chore: migrate from poetry to uv

.github/workflows/ci.yml

@@ -41,8 +41,6 @@ jobs:
       matrix:
         python-version:
           - "3.12"
-        poetry-version:
-          - "1.8.5"
     timeout-minutes: 5
     steps:
       - name: "Check out repository code"
@@ -52,28 +50,21 @@ jobs:
         uses: "actions/setup-python@v6"
         with:
           python-version: ${{ matrix.python-version }}
-      - name: "Install Poetry ${{ matrix.poetry-version }}"
-        uses: "snok/install-poetry@v1"
-        with:
-          version: ${{ matrix.poetry-version }}
-          virtualenvs-create: true
-          virtualenvs-in-project: true
-          installer-parallel: true
-      - name: "Setup Python environment"
-        run: |
-          poetry config virtualenvs.create true --local
-          poetry env use ${{ matrix.python-version }}
+
+      - name: "Install uv"
+        uses: "astral-sh/setup-uv@v5"
+
       - name: "Install dependencies"
-        run: "poetry install --no-interaction --no-ansi --with dev"
+        run: "uv sync --group dev"
 
       - name: "Linting: ruff check"
-        run: "poetry run ruff check ."
+        run: "uv run ruff check ."
       - name: "Linting: ruff format"
-        run: "poetry run ruff format --check --diff ."
+        run: "uv run ruff format --check --diff ."
       - name: "Mypy Tests"
-        run: "poetry run mypy --show-error-codes emma pages"
+        run: "uv run mypy --show-error-codes emma pages"
       - name: "Pylint Tests"
-        run: "poetry run pylint emma pages *.py"
+        run: "uv run pylint emma pages *.py"
 
   yaml-lint:
     if: needs.files-changed.outputs.yaml == 'true'
@@ -153,8 +144,6 @@ jobs:
       matrix:
         python-version:
           - "3.12"
-        poetry-version:
-          - "1.8.5"
     timeout-minutes: 5
     steps:
       - name: "Check out repository code"
@@ -165,25 +154,15 @@ jobs:
         with:
           python-version: ${{ matrix.python-version }}
 
-      - name: "Install Poetry ${{ matrix.poetry-version }}"
-        uses: "snok/install-poetry@v1"
-        with:
-          version: ${{ matrix.poetry-version }}
-          virtualenvs-create: true
-          virtualenvs-in-project: true
-          installer-parallel: true
-
-      - name: "Setup Python environment"
-        run: |
-          poetry config virtualenvs.create true --local
-          poetry env use ${{ matrix.python-version }}
+      - name: "Install uv"
+        uses: "astral-sh/setup-uv@v5"
 
       - name: "Install dependencies"
-        run: "poetry install --no-interaction --no-ansi"
+        run: "uv sync"
 
       - name: "Run Streamlit"
         run: |
-          timeout 30s poetry run streamlit run main.py &
+          timeout 30s uv run streamlit run main.py &
           PID=$!
           sleep 10
           if ps -p $PID > /dev/null; then

.vale/styles/spelling-exceptions.txt

@@ -167,6 +167,7 @@ userinfo
 uuid
 UUID
 UUIDs
+uv
 validator
 validators
 Version Control

