vectorstore/embedder.py

"""
Embed text using Ollama's embedding API.
"""
import requests
from typing import List
from config import OLLAMA_BASE_URL, EMBEDDING_MODEL


def embed_texts(texts: List[str]) -> List[List[float]]:
    """
    Embed a list of texts using Ollama.
    
    Args:
        texts: List of text strings to embed
        
    Returns:
        List of embedding vectors
    """
    embeddings = []
    
    for text in texts:
        try:
            resp = requests.post(
                f"{OLLAMA_BASE_URL}/api/embeddings",
                json={"model": EMBEDDING_MODEL, "prompt": text}
            )
            resp.raise_for_status()
            embeddings.append(resp.json()["embedding"])
        except Exception as e:
            print(f"Warning: Failed to embed text: {e}")
            # Return a zero vector of appropriate size as fallback
            # nomic-embed-text produces 768-dimensional vectors
            embeddings.append([0.0] * 768)
    
    return embeddings


def main():
    """Test function to verify embedding works correctly."""
    print("Embedder module ready for use.")


if __name__ == "__main__":
    main()