> ## 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.

# Moorcheh On-Prem

> Self-hosted semantic search and vector storage with moorcheh-client and Docker.

## What is Moorcheh On-Prem?

Moorcheh On-Prem runs on your machine: semantic search over text documents and precomputed vectors. **Text** embeddings use **Ollama** (local), **OpenAI**, or **Cohere** — configured once with `moorcheh configure` or on first `moorcheh up`. You install **`moorcheh-client`** from PyPI, start the stack with one command, and call the API from your app or the CLI.

|                   |                                       |
| ----------------- | ------------------------------------- |
| **PyPI package**  | `moorcheh-client`                     |
| **CLI**           | `moorcheh`                            |
| **Python import** | `from moorcheh import MoorchehClient` |
| **Server image**  | `moorcheh/server:latest` (Docker Hub) |
| **Default API**   | `http://localhost:8080`               |
| **Data on disk**  | `~/.moorcheh/data`                    |

<Note>
  On-prem has **no Moorcheh cloud API keys**. If you use **OpenAI** or **Cohere** for embeddings, your provider API key is stored locally in `~/.moorcheh/config.json`. **Ollama** needs no API key.
</Note>

## What you can do

* Create **text** namespaces (documents embedded via your configured provider) or **vector** namespaces (you supply vectors)
* Upload text **documents** by id, or **upload files** (PDF, DOCX, etc.) from `~/.moorcheh/uploads`
* Upload, get, and delete items by id; list and delete indexed **files** separately
* **Semantic search** across one or more namespaces (top hit can include batch `summary_text`)
* **AI Answer** — RAG or direct LLM via `POST /answer` (Ollama, OpenAI, or Cohere)
* Check global storage quota via `/health`

## Prerequisites

* **Python 3.10+**
* **Docker** (Desktop or Engine)
* **Embedding provider** for text workflows — [Ollama, OpenAI, or Cohere](/on-prem/guides/embedding-providers) (Ollama is optional if you use cloud embeddings or vector-only)

## Install and run

```bash theme={null}
pip install moorcheh-client
moorcheh configure   # optional; first moorcheh up can prompt instead
moorcheh up
moorcheh status
```

See [Quickstart](/on-prem/quickstart) for a full upload-and-search walkthrough.

<Note>
  **Config vs runtime:** `moorcheh configure` writes `~/.moorcheh/config.json` only. To apply new **embedding** or **LLM** settings to a server that is already running, use **`moorcheh down`** then **`moorcheh up`**. If you already have data under `~/.moorcheh/data`, changing the **embedding** model can break text search and RAG until you re-upload — see [Embedding providers](/on-prem/guides/embedding-providers#after-you-change-settings).
</Note>

## Limits

* **Unlimited namespaces** - no cloud-tier namespace count limit; create as many text or vector namespaces as you need
* **100,000 items** total across all namespaces (text + vectors)
* Item ids are unique **per namespace** (the same id string may exist in different namespaces)
* Get/delete by id: at most **100 ids** per request

## Documentation

| Section                                                    | Use when                                        |
| ---------------------------------------------------------- | ----------------------------------------------- |
| [Prerequisites](/on-prem/prerequisites)                    | Install Python, Docker; optional Ollama         |
| [Embedding providers](/on-prem/guides/embedding-providers) | Models, dimensions, `configure` / `up` behavior |
| [Quickstart](/on-prem/quickstart)                          | First run end-to-end                            |
| [API reference](/on-prem/api-references/health)            | Integrating via HTTP / `curl`                   |
| [Python client](/on-prem/python-client/introduction)       | Building apps with `MoorchehClient`             |
| [CLI](/on-prem/cli/introduction)                           | Local ops and testing with `moorcheh`           |

## Data persistence

Vectors and documents are stored under:

```
~/.moorcheh/data/
 moorcheh_data_store.json
 namespace_registry.json
 file_registry.json
~/.moorcheh/uploads/     # host files mounted as /uploads in the server (read-only)
```

`moorcheh down` stops containers but **does not delete** this folder. Back up `~/.moorcheh` to save everything. File upload indexes content from `uploads/`; deleting an index does not remove files on disk.