> ## Documentation Index
> Fetch the complete documentation index at: https://docs.memvid.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Install the Python SDK

> Use the released memvid-sdk package (with optional adapters)

<Info>
  **Quick Start** - Install with `pip install memvid-sdk`, import `use()` to open or create `.mv2` files, and call `put()`, `find()`, `ask()` to store and retrieve memories. Optional adapters available for LangChain, LlamaIndex, and OpenAI integrations.
</Info>

The published package is `memvid-sdk`. It bundles the PyO3 bindings, adapter registry, and CLI-parity helpers (`verify`, `doctor`, ticket tooling). You only need `pip` to get started.

## Install

```bash theme={null}
pip install memvid-sdk
# optional adapters
pip install "memvid-sdk[langchain]" "memvid-sdk[openai]"
```

The extras match the adapter names defined in the Binding PRD (`langchain`, `llamaindex`, `openai`, etc.).

## Quickstart

```python theme={null}
from memvid_sdk import LockedError, Memvid, use

mv = use("basic", "notes.mv2")
mv.put(text="hello world", kind="text/plain")
print(mv.stats())

report = Memvid.verify("notes.mv2", deep=True)
print(report["overall_status"])
mv.seal()
```

`use(kind, path, ...)` mirrors the CLI locking semantics: pass `read_only=True` when sharing files between processes or catch `LockedError` when an exclusive writer already exists. For a more complete script (including retrieval + LLM synthesis), explore the `existing_usage.py` example included with the SDK distribution.

Editable installs keep parity with CI but are no longer required for day-to-day usage now that `memvid-sdk` is on PyPI.