Release 0.17.0

docs/about/changelog.md

@@ -7,14 +7,24 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ---
 
-## [Unreleased]
-
-### Removed
-- **BREAKING CHANGE: Vector store** — removed the ChromaDB vector store backend (`ChromaConfig`, `ChromaVectorStore`) and the `chromadb` dependency, due to known security vulnerabilities in the `chromadb` package. `ai4rag.rag.vector_store` no longer exports `ChromaConfig`; the `"chroma"` value for `vector_store_type` is no longer accepted (only `"milvus"`, `"milvus_lite"`, and `"pgvector"` are supported)
+## [0.17.0](https://github.com/IBM/ai4rag/releases/tag/v0.17.0)
 
 ### Added
-- **Vector store** — Milvus Lite, the embedded, zero-server mode of the Milvus backend, is now the recommended local/zero-config replacement for the removed Chroma store: use the new `MilvusLiteConfig(db_path="./ai4rag.db")` (or `MilvusLiteConfig()` for the default path). Unlike Chroma, Milvus Lite supports hybrid (dense + BM25) search. `pymilvus[milvus-lite]` is now a core dependency, so no extra installation step is needed
-- **Vector store** — the Milvus config was split into `MilvusConfig` (remote server / Zilliz Cloud only, which now validates that `uri` is an `http(s)://` URL and raises `ValueError` otherwise) and a new `MilvusLiteConfig` (embedded, local only, configured via `db_path`, which conversely rejects `http(s)://` values). Previously, a single `MilvusConfig` selected between a remote server and embedded Milvus Lite based on whether `uri` looked like a URL or a local file path; a mistyped or unreachable `MILVUS_URI` could therefore be silently interpreted as a local path and create an unintended throwaway local database. That silent fallback is no longer possible — a misconfigured server URI now fails loudly instead. `ai4rag.rag.vector_store` now also exports `MilvusLiteConfig`, and the `vector_store_type` search-space parameter accepts `"milvus_lite"` in addition to `"milvus"` and `"pgvector"`
+- **Vector store** — Milvus Lite, the embedded, zero-server mode of the Milvus backend, is now the recommended local/zero-config replacement for the removed Chroma store: use the new `MilvusLiteConfig(db_path="./ai4rag.db")` (or `MilvusLiteConfig()` for the default path). Unlike Chroma, Milvus Lite supports hybrid (dense + BM25) search, though it computes BM25 statistics segment-locally rather than corpus-wide, so hybrid-search ranking fidelity may not transfer exactly to a production Milvus server. `pymilvus[milvus-lite]` is now a core dependency, so no extra installation step is needed
+- **Vector store** — new `temporary_milvus_lite_store()` helper (`ai4rag.rag.vector_store.local_store`) providing a disposable, file-backed Milvus Lite store for internal throwaway indexes (model pre-selection, judge calibration), replacing the previous ephemeral in-memory Chroma store used for the same purpose
+- **Notebooks** — the MaaS indexing notebook template gains a "Prerequisites for Disconnected Clusters" section (validation cells, configuration examples, download instructions) for pre-downloading Docling and HuggingFace artifacts before running on an air-gapped cluster; the README documents the pre-download/transfer workflow (`DOCLING_ARTIFACTS_PATH`, `HF_HOME`, `HF_HUB_OFFLINE`)
+
+### Changed
+- **Vector store** — the Milvus config was split into `MilvusConfig` (remote server / Zilliz Cloud only, which now validates that `uri` is an `http(s)://` URL and raises `ValueError` otherwise) and a new `MilvusLiteConfig` (embedded, local only, configured via `db_path`, which conversely rejects `http(s)://` values). Previously, a single `MilvusConfig` selected between a remote server and embedded Milvus Lite based on whether `uri` looked like a URL or a local file path; a mistyped or unreachable `MILVUS_URI` could therefore be silently interpreted as a local path and create an unintended throwaway local database. That silent fallback is no longer possible — a misconfigured server URI now fails loudly instead. `ai4rag.rag.vector_store` now also exports `MilvusLiteConfig`, and the `vector_store_type` search-space parameter accepts `"milvus_lite"` in addition to `"milvus"` and `"pgvector"`. **Breaking:** `get_vector_store()` now requires `MilvusLiteConfig` (not `MilvusConfig`) when `config.provider == "milvus_lite"`
+- **Search space** — hybrid search parameters (`search_mode`, `ranker_strategy`, `ranker_k`, `ranker_alpha`) are now unconditionally part of the default search space, since every remaining vector store backend supports hybrid search. **Breaking:** `AI4RAGSearchSpace`, `prepare_search_space_with_maas()`, and `get_default_ai4rag_search_space_parameters()` no longer accept a `vector_store_type` parameter
+- **Event handler** — `VectorStoreSettings` payload fields `provider_id` / `vector_store_id` replaced by `provider_type` / `collection_name`. **Breaking:** code reading `on_pattern_creation()` payloads must switch to the new field names
+- **Dependencies** — refreshed `uv.lock` (transitive dependency updates)
+
+### Fixed
+- **CI** — the `publish-pypi` maintainer check now reads the actor's `role_name` from the GitHub API instead of the removed `permission` field
+
+### Removed
+- **BREAKING CHANGE: Vector store** — removed the ChromaDB vector store backend (`ChromaConfig`, `ChromaVectorStore`), the `chromadb` dependency, and the now-unused `ai4rag.utils.compat.ensure_sqlite3()` compatibility shim, due to known security vulnerabilities in the `chromadb` package. `ai4rag.rag.vector_store` no longer exports `ChromaConfig`; the `"chroma"` value for `vector_store_type` is no longer accepted (only `"milvus"`, `"milvus_lite"`, and `"pgvector"` are supported)
 
