diff --git a/.github/workflows/checks.yml b/.github/workflows/checks.yml
index 999546e..d5ffe33 100644
--- a/.github/workflows/checks.yml
+++ b/.github/workflows/checks.yml
@@ -48,6 +48,26 @@ jobs:
           token: ${{ secrets.CODECOV_TOKEN }}
           files: ./coverage.xml
 
+  run-slim-tests:
+    # The base install depends on docling-slim only: no PyTorch, no local models.
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: ['3.12']
+    steps:
+      - uses: actions/checkout@v4
+      - name: Install uv and set the python version
+        uses: astral-sh/setup-uv@v5
+        with:
+          python-version: ${{ matrix.python-version }}
+          enable-cache: true
+      - name: Install dependencies without extras
+        run: uv sync --frozen
+      - name: Check that the local model stack is not installed
+        run: uv run --no-sync python -c "import importlib.util as u, sys; sys.exit(any(u.find_spec(m) for m in ('torch', 'docling_ibm_models')))"
+      - name: Run tests
+        run: uv run --no-sync pytest -m "not slow" tests
+
   build-package:
     runs-on: ubuntu-latest
     strategy:
diff --git a/README.md b/README.md
index 631e728..713e878 100644
--- a/README.md
+++ b/README.md
@@ -36,6 +36,27 @@ pip install docling-agent
 
 Requires Python 3.11 or higher.
 
+The base install builds on [`docling-slim`](https://pypi.org/project/docling-slim/) and needs no PyTorch or local models. The agents work on `DoclingDocument`s, and source files (PDF, DOCX, images, ...) are converted by a [Docling Serve](https://github.com/docling-project/docling-serve) endpoint, such as Docling for IBM watsonx. Extras add capabilities that run locally:
+
+| Extra | Install | Adds |
+|-------|---------|------|
+| `local` | `pip install 'docling-agent[local]'` | Convert source files in-process with the Docling models |
+| `vlm` | `pip install 'docling-agent[vlm]'` | `DoclingExtractingAgent`, which runs a vision-language model locally (includes `local`) |
+| `evaluation` | `pip install 'docling-agent[evaluation]'` | Dependencies of the evaluation scripts in [`perfs/`](perfs/) |
+
+### Converting Source Files
+
+Tasks that ingest files, such as the `add` mode of the `docling-agent` CLI, pick the converter from these environment variables (also read from a `.env` file):
+
+| Variable | Default | Description |
+|----------|---------|-------------|
+| `DOCLING_AGENT_CONVERSION_MODE` | `auto` | `remote`, `local`, or `auto`: remote when a service URL is set, local otherwise |
+| `DOCLING_AGENT_SERVICE_URL` | | Base URL of the Docling Serve endpoint |
+| `DOCLING_AGENT_SERVICE_API_KEY` | | API key for the endpoint |
+| `DOCLING_AGENT_SERVICE_TIMEOUT` | `300` | Timeout in seconds for a remote conversion |
+
+The `fast`, `standard`, and `expensive` conversion presets apply the same pipeline options locally and remotely.
+
 ## Getting Started
 
 Each snippet shows how to initialise an agent, run a task, and save the result.
@@ -84,7 +105,7 @@ updated.save_as_html("./scratch/updated_table.html")
 
 ### Extract Structured Data with a Schema
 
-Define a simple schema and provide a list of files (PDFs/images); the agent produces an HTML report with extracted fields ([example](examples/example_03_extract_schema.py)).
+Define a simple schema and provide a list of files (PDFs/images); the agent produces an HTML report with extracted fields ([example](examples/example_03_extract_schema.py)). This agent runs a vision-language model locally and needs the `vlm` extra.
 
 ```python
 from pathlib import Path
@@ -175,7 +196,7 @@ Typical defaults:
 
 ## Examples
 
-Explore the [`examples/`](examples/) folder for end-to-end scripts covering document writing, editing, extraction, enrichment, RAG querying, and more.
+Explore the [`examples/`](examples/) folder for end-to-end scripts covering document writing, editing, extraction, enrichment, RAG querying, and more. The examples that convert files with a local `DocumentConverter` (06 and 07) need the `local` extra, and the extraction example (03) needs the `vlm` extra.
