diff --git a/docs/extras/integrations/document_transformers/nuclia_transformer.ipynb b/docs/extras/integrations/document_transformers/nuclia_transformer.ipynb index d4317c9bba..468be00d94 100644 --- a/docs/extras/integrations/document_transformers/nuclia_transformer.ipynb +++ b/docs/extras/integrations/document_transformers/nuclia_transformer.ipynb @@ -18,7 +18,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -93,8 +93,22 @@ } ], "metadata": { + "kernelspec": { + "display_name": "langchain", + "language": "python", + "name": "python3" + }, "language_info": { - "name": "python" + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.5" }, "orig_nbformat": 4 }, diff --git a/docs/extras/integrations/vectorstores/nucliadb_vectorstore.ipynb b/docs/extras/integrations/vectorstores/nucliadb_vectorstore.ipynb new file mode 100644 index 0000000000..f652397b7e --- /dev/null +++ b/docs/extras/integrations/vectorstores/nucliadb_vectorstore.ipynb @@ -0,0 +1,151 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# NucliaDB vector store\n", + "\n", + "You can use a local NucliaDB instance or use [Nuclia Cloud](https://nuclia.cloud).\n", + "\n", + "When using a local instance, you need a Nuclia Understanding API key, so your texts are properly vectorized and indexed. You can get a key by creating a free account at [https://nuclia.cloud](https://nuclia.cloud), and then [create a NUA key](https://docs.nuclia.dev/docs/docs/using/understanding/intro)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#!pip install nuclia" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Usage with nuclia.cloud" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "ename": "ValueError", + "evalue": "nuclia python package not found. Please install it with `pip install nuclia`.", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)", + "File \u001b[0;32m~/dev/osprojects/langchain/libs/langchain/langchain/vectorstores/nucliadb.py:39\u001b[0m, in \u001b[0;36mNucliaDB.__init__\u001b[0;34m(self, knowledge_box, local, api_key, backend)\u001b[0m\n\u001b[1;32m 38\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[0;32m---> 39\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mnuclia\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39msdk\u001b[39;00m \u001b[39mimport\u001b[39;00m NucliaAuth\n\u001b[1;32m 40\u001b[0m \u001b[39mexcept\u001b[39;00m \u001b[39mImportError\u001b[39;00m:\n", + "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'nuclia'", + "\nDuring handling of the above exception, another exception occurred:\n", + "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[1], line 4\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mlangchain\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mvectorstores\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mnucliadb\u001b[39;00m \u001b[39mimport\u001b[39;00m NucliaDB\n\u001b[1;32m 2\u001b[0m API_KEY \u001b[39m=\u001b[39m \u001b[39m\"\u001b[39m\u001b[39mYOUR_API_KEY\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m----> 4\u001b[0m ndb \u001b[39m=\u001b[39m NucliaDB(knowledge_box\u001b[39m=\u001b[39;49m\u001b[39m\"\u001b[39;49m\u001b[39mYOUR_KB_ID\u001b[39;49m\u001b[39m\"\u001b[39;49m, local\u001b[39m=\u001b[39;49m\u001b[39mFalse\u001b[39;49;00m, api_key\u001b[39m=\u001b[39;49mAPI_KEY)\n", + "File \u001b[0;32m~/dev/osprojects/langchain/libs/langchain/langchain/vectorstores/nucliadb.py:41\u001b[0m, in \u001b[0;36mNucliaDB.__init__\u001b[0;34m(self, knowledge_box, local, api_key, backend)\u001b[0m\n\u001b[1;32m 39\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mnuclia\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39msdk\u001b[39;00m \u001b[39mimport\u001b[39;00m NucliaAuth\n\u001b[1;32m 40\u001b[0m \u001b[39mexcept\u001b[39;00m \u001b[39mImportError\u001b[39;00m:\n\u001b[0;32m---> 41\u001b[0m \u001b[39mraise\u001b[39;00m \u001b[39mValueError\u001b[39;00m(\n\u001b[1;32m 42\u001b[0m \u001b[39m\"\u001b[39m\u001b[39mnuclia python package not found. \u001b[39m\u001b[39m\"\u001b[39m\n\u001b[1;32m 43\u001b[0m \u001b[39m\"\u001b[39m\u001b[39mPlease install it with `pip install nuclia`.