1  """Pinecone Vector Store - Agent-First Example
 2  
 3  Requires: export PINECONE_API_KEY=...
 4  """
 5  import os
 6  import sys
 7  from praisonaiagents import Agent
 8  
 9  api_key = os.getenv("PINECONE_API_KEY")
10  if not api_key:
11      print("SKIPPED: Pinecone - PINECONE_API_KEY not set")
12      sys.exit(0)
13  
14  # Agent-first approach: use knowledge parameter with Pinecone
15  agent = Agent(
16      name="Assistant",
17      instructions="You are a helpful assistant with access to documents.",
18      knowledge={
19          "sources": ["./docs/guide.pdf"],
20          "vector_store": "pinecone",
21          "api_key": api_key,
22          "environment": "us-east-1"
23      }
24  )
25  
26  # Chat - agent uses knowledge for RAG
27  response = agent.chat("What information do you have?")
28  print(f"Response: {response}")
29  
30  print("PASSED: Pinecone with Agent")
31  
32  # --- Advanced: Direct Store Usage ---
33  # from pinecone import Pinecone
34  # pc = Pinecone(api_key=api_key)