docs: Qdrant-Genkit (#958)

* docs: Qdrant-Genkit

* docs: Fixed usage genkit.md

* import textEmbeddingGecko

qdrant-landing/content/documentation/frameworks/genkit.md

@@ -0,0 +1,108 @@
+---
+title: Firebase Genkit
+weight: 3400
+---
+
+# Firebase Genkit
+
+[Genkit](https://firebase.google.com/products/genkit) is a framework to build, deploy, and monitor production-ready AI-powered apps.
+
+You can build apps that generate custom content, use semantic search, handle unstructured inputs, answer questions with your business data, autonomously make decisions, orchestrate tool calls, and more.
+
+You can use Qdrant for indexing/semantic retrieval of data in your Genkit applications via the [Qdrant-Genkit plugin](https://github.com/qdrant/qdrant-genkit).
+
+Genkit currently supports server-side development in JavaScript/TypeScript (Node.js) with Go support in active development.
+
+## Installation
+
+```bash
+npm i genkitx-qdrant
+```
+
+## Configuration
+
+To use this plugin, specify it when you call `configureGenkit()`:
+
+```js
+import { qdrant } from 'genkitx-qdrant';
+import { textEmbeddingGecko } from '@genkit-ai/vertexai';
+
+export default configureGenkit({
+  plugins: [
+    qdrant([
+      {
+        clientParams: {
+          host: 'localhost',
+          port: 6333,
+        },
+        collectionName: 'some-collection',
+        embedder: textEmbeddingGecko,
+      },
+    ]),
+  ],
+  // ...
+});
+```
+
+You'll need to specify a collection name, the embedding model you want to use and the Qdrant client parameters. In
+addition, there are a few optional parameters:
+
+- `embedderOptions`: Additional options to pass options to the embedder:
+
+  ```js
+  embedderOptions: { taskType: 'RETRIEVAL_DOCUMENT' },
+  ```
+
+- `contentPayloadKey`: Name of the payload filed with the document content. Defaults to "content".
+
+  ```js
+  contentPayloadKey: 'content';
+  ```
+
+- `metadataPayloadKey`: Name of the payload filed with the document metadata. Defaults to "metadata".
+
+  ```js
+  metadataPayloadKey: 'metadata';
+  ```
+
+- `collectionCreateOptions`: [Additional options](<(https://qdrant.tech/documentation/concepts/collections/#create-a-collection)>) when creating the Qdrant collection.
+
+## Usage
+
+Import retriever and indexer references like so:
+
+```js
+import { qdrantIndexerRef, qdrantRetrieverRef } from 'genkitx-qdrant';
+import { Document, index, retrieve } from '@genkit-ai/ai/retriever';
+```
+
+Then, pass the references to `retrieve()` and `index()`:
+
+```js
+// To specify an indexer:
+export const qdrantIndexer = qdrantIndexerRef({
+  collectionName: 'some-collection',
+  displayName: 'Some Collection indexer',
+});
+
+await index({ indexer: qdrantIndexer, documents });
+```
+
+```js
+// To specify a retriever:
+export const qdrantRetriever = qdrantRetrieverRef({
+  collectionName: 'some-collection',
+  displayName: 'Some Collection Retriever',
+});
+
+let docs = await retrieve({ retriever: qdrantRetriever, query });
+```
+
+You can refer to [Retrieval-augmented generation](https://firebase.google.com/docs/genkit/rag) for a general
+discussion on indexers and retrievers.
+
+## Further Reading
+
+- [Introduction to Genkit](https://firebase.google.com/docs/genkit)
+- [Genkit Documentation](https://firebase.google.com/docs/genkit/get-started)
+- [Source Code](https://github.com/qdrant/qdrant-genkit)