feat(py): Local Vector Store Plugin

Author: kirgrim

py/bin/build_dists

@@ -29,6 +29,7 @@ TOP_DIR=$(git rev-parse --show-toplevel)
 PROJECT_DIRS=(
   "packages/genkit-ai"
   "plugins/chroma"
+  "plugins/dev-local-vector-store"
   "plugins/firebase"
   "plugins/google-ai"
   "plugins/google-cloud"
@@ -59,12 +60,12 @@ done
 
 TWINE_CHECK=$(twine check ${TOP_DIR}/py/dist/*)
 
-echo "$TWINE_CHECK" 
+echo "$TWINE_CHECK"
 
-if echo "$TWINE_CHECK" | grep -q "FAIL"; then 
+if echo "$TWINE_CHECK" | grep -q "FAIL"; then
   echo "Twine check failed"
   exit 1
-else 
+else
   echo "Twine passed"
 fi
 

py/plugins/dev-local-vector-store/LICENSE

@@ -0,0 +1,201 @@
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py/plugins/dev-local-vector-store/README.md

@@ -0,0 +1,3 @@
+# Dev Local Vector Store Plugin
+
+Local file-based vectorstore plugin that provides retriever and indexer helper for Genkit.

py/plugins/dev-local-vector-store/pyproject.toml

@@ -0,0 +1,30 @@
+[project]
+authors = [{ name = "Google" }]
+classifiers = [
+  "Development Status :: 3 - Alpha",
+  "Environment :: Console",
+  "Environment :: Web Environment",
+  "Intended Audience :: Developers",
+  "Operating System :: OS Independent",
+  "License :: OSI Approved :: Apache Software License",
+  "Programming Language :: Python",
+  "Programming Language :: Python :: 3.12",
+  "Programming Language :: Python :: 3.13",
+  "Programming Language :: Python :: 3 :: Only",
+  "Topic :: Scientific/Engineering :: Artificial Intelligence",
+  "Topic :: Software Development :: Libraries",
+]
+dependencies = ["genkit-ai", "pytest-mock", "pytest-asyncio"]
+description = "Genkit Local Vector Store Plugin"
+license = { text = "Apache-2.0" }
+name = "genkit-plugin-dev-local-vectorstore"
+readme = "README.md"
+requires-python = ">=3.12"
+version = "0.1.0"
+
+[build-system]
+build-backend = "hatchling.build"
+requires      = ["hatchling"]
+
+[tool.hatch.build.targets.wheel]
+packages = ["src/genkit", "src/genkit/plugins"]

py/plugins/dev-local-vector-store/src/genkit/plugins/dev_local_vector_store/__init__.py

@@ -0,0 +1,17 @@
+# Copyright 2025 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+# SPDX-License-Identifier: Apache-2.0
+
+

py/plugins/dev-local-vector-store/src/genkit/plugins/dev_local_vector_store/constant.py

@@ -0,0 +1,33 @@
+# Copyright 2025 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+# SPDX-License-Identifier: Apache-2.0
+
+
+from typing import Any
+
+from pydantic import BaseModel
+
+from genkit.core.typing import DocumentData, Embedding
+
+
+class Params(BaseModel):
+    index_name: str
+    embedder: str
+    embedder_options: dict[str, Any] | None = None
+
+
+class DbValue(BaseModel):
+    doc: DocumentData
+    embedding: Embedding

py/plugins/dev-local-vector-store/src/genkit/plugins/dev_local_vector_store/indexer.py

@@ -0,0 +1,77 @@
+# Copyright 2025 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+# SPDX-License-Identifier: Apache-2.0
+
+
+import asyncio
+import json
+from hashlib import md5
+
+from genkit.blocks.document import Document
+from genkit.core.typing import Docs, Embedding
+from genkit.plugins.dev_local_vector_store.constant import DbValue
+from genkit.plugins.dev_local_vector_store.local_vector_store_api import (
+    LocalVectorStoreAPI,
+)
+
+
+class DevLocalVectorStoreIndexer(LocalVectorStoreAPI):
+    async def index(self, docs: Docs) -> None:
+        data = self._load_filestore()
+        tasks = []
+
+        for doc_data in docs.root:
+            tasks.append(
+                self.process_document(
+                    document=Document.from_document_data(
+                        document_data=doc_data
+                    ),
+                    data=data,
+                )
+            )
+
+        await asyncio.gather(*tasks)
+
+        with open(self.index_file_name, 'w', encoding='utf-8') as f:
+            json.dump(data, f, indent=2)
+
+    async def process_document(
+        self, document: Document, data: dict[str, DbValue]
+    ) -> None:
+        embeddings = await self.ai.embed(
+            model=self.params.embedder,
+            documents=[document],
+            options=self.params.embedder_options,
+        )
+        embedding_docs = document.get_embedding_documents(embeddings.embeddings)
+
+        for embedding, emb_doc in zip(embeddings, embedding_docs):
+            self._add_document(data=data, embedding=embedding, doc=emb_doc)
+
+    def _add_document(
+        self,
+        data: dict[str, DbValue],
+        embedding: Embedding,
+        doc: Document,
+    ) -> None:
+        data_str = json.dumps(
+            self._serialize_data(data=data), ensure_ascii=False
+        )
+        _idx = md5(data_str.encode('utf-8')).hexdigest()
+        if _idx not in data:
+            data[_idx] = DbValue(
+                doc=doc,
+                embedding=embedding,
+            )