 
 ## Technical Report
 
diff --git a/docling_agent/agent/extractor.py b/docling_agent/agent/extractor.py
index 850994b..877b64a 100644
--- a/docling_agent/agent/extractor.py
+++ b/docling_agent/agent/extractor.py
@@ -2,8 +2,6 @@
 from pathlib import Path
 from typing import Any, ClassVar
 
-from docling.datamodel.base_models import InputFormat
-from docling.document_extractor import DocumentExtractor
 from docling_core.types.doc import (
     CodeLanguageLabel,
     DoclingDocument,
@@ -49,6 +47,18 @@ def __init__(
             backend=backend or self.default_backend(),
             tools=tools,
         )
+        # Imported here because DocumentExtractor pulls in the VLM stack (PyTorch, transformers),
+        # which importing docling_agent should not require when this agent is not used.
+        from docling.datamodel.base_models import InputFormat
+
+        try:
+            from docling.document_extractor import DocumentExtractor
+        except ImportError as exc:
+            raise ImportError(
+                "DoclingExtractingAgent runs a vision-language model locally. "
+                "Install the vlm extra with: pip install 'docling-agent[vlm]'"
+            ) from exc
+
         self._extractor: DocumentExtractor = DocumentExtractor(allowed_formats=[InputFormat.IMAGE, InputFormat.PDF])
         self._last_results: dict[str, list[Any]] = {}
 
diff --git a/docling_agent/agent/orchestrator.py b/docling_agent/agent/orchestrator.py
index 9817664..26d45d8 100644
--- a/docling_agent/agent/orchestrator.py
+++ b/docling_agent/agent/orchestrator.py
@@ -5,10 +5,9 @@
 import time
 from contextvars import ContextVar
 from pathlib import Path
-from typing import Literal, cast
+from typing import cast
 
 from docling.datamodel.base_models import ConversionStatus, FormatToMimeType, InputFormat
-from docling.document_converter import DocumentConverter
 from docling_core.transforms.serializer.markdown import MarkdownDocSerializer
 from docling_core.types.doc.document import (
     DocItemLabel,
@@ -29,6 +28,7 @@
 from docling_agent.agent.library import DocLibraryEntry, DoclingLibrary
 from docling_agent.agent.rag import DoclingRAGAgent
 from docling_agent.agent.writer import DoclingWritingAgent
+from docling_agent.conversion import ConversionPreset, SourceConverter, create_source_converter
 from docling_agent.logging import log_error, log_info, log_warning
 from docling_agent.task_model import (
     AddTask,
@@ -256,30 +256,26 @@ def _resolve_sources(self, task: AgentTask, library: DoclingLibrary) -> list[_So
 
         # Batch-convert all uncached files
         if raw_to_convert:
-            converter = self._build_source_converter(conversion)
-            for p in raw_to_convert:
-                source_key = str(p.resolve())
-                try:
-                    conv = converter.convert(p)
-                    if conv.status == ConversionStatus.SUCCESS:
-                        doc = conv.document
-                        entry = library.store(
-                            doc,
-                            source_key,
-                            project_id=task.project_id,
-                            original_mimetype=self._mimetype_for_input_format(conv.input.format),
-                            conversion_pipeline=self._pipeline_name_for_input_format(
-                                converter=converter,
-                                input_format=conv.input.format,
-                                conversion=conversion,
-                            ),
-                        )
-                        results.append((doc, entry.doc_id))
-                        log_info(f"Converted and cached: {p.name} → {entry.doc_id}")
-                    else:
-                        log_warning(f"Conversion failed for {p.name}: {conv.status}")
-                except Exception as exc:
-                    log_error(f"Error converting {p}: {exc}")
+            with self._build_source_converter(conversion) as converter:
+                for p in raw_to_convert:
+                    source_key = str(p.resolve())
+                    try:
+                        conv = converter.convert(p)
+                        if conv.status == ConversionStatus.SUCCESS:
+                            doc = conv.document
+                            entry = library.store(
+                                doc,
+                                source_key,
+                                project_id=task.project_id,
+                                original_mimetype=self._mimetype_for_input_format(conv.input.format),
