mirror of
https://github.com/tiennm99/DocsGPT.git
synced 2026-10-12 18:15:33 +00:00
Alex
f7baa1952f
Both SDKs' 1.x/3.x majors run on httpx2 (the maintained fork of httpx by its original author, published by Pydantic at github.com/pydantic/httpx2, version line 2.x) instead of httpx, which is what makes these two bumps one change. httpx2 is now a declared dependency because two modules import it directly. Everything else in the 0.x -> 1.x / 2.x -> 3.x change lists is absent here: no Text Completions, no `with_raw_response`, no raw `output_format` dicts, no Bedrock client, and `requires-python` is already 3.12. Three code changes, all forced by the bump: The BYOM DNS-pinning client in `docsgpt/security/safe_url.py` is handed to `OpenAI(http_client=...)`, and the SDK rejects an old-httpx client at construction — which would have taken the SSRF guard offline. It is built on httpx2 now, and its `sni_hostname` extension carries a `str` rather than ascii bytes: httpcore passes the value straight to `ssl.SSLContext.wrap_socket`, and the truststore backend httpx2 uses for the default system trust store encodes it instead of accepting bytes. Bytes therefore failed every real handshake while passing the existing tests, which stub the transport out; the test now pins the type and says why. The stream-retry error tuple in `docsgpt/llm/base.py` named `httpx` exceptions only. The two libraries' exception classes are unrelated types, so after the bump the retry silently stopped firing for openai and anthropic while still working for google-genai and elevenlabs. It now covers both stacks, with a parametrized test over each. anthropic 1.x dropped temperature/top_p/top_k from `messages.create`'s signature (passing one raises TypeError) without dropping them from the API, so the provider forwards them through `extra_body`. The wire request is unchanged and a model that rejects them 400s exactly as before.
218 lines
7.2 KiB
TOML
218 lines
7.2 KiB
TOML
[build-system]
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requires = ["hatchling>=1.27,<2"]
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build-backend = "hatchling.build"
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[project]
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name = "docsgpt"
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# The version is read from docsgpt/version.py (the release workflow reads the
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# same file); bump it there.
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dynamic = ["version"]
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description = "DocsGPT backend: chat with your documents, agents, and tools."
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readme = "README.md"
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requires-python = ">=3.12"
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license = "MIT"
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license-files = ["LICENSE"]
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authors = [{ name = "Arc53" }]
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keywords = ["rag", "llm", "agents", "documents", "chat", "search"]
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classifiers = [
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"Development Status :: 5 - Production/Stable",
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"Environment :: Web Environment",
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"Framework :: Flask",
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"Intended Audience :: Developers",
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"Operating System :: OS Independent",
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"Programming Language :: Python :: 3",
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"Programming Language :: Python :: 3.12",
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"Programming Language :: Python :: 3.13",
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"Topic :: Scientific/Engineering :: Artificial Intelligence",
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]
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# Direct dependencies only, as compatible ranges: the floor is the version
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# uv.lock pins, the ceiling the next major (next minor below 1.0), so the
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# PyPI package installs next to other packages. The pip-facing files under
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# docsgpt/ (requirements*.txt) are exported from the lock by
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# scripts/export_requirements.sh and must not be edited by hand; Docker, CI
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# and the checkout install those exact versions.
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dependencies = [
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"a2wsgi>=1.10.10,<2",
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"alembic>=1.13,<2",
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"anthropic>=1.5.0,<2",
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"beautifulsoup4>=4.15.0,<5",
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"boto3>=1.43.67,<2",
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"cel-python>=0.5.0,<0.6",
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"celery>=5.6.3,<6",
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"celery-redbeat>=2.4.2,<3",
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"croniter>=6.2.4,<7",
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"cryptography>=50.0.0,<51",
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"dataclasses-json>=0.6.7,<0.7",
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"daytona>=0.211.2,<0.212",
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"ddgs>=8.0.0,<10",
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"defusedxml>=0.7.1,<0.8",
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"docx2txt>=0.9,<0.10",
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"elevenlabs>=2.62.0,<3",
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"faiss-cpu>=1.15.0,<2",
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"fast-ebook>=0.2.0,<0.3",
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# Default document converter (DOC_PARSER_ENGINE=anydoc): a Rust extension
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# with no model downloads. The docling engine is the `docling` extra.
