diff --git a/.changeset/lovely-olives-carry.md b/.changeset/lovely-olives-carry.md
new file mode 100644
index 0000000000000000000000000000000000000000..99741125edde227bdf27d07dafe3fdad9a8c4664
--- /dev/null
+++ b/.changeset/lovely-olives-carry.md
@@ -0,0 +1,5 @@
+---
+"create-llama": patch
+---
+
+Add Qdrant support
diff --git a/helpers/env-variables.ts b/helpers/env-variables.ts
index 65782179acdcde6d9b33ff598c9c6e1d9dbff16e..ecaed32be6c69d774b2a57d9035533f18c7a2bc7 100644
--- a/helpers/env-variables.ts
+++ b/helpers/env-variables.ts
@@ -108,6 +108,23 @@ const getVectorDBEnvs = (vectorDb: TemplateVectorDB) => {
description: "The name of the collection in your Astra database",
},
];
+ case "qdrant":
+ return [
+ {
+ name: "QDRANT_URL",
+ description:
+ "The qualified REST URL of the Qdrant server. Eg: http://localhost:6333",
+ },
+ {
+ name: "QDRANT_COLLECTION",
+ description: "The name of Qdrant collection to use.",
+ },
+ {
+ name: "QDRANT_API_KEY",
+ description:
+ "Optional API key for authenticating requests to Qdrant.",
+ },
+ ];
default:
return [];
}
diff --git a/helpers/types.ts b/helpers/types.ts
index 52a300a757343e4fcf73d935bf4a9f5dffba8aa0..0db557ed1ccf753a95c353ab2211d22420d9bc3f 100644
--- a/helpers/types.ts
+++ b/helpers/types.ts
@@ -10,7 +10,8 @@ export type TemplateVectorDB =
| "pg"
| "pinecone"
| "milvus"
- | "astra";
+ | "astra"
+ | "qdrant";
export type TemplatePostInstallAction =
| "none"
| "VSCode"
diff --git a/questions.ts b/questions.ts
index 4afd0085478b102478881dfb4c7d950ed0c4c308..6efbc45d55add0ee441b9c29a822ad4d4cb2c02c 100644
--- a/questions.ts
+++ b/questions.ts
@@ -102,6 +102,7 @@ const getVectorDbChoices = (framework: TemplateFramework) => {
{ title: "Pinecone", value: "pinecone" },
{ title: "Milvus", value: "milvus" },
{ title: "Astra", value: "astra" },
+ { title: "Qdrant", value: "qdrant" },
];
const vectordbLang = framework === "fastapi" ? "python" : "typescript";
diff --git a/templates/components/vectordbs/python/qdrant/__init__.py b/templates/components/vectordbs/python/qdrant/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/templates/components/vectordbs/python/qdrant/generate.py b/templates/components/vectordbs/python/qdrant/generate.py
new file mode 100644
index 0000000000000000000000000000000000000000..db7c055e492311a5f6e6f01bbdf0406ce470cfde
--- /dev/null
+++ b/templates/components/vectordbs/python/qdrant/generate.py
@@ -0,0 +1,37 @@
+import logging
+import os
+from app.engine.loaders import get_documents
+from app.settings import init_settings
+from dotenv import load_dotenv
+from llama_index.core.indices import VectorStoreIndex
+from llama_index.core.storage import StorageContext
+from llama_index.vector_stores.qdrant import QdrantVectorStore
+load_dotenv()
+
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger()
+
+
+def generate_datasource():
+ init_settings()
+ logger.info("Creating new index with Qdrant")
+ # load the documents and create the index
+ documents = get_documents()
+ store = QdrantVectorStore(
+ collection_name=os.getenv("QDRANT_COLLECTION"),
+ url=os.getenv("QDRANT_URL"),
+ api_key=os.getenv("QDRANT_API_KEY"),
+ )
+ storage_context = StorageContext.from_defaults(vector_store=store)
+ VectorStoreIndex.from_documents(
+ documents,
+ storage_context=storage_context,
+ show_progress=True, # this will show you a progress bar as the embeddings are created
+ )
+ logger.info(
+ f"Successfully uploaded documents to the {os.getenv('QDRANT_COLLECTION')} collection."
+ )
+
+
+if __name__ == "__main__":
+ generate_datasource()
diff --git a/templates/components/vectordbs/python/qdrant/index.py b/templates/components/vectordbs/python/qdrant/index.py
new file mode 100644
index 0000000000000000000000000000000000000000..0a388d8a303f937aedec42aaecb73668b83f0c84
--- /dev/null
+++ b/templates/components/vectordbs/python/qdrant/index.py
@@ -0,0 +1,20 @@
+import logging
+import os
+
+from llama_index.core.indices import VectorStoreIndex
+from llama_index.vector_stores.qdrant import QdrantVectorStore
+
+
+logger = logging.getLogger("uvicorn")
+
+
+def get_index():
+ logger.info("Connecting to Qdrant collection..")
