> ## Documentation Index
> Fetch the complete documentation index at: https://praison.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Pinecone

> Pinecone vector store for PraisonAI

# Pinecone

Managed vector database for production RAG.

## Setup

```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
pip install pinecone-client
export PINECONE_API_KEY=your_api_key
```

## Quick Start (Agent with Knowledge)

Use Pinecone as a knowledge store with an agent:

```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
from praisonaiagents import Agent
import os

# Agent with knowledge backed by Pinecone
agent = Agent(
    name="Assistant",
    instructions="You are a helpful assistant with access to documents.",
    knowledge=["./docs/guide.pdf"]
)

agent.chat("What does the guide say?")
```

## Advanced Usage (Direct Store)

```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
from praisonai.persistence.factory import create_knowledge_store

store = create_knowledge_store(
    "pinecone",
    api_key="your_api_key",
    environment="us-east-1"
)

# Create index
store.create_collection("documents", dimension=384)

# Insert and search
store.insert("documents", [doc])
results = store.search("documents", query_embedding, limit=5)
```

## Configuration

| Option | Description |
| - | - |
| `api_key` | Pinecone API key |
| `environment` | Pinecone environment |
| `index_name` | Index name |


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