diff --git a/.vscode/settings.json b/.vscode/settings.json
index ab66c194b3df56c15b019bcc41adfaa20fb6621b..14c396fbe813f6463931ee5af3ff2476a115fdad 100644
--- a/.vscode/settings.json
+++ b/.vscode/settings.json
@@ -1,5 +1,6 @@
{
"cSpell.words": [
+ "Astra",
"Dockerized",
"Langchain",
"Milvus",
diff --git a/docker/.env.example b/docker/.env.example
index 0adabbdf7d0e1fcf4c71d013bdedf9cb6d703944..858e4098be04792ab8b1e355e48e40cfca406639 100644
--- a/docker/.env.example
+++ b/docker/.env.example
@@ -103,6 +103,11 @@ GID='1000'
# ZILLIZ_ENDPOINT="https://sample.api.gcp-us-west1.zillizcloud.com"
# ZILLIZ_API_TOKEN=api-token-here
+# Enable all below if you are using vector database: Astra DB.
+# VECTOR_DB="astra"
+# ASTRA_DB_APPLICATION_TOKEN=
+# ASTRA_DB_ENDPOINT=
+
# CLOUD DEPLOYMENT VARIRABLES ONLY
# AUTH_TOKEN="hunter2" # This is the password to your application if remote hosting.
diff --git a/frontend/src/components/Modals/MangeWorkspace/Settings/index.jsx b/frontend/src/components/Modals/MangeWorkspace/Settings/index.jsx
index b288dc6c14b0456b8063c5d4b20de1f89328b281..a9471388fe689e7fc3841df6184adc8cf9542e64 100644
--- a/frontend/src/components/Modals/MangeWorkspace/Settings/index.jsx
+++ b/frontend/src/components/Modals/MangeWorkspace/Settings/index.jsx
@@ -44,6 +44,7 @@ export default function WorkspaceSettings({ active, workspace, settings }) {
const formEl = useRef(null);
const [saving, setSaving] = useState(false);
const [hasChanges, setHasChanges] = useState(false);
+ const [deleting, setDeleting] = useState(false);
const defaults = recommendedSettings(settings?.LLMProvider);
const handleUpdate = async (e) => {
@@ -72,7 +73,15 @@ export default function WorkspaceSettings({ active, workspace, settings }) {
)
)
return false;
- await Workspace.delete(workspace.slug);
+
+ setDeleting(true);
+ const success = await Workspace.delete(workspace.slug);
+ if (!success) {
+ showToast("Workspace could not be deleted!", "error", { clear: true });
+ setDeleting(false);
+ return;
+ }
+
workspace.slug === slug
? (window.location = paths.home())
: window.location.reload();
@@ -310,7 +319,11 @@ export default function WorkspaceSettings({ active, workspace, settings }) {
</div>
</div>
<div className="flex items-center justify-between p-2 md:p-6 space-x-2 border-t rounded-b border-gray-600">
- <DeleteWorkspace workspace={workspace} onClick={deleteWorkspace} />
+ <DeleteWorkspace
+ deleting={deleting}
+ workspace={workspace}
+ onClick={deleteWorkspace}
+ />
{hasChanges && (
<button
type="submit"
@@ -324,7 +337,7 @@ export default function WorkspaceSettings({ active, workspace, settings }) {
);
}
-function DeleteWorkspace({ workspace, onClick }) {
+function DeleteWorkspace({ deleting, workspace, onClick }) {
const [canDelete, setCanDelete] = useState(false);
useEffect(() => {
async function fetchKeys() {
@@ -337,11 +350,12 @@ function DeleteWorkspace({ workspace, onClick }) {
if (!canDelete) return null;
return (
<button
+ disabled={deleting}
onClick={onClick}
type="button"
- className="transition-all duration-300 border border-transparent rounded-lg whitespace-nowrap text-sm px-5 py-2.5 focus:z-10 bg-transparent text-white hover:text-white hover:bg-red-600"
+ className="transition-all duration-300 border border-transparent rounded-lg whitespace-nowrap text-sm px-5 py-2.5 focus:z-10 bg-transparent text-white hover:text-white hover:bg-red-600 disabled:bg-red-600 disabled:text-red-200 disabled:animate-pulse"
>
- Delete Workspace
