> ## Documentation Index
> Fetch the complete documentation index at: https://phidatainc-studio-tools-doc.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Weaviate

## Code

```python cookbook/08_knowledge/vector_db/weaviate_db/weaviate_db.py theme={null}
from agno.agent import Agent
from agno.knowledge.knowledge import Knowledge
from agno.vectordb.search import SearchType
from agno.vectordb.weaviate import Weaviate
from agno.vectordb.weaviate.index import Distance, VectorIndex

vector_db = Weaviate(
    collection="vectors",
    search_type=SearchType.vector,
    vector_index=VectorIndex.HNSW,
    distance=Distance.COSINE,
    local=False,  # Set to True if using Weaviate locally
)

# Create Knowledge Instance with Weaviate
knowledge = Knowledge(
    name="Basic SDK Knowledge Base",
    description="Agno 2.0 Knowledge Implementation with Weaviate",
    vector_db=vector_db,
)

knowledge.insert(
    name="Recipes",
    url="https://agno-public.s3.amazonaws.com/recipes/ThaiRecipes.pdf",
    metadata={"doc_type": "recipe_book"},
    skip_if_exists=True,
)

# Create and use the agent
agent = Agent(knowledge=knowledge)
agent.print_response("List down the ingredients to make Massaman Gai", markdown=True)

# Delete operations
vector_db.delete_by_name("Recipes")
# or
vector_db.delete_by_metadata({"doc_type": "recipe_book"})
```

## Usage

<Steps>
  <Snippet file="create-venv-step.mdx" />

  <Step title="Install dependencies">
    ```bash theme={null}
    uv pip install -U weaviate-client pypdf openai agno
    ```
  </Step>

  <Step title="Setup Weaviate">
    <CodeGroup>
      ```bash Weaviate Cloud theme={null}
      # 1. Create account at https://console.weaviate.cloud/
      # 2. Create a cluster and copy the "REST endpoint" and "Admin" API Key
      # 3. Set environment variables:
      export WCD_URL="your-cluster-url"
      export WCD_API_KEY="your-api-key"
      # 4. Set local=False in the code
      ```

      ```bash Local Development theme={null}
      # 1. Install Docker from https://docs.docker.com/get-docker/
      # 2. Run Weaviate locally:
      docker run -d \
          -p 8080:8080 \
          -p 50051:50051 \
          --name weaviate \
          cr.weaviate.io/semitechnologies/weaviate:1.28.4
      # 3. Set local=True in the code
      ```
    </CodeGroup>
  </Step>

  <Step title="Set environment variables">
    ```bash theme={null}
    export OPENAI_API_KEY=xxx
    ```
  </Step>

  <Step title="Run Agent">
    ```bash theme={null}
    python cookbook/08_knowledge/vector_db/weaviate_db/weaviate_db.py
    ```
  </Step>
</Steps>