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+---
+title: Pinecone Canopy
+weight: 2500
+---
+
+# Pinecone Canopy
+
+[Canopy](https://github.com/pinecone-io/canopy) is an open-source framework and context engine to build chat assistants at scale.
+
+Qdrant is supported as a knowledge base within Canopy for context retrieval and augmented generation.
+
+## Usage
+
+Install the SDK with the Qdrant extra as described in the [Canopy README](https://github.com/pinecone-io/canopy?tab=readme-ov-file#extras).
+
+```bash
+pip install canopy-sdk[qdrant]
+```
+
+### Creating a knowledge base
+
+```python
+from canopy.knowledge_base import QdrantKnowledgeBase
+
+kb = QdrantKnowledgeBase(collection_name="<YOUR_COLLECTION_NAME>")
+```
+
+<aside role="status">The constructor accepts additional <a href="https://github.com/qdrant/qdrant-client/blob/eda201a1dbf1bbc67415f8437a5619f6f83e8ac6/qdrant_client/qdrant_client.py#L36-L61">options</a> to customize your connection to Qdrant.</aside>
+
+To create a new Qdrant collection and connect it to the knowledge base, use the `create_canopy_collection` method:
+
+```python
+kb.create_canopy_collection()
+```
+
+You can always verify the connection to the collection with the `verify_index_connection` method:
+
+```python
+kb.verify_index_connection()
+```
+
+Learn more about customizing the knowledge base and its inner components [in the Canopy library](https://github.com/pinecone-io/canopy/blob/main/docs/library.md#understanding-knowledgebase-workings).
+
+### Adding data to the knowledge base
+
+To insert data into the knowledge base, you can create a list of documents and use the `upsert` method:
+
+```python
+from canopy.models.data_models import Document
+
+documents = [
+    Document(
+        id="1",
+        text="U2 are an Irish rock band from Dublin, formed in 1976.",
+        source="https://en.wikipedia.org/wiki/U2",
+    ),
+    Document(
+        id="2",
+        text="Arctic Monkeys are an English rock band formed in Sheffield in 2002.",
+        source="https://en.wikipedia.org/wiki/Arctic_Monkeys",
+        metadata={"my-key": "my-value"},
+    ),
+]
+
+kb.upsert(documents)
+```
+
+### Querying the knowledge base
+
+You can query the knowledge base with the `query` method to find the most similar documents to a given text:
+
+```python
+from canopy.models.data_models import Query
+
+kb.query(
+    [
+        Query(text="Arctic Monkeys music genre"),
+        Query(
+            text="U2 music genre",
+            top_k=10,
+            metadata_filter={"key": "my-key", "match": {"value": "my-value"}},
+        ),
+    ]
+)
+```
+
+## Further Reading
+
+- [Introduction to Canopy](https://www.pinecone.io/blog/canopy-rag-framework/)
+- [Canopy library reference](https://github.com/pinecone-io/canopy/blob/main/docs/library.md)
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