CLAUDE.md

@@ -12,16 +12,16 @@ Emma is an experimental AI-powered assistant for Infrahub, a network infrastruct
 
 ```bash
 # Install dependencies
-poetry install
+uv sync
 
 # Run the application
-poetry run streamlit run main.py
+uv run streamlit run main.py
 
 # Format code
-poetry run invoke format
+uv run invoke format
 
 # Run all linters (yaml, ruff, mypy, pylint)
-poetry run invoke lint
+uv run invoke lint
 
 # Run tests
 pytest
@@ -88,7 +88,7 @@ Infrastructure schemas are YAML-based and stored in `schema-library/`. They defi
 - Streamlit for web UI
 - Infrahub SDK for backend operations
 - OpenAI/LangChain for AI features
-- Poetry for dependency management
+- uv for dependency management
 - Ruff, MyPy, Pylint for code quality
 
 ## Development Guidelines

Dockerfile

@@ -1,35 +1,31 @@
 # TODO: Make python version an arg
 FROM docker.io/python:3.12-slim
 
-# Env variable for the build
-# TODO: Review that part (e.g. poetry version ...)
-ENV POETRY_NO_INTERACTION=1 \
-    POETRY_CACHE_DIR=/tmp/poetry_cache \
-    POETRY_VIRTUALENVS_CREATE=false \
-    POETRY_HOME='/usr/local' \
-    POETRY_VERSION=1.8.3
+# Install uv
+COPY --from=ghcr.io/astral-sh/uv:latest /uv /usr/local/bin/uv
+
+# Env variables for the build
+ENV UV_COMPILE_BYTECODE=1
+ENV UV_LINK_MODE=copy
 
 # Install libraries and packages
 RUN apt-get update && \
     apt-get upgrade -y && \
     apt-get install --no-install-recommends -y curl git pkg-config build-essential ca-certificates && \
-    curl -sSL https://install.python-poetry.org | python3 - &&\
     apt-get autoremove -y && \
     apt-get clean all && \
-    rm -rf /var/lib/apt/lists/* && \
-    pip --no-cache-dir install --no-compile --upgrade pip wheel
+    rm -rf /var/lib/apt/lists/*
 
-# Copy lock and install all dependancies
+# Copy lock and install all dependencies
 WORKDIR /source
-COPY poetry.lock pyproject.toml /source/
-RUN poetry install --no-ansi --no-root --no-directory --without dev  && \
-    rm -rf $POETRY_CACHE_DIR
+COPY pyproject.toml uv.lock ./
+RUN uv sync --frozen --no-dev --no-install-project
 
 # Copy application and install it
 COPY . ./
-RUN poetry install --no-ansi --no-directory --without dev
+RUN uv sync --frozen --no-dev
 
-# Run streamlite app
+# Run streamlit app
 EXPOSE 8501
 HEALTHCHECK CMD curl --fail http://localhost:8501/_stcore/health
-ENTRYPOINT ["streamlit", "run", "main.py", "--server.port=8501", "--server.address=0.0.0.0"]
+ENTRYPOINT ["uv", "run", "streamlit", "run", "main.py", "--server.port=8501", "--server.address=0.0.0.0"]

docs/docs/getting-started/installation.mdx

@@ -12,7 +12,7 @@ Emma is an experimental AI-powered assistant for Infrahub that helps you manage
 Before installing Emma, ensure you have:
 
 - **Infrahub instance**: Emma requires a running Infrahub instance to connect to
-- **Docker** (for containerized deployment) or **Python 3.10+** and **Poetry** (for local development)
+- **Docker** (for containerized deployment) or **Python 3.10+** and **uv** (for local development)
 
 ## Installation methods
 
@@ -23,7 +23,7 @@ The easiest way to get started is using the Infrahub quickstart with Emma includ
 
 ```bash
 # Download and start Infrahub + Emma with Docker Compose
-curl https://infrahub.opsmill.io/1.4.12-emma | docker compose -f - up -d
+curl https://infrahub.opsmill.io/1.6.2-emma | docker compose -f - up -d
 ```
 
 This command will:
@@ -79,16 +79,16 @@ git clone https://github.com/opsmill/emma.git
 cd emma
 ```
 
-2. **Install dependencies with Poetry:**
+2. **Install dependencies with uv:**
 
 ```bash
-poetry install
+uv sync
 ```
 
 3. **Run Emma:**
 
 ```bash
-poetry run streamlit run main.py
+uv run streamlit run main.py
 ```
 
 Emma will start on http://localhost:8501
@@ -108,4 +108,4 @@ If you encounter issues during installation:
 - **Docker issues**: Check Docker is running and you have sufficient resources allocated
 - **Network connectivity**: Verify Emma can reach your Infrahub instance
 
-For more detailed troubleshooting, see the [Troubleshooting Guide](../reference/troubleshooting).
+For more detailed troubleshooting, see the [Troubleshooting Guide](../reference/troubleshooting).

