add embeddings

qdrant-landing/content/documentation/embeddings/openclip.md

@@ -0,0 +1,46 @@
+
+---
+title: OpenCLIP
+weight: 2750
+aliases:
+  - /documentation/examples/openclip-search/
+  - /documentation/tutorials/openclip-search/
+  - /documentation/integrations/openclip/
+---
+
+# Using OpenCLIP with Qdrant
+
+OpenCLIP is an open-source implementation of the CLIP model, allowing for open source generation of multimodal embeddings that link text and images. 
+
+```python
+import qdrant_client
+from qdrant_client.models import Batch
+import open_clip
+
+# Load the OpenCLIP model and tokenizer
+model, preprocess = open_clip.create_model_and_transforms('ViT-B-32', pretrained='openai')
+tokenizer = open_clip.get_tokenizer('ViT-B-32')
+
+# Generate embeddings for a text
+text = "A photo of a cat"
+text_inputs = tokenizer([text])
+
+with torch.no_grad():
+    text_features = model.encode_text(text_inputs)
+
+# Convert tensor to a list
+embeddings = text_features[0].cpu().numpy().tolist()
+
+# Initialize Qdrant client
+qdrant_client = qdrant_client.QdrantClient(host="localhost", port=6333)
+
+# Upsert the embedding into Qdrant
+qdrant_client.upsert(
+    collection_name="OpenCLIPEmbeddings",
+    points=Batch(
+        ids=[1],
+        vectors=[embeddings],
+    )
+)
+```
+