\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[1;32m 44\u001b[0m )\n\u001b[1;32m 45\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_config[\u001b[39m\"\u001b[39m\u001b[39mLOCAL\u001b[39m\u001b[39m\"\u001b[39m] \u001b[39m=\u001b[39m local\n\u001b[1;32m 46\u001b[0m zone \u001b[39m=\u001b[39m os\u001b[39m.\u001b[39menviron\u001b[39m.\u001b[39mget(\u001b[39m\"\u001b[39m\u001b[39mNUCLIA_ZONE\u001b[39m\u001b[39m\"\u001b[39m, \u001b[39m\"\u001b[39m\u001b[39meurope-1\u001b[39m\u001b[39m\"\u001b[39m)\n", + "\u001b[0;31mValueError\u001b[0m: nuclia python package not found. Please install it with `pip install nuclia`." + ] + } + ], + "source": [ + "from langchain.vectorstores.nucliadb import NucliaDB\n", + "API_KEY = \"YOUR_API_KEY\"\n", + "\n", + "ndb = NucliaDB(knowledge_box=\"YOUR_KB_ID\", local=False, api_key=API_KEY)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Usage with a local instance\n", + "\n", + "Note: By default `backend` is set to `http://localhost:8080`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from langchain.vectorstores.nucliadb import NucliaDB\n", + "\n", + "ndb = NucliaDB(knowledge_box=\"YOUR_KB_ID\", local=True, backend=\"http://my-local-server\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Add and delete texts to your Knowledge Box" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ids = ndb.add_texts([\"This is a new test\", \"This is a second test\"])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ndb.delete(ids=ids)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Search in your Knowledge Box" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "results = ndb.similarity_search(\"Who was inspired by Ada Lovelace?\")\n", + "print(res.page_content)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "langchain", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.5" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/libs/langchain/langchain/vectorstores/nucliadb.py b/libs/langchain/langchain/vectorstores/nucliadb.py new file mode 100644 index 0000000000..8ba9d4454c --- /dev/null +++ b/libs/langchain/langchain/vectorstores/nucliadb.py @@ -0,0 +1,159 @@ +import os +from typing import Any, Dict, Iterable, List, Optional, Type + +from langchain.embeddings.base import Embeddings +from langchain.schema.document import Document +from langchain.vectorstores.base import VST, VectorStore + +FIELD_TYPES = { + "f": "files", + "t": "texts", + "l": "links", +} + + +class NucliaDB(VectorStore): + """NucliaDB vector store.""" + + _config: Dict[str, Any] = {} + + def __init__( + self, + knowledge_box: str, + local: bool, + api_key: Optional[str] = None, + backend: Optional[str] = None, + ) -> None: + """Initialize the NucliaDB client. + + Args: + knowledge_box: the Knowledge Box id. + local: Whether to use a local NucliaDB instance or Nuclia Cloud + api_key: A contributor API key for the kb (needed when local is False) + backend: The backend url to use when local is True, defaults to + http://localhost:8080 + """ + try: + from nuclia.sdk import NucliaAuth + except ImportError: + raise ValueError( + "nuclia python package not found. " + "Please install it with `pip install nuclia`." + ) + self._config["LOCAL"] = local + zone = os.environ.get("NUCLIA_ZONE", "europe-1") + self._kb = knowledge_box + if local: + if not backend: + backend = "http://localhost:8080" + self._config["BACKEND"] = f"{backend}/api/v1" + self._config["TOKEN"] = None + NucliaAuth().nucliadb(url=backend) + NucliaAuth().kb(url=self.kb_url, interactive=False) + else: + self._config["BACKEND"] = f"https://{zone}.nuclia.cloud/api/v1" + self._config["TOKEN"] = api_key + NucliaAuth().kb( + url=self.kb_url, token=self._config["TOKEN"], interactive=False + ) + + @property + def is_local(self) -> str: + return self._config["LOCAL"] + + @property + def kb_url(self) -> str: + return f"{self._config['BACKEND']}/kb/{self._kb}" + + def add_texts( + self, + texts: Iterable[str], + metadatas: Optional[List[dict]] = None, + **kwargs: Any, + ) -> List[str]: + """Upload texts to NucliaDB""" + ids = [] + from nuclia.sdk import NucliaResource + + factory = NucliaResource() + for i, text in enumerate(texts): + extra: Dict[str, Any] = {"metadata": ""} + if metadatas: + extra = {"metadata": metadatas[i]} + id = factory.create( + texts={"text": {"body": text}}, + extra=extra, + url=self.kb_url, + api_key=self._config["TOKEN"], + ) + ids.append(id) + return ids + + def delete(self, ids: Optional[List[str]] = None, **kwargs: Any) -> Optional[bool]: + if not ids: + return None + from nuclia.sdk import NucliaResource + + factory = NucliaResource() + results: List[bool] = [] + for id in ids: + try: + factory.delete(rid=id, url=self.kb_url, api_key=self._config["TOKEN"]) + results.append(True) + except ValueError: + results.append(False) + return all(results) + + def similarity_search( + self, query: str, k: int = 4, **kwargs: Any + ) -> List[Document]: + from nuclia.sdk import NucliaSearch + from nucliadb_models.search import FindRequest, ResourceProperties + + request = FindRequest( + query=query, + page_size=k, + show=[ResourceProperties.VALUES, ResourceProperties.EXTRA], + ) + search = NucliaSearch() + results = search.find( + query=request, url=self.kb_url, api_key=self._config["TOKEN"] + ) + paragraphs = [] + for resource in results.resources.values(): + for field in resource.fields.values(): + for paragraph_id, paragraph in field.paragraphs.items(): + info = paragraph_id.split("/") + field_type = FIELD_TYPES.get(info[1], None) + field_id = info[2] + if not field_type: + continue + value = getattr(resource.data, field_type, {}).get(field_id, None) + paragraphs.append( + { + "text": paragraph.text, + "metadata": { + "extra": getattr( + getattr(resource, "extra", {}), "metadata", None + ), + "value": value, + }, + "order": paragraph.order, + } + ) + sorted_paragraphs = sorted(paragraphs, key=lambda x: x["order"]) + return [ + Document(page_content=paragraph["text"], metadata=paragraph["metadata"]) + for paragraph in sorted_paragraphs + ] + + @classmethod + def from_texts( + cls: Type[VST], + texts: List[str], + embedding: Embeddings, + metadatas: Optional[List[dict]] = None, + **kwargs: Any, + ) -> VST: + """Return VectorStore initialized from texts and embeddings.""" + raise NotImplementedError diff --git a/libs/langchain/poetry.lock b/libs/langchain/poetry.lock index d742e5a896..49da0cda86 100644 --- a/libs/langchain/poetry.lock +++ b/libs/langchain/poetry.lock @@ -2440,6 +2440,20 @@ calc = ["shapely"] s3 = ["boto3 (>=1.3.1)"] test = ["Fiona[s3]", "pytest (>=7)", "pytest-cov", "pytz"] +[[package]] +name = "fire" +version = "0.5.0" +description = "A library for automatically generating command line interfaces." +optional = true +python-versions = "*" +files = [ + {file = "fire-0.5.0.tar.gz", hash = "sha256:a6b0d49e98c8963910021f92bba66f65ab440da2982b78eb1bbf95a0a34aacc6"}, +] + +[package.dependencies] +six = "*" +termcolor = "*" + [[package]] name = "flatbuffers" version = "23.5.26" @@ -2686,6 +2700,42 @@ files = [ [package.dependencies] gitdb = ">=4.0.1,<5" +[[package]] 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-version = "1.22.0" +version = "1.26.0" description = "A faster way to build and share data apps" category = "main" optional = true -python-versions = ">=3.7, !=3.9.7" +python-versions = ">=3.8, !