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pip install docsgpt now brings the web UI with it: `docsgpt api` serves the API and the UI on one port. - scripts/build_frontend.sh builds the frontend into docsgpt/static (gitignored) the way the frontend image does: .env.development as the production baseline, and index.html loading /config.js ahead of the bundle. hatch admits the directory into the wheel and the sdist through `artifacts`; the package workflows run the script before `uv build` and fail if the wheel lacks the UI. The backend image keeps ignoring it. - docsgpt/ui.py serves the build in front of Flask: files as they are, hashed assets immutable, Flask's own path prefixes (taken from its URL map, so new blueprints need no registration) passed through, every other GET rendered as index.html for the client-side router. /config.js is generated per request with VITE_API_HOST and VITE_BASE_URL set to the page's origin, VITE_* environment variables winning. SERVE_UI=false leaves the API alone. - docsgpt api configures gunicorn in code (gunicorn.app.base.Application) instead of rewriting sys.argv, so the SIGUSR2 re-exec that gunicorn uses for zero-downtime upgrades runs the docsgpt console script again and works; verified with a live handover. - Docs: the pip page says the UI is included, that DOCSGPT_HOME and DOCSGPT_ENV_FILE are process environment variables rather than .env entries, and the settings page describes SERVE_UI.
102 lines
4.7 KiB
Plaintext
102 lines
4.7 KiB
Plaintext
---
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title: Install with pip
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description: Run the DocsGPT backend from the PyPI package, inside your own Python environment.
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---
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import { Callout } from 'nextra/components'
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# Install with pip
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DocsGPT is on PyPI as [`docsgpt`](https://pypi.org/project/docsgpt/): the API server, the web UI, 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).
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<Callout type="info">
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`docsgpt api` serves the web UI on the same port as the API. Set `SERVE_UI=false` to run the API alone, for example behind the frontend Docker image or a UI you host yourself.
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</Callout>
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## Requirements
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- Python 3.12 or newer
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- [PostgreSQL](/Deploying/Postgres-Migration) for user data, with the `vector` extension if you set `VECTOR_STORE=pgvector`
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- Redis for the task queue and the cache
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- An LLM: an API key for a hosted provider, or a local model server
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## Install
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```bash
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python -m venv .venv && source .venv/bin/activate
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pip install docsgpt
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```
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Extras add the optional engines:
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```bash
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pip install "docsgpt[docling]" # DOC_PARSER_ENGINE=docling: OCR backend, structured output
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pip install "docsgpt[milvus]" # VECTOR_STORE=milvus
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```
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The `docling` extra pulls in PyTorch, and on Linux the PyPI torch wheels bring the CUDA stack with them. On a CPU-only machine install the CPU build first, then the extra; pip keeps the torch it already has:
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```bash
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pip install --index-url https://download.pytorch.org/whl/cpu torch torchvision
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pip install "docsgpt[docling]"
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```
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`uv pip install` accepts the same two commands. With `pipx`, install `docsgpt[docling]` first, then replace the CUDA build inside its environment (`--no-deps` keeps pip from touching torch's dependencies, which the PyTorch index carries in older copies):
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```bash
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pipx runpip docsgpt install --force-reinstall --no-deps --index-url https://download.pytorch.org/whl/cpu torch torchvision
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```
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## Configure
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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. Both variables must be set in the process environment, not in `.env`: they decide where `.env` is read from.
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Create a `.env` in the data home. The minimum for a hosted LLM:
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```ini
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# LLM provider and model: see App Configuration for the options
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LLM_PROVIDER=openai
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LLM_NAME=<model name>
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API_KEY=<provider API key>
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# User data
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POSTGRES_URI=postgresql://docsgpt:<password>@localhost:5432/docsgpt
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# Worker-to-API authentication (required for uploads)
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INTERNAL_KEY=<a long random string>
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```
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Redis defaults to `localhost:6379` (`CELERY_BROKER_URL`, `CELERY_RESULT_BACKEND`, `CACHE_REDIS_URL`). Every setting is listed in [App Configuration](/Deploying/DocsGPT-Settings).
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## Run
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```bash
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docsgpt migrate # create the database if it is missing and apply the migrations
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docsgpt api # the API and the web UI on http://127.0.0.1:7091
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docsgpt worker # in a second terminal: the Celery worker, with the scheduler
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```
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`docsgpt api` listens on localhost only. Pass `--host 0.0.0.0` to accept connections from other machines or containers, and put a reverse proxy with TLS in front of it for anything public.
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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.
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Both commands print the data home they resolved on start-up. Run them from the same directory, or set `DOCSGPT_HOME` for both, so the worker finds the files the API stores and the API finds the indexes the worker builds.
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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. On Windows the scheduler cannot be embedded, so run `docsgpt beat` in a third terminal.
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Other commands:
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- `docsgpt api --reload`: a development server with auto-reload.
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- `docsgpt prefetch-models`: download the embedding, tokenizer and parser models ahead of time, for machines that go offline.
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- `docsgpt verify-offline`: check that a prepared install starts with networking off.
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- `docsgpt reembed`: re-embed every index after changing `EMBEDDINGS_NAME` (see [Upgrading](/upgrading)).
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## Upgrade
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```bash
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pip install -U docsgpt
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docsgpt migrate
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```
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Read the [upgrade notes](/upgrading) first when moving between minor versions.
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