API endpoint retrieves complete individual object data from collections using unique identifiers through a GET request that returns full object properties including system-generated timestamps.
Tallyfy Answers search combines AI semantic understanding with traditional keyword matching to deliver relevant results through natural language queries and exact term searches with smart filtering and instant results.
The DELETE endpoint permanently removes specific objects from Tallyfy Answers collections using unique identifiers and returns confirmation upon successful deletion with no recovery option available.
-
Cosine similarity scoring where perfect match equals 1.0, high similarity above 0.8, low below 0.5 ↩
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