pinecone_serverless_index_upsert_and_similarity_search.py

1from pinecone import Pinecone, ServerlessSpec
2
3# Initialize Pinecone client
4pc = Pinecone(api_key="YOUR_API_KEY")
5
6# Create a serverless index
7index_name = "quickstart"
8
9if index_name not in pc.list_indexes().names():
10    pc.create_index(
11        name=index_name,
12        dimension=2,
13        metric="cosine",
14        spec=ServerlessSpec(
15            cloud="aws",
16            region="us-east-1"
17        )
18    )
19
20# Target the index
21index = pc.Index(index_name)
22
23# Upsert sample data (vector IDs and values)
24index.upsert(
25    vectors=[
26        {"id": "vec1", "values": [0.1, 0.1]},
27        {"id": "vec2", "values": [0.2, 0.2]},
28        {"id": "vec3", "values": [0.3, 0.3]},
29        {"id": "vec4", "values": [0.4, 0.4]}
30    ],
31    namespace="ns1"
32)
33
34# Search the index
35query_results = index.query(
36    namespace="ns1",
37    vector=[0.3, 0.3],
38    top_k=2,
39    include_values=True
40)
41
42print(query_results)