+ {deleting ? "Deleting Workspace..." : "Delete Workspace"}
</button>
);
}
diff --git a/frontend/src/components/VectorDBSelection/AstraDBOptions/index.jsx b/frontend/src/components/VectorDBSelection/AstraDBOptions/index.jsx
new file mode 100644
index 0000000000000000000000000000000000000000..11990dc44c82e8dc96f62a0759df7f4a4602e012
--- /dev/null
+++ b/frontend/src/components/VectorDBSelection/AstraDBOptions/index.jsx
@@ -0,0 +1,41 @@
+export default function AstraDBOptions({ settings }) {
+ return (
+ <div className="w-full flex flex-col gap-y-4">
+ <div className="w-full flex items-center gap-4">
+ <div className="flex flex-col w-60">
+ <label className="text-white text-sm font-semibold block mb-4">
+ Astra DB Endpoint
+ </label>
+ <input
+ type="url"
+ name="AstraDBEndpoint"
+ className="bg-zinc-900 text-white placeholder-white placeholder-opacity-60 text-sm rounded-lg focus:border-white block w-full p-2.5"
+ placeholder="Astra DB API endpoint"
+ defaultValue={settings?.AstraDBEndpoint}
+ required={true}
+ autoComplete="off"
+ spellCheck={false}
+ />
+ </div>
+
+ <div className="flex flex-col w-60">
+ <label className="text-white text-sm font-semibold block mb-4">
+ Astra DB Application Token
+ </label>
+ <input
+ type="password"
+ name="AstraDBApplicationToken"
+ className="bg-zinc-900 text-white placeholder-white placeholder-opacity-60 text-sm rounded-lg focus:border-white block w-full p-2.5"
+ placeholder="AstraCS:..."
+ defaultValue={
+ settings?.AstraDBApplicationToken ? "*".repeat(20) : ""
+ }
+ required={true}
+ autoComplete="off"
+ spellCheck={false}
+ />
+ </div>
+ </div>
+ </div>
+ );
+}
diff --git a/frontend/src/media/vectordbs/astraDB.png b/frontend/src/media/vectordbs/astraDB.png
new file mode 100644
index 0000000000000000000000000000000000000000..3403c72f2c35ffa793b4736013a5d24bcd2b71c1
Binary files /dev/null and b/frontend/src/media/vectordbs/astraDB.png differ
diff --git a/frontend/src/pages/GeneralSettings/VectorDatabase/index.jsx b/frontend/src/pages/GeneralSettings/VectorDatabase/index.jsx
index f5f697a72c12cf85e9784b50b6571ba0f7fd4c57..dd43fda5703a57845cee5fe2d0be7c7745cc9832 100644
--- a/frontend/src/pages/GeneralSettings/VectorDatabase/index.jsx
+++ b/frontend/src/pages/GeneralSettings/VectorDatabase/index.jsx
@@ -10,6 +10,7 @@ import WeaviateLogo from "@/media/vectordbs/weaviate.png";
import QDrantLogo from "@/media/vectordbs/qdrant.png";
import MilvusLogo from "@/media/vectordbs/milvus.png";
import ZillizLogo from "@/media/vectordbs/zilliz.png";
+import AstraDBLogo from "@/media/vectordbs/astraDB.png";
import PreLoader from "@/components/Preloader";
import ChangeWarningModal from "@/components/ChangeWarning";
import { MagnifyingGlass } from "@phosphor-icons/react";
@@ -23,6 +24,7 @@ import MilvusDBOptions from "@/components/VectorDBSelection/MilvusDBOptions";
import ZillizCloudOptions from "@/components/VectorDBSelection/ZillizCloudOptions";
import { useModal } from "@/hooks/useModal";
import ModalWrapper from "@/components/ModalWrapper";
+import AstraDBOptions from "@/components/VectorDBSelection/AstraDBOptions";
export default function GeneralVectorDatabase() {
const [saving, setSaving] = useState(false);
@@ -100,6 +102,13 @@ export default function GeneralVectorDatabase() {
options: <MilvusDBOptions settings={settings} />,
description: "Open-source, highly scalable, and blazing fast.",
},
+ {
+ name: "AstraDB",
+ value: "astra",
+ logo: AstraDBLogo,
+ options: <AstraDBOptions settings={settings} />,
