8000 build(deps): bump the python-minor group across 1 directory with 25 updates by dependabot[bot] · Pull Request #719 · adeelahmad/lense · GitHub
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build(deps): bump the python-minor group across 1 directory with 25 updates #719

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build(deps): bump the python-minor group across 1 directory with 25 updates #719

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40 changes: 20 additions & 20 deletions fastapi_backend/pyproject.toml
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Original file line number Diff line number Diff line change
Expand Up @@ -7,23 +7,23 @@ readme = "README.md"
license = "MIT"
dependencies = [
"fastapi[standard]>=0.143.0,<0.144",
"starlette>=1.8.0", # security floor (Dependabot); fastapi itself allows older
"pydantic-settings>=2.5.2,<3",
"starlette>=1.10.0", # security floor (Dependabot); fastapi itself allows older
"pydantic-settings>=2.16.2,<3",
"pyjwt>=2.9,<3",
"fastapi-mail>=1.4.1,<2",
"surrealdb>=2.0,<3",
"numpy>=2.5.4",
"scipy>=1.11",
"pyyaml>=6",
"jinja2>=3.1",
"pypdf>=6.20.1",
"pypdf>=6.21.4",
"pillow>=10",
"markdown>=3.11.1",
"markdown>=3.11.2",
"cryptography>=50",
"rdflib>=7.1,<8", # the archive as RDF (Dublin Core): export, import, SPARQL
"opentelemetry-api>=1.45.1,<2",
"opentelemetry-api>=1.45.2,<2",
"opentelemetry-sdk>=1.27,<2",
"opentelemetry-exporter-otlp-proto-http>=1.45.1,<2",
"opentelemetry-exporter-otlp-proto-http>=1.45.2,<2",
"webauthn>=3.0.1,<4",
"feedparser>=6.0.11,<7",
"regex>=2024.11", # patterns in automations' conditions, with a time limit (Apache-2.0; fastapi-mail needs it too)
Expand All @@ -35,7 +35,7 @@ sensevoice = ["funasr", "modelscope", "torch", "torchaudio"]
whisper = ["faster-whisper"]
mlx = ["mlx-whisper"]
# Laya typed decision models on MLX (Apple Silicon only): a local decision engine beside Jev
laya = ["laya-mlx>=0.4.0"]
laya = ["laya-mlx>=0.6.0"]
voices = ["speechbrain", "torch", "torchaudio"]
pyannote = ["pyannote.audio"]
# Video: faces and alternative OCR engines (Tesseract is used through its binary)
Expand All @@ -50,7 +50,7 @@ objects = ["onnxruntime"]
# Punctuation put back in transcripts (analysis.cleanup_punctuation): kredor/punctuate-all on Transformers and PyTorch
punctuation = ["transformers", "torch"]
# Named entities found by spaCy (analysis.entities "spacy"); its MIT-licensed models are fetched as pinned wheels
spacy = ["spacy>=3.8,<3.9"]
spacy = ["spacy>=3.8.18,<3.9"]
# A local prompt-injection classifier (ai.injection_check "classifier"): ProtectAI's DeBERTa model on ONNX Runtime
injection = ["onnxruntime", "tokenizers"]
# Florence-2 (MIT) describing pictures on this machine (llm.describe_engine "florence-2"): its ONNX export on ONNX Runtime
Expand All @@ -65,10 +65,10 @@ validate = ["jsonschema"]
smb = ["impacket>=0.13"]
# the assistant's code sandbox (sandbox.py): NVIDIA OpenShell's client (Apache-2.0), to reach its gateway; fetched when
# Settings › Code sandbox is turned on
sandbox = ["openshell>=0.1.4,<0.2"]
sandbox = ["openshell>=0.1.6,<0.2"]
# the assistant's web search through DuckDuckGo (web.py): ddgs (MIT), with its Rust HTTP client (primp) and lxml;
# fetched when DuckDuckGo is picked in Settings › AI assistant › Web search
web = ["ddgs>=9.16,<10"]
web = ["ddgs>=9.16.1,<10"]
# Kokoro v1.0 reading answers and podcasts aloud on this machine (kokoro.py, voice.tts_provider "kokoro"): kokoro-onnx
# (MIT) on ONNX Runtime. It turns text into phonemes with espeak-ng through phonemizer, both GPL-3.0, so it's fetched
# only once Kokoro is picked in Settings › AI assistant › Voice
Expand All @@ -78,7 +78,7 @@ kokoro = ["kokoro-onnx>=0.6.1,<0.7"]
webrtc = ["pywebrtc-audio>=0.2.0,<0.3"]
# auto scaling onto AWS EC2 (scaling_aws.py): botocore (Apache-2.0); fetched when the first AWS provider is saved in
# Settings › Auto scaling
aws = ["botocore>=1.43.113"]
aws = ["botocore>=1.43.123"]
# Outlook .msg emails (extract-msg is GPL-3.0; .eml needs nothing)
msg = ["extract-msg"]
# secrets read from a Vaultwarden or Bitwarden vault (vaultwarden_secrets.py): python-vaultwarden (Apache-2.0); fetched
Expand All @@ -94,28 +94,28 @@ lens = "app.cli:main"
[dependency-groups]
dev = [
"pre-commit>=4.7.0,<5",
"ruff>=0.17.0,<0.18",
"ruff>=0.17.3,<0.18",
"watchdog>=6.0.0,<7",
"python-dotenv>=1.2.4,<2",
"pytest>=9.0.3,<10",
"pytest-mock>=3.14.0,<4",
"pytest>=9.2.0,<10",
"pytest-mock>=3.17.0,<4",
"pytest-xdist>=3.6,<4",
"pytest-cov>=5,<8",
"httpx>=0.27",
"jsonschema>=4.23",
"mypy>=2.4.0,<3",
"mypy>=2.4.1,<3",
"types-pyyaml",
"coverage>=7.6",
"coverage>=7.17.0",
"coveralls>=4.0.1,<5",
"mkdocs-material>=9.6.9",
"mkdocs-material>=9.8.0",
"mkdocs-material[imaging]>=9.7.7",
"onnxruntime>=1.31.0", # the objects tests run a small YOLOX-shaped model
"onnxruntime>=1.31.1", # the objects tests run a small YOLOX-shaped model
"onnx>=1.23.2", # ... which they build
"tokenizers>=0.23.3", # the injection classifier tests run a tiny model and tokenizer
"mcp>=2.3.0", # the official MCP client, to test the MCP server with
"impacket>=0.13", # the SMB share's server, and the SMB client its tests sign in with
"openshell>=0.1.4,<0.2", # the code sandbox's client, tested against a fake OpenShell gateway
"botocore>=1.43.113",
"openshell>=0.1.6,<0.2", # the code sandbox's client, tested against a fake OpenShell gateway
"botocore>=1.43.123",
"kokoro-onnx>=0.6.1,<0.7", # Kokoro's tests phonemize with espeak-ng and read with a tiny Kokoro-shaped model
"pywebrtc-audio>=0.2.0,<0.3", # the clean_audio step's WebRTC audio processing, tested on synthetic audio
"python-vaultwarden>=1.1.2,<2", # the Vaultwarden client, tested against a fake Vaultwarden
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