crop_db/query_crops.py

import chromadb
from chromadb.utils.embedding_functions import SentenceTransformerEmbeddingFunction

client = chromadb.PersistentClient(path="crop_db")
embedder = SentenceTransformerEmbeddingFunction(model_name="all-MiniLM-L6-v2")
collection = client.get_collection(name="crop_data", embedding_function=embedder)

results = collection.query(
    query_texts=["crops suitable for clay soil"],
    n_results=3,
    include=["documents", "metadatas"]
)

print("Top crop recommendations:")
for doc, meta in zip(results['documents'][0], results['metadatas'][0]):
    print(f"- {doc}")
    print(f"  Region: {meta['region']} | Season: {meta['season']}\n")