+ description: "Vector Search for Real-world GenAI.",
+ },
];
const updateVectorChoice = (selection) => {
diff --git a/frontend/src/pages/OnboardingFlow/Steps/DataHandling/index.jsx b/frontend/src/pages/OnboardingFlow/Steps/DataHandling/index.jsx
index ae573027639ea8318a8bdd1dfc45deb48c2d871c..60a3b6da4d5c1b2792899750900c4bff108042a8 100644
--- a/frontend/src/pages/OnboardingFlow/Steps/DataHandling/index.jsx
+++ b/frontend/src/pages/OnboardingFlow/Steps/DataHandling/index.jsx
@@ -11,6 +11,7 @@ import LMStudioLogo from "@/media/llmprovider/lmstudio.png";
import LocalAiLogo from "@/media/llmprovider/localai.png";
import MistralLogo from "@/media/llmprovider/mistral.jpeg";
import ZillizLogo from "@/media/vectordbs/zilliz.png";
+import AstraDBLogo from "@/media/vectordbs/astraDB.png";
import ChromaLogo from "@/media/vectordbs/chroma.png";
import PineconeLogo from "@/media/vectordbs/pinecone.png";
import LanceDbLogo from "@/media/vectordbs/lancedb.png";
@@ -147,6 +148,13 @@ const VECTOR_DB_PRIVACY = {
],
logo: ZillizLogo,
},
+ astra: {
+ name: "AstraDB",
+ description: [
+ "Your vectors and document text are stored on your cloud AstraDB database.",
+ ],
+ logo: AstraDBLogo,
+ },
lancedb: {
name: "LanceDB",
description: [
diff --git a/frontend/src/pages/OnboardingFlow/Steps/VectorDatabaseConnection/index.jsx b/frontend/src/pages/OnboardingFlow/Steps/VectorDatabaseConnection/index.jsx
index af0b5662d2a707b526d76a89f25a0c5c1234f990..98034528d516e012fb196c79d7459abc24a62cd3 100644
--- a/frontend/src/pages/OnboardingFlow/Steps/VectorDatabaseConnection/index.jsx
+++ b/frontend/src/pages/OnboardingFlow/Steps/VectorDatabaseConnection/index.jsx
@@ -7,6 +7,7 @@ import WeaviateLogo from "@/media/vectordbs/weaviate.png";
import QDrantLogo from "@/media/vectordbs/qdrant.png";
import MilvusLogo from "@/media/vectordbs/milvus.png";
import ZillizLogo from "@/media/vectordbs/zilliz.png";
+import AstraDBLogo from "@/media/vectordbs/astraDB.png";
import System from "@/models/system";
import paths from "@/utils/paths";
import PineconeDBOptions from "@/components/VectorDBSelection/PineconeDBOptions";
@@ -16,6 +17,7 @@ import WeaviateDBOptions from "@/components/VectorDBSelection/WeaviateDBOptions"
import LanceDBOptions from "@/components/VectorDBSelection/LanceDBOptions";
import MilvusOptions from "@/components/VectorDBSelection/MilvusDBOptions";
import ZillizCloudOptions from "@/components/VectorDBSelection/ZillizCloudOptions";
+import AstraDBOptions from "@/components/VectorDBSelection/AstraDBOptions";
import showToast from "@/utils/toast";
import { useNavigate } from "react-router-dom";
import VectorDBItem from "@/components/VectorDBSelection/VectorDBItem";
@@ -100,6 +102,13 @@ export default function VectorDatabaseConnection({
options: <MilvusOptions settings={settings} />,
description: "Open-source, highly scalable, and blazing fast.",
},
+ {
+ name: "AstraDB",
+ value: "astra",
+ logo: AstraDBLogo,
+ options: <AstraDBOptions settings={settings} />,
+ description: "Vector Search for Real-world GenAI.",
+ },
];
function handleForward() {
diff --git a/server/.env.example b/server/.env.example
index e44748b41f5eb9c01e795e3f9f891c1087385c0e..f497fea91de8a9f09688d541e894eafdd94389ba 100644
--- a/server/.env.example
+++ b/server/.env.example
@@ -76,6 +76,11 @@ JWT_SECRET="my-random-string-for-seeding" # Please generate random string at lea
# PINECONE_API_KEY=
# PINECONE_INDEX=
+# Enable all below if you are using vector database: Astra DB.
