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"""
Mistral Embedder
================

Demonstrates Mistral embeddings and knowledge insertion, including a batching variant.
"""

import asyncio

from agno.knowledge.embedder.mistral import MistralEmbedder
from agno.knowledge.knowledge import Knowledge
from agno.vectordb.pgvector import PgVector


# ---------------------------------------------------------------------------
# Create Knowledge Base
# ---------------------------------------------------------------------------
def create_knowledge() -> Knowledge:
    # Standard mode
    embedder = MistralEmbedder()

    # Batching mode (uncomment to use)
    # embedder = MistralEmbedder(enable_batch=True)

    return Knowledge(
        vector_db=PgVector(
            db_url="postgresql+psycopg://ai:ai@localhost:5532/ai",
            table_name="mistral_embeddings",
            embedder=embedder,
        ),
        max_results=2,
    )


# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------
async def main() -> None:
    embeddings = MistralEmbedder().get_embedding(
        "The quick brown fox jumps over the lazy dog."
    )
    print(f"Embeddings: {embeddings[:5]}")
    print(f"Dimensions: {len(embeddings)}")

    knowledge = create_knowledge()
    await knowledge.ainsert(path="cookbook/07_knowledge/testing_resources/cv_1.pdf")


if __name__ == "__main__":
    asyncio.run(main())

​
Run the Example

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

# 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 mistral_embedder.py