dodil 0.0.3

DODIL Python SDK

DODIL Python SDK

The DODIL Python SDK lets you interact with DODIL services from Python.

Today the SDK includes:

• VNG: ingestion / processing service (primarily gRPC, async-first)
• VBase: vector database service (Milvus-backed).

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Installation

Using Poetry:

poetry add dodil

Using pip:

pip install dodil

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Quick start

1) Create a client (service account)

Set your credentials as environment variables (recommended):

export DODIL_SERVICE_ACCOUNT_ID="..."
export DODIL_SERVICE_ACCOUNT_SECRET="..."

Then in Python:

from dodil import Client

client = Client(
    service_account_id="...",
    service_account_secret="...",
)

• Service Account ID and Secret are found in console IAM page.

2) Use VNG

VNG is designed to be async-first.

import asyncio
from dodil import Client

async def main():
    c = Client(
        profile="staging",
        service_account_id="...",
        service_account_secret="...",
    )

    # Create a bound VNG client (gRPC)
    vng = c.vng.connect()
    await vng.close()
    c.close()

What VNG does (typical use cases):

• Submit ingestion / processing jobs
• Track job status via polling
• Fetch outputs and manifests

3) Use VBase

VBase uses a Milvus-compatible endpoint. Your platform might show host + port (address and port) or a full URI; the SDK supports both.

A) Connect using host + port

from dodil import Client, VBaseConfig

c = Client(
    service_account_id="...",
    service_account_secret="...",
)

vbase = c.vbase.connect(
    VBaseConfig(
        host="vbase-db-<id>.dodil.cloud",
        port=443,
        scheme="https",
        db_name="db_12934",
    )
)

print(vbase.list_collections())

vbase.close()
c.close()

What VBase does (typical use cases):

• Create collections (schemas)
• Insert / upsert embeddings
• Search vectors and query metadata
• Manage indexes

4) Schema definitions (FieldSchema, CollectionSchema, DataType)

If you want to build Milvus-style schemas, you can import definitions from dodil.vbase.

from dodil.vbase import FieldSchema, CollectionSchema, DataType

# Example schema objects (usage depends on your backend / PyMilvus version)
fields = [
    FieldSchema(name="id", dtype=DataType.INT64, is_primary=True, auto_id=False),
    FieldSchema(name="vec", dtype=DataType.FLOAT_VECTOR, dim=768),
]

schema = CollectionSchema(fields=fields, description="example")

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Configuration

Profiles

• profile="staging" (default): uses staging identity + API endpoints.
• profile="prod": uses production endpoints.

Timeouts

You can pass timeout_s to the root Client and service configs (where supported).

from dodil import Client

c = Client(
    profile="staging",
    service_account_id="...",
    service_account_secret="...",
    timeout_s=60.0,
)

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Testing

Install dev dependencies then run tests:

poetry install
pytest

Integration tests

Integration tests hit real external services and are marked with integration.

pytest -m integration -s

You may need to set environment variables for endpoints and credentials depending on your setup.

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Contributing

• Keep public APIs stable (prefer additive changes).
• Prefer service handles (client.vng, client.vbase) that create bound clients via .connect(...).

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