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Documentation Index

Fetch the complete documentation index at: https://docs.moorcheh.ai/llms.txt

Use this file to discover all available pages before exploring further.

Prerequisites

pip install moorcheh-edge
moorcheh-edge up

Full example

import random
from moorcheh_edge import MoorchehEdge, MoorchehEdgeApiError

def rand_vec(dim: int = 1024) -> list[float]:
    return [random.random() for _ in range(dim)]

with MoorchehEdge(port=8080, skip_pull=False) as client:
    health = client.health()
    print(f"Items: {health['items']} / {health['max_items']}")

    client.upload([
        {"id": "item-1", "vector": rand_vec()},
        {"id": "item-2", "vector": rand_vec()},
    ])

    results = client.search(query=rand_vec(), top_k=3)
    for r in results:
        print(r["id"], r["score"], r["label"])

    client.delete(["item-1"])

Attach to an existing server

from moorcheh_edge import MoorchehEdgeApiClient

client = MoorchehEdgeApiClient("http://localhost:8083")
print(client.health())

CLI equivalent

moorcheh-edge status
moorcheh-edge upload-vectors --vectors-file payload.json
moorcheh-edge search --query-vector-json "[...]" --top-k 5
moorcheh-edge delete --ids-json '["item-1"]'

Tips

  • Vectors must be exactly 1024 floats
  • Plain text search is not supported
  • Store cap is 10,000 items — handle MoorchehEdgeApiError with status 409

Next steps