add embeddings

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

@@ -0,0 +1,50 @@
+
+---
+title: Watsonx
+weight: 3000
+aliases:
+  - /documentation/examples/watsonx-search/
+  - /documentation/tutorials/watsonx-search/
+  - /documentation/integrations/watsonx/ 
+---
+
+# Using Watsonx with Qdrant 
+
+Watsonx is IBM's platform for AI embeddings, focusing on enterprise-level text and data analytics. These embeddings are suitable for high-precision vector searches in Qdrant.
+
+## Installation
+
+You can install the required package using the following pip command:
+
+```bash
+pip install watsonx
+```
+
+## Code Example
+
+
+```python
+import qdrant_client
+from qdrant_client.models import Batch
+from watsonx import Watsonx
+
+# Initialize Watsonx AI model
+model = Watsonx("watsonx-model")
+
+# Generate embeddings for enterprise data
+text = "Watsonx provides enterprise-level NLP solutions."
+embeddings = model.embed(text)
+
+# Initialize Qdrant client
+qdrant_client = qdrant_client.QdrantClient(host="localhost", port=6333)
+
+# Upsert the embedding into Qdrant
+qdrant_client.upsert(
+    collection_name="EnterpriseData",
+    points=Batch(
+        ids=[1],
+        vectors=[embeddings],
+    )
+)
+
+```