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Small typo, grammar and style fixes

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Bastian Hofmann
2025-07-15 11:55:48 +02:00
parent 778f365d36
commit efa37e545b
4 changed files with 31 additions and 35 deletions
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qdrant-landing/content/documentation/headless/snippets/cloud-inference/image/_description.md
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This code snippet shows how to use Qdrant Cloud's cloud-side inference to automatically generate vector embeddings from images and text during upsert and search operations.
This code snippet shows how to use Qdrant Cloud Inference to automatically generate vector embeddings from images and text during upsert and search operations.
In the example, a new point is inserted with an image URL and a specified model. The vector embedding is generated on the Qdrant Cloud side using the provided model. The `image` and `model` fields specify the image to embed and the model to use.
In this example, a new point is inserted with an image URL and a specified model. The vector embedding is generated on the Qdrant Cloud side using the provided model. The `image` and `model` fields specify the image to embed and the model to use.
After the point is inserted, it becomes searchable. The snippet also demonstrates how to perform a search query using cloud-side inference: a `text` and `model` are provided, and Qdrant Cloud generates the query vector automatically. This allows you to search your collection using natural language queries without manually generating embeddings.
After the point is inserted, it becomes searchable. The snippet also demonstrates how to perform a search query using Qdrant Cloud Inference. A `text` and `model` are provided, and Qdrant Cloud generates the query vector automatically. This allows you to search your collection using natural language queries without manually generating embeddings.
Example demonstrates multimodal search with `CLIP` model and cloud-side inference.
This example demonstrates multimodal search using the `CLIP` model and Qdrant Cloud Inference.
qdrant-landing/content/documentation/headless/snippets/cloud-inference/image/bash.md
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{
"id": 1,
"vector": {
"text": "https://qdrant.tech/example.png",
"image": "https://qdrant.tech/example.png",
"model": "qdrant/clip-vit-b-32-vision"
},
"payload": {