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

# Loading Content: All Source Types

> Knowledge supports loading content from many sources: local files, URLs, raw text, topics (Wikipedia/ArXiv), and batch operations.

```python loading_content.py theme={null}
"""
Loading Content: All Source Types
==================================
Knowledge supports loading content from many sources: local files, URLs,
raw text, topics (Wikipedia/ArXiv), and batch operations.

This example demonstrates each source type. In production, you'll typically
use one or two of these patterns.

Steps:
1. From a local file path
2. From a URL
3. From raw text
4. From topics (Wikipedia, ArXiv)
5. Batch loading from multiple sources

Note: All examples use async methods (ainsert, ainsert_many).
Sync equivalents (insert, insert_many) are also available.
"""

import asyncio

from agno.agent import Agent
from agno.knowledge.embedder.openai import OpenAIEmbedder
from agno.knowledge.knowledge import Knowledge
from agno.knowledge.reader.wikipedia_reader import WikipediaReader

# Also available: from agno.knowledge.reader.arxiv_reader import ArxivReader
from agno.models.openai import OpenAIResponses
from agno.vectordb.qdrant import Qdrant
from agno.vectordb.search import SearchType

# ---------------------------------------------------------------------------
# Setup
# ---------------------------------------------------------------------------

qdrant_url = "http://localhost:6333"

knowledge = Knowledge(
    vector_db=Qdrant(
        collection="loading_content",
        url=qdrant_url,
        search_type=SearchType.hybrid,
        embedder=OpenAIEmbedder(id="text-embedding-3-small"),
    ),
)

agent = Agent(
    model=OpenAIResponses(id="gpt-5.2"),
    knowledge=knowledge,
    search_knowledge=True,
    markdown=True,
)

# ---------------------------------------------------------------------------
# Run Demo
# ---------------------------------------------------------------------------

if __name__ == "__main__":

    async def main():
        # --- 1. From a local file path ---
        print("\n" + "=" * 60)
        print("SOURCE 1: Local file")
        print("=" * 60 + "\n")

        await knowledge.ainsert(
            name="CV",
            path="cookbook/07_knowledge/testing_resources/cv_1.pdf",
            metadata={"source": "local_file"},
        )

        agent.print_response("What skills does Jordan Mitchell have?", stream=True)

        # --- 2. From a URL ---
        print("\n" + "=" * 60)
        print("SOURCE 2: URL")
        print("=" * 60 + "\n")

        await knowledge.ainsert(
            name="Recipes",
            url="https://agno-public.s3.amazonaws.com/recipes/ThaiRecipes.pdf",
            metadata={"source": "url"},
        )
        agent.print_response("What Thai recipes do you know about?", stream=True)

        # --- 3. From raw text ---
        print("\n" + "=" * 60)
        print("SOURCE 3: Raw text")
        print("=" * 60 + "\n")

        await knowledge.ainsert(
            name="Company Info",
            text_content="Acme Corp was founded in 2020. They build AI tools for developers.",
            metadata={"source": "text"},
        )
        agent.print_response("What does Acme Corp do?", stream=True)

        # --- 4. From topics (Wikipedia + ArXiv) ---
        print("\n" + "=" * 60)
        print("SOURCE 4: Topics (Wikipedia)")
        print("=" * 60 + "\n")

        await knowledge.ainsert(
            topics=["Retrieval-Augmented Generation"],
            reader=WikipediaReader(),
        )
        agent.print_response("What is RAG?", stream=True)

        # --- 5. Batch loading from multiple sources ---
        print("\n" + "=" * 60)
        print("SOURCE 5: Batch loading (insert_many)")
        print("=" * 60 + "\n")

        await knowledge.ainsert_many(
            [
                {
                    "name": "Doc 1",
                    "text_content": "Python is a programming language.",
                    "metadata": {"topic": "programming"},
                },
                {
                    "name": "Doc 2",
                    "text_content": "TypeScript adds types to JavaScript.",
                    "metadata": {"topic": "programming"},
                },
            ]
        )
        agent.print_response("Compare Python and TypeScript", stream=True)

    asyncio.run(main())
```

## Run the Example

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

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

  <Step title="Export your OpenAI API key">
    <CodeGroup>
      ```bash Mac/Linux theme={null}
      export OPENAI_API_KEY="your_openai_api_key_here"
      ```

      ```bash Windows theme={null}
      $Env:OPENAI_API_KEY="your_openai_api_key_here"
      ```
    </CodeGroup>
  </Step>

  <Step title="Run Qdrant">
    ```bash theme={null}
    docker run -d --name qdrant -p 6333:6333 qdrant/qdrant:latest
    ```
  </Step>

  <Step title="Run the example">
    Save the code above as `loading_content.py`, then run:

    ```bash theme={null}
    python loading_content.py
    ```
  </Step>
</Steps>

Full source: [cookbook/07\_knowledge/01\_getting\_started/03\_loading\_content.py](https://github.com/agno-agi/agno/blob/main/cookbook/07_knowledge/01_getting_started/03_loading_content.py)