Text Content

"""
Text Content
============

Demonstrates adding direct text content to knowledge using sync and async APIs.
"""

import asyncio

from agno.db.postgres.postgres import PostgresDb
from agno.knowledge.knowledge import Knowledge
from agno.vectordb.pgvector import PgVector

# ---------------------------------------------------------------------------
# Setup
# ---------------------------------------------------------------------------
contents_db = PostgresDb(
    db_url="postgresql+psycopg://ai:ai@localhost:5532/ai",
    knowledge_table="knowledge_contents",
)
vector_db = PgVector(
    table_name="vectors", db_url="postgresql+psycopg://ai:ai@localhost:5532/ai"
)


# ---------------------------------------------------------------------------
# Create Knowledge Base
# ---------------------------------------------------------------------------
def create_knowledge() -> Knowledge:
    return Knowledge(
        name="Basic SDK Knowledge Base",
        description="Agno 2.0 Knowledge Implementation",
        vector_db=vector_db,
        contents_db=contents_db,
    )


# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------
def run_sync() -> None:
    knowledge = create_knowledge()
    knowledge.insert(
        name="Text Content",
        text_content="Cats and dogs are pets.",
        metadata={"user_tag": "Animals"},
    )

    knowledge.insert_many(
        name="Text Content",
        text_contents=["Cats and dogs are pets.", "Birds and fish are not pets."],
        metadata={"user_tag": "Animals"},
    )

    knowledge.insert_many(
        [
            {
                "text_content": "Cats and dogs are pets.",
                "metadata": {"user_tag": "Animals"},
            },
            {
                "text_content": "Birds and fish are not pets.",
                "metadata": {"user_tag": "Animals"},
            },
        ],
    )


async def run_async() -> None:
    knowledge = create_knowledge()
    await knowledge.ainsert(
        name="Text Content",
        text_content="Cats and dogs are pets.",
        metadata={"user_tag": "Animals"},
    )

    await knowledge.ainsert_many(
        name="Text Content",
        text_contents=["Cats and dogs are pets.", "Birds and fish are not pets."],
        metadata={"user_tag": "Animals"},
    )

    await knowledge.ainsert_many(
        [
            {
                "text_content": "Cats and dogs are pets.",
                "metadata": {"user_tag": "Animals"},
            },
            {
                "text_content": "Birds and fish are not pets.",
                "metadata": {"user_tag": "Animals"},
            },
        ],
    )


if __name__ == "__main__":
    run_sync()
    asyncio.run(run_async())

# Clone and setup repo
git clone https://github.com/agno-agi/agno.git
cd agno/cookbook/07_knowledge/01_quickstart

# Create and activate virtual environment
./scripts/demo_setup.sh
source .venvs/demo/bin/activate

# Optiona: Run PgVector (needs docker)
./cookbook/scripts/run_pgvector.sh

python 14_text_content.py