[project]
name = "docsgpt"
# Bump together with docsgpt/version.py and frontend/package.json.
version = "0.19.0"
description = "DocsGPT backend: chat with your documents, agents, and tools."
readme = "README.md"
requires-python = ">=3.12"
license = { file = "LICENSE" }

# Direct dependencies only. Transitive pins live in uv.lock; the pip-facing
# files under docsgpt/ (requirements*.txt) are exported from that lock by
# scripts/export_requirements.sh and must not be edited by hand.
dependencies = [
  "a2wsgi==1.10.10",
  "alembic>=1.13,<2",
  "anthropic==0.121.0",
  "beautifulsoup4==4.15.0",
  "boto3==1.43.67",
  "cel-python==0.5.0",
  "celery==5.6.3",
  "celery-redbeat==2.4.2",
  "croniter==6.2.4",
  "cryptography==50.0.0",
  "dataclasses-json==0.6.7",
  "daytona==0.205.1",
  "ddgs>=8.0.0",
  "defusedxml==0.7.1",
  "docx2txt==0.9",
  "elevenlabs==2.62.0",
  "faiss-cpu==1.15.0",
  "fast-ebook",
  # Default document converter (DOC_PARSER_ENGINE=anydoc): a Rust extension
  # with no model downloads. The docling engine is the `docling` extra.
  "firecrawl-anydoc==0.2.3",
  "fastembed==0.8.0",
  "fastmcp==3.4.6",
  "Flask==3.1.3",
  "flask-restx==1.3.2",
  "google-api-python-client==2.198.0",
  "google-auth-oauthlib==1.4.0",
  "google-genai==2.17.0",
  "gTTS==2.5.4",
  "gunicorn==26.0.0",
  "jinja2==3.1.6",
  "kombu==5.6.2",
  "markdownify==1.2.3",
  "msal==1.37.0",
  "networkx==3.6.1",
  "numpy==2.5.1",
  # fastembed's runtime: local embeddings execute on it.
  "onnxruntime==1.28.0",
  "openai==2.53.0",
  "openapi3-parser==1.1.22",
  # pandas reads .xlsx through openpyxl but does not depend on it.
  "openpyxl==3.1.5",
  "opentelemetry-distro>=0.50b0,<1",
  "opentelemetry-exporter-otlp>=1.29.0,<2",
  "opentelemetry-instrumentation-celery>=0.50b0,<1",
  "opentelemetry-instrumentation-flask>=0.50b0,<1",
  "opentelemetry-instrumentation-logging>=0.50b0,<1",
  "opentelemetry-instrumentation-psycopg>=0.50b0,<1",
  "opentelemetry-instrumentation-redis>=0.50b0,<1",
  "opentelemetry-instrumentation-requests>=0.50b0,<1",
  "opentelemetry-instrumentation-sqlalchemy>=0.50b0,<1",
  "opentelemetry-instrumentation-starlette>=0.50b0,<1",
  "pandas==3.0.5",
  "pdf2image>=1.17.0",
  "pgvector>=0.5,<1",
  "pillow==12.3.0",
  "praw==8.0.2",
  "psycopg[binary,pool]>=3.1,<4",
  "pydantic",
  "pydantic-settings",
  "pypdf==6.15.0",
  "pypdfium2==5.12.1",
  "python-dateutil==2.9.0.post0",
  "python-dotenv",
  "python-jose==3.5.0",
  "python-pptx==1.0.2",
  "PyYAML",
  "qdrant-client==1.19.0",
  "redis==7.4.0",
  "requests==2.34.2",
  "retry==0.9.2",
  "sqlalchemy>=2.0,<3",
  "starlette>=1.0,<2",
  "tiktoken==0.13.0",
  "tldextract==5.3.2",
  "tokenizers==0.22.2",
  "tqdm==4.67.3",
  "uvicorn[standard]>=0.30,<1",
  "uvicorn-worker>=0.4,<1",
  "websocket-client==1.9.0",
  "werkzeug>=3.1.0",
]

[project.optional-dependencies]
# Docling parser engine: DOC_PARSER_ENGINE=docling, the docling OCR backend
# (layout-model hybrid OCR, ocrmac/rapidocr engines), .adoc/.vtt/.xml
# attachment parsing, and read_document's `structured` output. Pulls torch and
# transformers; on Linux torch resolves from the CPU-only PyTorch index (see
# [tool.uv.sources]) so the extra does not drag the CUDA stack in.
docling = [
  "docling==2.119.0",
  "rapidocr==3.9.2",
  # docling's model stack. Declared here (not left transitive) so the pins
  # hold and the CPU index source below applies. transformers is capped by
  # docling-core at <5.9: 5.9+ breaks the PDF layout model on Apple Silicon.
  "torch==2.11.0",
  "torchvision==0.26.0",
  "transformers==5.8.1",
]
# VECTOR_STORE=milvus. milvus-lite (the embedded server) pulls pyarrow.
milvus = [
  "pymilvus==3.0.1",
  "milvus-lite==3.2.0; sys_platform != 'win32'",
]

[dependency-groups]
# Mirrors tests/requirements.txt for `uv sync`; pip users install that file.
dev = [
  "pytest>=8.0.0",
  "pytest-asyncio>=0.23",
  "pytest-cov>=4.1.0",
  "pytest-xdist>=3.5",
  "coverage>=7.4.0",
  "pytest-postgresql>=6.0.0",
  "jupyter-client>=8.0",
  "python-docx>=1.1",
  "reportlab>=4.0,<5",
  "ruff",
]

[tool.uv]
# The repo is run in place (`application.*` imported from the checkout), not
# installed as a distribution.
package = false

[[tool.uv.index]]
name = "pytorch-cpu"
url = "https://download.pytorch.org/whl/cpu"
explicit = true

[tool.uv.sources]
# PyPI's Linux torch wheels depend on the full CUDA 13 stack (~2.7 GB of
# wheels). The docling extra runs its models on CPU, so take torch from the
# CPU index there. macOS and Windows PyPI wheels are CPU-only already.
torch = [{ index = "pytorch-cpu", marker = "sys_platform == 'linux'" }]
torchvision = [{ index = "pytorch-cpu", marker = "sys_platform == 'linux'" }]