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"firecrawl-anydoc>=0.2.4,<0.3",
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"fastembed>=0.8.0,<0.9",
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"fastmcp>=3.4.6,<4",
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"Flask>=3.1.3,<4",
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"flask-restx>=1.3.2,<2",
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"google-api-python-client>=2.198.0,<3",
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"google-auth-oauthlib>=1.4.0,<2",
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"google-genai>=2.17.0,<3",
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"gTTS>=2.5.4,<3",
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"gunicorn>=26.0.0,<27",
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# Imported directly by the BYOM DNS-pinning transport and the LLM
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# stream-retry error tuple; it is what anthropic and openai run on.
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"httpx2>=2.7.0,<3",
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"jinja2>=3.1.6,<4",
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"kombu>=5.6.2,<6",
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"markdownify>=1.2.3,<2",
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"msal>=1.37.0,<2",
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"networkx>=3.6.1,<4",
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"numpy>=2.5.1,<3",
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# fastembed's runtime: local embeddings execute on it.
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"onnxruntime>=1.28.0,<2",
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"openai>=3.13.0,<4",
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"openapi3-parser>=2.0.0,<3",
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# pandas reads .xlsx through openpyxl but does not depend on it.
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"openpyxl>=3.1.5,<4",
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"opentelemetry-distro>=0.50b0,<1",
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"opentelemetry-exporter-otlp>=1.29.0,<2",
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"opentelemetry-instrumentation-celery>=0.50b0,<1",
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"opentelemetry-instrumentation-flask>=0.50b0,<1",
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"opentelemetry-instrumentation-logging>=0.50b0,<1",
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"opentelemetry-instrumentation-psycopg>=0.50b0,<1",
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"opentelemetry-instrumentation-redis>=0.50b0,<1",
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"opentelemetry-instrumentation-requests>=0.50b0,<1",
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"opentelemetry-instrumentation-sqlalchemy>=0.50b0,<1",
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"opentelemetry-instrumentation-starlette>=0.50b0,<1",
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"pandas>=3.0.5,<4",
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"pdf2image>=1.17.0,<2",
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"pgvector>=0.5,<1",
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"pillow>=12.3.0,<13",
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"praw>=8.0.2,<9",
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"psycopg[binary,pool]>=3.1,<4",
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"pydantic>=2.13.5,<3",
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"pydantic-settings>=2.15.0,<3",
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"pypdf>=6.15.0,<7",
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"pypdfium2>=5.12.1,<6",
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"python-dateutil>=2.9.0,<3",
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"python-dotenv>=1.2.3,<2",
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"python-jose>=3.5.0,<4",
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"python-pptx>=1.0.2,<2",
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"PyYAML>=6.0.3,<7",
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"qdrant-client>=1.19.0,<2",
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"redis>=8.1.0,<9",
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"requests>=2.34.2,<3",
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"retry>=0.9.2,<0.10",
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"sqlalchemy>=2.0,<3",
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"starlette>=1.0,<2",
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"tiktoken>=0.14.0,<0.15",
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"tldextract>=5.3.2,<6",
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"tokenizers>=0.22.2,<0.23",
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"tqdm>=4.67.3,<5",
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"uvicorn[standard]>=0.30,<1",
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"uvicorn-worker>=0.4,<1",
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"websocket-client>=1.9.0,<2",
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"werkzeug>=3.1.0,<4",
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]
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[project.optional-dependencies]
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# Docling parser engine: DOC_PARSER_ENGINE=docling, the docling OCR backend
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# (layout-model hybrid OCR, ocrmac/rapidocr engines), .adoc/.vtt/.xml
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# attachment parsing, and read_document's `structured` output. Pulls torch and
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# transformers; with uv on Linux torch resolves from the CPU-only PyTorch index
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# (see [tool.uv.sources]) so the extra does not drag the CUDA stack in. pip
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# users on Linux install torch and torchvision from that index first
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# (--index-url https://download.pytorch.org/whl/cpu), then the extra; pip keeps
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# the torch it already has.