+# VECTOR_DB="astra"
+# ASTRA_DB_APPLICATION_TOKEN=
+# ASTRA_DB_ENDPOINT=
+
# Enable all below if you are using vector database: LanceDB.
VECTOR_DB="lancedb"
diff --git a/server/models/systemSettings.js b/server/models/systemSettings.js
index b4e93bde627823c6ede6951c972d8990a3a84ed2..b8c46524cfaff11fb8b34f5fe73bb10ae0b5105d 100644
--- a/server/models/systemSettings.js
+++ b/server/models/systemSettings.js
@@ -68,6 +68,12 @@ const SystemSettings = {
ZillizApiToken: process.env.ZILLIZ_API_TOKEN,
}
: {}),
+ ...(vectorDB === "astra"
+ ? {
+ AstraDBApplicationToken: process?.env?.ASTRA_DB_APPLICATION_TOKEN,
+ AstraDBEndpoint: process?.env?.ASTRA_DB_ENDPOINT,
+ }
+ : {}),
LLMProvider: llmProvider,
...(llmProvider === "openai"
? {
diff --git a/server/package.json b/server/package.json
index c8a41b795eb63243d821f09e3f244792a54032d3..bf1b85c06e866fd1425aa794d833029812ea8fad 100644
--- a/server/package.json
+++ b/server/package.json
@@ -22,6 +22,7 @@
"dependencies": {
"@anthropic-ai/sdk": "^0.8.1",
"@azure/openai": "1.0.0-beta.10",
+ "@datastax/astra-db-ts": "^0.1.3",
"@google/generative-ai": "^0.1.3",
"@googleapis/youtube": "^9.0.0",
"@pinecone-database/pinecone": "^2.0.1",
diff --git a/server/utils/helpers/index.js b/server/utils/helpers/index.js
index b72bb7977b7857b788c7b977950d7c44560cf673..53a76faebf269ea7bbf4965261d932d1f83d7042 100644
--- a/server/utils/helpers/index.js
+++ b/server/utils/helpers/index.js
@@ -22,6 +22,9 @@ function getVectorDbClass() {
case "zilliz":
const { Zilliz } = require("../vectorDbProviders/zilliz");
return Zilliz;
+ case "astra":
+ const { AstraDB } = require("../vectorDbProviders/astra");
+ return AstraDB;
default:
throw new Error("ENV: No VECTOR_DB value found in environment!");
}
diff --git a/server/utils/helpers/updateENV.js b/server/utils/helpers/updateENV.js
index b061061e82de0ac7f296e9453d38568716bf0ed6..50b423474a8c12327572520c884b259f835172f0 100644
--- a/server/utils/helpers/updateENV.js
+++ b/server/utils/helpers/updateENV.js
@@ -204,6 +204,17 @@ const KEY_MAPPING = {
checks: [isNotEmpty],
},
+ // Astra DB Options
+
+ AstraDBApplicationToken: {
+ envKey: "ASTRA_DB_APPLICATION_TOKEN",
+ checks: [isNotEmpty],
+ },
+ AstraDBEndpoint: {
+ envKey: "ASTRA_DB_ENDPOINT",
+ checks: [isNotEmpty],
+ },
+
// Together Ai Options
TogetherAiApiKey: {
envKey: "TOGETHER_AI_API_KEY",
@@ -322,6 +333,7 @@ function supportedVectorDB(input = "") {
"qdrant",
"milvus",
"zilliz",
+ "astra",
];
return supported.includes(input)
? null
diff --git a/server/utils/vectorDbProviders/astra/ASTRA_SETUP.md b/server/utils/vectorDbProviders/astra/ASTRA_SETUP.md
new file mode 100644
index 0000000000000000000000000000000000000000..e3749f0779468a415735a7e64ca79df65f52d534
--- /dev/null
+++ b/server/utils/vectorDbProviders/astra/ASTRA_SETUP.md
@@ -0,0 +1,22 @@
+# How to setup Astra Vector Database for AnythingLLM
+
+[Official Astra DB Docs](https://docs.datastax.com/en/astra/astra-db-vector/get-started/quickstart.html) for reference.