+                                conversion_pipeline=converter.pipeline_name(conv.input.format),
+                            )
+                            results.append((doc, entry.doc_id))
+                            log_info(f"Converted and cached: {p.name} → {entry.doc_id}")
+                        else:
+                            log_warning(f"Conversion failed for {p.name}: {conv.status}")
+                    except Exception as exc:
+                        log_error(f"Error converting {p}: {exc}")
 
         log_info(f"Resolved {len(results)} document(s)")
         return results
@@ -756,46 +752,19 @@ def _mimetype_for_input_format(self, input_format: InputFormat) -> str | None:
         mimetypes = FormatToMimeType.get(input_format, [])
         return mimetypes[0] if mimetypes else None
 
-    def _pipeline_name_for_input_format(
-        self,
-        *,
-        converter: DocumentConverter,
-        input_format: InputFormat,
-        conversion: Literal["fast", "standard", "expensive"],
-    ) -> str:
-        format_option = converter.format_to_options.get(input_format)
-        if format_option is None:
-            return f"unknown:{conversion}"
-        return f"{format_option.pipeline_cls.__name__}:{conversion}"
-
-    def _source_conversion_preset(self, task: AgentTask) -> Literal["fast", "standard", "expensive"]:
+    def _source_conversion_preset(self, task: AgentTask) -> ConversionPreset:
         if isinstance(task, AddTask):
             return task.conversion
         return "standard"
 
-    def _build_source_converter(self, conversion: Literal["fast", "standard", "expensive"]) -> DocumentConverter:
-        converter = DocumentConverter()
-        for format_option in converter.format_to_options.values():
-            pipeline_options = format_option.pipeline_options
-            if pipeline_options is None:
-                continue
-            if hasattr(pipeline_options, "do_ocr"):
-                pipeline_options.do_ocr = conversion != "fast"
-            if hasattr(pipeline_options, "do_table_structure"):
-                pipeline_options.do_table_structure = conversion != "fast"
-            if hasattr(pipeline_options, "do_picture_classification"):
-                pipeline_options.do_picture_classification = True
-            if hasattr(pipeline_options, "do_chart_extraction"):
-                pipeline_options.do_chart_extraction = conversion == "expensive"
-            if hasattr(pipeline_options, "generate_page_images"):
-                pipeline_options.generate_page_images = True
-        return converter
+    def _build_source_converter(self, conversion: ConversionPreset) -> SourceConverter:
+        return create_source_converter(conversion)
 
     def _cache_entry_matches_conversion(
         self,
         entry: DocLibraryEntry,
         *,
-        conversion: Literal["fast", "standard", "expensive"],
+        conversion: ConversionPreset,
     ) -> bool:
         for run in entry.status.pipelines:
             if run.name.endswith(f":{conversion}"):
diff --git a/docling_agent/conversion.py b/docling_agent/conversion.py
new file mode 100644
index 0000000..e5ed998
--- /dev/null
+++ b/docling_agent/conversion.py
@@ -0,0 +1,219 @@
+"""Conversion of source files into DoclingDocuments, locally or with a Docling service.
+
+The base install of docling-agent depends on ``docling-slim`` only, which can convert sources through a
+Docling Serve endpoint (for example Docling for IBM watsonx). Converting them in-process needs the
+local models and parsers, which come with the ``local`` extra (``pip install 'docling-agent[local]'``).
+"""
+
+from __future__ import annotations
+
+import importlib.util
+from enum import Enum
+from pathlib import Path
+from types import TracebackType
+from typing import TYPE_CHECKING, Annotated, Literal
+
+from docling.datamodel.base_models import InputFormat
+from docling.datamodel.document import ConversionResult
+from pydantic import Field
+from pydantic_settings import BaseSettings, SettingsConfigDict
+from typing_extensions import Self
+
+from docling_agent.logging import log_info
+
+if TYPE_CHECKING:
+    from docling.document_converter import DocumentConverter
+    from docling.service_client import DoclingServiceClient
+
+ConversionPreset = Literal["fast", "standard", "expensive"]
+
+LOCAL_EXTRA_HINT = "Install the local extra with: pip install 'docling-agent[local]'"
+
+
+class ConversionMode(str, Enum):
+    """Where source files are converted."""
