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