Ollama Embedder

Code

from agno.knowledge.embedder.ollama import OllamaEmbedder
from agno.knowledge.knowledge import Knowledge
from agno.vectordb.pgvector import PgVector

embeddings = OllamaEmbedder().get_embedding(
    "The quick brown fox jumps over the lazy dog."
)

# Print the embeddings and their dimensions
print(f"Embeddings: {embeddings[:5]}")
print(f"Dimensions: {len(embeddings)}")

# Example usage:
knowledge = Knowledge(
    vector_db=PgVector(
        db_url="postgresql+psycopg://ai:ai@localhost:5532/ai",
        table_name="ollama_embeddings",
        embedder=OllamaEmbedder(),
    ),
    max_results=2,
)

Usage

1. Set up your virtual environment

   Mac

   uv venv --python 3.12
   source .venv/bin/activate
   

   uv venv --python 3.12
   .venv\Scripts\activate
   
2. Install Ollama

   Follow the installation instructions at Ollama’s website

3. Install dependencies

   uv pip install -U sqlalchemy psycopg pgvector agno
   
4. Run PgVector

   docker run -d \
     -e POSTGRES_DB=ai \
     -e POSTGRES_USER=ai \
     -e POSTGRES_PASSWORD=ai \
     -e PGDATA=/var/lib/postgresql/data/pgdata \
     -v pgvolume:/var/lib/postgresql/data \
     -p 5532:5432 \
     --name pgvector \
     agnohq/pgvector:16
   
5. Run Agent

   Mac

   python cookbook/08_knowledge/embedders/ollama_embedder.py
   

   python cookbook/08_knowledge/embedders/ollama_embedder.py