+
+    AUTO = "auto"
+    """Use the Docling service when ``DOCLING_AGENT_SERVICE_URL`` is set, convert locally otherwise."""
+
+    LOCAL = "local"
+    """Convert in-process with docling (requires the ``local`` extra)."""
+
+    REMOTE = "remote"
+    """Convert with a Docling Serve endpoint."""
+
+
+class ConversionSettings(BaseSettings):
+    """Settings for converting source files, read from ``DOCLING_AGENT_*`` environment variables or ``.env``."""
+
+    model_config = SettingsConfigDict(env_prefix="DOCLING_AGENT_", env_file=".env", extra="ignore")
+
+    conversion_mode: Annotated[
+        ConversionMode,
+        Field(description="Where source files are converted: auto, local or remote."),
+    ] = ConversionMode.AUTO
+    service_url: Annotated[
+        str | None,
+        Field(description="Base URL of the Docling Serve endpoint used for remote conversion."),
+    ] = None
+    service_api_key: Annotated[
+        str | None,
+        Field(repr=False, description="API key for the Docling Serve endpoint."),
+    ] = None
+    service_timeout: Annotated[
+        float,
+        Field(description="Timeout in seconds for a remote conversion."),
+    ] = 300.0
+
+    def resolved_mode(self) -> ConversionMode:
+        """Return the conversion mode, resolving ``auto`` from the presence of a service URL."""
+        if self.conversion_mode == ConversionMode.AUTO:
+            return ConversionMode.REMOTE if self.service_url else ConversionMode.LOCAL
+        return self.conversion_mode
+
+
+def local_conversion_available() -> bool:
+    """Return whether the local conversion stack (models and parsers) is installed."""
+    return importlib.util.find_spec("docling_ibm_models") is not None
+
+
+class LocalSourceConverter:
+    """Convert source files in-process with docling's DocumentConverter."""
+
+    def __init__(self, preset: ConversionPreset) -> None:
+        """Build a DocumentConverter configured for the given preset.
+
+        Args:
+            preset: The named conversion preset.
+
+        Raises:
+            ImportError: If the ``local`` extra is not installed.
+        """
+        if not local_conversion_available():
+            raise ImportError(
+                "Converting source files locally needs the local docling models and parsers. "
+                f"{LOCAL_EXTRA_HINT}, or set DOCLING_AGENT_SERVICE_URL to convert with a Docling service."
+            )
+        from docling.document_converter import DocumentConverter
+
+        self.preset = preset
+        self.converter: DocumentConverter = DocumentConverter()
+        for format_option in self.converter.format_to_options.values():
+            pipeline_options = format_option.pipeline_options
+            if pipeline_options is None:
+                continue
+            if hasattr(pipeline_options, "do_ocr"):
+                pipeline_options.do_ocr = preset != "fast"
+            if hasattr(pipeline_options, "do_table_structure"):
+                pipeline_options.do_table_structure = preset != "fast"
+            if hasattr(pipeline_options, "do_picture_classification"):
+                pipeline_options.do_picture_classification = True
+            if hasattr(pipeline_options, "do_chart_extraction"):
+                pipeline_options.do_chart_extraction = preset == "expensive"
+            if hasattr(pipeline_options, "generate_page_images"):
+                pipeline_options.generate_page_images = True
+
+    def convert(self, source: Path) -> ConversionResult:
+        """Convert one source file."""
+        return self.converter.convert(source)
+
+    def pipeline_name(self, input_format: InputFormat) -> str:
+        """Return the name of the pipeline used for an input format, recorded in the library."""
+        format_option = self.converter.format_to_options.get(input_format)
+        if format_option is None:
+            return f"unknown:{self.preset}"
+        return f"{format_option.pipeline_cls.__name__}:{self.preset}"
+
+    def close(self) -> None:
+        """Release resources (nothing to release for local conversion)."""