+ store = QdrantVectorStore(
+ collection_name=os.getenv("QDRANT_COLLECTION"),
+ url=os.getenv("QDRANT_URL"),
+ api_key=os.getenv("QDRANT_API_KEY"),
+ )
+ index = VectorStoreIndex.from_vector_store(store)
+ logger.info("Finished connecting to Qdrant collection.")
+ return index
diff --git a/templates/components/vectordbs/typescript/qdrant/generate.ts b/templates/components/vectordbs/typescript/qdrant/generate.ts
new file mode 100644
index 0000000000000000000000000000000000000000..f0e7fa40f9943bd5426d57324b06102dafed3102
--- /dev/null
+++ b/templates/components/vectordbs/typescript/qdrant/generate.ts
@@ -0,0 +1,37 @@
+/* eslint-disable turbo/no-undeclared-env-vars */
+import * as dotenv from "dotenv";
+import {
+ QdrantVectorStore,
+ VectorStoreIndex,
+ storageContextFromDefaults,
+} from "llamaindex";
+import { getDocuments } from "./loader";
+import { initSettings } from "./settings";
+import { checkRequiredEnvVars, getQdrantClient } from "./shared";
+
+dotenv.config();
+
+const collectionName = process.env.QDRANT_COLLECTION;
+
+async function loadAndIndex() {
+ // load objects from storage and convert them into LlamaIndex Document objects
+ const documents = await getDocuments();
+
+ // Connect to Qdrant
+ const vectorStore = new QdrantVectorStore(collectionName, getQdrantClient());
+
+ const storageContext = await storageContextFromDefaults({ vectorStore });
+ await VectorStoreIndex.fromDocuments(documents, {
+ storageContext: storageContext,
+ });
+ console.log(
+ `Successfully upload embeddings to Qdrant collection ${collectionName}.`,
+ );
+}
+
+(async () => {
+ checkRequiredEnvVars();
+ initSettings();
+ await loadAndIndex();
+ console.log("Finished generating storage.");
+})();
diff --git a/templates/components/vectordbs/typescript/qdrant/index.ts b/templates/components/vectordbs/typescript/qdrant/index.ts
new file mode 100644
index 0000000000000000000000000000000000000000..229d7a3984c921c631dcd6be4a9b6cd6cf244bca
--- /dev/null
+++ b/templates/components/vectordbs/typescript/qdrant/index.ts
@@ -0,0 +1,13 @@
+import * as dotenv from "dotenv";
+import { QdrantVectorStore, VectorStoreIndex } from "llamaindex";
+import { checkRequiredEnvVars, getQdrantClient } from "./shared";
+
+dotenv.config();
+
+export async function getDataSource() {
+ checkRequiredEnvVars();
+ const collectionName = process.env.QDRANT_COLLECTION;
+ const store = new QdrantVectorStore(collectionName, getQdrantClient());
+
+ return await VectorStoreIndex.fromVectorStore(store);
+}
diff --git a/templates/components/vectordbs/typescript/qdrant/shared.ts b/templates/components/vectordbs/typescript/qdrant/shared.ts
new file mode 100644
index 0000000000000000000000000000000000000000..e1475eeed3486ce7f40fb92cac6efc934bbbf9c8
--- /dev/null
+++ b/templates/components/vectordbs/typescript/qdrant/shared.ts
@@ -0,0 +1,32 @@
+import { QdrantClient } from "@qdrant/js-client-rest";
+
+const REQUIRED_ENV_VARS = ["QDRANT_URL", "QDRANT_COLLECTION"]; // QDRANT_API_KEY is optional
+
+export function getQdrantClient() {
+ const url = process.env.QDRANT_URL;
+ if (!url) {
+ throw new Error("QDRANT_URL environment variable is required");
+ }
+ const apiKey = process.env?.QDRANT_API_KEY;
+ return new QdrantClient({
+ url,
+ apiKey,
+ });
+}
+
+export function checkRequiredEnvVars() {
+ const missingEnvVars = REQUIRED_ENV_VARS.filter((envVar) => {
+ return !process.env[envVar];
+ });
+
+ if (missingEnvVars.length > 0) {
+ console.log(
+ `The following environment variables are required but missing: ${missingEnvVars.join(
+ ", ",
+ )}`,
+ );
+ throw new Error(
+ `Missing environment variables: ${missingEnvVars.join(", ")}`,
+ );
+ }
+}