docs/docs/readme.mdx

@@ -40,7 +40,7 @@ Ready to get started? Choose your preferred installation method:
 Use the one-command quickstart to get Emma and Infrahub running together:
 
 ```bash
-curl https://infrahub.opsmill.io/1.4.12-emma | docker compose -f - up -d
+curl https://infrahub.opsmill.io/1.6.2-emma | docker compose -f - up -d
 ```
 
 Then open [Emma](http://localhost:8501) and [Infrahub](http://localhost:8000) in your browser.

docs/docs/reference/configuration.mdx

@@ -382,7 +382,7 @@ WARNING: Unknown feature flag 'invalid_flag' ignored
 
 ```bash
 # Test configuration without starting full application
-poetry run python -c "from emma.utils import validate_config; validate_config()"
+uv run python -c "from emma.utils import validate_config; validate_config()"
 ```
 
 ## Migration and upgrades

docs/docs/reference/troubleshooting.mdx

@@ -265,7 +265,7 @@ This guide covers common issues you might encounter while using Emma and how to
 
 ```bash
 # Ensure you're using the correct command
-poetry run streamlit run main.py
+uv run streamlit run main.py
 
 # Or for direct Python execution
 python -m streamlit run main.py
@@ -343,7 +343,7 @@ export STREAMLIT_LOGGER_LEVEL=debug
 
 # Set Python logging level
 export PYTHONPATH=.
-poetry run python -c "import logging; logging.basicConfig(level=logging.DEBUG)"
+uv run python -c "import logging; logging.basicConfig(level=logging.DEBUG)"
 ```
 
 **For Docker:**
@@ -361,7 +361,7 @@ environment:
 
 ```bash
 # Run with verbose output
-poetry run streamlit run main.py --logger.level=debug
+uv run streamlit run main.py --logger.level=debug
 
 # Check Emma logs
 tail -f ~/.streamlit/logs/

emma/gql_queries.py

@@ -1,5 +1,3 @@
-from typing import Optional
-
 from graphql import GraphQLList, GraphQLNonNull, GraphQLObjectType, build_client_schema, get_introspection_query
 from langchain.tools import tool
 
@@ -24,7 +22,7 @@
 )
 
 
-def get_gql_schema(branch: Optional[str] = None) -> Optional[GraphQLObjectType]:
+def get_gql_schema(branch: str | None = None) -> GraphQLObjectType | None:
     schema_query = get_introspection_query()
     introspection_result = run_gql_query(query=schema_query, branch=branch)
 
@@ -35,7 +33,7 @@ def get_gql_schema(branch: Optional[str] = None) -> Optional[GraphQLObjectType]:
     return None
 
 
-def generate_query(object_type: GraphQLObjectType, visited_types: Optional[set] = None) -> str:
+def generate_query(object_type: GraphQLObjectType, visited_types: set | None = None) -> str:
     if visited_types is None:
         visited_types = set()
 
@@ -71,7 +69,7 @@ def generate_query(object_type: GraphQLObjectType, visited_types: Optional[set]
 
 
 @tool
-def generate_full_query(branch: Optional[str], root_object_name: str) -> Optional[str]:
+def generate_full_query(branch: str | None, root_object_name: str) -> str | None:
     """
     Generates a comprehensive GraphQL query for a specified root object, including all its fields
     and nested sub-objects, based on the schema retrieved from the specified branch.

pages/data_exporter.py

@@ -58,7 +58,7 @@ def create_column_label_mapping(
         f"{col} (Mandatory)" if col in mandatory_columns and col not in to_omit else f"{col} (Optional)"
         for col in mandatory_columns + optional_columns
     ]
-    label_to_col = {label: col for label, col in zip(column_labels, mandatory_columns + optional_columns)}
+    label_to_col = {label: col for label, col in zip(column_labels, mandatory_columns + optional_columns, strict=True)}
     return ColumnMapping(labels=column_labels, label_to_col=label_to_col)