+
+    def __enter__(self) -> Self:
+        return self
+
+    def __exit__(
+        self,
+        exc_type: type[BaseException] | None,
+        exc: BaseException | None,
+        tb: TracebackType | None,
+    ) -> None:
+        self.close()
+
+
+class RemoteSourceConverter:
+    """Convert source files with a Docling Serve endpoint."""
+
+    def __init__(self, preset: ConversionPreset, settings: ConversionSettings) -> None:
+        """Create a service client and the request options for the given preset.
+
+        Args:
+            preset: The named conversion preset.
+            settings: The conversion settings holding the service URL and API key.
+
+        Raises:
+            ValueError: If no service URL is configured.
+        """
+        if not settings.service_url:
+            raise ValueError(
+                "DOCLING_AGENT_CONVERSION_MODE is 'remote' but DOCLING_AGENT_SERVICE_URL is not set. "
+                f"Set the service URL, or convert locally ({LOCAL_EXTRA_HINT})."
+            )
+        from docling.datamodel.service.options import ConvertDocumentsOptions
+        from docling.service_client import DoclingServiceClient
+
+        self.preset = preset
+        self.options = ConvertDocumentsOptions(
+            do_ocr=preset != "fast",
+            do_table_structure=preset != "fast",
+            do_picture_classification=True,
+            do_chart_extraction=preset == "expensive",
+            include_images=True,
+        )
+        self.client: DoclingServiceClient = DoclingServiceClient(
+            url=settings.service_url,
+            api_key=settings.service_api_key or "",
+            job_timeout=settings.service_timeout,
+        )
+
+    def convert(self, source: Path) -> ConversionResult:
+        """Convert one source file."""
+        return self.client.convert(source=source, options=self.options)
+
+    def pipeline_name(self, input_format: InputFormat) -> str:
+        """Return the name of the pipeline used for an input format, recorded in the library."""
+        return f"DoclingServiceClient:{self.preset}"
+
+    def close(self) -> None:
+        """Close the service client."""
+        self.client.close()
+
+    def __enter__(self) -> Self:
+        return self
+
+    def __exit__(
+        self,
+        exc_type: type[BaseException] | None,
+        exc: BaseException | None,
+        tb: TracebackType | None,
+    ) -> None:
+        self.close()
+
+
+SourceConverter = LocalSourceConverter | RemoteSourceConverter
+
+
+def create_source_converter(preset: ConversionPreset, settings: ConversionSettings | None = None) -> SourceConverter:
+    """Return a local or remote converter for the given preset, according to the settings.
+
+    Args:
+        preset: The named conversion preset.
+        settings: The conversion settings. Read from the environment when omitted.
+
+    Returns:
+        A converter usable as a context manager.
+    """
+    settings = settings or ConversionSettings()
+    mode = settings.resolved_mode()
+    log_info(f"Converting sources with the {mode.value} converter (preset: {preset})")
+    if mode == ConversionMode.REMOTE:
+        return RemoteSourceConverter(preset, settings)
+    return LocalSourceConverter(preset)
diff --git a/perfs/agentic_rag_eval_README.md b/perfs/agentic_rag_eval_README.md
index d77cacb..ed36e34 100644
--- a/perfs/agentic_rag_eval_README.md
+++ b/perfs/agentic_rag_eval_README.md
@@ -221,13 +221,13 @@ scratch/agentic_rag_eval/
 
 ## Requirements
 
-In addition to the standard `docling-agent` dependencies:
+Install `docling-agent` with the `evaluation` extra, which adds local PDF conversion with the VLM models and the metrics libraries:
 
 ```bash
-pip install ranx pandas pyarrow tqdm
+pip install 'docling-agent[evaluation]'
 ```
 
-- `docling` — PDF conversion.
+- `docling-slim[standard,models-vlm-inline]` — PDF conversion, picture description, and chart extraction.
 - `docling-core` — `DoclingDocument` manipulation.
 - `docling-agent` — Editing, enriching, and RAG agents.
 - `ranx` — NDCG computation.
diff --git a/pyproject.toml b/pyproject.toml
index d481a81..f6e05e6 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -34,7 +34,7 @@ classifiers = [
 ]
 requires-python = ">=3.11,<4.0"
 dependencies = [
-    "docling>=2.61.0",
+    "docling-slim[service-client,format-html,format-markdown]~=2.140",
     "docling-core>=2.79.0",
     "pydantic~=2.10",
     "pydantic-settings~=2.4",
@@ -50,14 +50,19 @@ dependencies = [
 ]
 
 [project.optional-dependencies]
+# Convert source files in-process (PDF, DOCX, images, ...) instead of with a Docling service.