 ---
 

docs/architecture/core-components.md

@@ -429,11 +429,10 @@ class AI4RAGSearchSpace(SearchSpace):
         self,
         params: list[Parameter] | None = None,
         rules: list[RuleFunction] | None = None,
-        vector_store_type: str = "milvus",
     ):
 ```
 
-`vector_store_type` selects the target backend for search-space defaults; supported values are `"milvus"` (remote server, `MilvusConfig`), `"milvus_lite"` (embedded, local file, `MilvusLiteConfig`), and `"pgvector"` — an unsupported value raises `ValueError`. All three backends support hybrid search, so the same validation rules and defaults apply across them.
+All supported vector store backends (`MilvusConfig`, `MilvusLiteConfig`, `PGVectorConfig`) support hybrid search, so the same validation rules and defaults apply regardless of which backend is used at runtime.
 
 **Built-in Validation Rules:**
 

docs/development/testing.md

@@ -367,7 +367,6 @@ class TestExperimentMilvusLite:
         self, client, documents, benchmark_data, foundation_model, embedding_model, tmp_path
     ):
         search_space = AI4RAGSearchSpace(
-            vector_store_type="milvus_lite",
             params=[
                 Parameter(name="foundation_model", param_type="C", values=[foundation_model]),
                 Parameter(name="embedding_model", param_type="C", values=[embedding_model]),

docs/user-guide/event-handlers.md

@@ -89,7 +89,7 @@ def on_pattern_creation(
         "embedding":   {"model_id": "...", "embedding_params": {"embedding_dimension": 768}},
         "retrieval":   {"method": "simple", "number_of_chunks": 5, "search_mode": "vector"},
         "generation":  {"model_id": "...", ...},
-        "vector_store_binding": {"provider_id": "local_milvus", "vector_store_id": "..."},
+        "vector_store_binding": {"provider_type": "local_milvus", "collection_name": "..."},
     },
 }
 ```

docs/user-guide/search-space.md

@@ -251,7 +251,7 @@ Parameter(
 
 ## Default Parameters
 
-If you don't specify certain parameters, `AI4RAGSearchSpace` uses sensible defaults. The `vector_store_type` parameter defaults to `"milvus"` and accepts `"milvus"` (remote server, `MilvusConfig`), `"milvus_lite"` (embedded local, `MilvusLiteConfig`), or `"pgvector"` — an unsupported value raises `ValueError`. All three support dense and hybrid search (Milvus and Milvus Lite via server-side/embedded BM25, PGVector via PostgreSQL full-text search), so they share the same default parameter set.
+If you don't specify certain parameters, `AI4RAGSearchSpace` uses sensible defaults. All supported vector store backends (`MilvusConfig`, `MilvusLiteConfig`, `PGVectorConfig`) support dense and hybrid search (Milvus and Milvus Lite via server-side/embedded BM25, PGVector via PostgreSQL full-text search), so hybrid search parameters are always included in the default parameter set.
 
 ### Default Values
 
@@ -628,7 +628,6 @@ search_space = AI4RAGSearchSpace(
         Parameter(name="ranker_k", param_type="C", values=[0, 30, 60, 100]),
         Parameter(name="ranker_alpha", param_type="C", values=[1, 0.3, 0.5, 0.7]),
     ],
-    vector_store_type="milvus",  # Required for hybrid search
 )
 ```