+
+### How to get started
+
+**Requirements**
+
+- Astra Vector Database with active status.
+
+**Instructions**
+
+- [Create an Astra account or sign in to an existing Astra account](astra.datastax.com)
+- Create an Astra Serverless(Vector) Database.
+- Make sure DB is in active state.
+- Get `API ENDPOINT`and `Application Token` from Overview screen
+
+```
+VECTOR_DB="astra"
+ASTRA_DB_ENDPOINT=Astra DB API endpoint
+ASTRA_DB_APPLICATION_TOKEN=AstraCS:..
+```
diff --git a/server/utils/vectorDbProviders/astra/index.js b/server/utils/vectorDbProviders/astra/index.js
new file mode 100644
index 0000000000000000000000000000000000000000..df983d4f488a393375fc3f8c88cb07af17f5e224
--- /dev/null
+++ b/server/utils/vectorDbProviders/astra/index.js
@@ -0,0 +1,380 @@
+const { AstraDB: AstraClient } = require("@datastax/astra-db-ts");
+const { RecursiveCharacterTextSplitter } = require("langchain/text_splitter");
+const { storeVectorResult, cachedVectorInformation } = require("../../files");
+const { v4: uuidv4 } = require("uuid");
+const {
+ toChunks,
+ getLLMProvider,
+ getEmbeddingEngineSelection,
+} = require("../../helpers");
+
+const AstraDB = {
+ name: "AstraDB",
+ connect: async function () {
+ if (process.env.VECTOR_DB !== "astra")
+ throw new Error("AstraDB::Invalid ENV settings");
+
+ const client = new AstraClient(
+ process?.env?.ASTRA_DB_APPLICATION_TOKEN,
+ process?.env?.ASTRA_DB_ENDPOINT
+ );
+ return { client };
+ },
+ heartbeat: async function () {
+ return { heartbeat: Number(new Date()) };
+ },
+ // Astra interface will return a valid collection object even if the collection
+ // does not actually exist. So we run a simple check which will always throw
+ // when the table truly does not exist. Faster than iterating all collections.
+ isRealCollection: async function (astraCollection = null) {
+ if (!astraCollection) return false;
+ return await astraCollection
+ .countDocuments()
+ .then(() => true)
+ .catch(() => false);
+ },
+ totalVectors: async function () {
+ const { client } = await this.connect();
+ const collectionNames = await this.allNamespaces(client);
+ var totalVectors = 0;
+ for (const name of collectionNames) {
+ const collection = await client.collection(name).catch(() => null);
+ const count = await collection.countDocuments().catch(() => 0);
+ totalVectors += count ? count : 0;
+ }
+ return totalVectors;
+ },
+ namespaceCount: async function (_namespace = null) {
+ const { client } = await this.connect();
+ const namespace = await this.namespace(client, _namespace);
+ return namespace?.vectorCount || 0;
+ },
+ namespace: async function (client, namespace = null) {
+ if (!namespace) throw new Error("No namespace value provided.");
+ const collection = await client.collection(namespace).catch(() => null);
+ if (!(await this.isRealCollection(collection))) return null;
+
+ const count = await collection.countDocuments().catch((e) => {
+ console.error("Astra::namespaceExists", e.message);
+ return null;
+ });
+
+ return {
+ name: namespace,
+ ...collection,
+ vectorCount: typeof count === "number" ? count : 0,
+ };
+ },
+ hasNamespace: async function (namespace = null) {
+ if (!namespace) return false;
+ const { client } = await this.connect();
+ return await this.namespaceExists(client, namespace);
+ },
+ namespaceExists: async function (client, namespace = null) {
+ if (!namespace) throw new Error("No namespace value provided.");
+ const collection = await client.collection(namespace);
+ return await this.isRealCollection(collection);
+ },
+ deleteVectorsInNamespace: async function (client, namespace = null) {
+ await client.dropCollection(namespace);
+ return true;
+ },
+ // AstraDB requires a dimension aspect for collection creation
+ // we pass this in from the first chunk to infer the dimensions like other
+ // providers do.