+local = [
+    "docling-slim[standard]~=2.140",
+]
+# Run the DoclingExtractingAgent, which uses a vision-language model locally.
 vlm = [
-    "docling[vlm]~=2.53",
+    "docling-slim[standard,models-vlm-inline]~=2.140",
 ]
 evaluation = [
+    "docling-slim[standard,models-vlm-inline]~=2.140",
     "ranx>=0.3.21",
     "ocrmac>=1.0.0,<2.0.0; sys_platform == 'darwin'",
     "nemotron-ocr>=2.0.0; sys_platform == 'linux' and python_version == '3.12' and platform_machine == 'x86_64'",
-    "transformers>=5.4,<5.9",  # workaround until docling-project/docling#4205 is fixed 
 ]
 
 [dependency-groups]
diff --git a/tests/test_agents_instantiation.py b/tests/test_agents_instantiation.py
index f60d9a0..d4ec32c 100644
--- a/tests/test_agents_instantiation.py
+++ b/tests/test_agents_instantiation.py
@@ -1,3 +1,6 @@
+import importlib.util
+import sys
+
 import pytest
 
 from docling_agent.backends import create_backend
@@ -34,6 +37,7 @@ def test_instantiate_docling_editing_agent():
         pytest.fail(f"DoclingEditingAgent instantiation raised: {e}")
 
 
+@pytest.mark.skipif(importlib.util.find_spec("torch") is None, reason="requires the vlm extra")
 def test_instantiate_docling_extracting_agent():
     from docling_agent.agent.extractor import DoclingExtractingAgent
 
@@ -43,6 +47,15 @@ def test_instantiate_docling_extracting_agent():
         pytest.fail(f"DoclingExtractingAgent instantiation raised: {e}")
 
 
+def test_extracting_agent_names_the_vlm_extra_when_missing(monkeypatch):
+    from docling_agent.agent.extractor import DoclingExtractingAgent
+
+    # A None entry in sys.modules makes the import fail as if the VLM stack were not installed
+    monkeypatch.setitem(sys.modules, "docling.document_extractor", None)
+    with pytest.raises(ImportError, match=r"docling-agent\[vlm\]"):
+        DoclingExtractingAgent(backend=_backend(), tools=[])
+
+
 def test_instantiate_docling_enriching_agent():
     from docling_agent.agent.enricher import DoclingEnrichingAgent
 
diff --git a/tests/test_conversion.py b/tests/test_conversion.py
new file mode 100644
index 0000000..8b316cc
--- /dev/null
+++ b/tests/test_conversion.py
@@ -0,0 +1,77 @@
+"""Tests for converting source files locally or with a Docling service."""
