feat: publish the backend to PyPI as docsgpt

pip install docsgpt (extras: docling, milvus) installs the backend with a
docsgpt command: api, worker, migrate, prefetch-models, verify-offline,
reembed. Second step of the PyPI work after the package rename.

- hatchling build; the version comes from docsgpt/version.py. The wheel is
  the docsgpt package with the data it reads at runtime (prompts, model
  catalogs, seed config, alembic.ini and migrations) and without the
  Dockerfile, the exported requirements, the sample index and local runtime
  data. The application import alias stays checkout-only. uv sync installs
  the package editable now that [tool.uv] package = false is gone.
- docsgpt/cli.py: api (gunicorn + BoundedDrainUvicornWorker with the image's
  flags, --reload for uvicorn), worker (Celery worker with beat embedded,
  --no-beat/-Q/--concurrency/--pool, solo pool on macOS), migrate, and
  argument pass-through to the maintenance scripts. --help imports no app.
- docsgpt/core/paths.py: runtime data lives in a data home (DOCSGPT_HOME,
  else the checkout, else cwd); DOCSGPT_ENV_FILE overrides the env file.
  Settings, the dotenv load, LocalStorage and the internal upload route use
  it instead of "three directories above this file", which is site-packages
  for an installed package. A checkout and the Docker image behave as before.
- [project] dependencies are compatible ranges so the package installs next
  to other packages; uv.lock resolves to the same versions and the exported
  requirements files are unchanged.
- package-build.yml builds and checks the wheel on PRs and installs it into
  a clean venv; pypi-publish.yml publishes on a published release through
  trusted publishing (environment pypi), or to TestPyPI on a manual run.
- Docs: Deploying -> Install with pip. AGENTS.md notes the package.

docs/content/Deploying/Pip-Install.mdx

@@ -0,0 +1,86 @@
+---
+title: Install with pip
+description: Run the DocsGPT backend from the PyPI package, inside your own Python environment.
+---
+
+import { Callout } from 'nextra/components'
+
+# Install with pip
+
+The DocsGPT backend is on PyPI as [`docsgpt`](https://pypi.org/project/docsgpt/): the API server, the Celery worker and the maintenance scripts in one package, behind a single `docsgpt` command. Use it when you want DocsGPT inside your own Python environment or process manager rather than the [Docker images](/Deploying/Docker-Deploying).
+
+<Callout type="info">
+  The package is the backend only. The web UI ships in the Docker images and in the repository under `frontend/`; serving it from the package is planned.
+</Callout>
+
+## Requirements
+
+- Python 3.12 or newer
+- [PostgreSQL](/Deploying/Postgres-Migration) for user data, with the `vector` extension if you set `VECTOR_STORE=pgvector`
+- Redis for the task queue and the cache
+- An LLM: an API key for a hosted provider, or a local model server
+
+## Install
+
+```bash
+python -m venv .venv && source .venv/bin/activate
+pip install docsgpt
+```
+
+Extras add the optional engines:
+
+```bash
+pip install "docsgpt[docling]"   # DOC_PARSER_ENGINE=docling: OCR backend, structured output
+pip install "docsgpt[milvus]"    # VECTOR_STORE=milvus
+```
+
+The `docling` extra pulls in PyTorch. On Linux, PyPI's torch wheels bring the CUDA stack with them; on a CPU-only machine add `--extra-index-url https://download.pytorch.org/whl/cpu` to the install command to get the CPU build instead. `uv pip install` and `pipx install` work the same way.
+
+## Configure
+
+DocsGPT keeps its runtime files in a **data home**: the `.env` file it reads settings from, uploaded files under `inputs/` and vector indexes under `indexes/`. The data home is the directory you run the commands from, or the directory `DOCSGPT_HOME` points to. `DOCSGPT_ENV_FILE` points at a `.env` kept somewhere else.
+
+Create a `.env` in the data home. The minimum for a hosted LLM:
+
+```ini
+# LLM provider and model: see App Configuration for the options
+LLM_PROVIDER=openai
+LLM_NAME=<model name>
+API_KEY=<provider API key>
+
+# User data
+POSTGRES_URI=postgresql://docsgpt:docsgpt@localhost:5432/docsgpt
+
+# Worker-to-API authentication (required for uploads)
+INTERNAL_KEY=<a long random string>
+```
+
+Redis defaults to `localhost:6379` (`CELERY_BROKER_URL`, `CELERY_RESULT_BACKEND`, `CACHE_REDIS_URL`). Every setting is listed in [App Configuration](/Deploying/DocsGPT-Settings).
+
+## Run
+
+```bash
+docsgpt migrate    # create the database if it is missing and apply the migrations
+docsgpt api        # the API on http://localhost:7091
+docsgpt worker     # in a second terminal: the Celery worker, with the scheduler
+```
+
+The API applies pending migrations when it starts (`AUTO_MIGRATE`), so `docsgpt migrate` is the explicit step for deployments that want the schema in place before the first request or that run the API with a restricted database role.
+
+The worker is not optional: query embedding runs on it, so search fails without one. `docsgpt worker --help` lists the queue, concurrency and pool options; `--no-beat` starts a worker without the scheduler when another worker already runs it.
+
+Other commands:
+
+- `docsgpt api --reload`: a development server with auto-reload.
+- `docsgpt prefetch-models`: download the embedding, tokenizer and parser models ahead of time, for machines that go offline.
+- `docsgpt verify-offline`: check that a prepared install starts with networking off.
+- `docsgpt reembed`: re-embed every index after changing `EMBEDDINGS_NAME` (see [Upgrading](/upgrading)).
+
+## Upgrade
+
+```bash
+pip install -U docsgpt
+docsgpt migrate
+```
+
+Read the [upgrade notes](/upgrading) first when moving between minor versions.

docs/content/Deploying/_meta.js

@@ -15,6 +15,10 @@ export default {
     "title": "🛳️ Docker Setup",
     "href": "/Deploying/Docker-Deploying"
   },
+  "Pip-Install": {
+    "title": "🐍 Install with pip",
+    "href": "/Deploying/Pip-Install"
+  },
   "Development-Environment": {
     "title": "🛠️Development Environment",
     "href": "/Deploying/Development-Environment"