Search for documents in a collection
Search for documents in a collection that match the search criteria. AACSearch extension: with `debug=true` (or the `X-NOVA-DEBUG: 1` header) the response includes `_trace` — what the platform did to the request (search rules applied, experiment variants, query rewrite and fallback outcome, stage timings, engine status) — and every hit an `_explain` object with the engine's scoring signals and which search-rule boosts matched. Every search response also carries an `X-Nova-Trace-Id` header identifying it in the query log.
Search-key operation
Search for documents in a collection that match the search criteria. AACSearch extension: with debug=true (or the X-NOVA-DEBUG: 1 header) the response includes _trace — what the platform did to the request (search rules applied, experiment variants, query rewrite and fallback outcome, stage timings, engine status) — and every hit an _explain object with the engine's scoring signals and which search-rule boosts matched. Every search response also carries an X-Nova-Trace-Id header identifying it in the query log.
Authorization
api_key_header Every request carries an organization API key. A key has one of two scopes. A full key reaches every operation in this document and belongs on your server. A search key is the one to ship in a browser widget or a storefront page: it reaches only the operations marked x-nova-key-scope: search — searching, federated search, recommendations, event ingestion, and the visitor-facing AI operations (semantic and image search, voice transcription and voice search, assistant chat, and the visitor's own conversation). It cannot write documents or read or change configuration; any other operation answers 403. AI operations are paid in credits from the organization's wallet whichever key calls them (402 when the balance runs out), and a search key needs X-NOVA-SESSION-ID on them: the session is what a conversation belongs to, and what the per-session allowance (429) is counted against. A key of either scope may additionally carry restrictions set in the console: an allowlist of collections (403 elsewhere), a forced filter_by per collection that is ANDed into every search (document-level access control), an allowlist of fields (include_fields is limited to it and a request naming any other field in query_by, facet_by, sort_by, filter_by or highlight_fields answers 400), an IP/CIDR allowlist and an Origin/Referer allowlist (403), and a per-key rate limit (429 with Retry-After).
In: header
Path Parameters
The name of the collection to search for the document under
Query Parameters
Header Parameters
AACSearch extension. 1 requests debug output, same as the debug search parameter: the response carries _trace and every hit an _explain object.
The caller's session. Enrols the request in running experiments on the collection (sticky per session); the applied variants come back in the X-Nova-Experiment response header as <experiment_id>:<variant_id>. Send the same value as session_id in your events so experiment reports can attribute them.
Response Body
application/json
application/json
application/json
application/json
application/json
application/json
curl -X GET "https://example.com/collections/string/documents/search?q=string&query_rewrite=layout%2Ctranslit&refinements=off&search_policy=string&x_user_id=string&x_anonymous_id=string&x_personalization_strength=0&x_surface=search&debug=true&rerank=true&rerank_top_k=1&rerank_model=bge-reranker-base&query_by=string&validate_field_names=true&nl_query=true&nl_model_id=string&nl_query_debug=true&nl_query_prompt_cache_ttl=0&query_by_weights=string&text_match_type=string&prefix=string&infix=string&max_extra_prefix=0&max_extra_suffix=0&filter_by=num_employees%3A%3E100+%26%26+country%3A+%5BUSA%2C+UK%5D&max_filter_by_candidates=0&sort_by=num_employees%3Adesc&facet_by=string&max_facet_values=0&facet_query=string&facet_query_num_typos=0&num_typos=string&page=0&per_page=0&limit=0&offset=0&group_by=string&group_limit=0&group_missing_values=true&include_fields=string&exclude_fields=string&highlight_full_fields=string&highlight_affix_num_tokens=0&highlight_start_tag=string&highlight_end_tag=string&enable_highlight_v1=true&enable_analytics=true&snippet_threshold=0&synonym_sets=synonym_set_1%2Csynonym_set_2&drop_tokens_threshold=0&drop_tokens_mode=right_to_left&typo_tokens_threshold=0&enable_typos_for_alpha_numerical_tokens=true&filter_curated_hits=true&enable_synonyms=true&synonym_prefix=true&synonym_num_typos=0&pinned_hits=string&hidden_hits=string&curation_tags=string&highlight_fields=string&split_join_tokens=string&pre_segmented_query=true&preset=string&profile=string&sort=string&enable_curations=false&prioritize_exact_match=true&max_candidates=0&prioritize_token_position=false&prioritize_num_matching_fields=true&enable_typos_for_numerical_tokens=true&exhaustive_search=true&search_cutoff_ms=0&use_cache=true&cache_ttl=0&min_len_1typo=0&min_len_2typo=0&vector_query=string&remote_embedding_timeout_ms=0&remote_embedding_num_tries=0&facet_strategy=string&stopwords=string&facet_return_parent=string&voice_query=string&conversation=true&conversation_model_id=string&conversation_id=string&conversation_stream=true"{ "_trace": {}, "facet_counts": [ { "counts": [ { "count": 0, "highlighted": "string", "value": "string", "parent": {} } ], "field_name": "string", "sampled": true, "stats": { "max": 0.1, "min": 0.1, "sum": 0.1, "total_values": 0, "avg": 0.1 } } ], "found": 0, "found_docs": 0, "search_time_ms": 0, "out_of": 0, "search_cutoff": true, "page": 0, "grouped_hits": [ { "found": 0, "group_key": [ null ], "hits": [ { "highlights": [ { "field": "company_name", "snippet": "<mark>Stark</mark> Industries" } ], "document": { "id": "124", "company_name": "Stark Industries", "num_employees": 5215, "country": "USA" }, "text_match": 1234556 } ] } ], "hits": [ { "highlights": [ { "field": "company_name", "snippet": "<mark>Stark</mark> Industries" } ], "document": { "id": "124", "company_name": "Stark Industries", "num_employees": 5215, "country": "USA" }, "text_match": 1234556 } ], "request_params": { "collection_name": "string", "first_q": "string", "q": "string", "per_page": 0, "voice_query": { "transcribed_query": "string" } }, "conversation": { "answer": "string", "conversation_history": [ {} ], "conversation_id": "string", "query": "string" }, "union_request_params": [ { "collection_name": "string", "first_q": "string", "q": "string", "per_page": 0, "voice_query": { "transcribed_query": "string" } } ], "metadata": {}, "parsed_nl_query": { "parse_time_ms": 0, "generated_params": {}, "augmented_params": {}, "llm_response": {} }, "query_rewrite": { "strategy": "layout", "original_q": "string", "q": "string" }, "rerank": { "applied": true, "model": "bge-reranker-base", "scored": 0, "ms": 0, "skipped": "string" }, "redirect": { "url": "string", "query": "string" }, "suggestions": [ { "query": "string", "source": "manual", "filter_by": "string", "facet": { "field": "string", "value": "string", "count": 0 } } ], "query_understanding": { "intent": "navigational", "relation": "SUBSTITUTE", "strategy": "string", "policy": "string", "search_text": "string", "protected_tokens": [ "string" ], "entities": [ { "entity_id": "string", "type": "brand", "canonical": "string", "alias": "string", "confidence": 0 } ], "constraints": [ { "kind": "string", "op": "eq", "value": null, "unit": "string", "currency": "string", "hardness": "hard", "text": "string", "filter_by": "string" } ], "confidence": 0 }, "correction": { "state": "NO_CORRECTION", "applied": { "q": "string", "type": "RAW", "score": 0, "found": 0 }, "suggestions": [ { "q": "string", "type": "RAW", "score": 0, "found": 0 } ], "reason": "string" }, "refinements": [ { "id": "string", "type": "facet", "label": "string", "query": "string", "filter_by": "string", "field": "string", "value": "string", "count": 0, "score": 0, "dimension": "string" } ]}Delete a bunch of documents DELETE
Delete a bunch of documents that match a specific filter condition. Use the `batch_size` parameter to control the number of documents that should deleted at a time. A larger value will speed up deletions, but will impact performance of other operations running on the server.
Export all documents in a collection GET
Export all documents in a collection in JSON lines format.