+
+import pytest
+
+from docling_agent import conversion
+from docling_agent.conversion import (
+    ConversionMode,
+    ConversionSettings,
+    LocalSourceConverter,
+    RemoteSourceConverter,
+    create_source_converter,
+)
+
+
+def _settings(**kwargs) -> ConversionSettings:
+    # Ignore the environment and any .env file, so tests only see what they pass
+    return ConversionSettings(_env_file=None, **kwargs)
+
+
+@pytest.fixture(autouse=True)
+def _clean_env(monkeypatch: pytest.MonkeyPatch) -> None:
+    for name in ("CONVERSION_MODE", "SERVICE_URL", "SERVICE_API_KEY", "SERVICE_TIMEOUT"):
+        monkeypatch.delenv(f"DOCLING_AGENT_{name}", raising=False)
+
+
+def test_auto_mode_uses_remote_when_service_url_is_set() -> None:
+    assert _settings(service_url="https://docling.example.com").resolved_mode() == ConversionMode.REMOTE
+
+
+def test_auto_mode_uses_local_without_service_url() -> None:
+    assert _settings().resolved_mode() == ConversionMode.LOCAL
+
+
+def test_explicit_mode_wins_over_service_url() -> None:
+    settings = _settings(conversion_mode="local", service_url="https://docling.example.com")
+    assert settings.resolved_mode() == ConversionMode.LOCAL
+
+
+def test_settings_read_from_environment(monkeypatch: pytest.MonkeyPatch) -> None:
+    monkeypatch.setenv("DOCLING_AGENT_SERVICE_URL", "https://docling.example.com")
+    monkeypatch.setenv("DOCLING_AGENT_SERVICE_API_KEY", "secret")
+    settings = _settings()
+    assert settings.service_url == "https://docling.example.com"
+    assert settings.service_api_key == "secret"
+    assert "secret" not in repr(settings)
+
+
+@pytest.mark.parametrize(
+    ("preset", "heavy", "charts"),
+    [("fast", False, False), ("standard", True, False), ("expensive", True, True)],
+)
+def test_remote_converter_maps_presets_to_options(preset, heavy, charts) -> None:
+    converter = create_source_converter(preset, _settings(service_url="https://docling.example.com"))
+    with converter:
+        assert isinstance(converter, RemoteSourceConverter)
+        assert converter.options.do_ocr is heavy
+        assert converter.options.do_table_structure is heavy
+        assert converter.options.do_picture_classification is True
+        assert converter.options.do_chart_extraction is charts
+        assert converter.pipeline_name(input_format=None) == f"DoclingServiceClient:{preset}"
+
+
+def test_remote_converter_requires_service_url() -> None:
+    with pytest.raises(ValueError, match="DOCLING_AGENT_SERVICE_URL"):
+        create_source_converter("standard", _settings(conversion_mode="remote"))
+
+
+def test_local_converter_requires_local_extra(monkeypatch: pytest.MonkeyPatch) -> None:
+    monkeypatch.setattr(conversion, "local_conversion_available", lambda: False)
+    with pytest.raises(ImportError, match=r"docling-agent\[local\]"):
+        create_source_converter("standard", _settings())
+
+
+@pytest.mark.skipif(not conversion.local_conversion_available(), reason="requires the local extra")
+def test_local_converter_is_used_without_service_url() -> None:
+    with create_source_converter("fast", _settings()) as converter:
+        assert isinstance(converter, LocalSourceConverter)
diff --git a/tests/test_imports.py b/tests/test_imports.py
new file mode 100644
index 0000000..dbec329
--- /dev/null
+++ b/tests/test_imports.py
@@ -0,0 +1,11 @@
+"""Tests for the import-time footprint of docling_agent."""
+
+import subprocess
+import sys
+
+
+def test_import_does_not_load_document_extractor():
+    """Importing the package must not require the VLM stack behind DocumentExtractor."""
+    code = "import sys, docling_agent; sys.exit('docling.document_extractor' in sys.modules)"
+    result = subprocess.run([sys.executable, "-c", code], capture_output=True, text=True)
+    assert result.returncode == 0, result.stderr or "docling.document_extractor was imported"
diff --git a/tests/test_orchestrator.py b/tests/test_orchestrator.py
index 3509aad..d977e2b 100644
--- a/tests/test_orchestrator.py
+++ b/tests/test_orchestrator.py
@@ -16,6 +16,7 @@
 from docling_agent.agent.library import DocLibraryEntry, DoclingLibrary
 from docling_agent.agent.orchestrator import DoclingOrchestratorAgent
 from docling_agent.agent.writer import DoclingWritingAgent
+from docling_agent.conversion import LocalSourceConverter, local_conversion_available