+ getOrCreateCollection: async function (client, namespace, dimensions = null) {
+ const isExists = await this.namespaceExists(client, namespace);
+ if (!isExists) {
+ if (!dimensions)
+ throw new Error(
+ `AstraDB:getOrCreateCollection Unable to infer vector dimension from input. Open an issue on Github for support.`
+ );
+
+ await client.createCollection(namespace, {
+ vector: {
+ dimension: dimensions,
+ metric: "cosine",
+ },
+ });
+ }
+ return await client.collection(namespace);
+ },
+ addDocumentToNamespace: async function (
+ namespace,
+ documentData = {},
+ fullFilePath = null
+ ) {
+ const { DocumentVectors } = require("../../../models/vectors");
+ try {
+ let vectorDimension = null;
+ const { pageContent, docId, ...metadata } = documentData;
+ if (!pageContent || pageContent.length == 0) return false;
+
+ console.log("Adding new vectorized document into namespace", namespace);
+ const cacheResult = await cachedVectorInformation(fullFilePath);
+ if (cacheResult.exists) {
+ const { client } = await this.connect();
+ const { chunks } = cacheResult;
+ const documentVectors = [];
+ vectorDimension = chunks[0][0].values.length || null;
+
+ const collection = await this.getOrCreateCollection(
+ client,
+ namespace,
+ vectorDimension
+ );
+ if (!(await this.isRealCollection(collection)))
+ throw new Error("Failed to create new AstraDB collection!", {
+ namespace,
+ });
+
+ for (const chunk of chunks) {
+ // Before sending to Astra and saving the records to our db
+ // we need to assign the id of each chunk that is stored in the cached file.
+ const newChunks = chunk.map((chunk) => {
+ const _id = uuidv4();
+ documentVectors.push({ docId, vectorId: _id });
+ return {
+ _id: _id,
+ $vector: chunk.values,
+ metadata: chunk.metadata || {},
+ };
+ });
+
+ await collection.insertMany(newChunks);
+ }
+ await DocumentVectors.bulkInsert(documentVectors);
+ return { vectorized: true, error: null };
+ }
+
+ const textSplitter = new RecursiveCharacterTextSplitter({
+ chunkSize:
+ getEmbeddingEngineSelection()?.embeddingMaxChunkLength || 1_000,
+ chunkOverlap: 20,
+ });
+ const textChunks = await textSplitter.splitText(pageContent);
+
+ console.log("Chunks created from document:", textChunks.length);
+ const LLMConnector = getLLMProvider();
+ const documentVectors = [];
+ const vectors = [];
+ const vectorValues = await LLMConnector.embedChunks(textChunks);
+
+ if (!!vectorValues && vectorValues.length > 0) {
+ for (const [i, vector] of vectorValues.entries()) {
+ if (!vectorDimension) vectorDimension = vector.length;
+ const vectorRecord = {
+ _id: uuidv4(),
+ $vector: vector,
+ metadata: { ...metadata, text: textChunks[i] },
+ };
+
+ vectors.push(vectorRecord);
+ documentVectors.push({ docId, vectorId: vectorRecord._id });
+ }
+ } else {
+ throw new Error(
+ "Could not embed document chunks! This document will not be recorded."
+ );
+ }
+ const { client } = await this.connect();
+ const collection = await this.getOrCreateCollection(
+ client,
+ namespace,
+ vectorDimension
+ );
+ if (!(await this.isRealCollection(collection)))
+ throw new Error("Failed to create new AstraDB collection!", {
+ namespace,
+ });
+
+ if (vectors.length > 0) {
+ const chunks = [];
+
+ console.log("Inserting vectorized chunks into Astra DB.");
+
+ // AstraDB has maximum upsert size of 20 records per-request so we have to use a lower chunk size here
+ // in order to do the queries - this takes a lot more time than other providers but there
+ // is no way around it. This will save the vector-cache with the same layout, so we don't
+ // have to chunk again for cached files.