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docling = [
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"docling>=2.119.0,<3",
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"rapidocr>=3.9.2,<4",
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# docling's model stack. Declared here (not left transitive) so the floors
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# hold and the CPU index source below applies. transformers is capped by
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# docling-core at <5.9: 5.9+ breaks the PDF layout model on Apple Silicon.
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"torch>=2.11.0,<3",
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"torchvision>=0.26.0,<0.27",
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"transformers>=5.8.1,<5.9",
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]
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# VECTOR_STORE=milvus. milvus-lite (the embedded server) pulls pyarrow.
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milvus = [
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"pymilvus>=3.0.1,<4",
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"milvus-lite>=3.2.0,<4; sys_platform != 'win32'",
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]
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[project.scripts]
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docsgpt = "docsgpt.cli:main"
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[project.urls]
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Homepage = "https://www.docsgpt.cloud/"
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Documentation = "https://docs.docsgpt.cloud/"
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Repository = "https://github.com/arc53/DocsGPT"
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Issues = "https://github.com/arc53/DocsGPT/issues"
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Changelog = "https://github.com/arc53/DocsGPT/releases"
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[dependency-groups]
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# Mirrors tests/requirements.txt for `uv sync`; pip users install that file.
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dev = [
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"pytest>=8.0.0",
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"pytest-asyncio>=0.23",
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"pytest-cov>=4.1.0",
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"pytest-xdist>=3.5",
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"coverage>=7.4.0",
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"pytest-postgresql>=6.0.0",
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"jupyter-client>=8.0",
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"python-docx>=1.1",
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"reportlab>=5.0.1,<6",
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"ruff",
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]
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[tool.hatch.version]
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path = "docsgpt/version.py"
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# The wheel is the docsgpt package with the data it reads at runtime: prompts,
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# model catalogs, the seed config, alembic.ini and the migrations, plus the web
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# UI build under docsgpt/static (gitignored; scripts/build_frontend.sh makes
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# it, and `artifacts` admits it). Build inputs (Dockerfile, exported
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# requirements), the sample index and local runtime data stay out. The
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# one-release `application` import alias is checkout-only.
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[tool.hatch.build.targets.wheel]
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packages = ["docsgpt"]
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artifacts = ["docsgpt/static/**"]
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exclude = [
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"docsgpt/Dockerfile",
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"docsgpt/requirements*.txt",
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"docsgpt/index.faiss",
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"docsgpt/index.pkl",
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"docsgpt/indexes/",
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"docsgpt/inputs/",
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"docsgpt/vectors/",
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]
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[tool.hatch.build.targets.sdist]
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include = ["/docsgpt"]
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artifacts = ["docsgpt/static/**"]
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exclude = [
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"docsgpt/Dockerfile",
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"docsgpt/requirements*.txt",
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"docsgpt/index.faiss",
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"docsgpt/index.pkl",
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"docsgpt/indexes/",
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"docsgpt/inputs/",
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"docsgpt/vectors/",
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]
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[[tool.uv.index]]
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name = "pytorch-cpu"
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url = "https://download.pytorch.org/whl/cpu"
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explicit = true
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[tool.uv.sources]
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# PyPI's Linux torch wheels depend on the full CUDA 13 stack (~2.7 GB of
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# wheels). The docling extra runs its models on CPU, so take torch from the
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# CPU index there. macOS and Windows PyPI wheels are CPU-only already.
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torch = [{ index = "pytorch-cpu", marker = "sys_platform == 'linux'" }]
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torchvision = [{ index = "pytorch-cpu", marker = "sys_platform == 'linux'" }]
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