=3.9.7" files = [ - {file = "streamlit-1.22.0-py2.py3-none-any.whl", hash = "sha256:520dd9b9e6efb559b5a9a22feadb48b1e6f0340ec83da3514810059fdecd4167"}, - {file = "streamlit-1.22.0.tar.gz", hash = "sha256:5bef9bf8deef32814d9565c9df48331e6357eb0b90dabc3ec4f53c44fb34fc73"}, + {file = "streamlit-1.26.0-py2.py3-none-any.whl", hash = "sha256:2bfdac041816e2e1ba27f061d40112afe61e0d4e72d25f354b38ba81107b4cb3"}, + {file = "streamlit-1.26.0.tar.gz", hash = "sha256:25475fb15a3cc9fb184945f3fc936f011998bd8386e0c892febe14c9625bf47a"}, ] [package.dependencies] -altair = ">=3.2.0,<5" -blinker = ">=1.0.0" -cachetools = ">=4.0" -click = ">=7.0" -gitpython = "!=3.1.19" -importlib-metadata = ">=1.4" -numpy = "*" -packaging = ">=14.1" -pandas = ">=0.25,<3" -pillow = ">=6.2.0" -protobuf = ">=3.12,<4" -pyarrow = 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snowflake = ["snowflake-snowpark-python"] @@ -10927,4 +11045,4 @@ text-helpers = ["chardet"] [metadata] lock-version = "2.0" python-versions = ">=3.8.1,<4.0" -content-hash = "b63078268a80c07577b432114302f4f86d47be25b83a245affb0dbc999fb2c1f" +content-hash = "600bb53efb135b6058aed19ff13c41de9b27f18a85f14fb4fb425a89644001ec" diff --git a/libs/langchain/pyproject.toml b/libs/langchain/pyproject.toml index d3c80bbeae..8ecc83d83f 100644 --- a/libs/langchain/pyproject.toml +++ b/libs/langchain/pyproject.toml @@ -129,6 +129,7 @@ markdownify = {version = "^0.11.6", optional = true} assemblyai = {version = "^0.17.0", optional = true} dashvector = {version = "^1.0.1", optional = true} sqlite-vss = {version = "^0.1.2", optional = true} +nuclia = {version = "^1.1.10", optional = true} [tool.poetry.group.test.dependencies] @@ -345,6 +346,7 @@ extended_testing = [ "markdownify", "dashvector", "sqlite-vss", + "nuclia", ] [tool.ruff] diff --git a/libs/langchain/tests/integration_tests/vectorstores/test_nucliadb.py b/libs/langchain/tests/integration_tests/vectorstores/test_nucliadb.py new file mode 100644 index 0000000000..1cfeea0da4 --- /dev/null +++ b/libs/langchain/tests/integration_tests/vectorstores/test_nucliadb.py @@ -0,0 +1,98 @@ +from typing import Any +from unittest import mock + +from langchain.vectorstores.nucliadb import NucliaDB + + +class attrdict(dict): + def __getitem__(self, key: str) -> Any: + value = dict.__getitem__(self, key) + return attrdict(value) if isinstance(value, dict) else value + + __getattr__ = __getitem__ + + +def FakeCreate(**args: Any) -> Any: + def fn(self: Any, **kwargs: Any) -> str: + return "fake_uuid" + + return fn + + +def FakeDelete(**args: Any) -> Any: + def fn(self: Any, **kwargs: Any) -> None: + return None + + return fn + + +def FakeFind(**args: Any) -> Any: + def fn(self: Any, **kwargs: Any) -> Any: + return attrdict( + { + "resources": { + "123": attrdict( + { + "fields": { + "456": attrdict( + { + "paragraphs": { + "123/t/text/0-14": attrdict( + { + "text": "This is a test", + "order": 0, + } + ), + } + } + ) + }, + "data": { + "texts": { + "text": { + "body": "This is a test", + } + } + }, + "extra": attrdict({"metadata": {"some": "metadata"}}), + } + ) + } + } + ) + + return fn + + +def test_add_texts() -> None: + with mock.patch( + "nuclia.sdk.resource.NucliaResource.create", + new_callable=FakeCreate, + ): + ndb = NucliaDB(knowledge_box="YOUR_KB_ID", local=False, api_key="YOUR_API_KEY") + assert ndb.is_local is False + ids = ndb.add_texts(["This is a new test", "This is a second test"]) + assert len(ids) == 2 + + +def test_delete() -> None: + with mock.patch( + "nuclia.sdk.resource.NucliaResource.delete", + new_callable=FakeDelete, + ): + ndb = NucliaDB(knowledge_box="YOUR_KB_ID", local=False, api_key="YOUR_API_KEY") + success = ndb.delete(["123", "456"]) + assert success + + +def test_search() -> None: + with mock.patch( + "nuclia.sdk.search.NucliaSearch.find", + new_callable=FakeFind, + ): + ndb = NucliaDB(knowledge_box="YOUR_KB_ID", local=False, api_key="YOUR_API_KEY") + results = ndb.similarity_search("Who was inspired by Ada Lovelace?") + assert len(results) == 1 + assert results[0].page_content == "This is a test" + assert results[0].metadata["extra"]["some"] == "metadata" + assert results[0].metadata["value"]["body"] == "This is a test"