+ for (const chunk of toChunks(vectors, 20)) {
+ chunks.push(
+ chunk.map((c) => {
+ return { id: c._id, values: c.$vector, metadata: c.metadata };
+ })
+ );
+ await collection.insertMany(chunk);
+ }
+ await storeVectorResult(chunks, fullFilePath);
+ }
+
+ await DocumentVectors.bulkInsert(documentVectors);
+ return { vectorized: true, error: null };
+ } catch (e) {
+ console.error("addDocumentToNamespace", e.message);
+ return { vectorized: false, error: e.message };
+ }
+ },
+ deleteDocumentFromNamespace: async function (namespace, docId) {
+ const { DocumentVectors } = require("../../../models/vectors");
+ const { client } = await this.connect();
+ if (!(await this.namespaceExists(client, namespace)))
+ throw new Error(
+ "Invalid namespace - has it been collected and populated yet?"
+ );
+ const collection = await client.collection(namespace);
+
+ const knownDocuments = await DocumentVectors.where({ docId });
+ if (knownDocuments.length === 0) return;
+
+ const vectorIds = knownDocuments.map((doc) => doc.vectorId);
+ for (const id of vectorIds) {
+ await collection.deleteMany({
+ _id: id,
+ });
+ }
+
+ const indexes = knownDocuments.map((doc) => doc.id);
+ await DocumentVectors.deleteIds(indexes);
+ return true;
+ },
+ performSimilaritySearch: async function ({
+ namespace = null,
+ input = "",
+ LLMConnector = null,
+ similarityThreshold = 0.25,
+ topN = 4,
+ }) {
+ if (!namespace || !input || !LLMConnector)
+ throw new Error("Invalid request to performSimilaritySearch.");
+
+ const { client } = await this.connect();
+ if (!(await this.namespaceExists(client, namespace))) {
+ return {
+ contextTexts: [],
+ sources: [],
+ message:
+ "Invalid query - no namespace found for workspace in vector db!",
+ };
+ }
+
+ const queryVector = await LLMConnector.embedTextInput(input);
+ const { contextTexts, sourceDocuments } = await this.similarityResponse(
+ client,
+ namespace,
+ queryVector,
+ similarityThreshold,
+ topN
+ );
+
+ const sources = sourceDocuments.map((metadata, i) => {
+ return { ...metadata, text: contextTexts[i] };
+ });
+ return {
+ contextTexts,
+ sources: this.curateSources(sources),
+ message: false,
+ };
+ },
+ similarityResponse: async function (
+ client,
+ namespace,
+ queryVector,
+ similarityThreshold = 0.25,
+ topN = 4
+ ) {
+ const result = {
+ contextTexts: [],
+ sourceDocuments: [],
+ scores: [],
+ };
+
+ const collection = await client.collection(namespace);
+ const responses = await collection
+ .find(
+ {},
+ {
+ sort: { $vector: queryVector },
+ limit: topN,
+ includeSimilarity: true,
+ }
+ )
+ .toArray();
+
+ responses.forEach((response) => {
+ if (response.$similarity < similarityThreshold) return;
+ result.contextTexts.push(response.metadata.text);
+ result.sourceDocuments.push(response);
+ result.scores.push(response.$similarity);
+ });
+ return result;
+ },
+ allNamespaces: async function (client) {
+ try {
+ let header = new Headers();
+ header.append("Token", client?.httpClient?.applicationToken);
+ header.append("Content-Type", "application/json");
+
+ let raw = JSON.stringify({
+ findCollections: {},
+ });
+
+ let requestOptions = {
+ method: "POST",
+ headers: header,
+ body: raw,
+ redirect: "follow",
+ };
+
+ const call = await fetch(client?.httpClient?.baseUrl, requestOptions);
+ const resp = await call?.text();
+ const collections = resp ? JSON.parse(resp)?.status?.collections : [];
+ return collections;
+ } catch (e) {
+ console.error("Astra::AllNamespace", e);
+ return [];
+ }
+ },
+ "namespace-stats": async function (reqBody = {}) {
+ const { namespace = null } = reqBody;
+ if (!namespace) throw new Error("namespace required");
+ const { client } = await this.connect();
+ if (!(await this.namespaceExists(client, namespace)))
+ throw new Error("Namespace by that name does not exist.");
+ const stats = await this.namespace(client, namespace);
+ return stats
+ ? stats
+ : { message: "No stats were able to be fetched from DB for namespace" };
+ },
+ "delete-namespace": async function (reqBody = {}) {
+ const { namespace = null } = reqBody;
+ const { client } = await this.connect();
+ if (!(await this.namespaceExists(client, namespace)))
+ throw new Error("Namespace by that name does not exist.");
+
+ const details = await this.namespace(client, namespace);
+ await this.deleteVectorsInNamespace(client, namespace);
+ return {
+ message: `Namespace ${namespace} was deleted along with ${
+ details?.vectorCount || "all"
+ } vectors.`,
+ };
+ },
+ curateSources: function (sources = []) {
+ const documents = [];
+ for (const source of sources) {
+ if (Object.keys(source).length > 0) {
+ const metadata = source.hasOwnProperty("metadata")
+ ? source.metadata
+ : source;
+ documents.push({
+ ...metadata,
+ });
+ }
+ }
+
+ return documents;
+ },
+};
+
+module.exports.AstraDB = AstraDB;
diff --git a/server/yarn.lock b/server/yarn.lock
index 67b4e11b67c7d7681fdc1ce22ffa2f9f8d1fbc20..ecc8f1a75555e57078e20566c12d814f70661aba 100644
--- a/server/yarn.lock
+++ b/server/yarn.lock
@@ -174,6 +174,15 @@
enabled "2.0.x"
kuler "^2.0.0"
+"@datastax/astra-db-ts@^0.1.3":
+ version "0.1.3"
+ resolved "https://registry.yarnpkg.com/@datastax/astra-db-ts/-/astra-db-ts-0.1.3.tgz#fcc25cda8d146c06278860054f09d687ff031568"
+ integrity sha512-7lnpym0HhUtfJVd8+vu6vYdDQpFyYof7TVLFVD2fgoIjUwj3EksFXmqDqicLAlLferZDllqSVthX9pXQ5Rdapw==
+ dependencies:
+ axios "^1.4.0"
+ bson "^6.2.0"
+ winston "^3.7.2"
+
"@eslint-community/eslint-utils@^4.2.0":
version "4.4.0"
resolved "https://registry.yarnpkg.com/@eslint-community/eslint-utils/-/eslint-utils-4.4.0.tgz#a23514e8fb9af1269d5f7788aa556798d61c6b59"
@@ -1353,6 +1362,11 @@ braces@~3.0.2:
dependencies:
fill-range "^7.0.1"
+bson@^6.2.0:
+ version "6.2.0"
+ resolved "https://registry.yarnpkg.com/bson/-/bson-6.2.0.tgz#4b6acafc266ba18eeee111373c2699304a9ba0a3"
+ integrity sha512-ID1cI+7bazPDyL9wYy9GaQ8gEEohWvcUl/Yf0dIdutJxnmInEEyCsb4awy/OiBfall7zBA179Pahi3vCdFze3Q==
+
btoa-lite@^1.0.0:
version "1.0.0"
resolved "https://registry.yarnpkg.com/btoa-lite/-/btoa-lite-1.0.0.tgz#337766da15801210fdd956c22e9c6891ab9d0337"
@@ -5636,7 +5650,7 @@ winston-transport@^4.5.0:
readable-stream "^3.6.0"
triple-beam "^1.3.0"
-winston@^3.9.0:
+winston@^3.7.2, winston@^3.9.0:
version "3.11.0"
resolved "https://registry.yarnpkg.com/winston/-/winston-3.11.0.tgz#2d50b0a695a2758bb1c95279f0a88e858163ed91"
integrity sha512-L3yR6/MzZAOl0DsysUXHVjOwv8mKZ71TrA/41EIduGpOOV5LQVodqN+QdQ6BS6PJ/RdIshZhq84P/fStEZkk7g==