 from docling_agent.task_model import AddTask, ClearTask, ListTask, ViewTask, WriteTask
 
 
@@ -143,14 +144,21 @@ def test_add_mode_adds_sources_to_library(
     assert entries[0].doc_id in markdown
 
 
-def test_build_source_converter_applies_named_presets(orchestrator: DoclingOrchestratorAgent) -> None:
+@pytest.mark.skipif(not local_conversion_available(), reason="requires the local extra")
+def test_build_source_converter_applies_named_presets(
+    monkeypatch: pytest.MonkeyPatch, orchestrator: DoclingOrchestratorAgent
+) -> None:
+    monkeypatch.setenv("DOCLING_AGENT_CONVERSION_MODE", "local")
     fast = orchestrator._build_source_converter("fast")
     standard = orchestrator._build_source_converter("standard")
     expensive = orchestrator._build_source_converter("expensive")
+    assert isinstance(fast, LocalSourceConverter)
+    assert isinstance(standard, LocalSourceConverter)
+    assert isinstance(expensive, LocalSourceConverter)
 
-    fast_pdf = fast.format_to_options[InputFormat.PDF].pipeline_options
-    standard_pdf = standard.format_to_options[InputFormat.PDF].pipeline_options
-    expensive_pdf = expensive.format_to_options[InputFormat.PDF].pipeline_options
+    fast_pdf = fast.converter.format_to_options[InputFormat.PDF].pipeline_options
+    standard_pdf = standard.converter.format_to_options[InputFormat.PDF].pipeline_options
+    expensive_pdf = expensive.converter.format_to_options[InputFormat.PDF].pipeline_options
 
     assert fast_pdf.do_ocr is False
     assert fast_pdf.do_table_structure is False
diff --git a/uv.lock b/uv.lock
index d2a045e..2ade859 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1,13 +1,13 @@
 version = 1
-revision = 3
+revision = 5
 requires-python = ">=3.11, <4.0"
 resolution-markers = [
-    "python_full_version == '3.12.*' and platform_machine == 'x86_64' and sys_platform == 'linux'",
     "python_full_version >= '3.15' and sys_platform == 'darwin'",
-    "python_full_version >= '3.12' and python_full_version < '3.15' and sys_platform == 'darwin'",
-    "python_full_version < '3.12' and sys_platform == 'darwin'",
     "python_full_version >= '3.15' and sys_platform != 'darwin'",
+    "python_full_version == '3.12.*' and platform_machine == 'x86_64' and sys_platform == 'linux'",
+    "python_full_version >= '3.12' and python_full_version < '3.15' and sys_platform == 'darwin'",
     "(python_full_version >= '3.12' and python_full_version < '3.15' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version >= '3.13' and python_full_version < '3.15' and platform_machine == 'x86_64' and sys_platform == 'linux') or (python_full_version >= '3.12' and python_full_version < '3.15' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version < '3.12' and sys_platform == 'darwin'",
     "python_full_version < '3.12' and sys_platform != 'darwin'",
 ]
 
@@ -52,14 +52,14 @@ name = "aiohttp"
 version = "3.14.3"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "aiohappyeyeballs", marker = "sys_platform == 'darwin'" },
-    { name = "aiosignal", marker = "sys_platform == 'darwin'" },
-    { name = "attrs", marker = "sys_platform == 'darwin'" },
-    { name = "frozenlist", marker = "sys_platform == 'darwin'" },
-    { name = "multidict", marker = "sys_platform == 'darwin'" },
-    { name = "propcache", marker = "sys_platform == 'darwin'" },
-    { name = "typing-extensions", marker = "python_full_version < '3.13' and sys_platform == 'darwin'" },
-    { name = "yarl", marker = "sys_platform == 'darwin'" },
+    { name = "aiohappyeyeballs" },
+    { name = "aiosignal" },
+    { name = "attrs" },
+    { name = "frozenlist" },
+    { name = "multidict" },
+    { name = "propcache" },
+    { name = "typing-extensions", marker = "python_full_version < '3.13'" },
+    { name = "yarl" },
 ]
 sdist = { url = "https://files.pythonhosted.org/packages/58/d9/22ce5786ac0c1653ae8b6c23bded02c1686d11f0dbb45b31ce128e0df985/aiohttp-3.14.3.tar.gz", hash = "sha256:9491196535a88924a60afd5b5f434b5b203b6cc616250878dbdb223a8f7844bc", size = 7971213, upload-time = "2026-07-23T01:57:27.037Z" }
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@@ -88,8 +84,8 @@ name = "aiosignal"
 version = "1.4.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "frozenlist", marker = "sys_platform == 'darwin'" },
-    { name = "typing-extensions", marker = "python_full_version < '3.13' and sys_platform == 'darwin'" },
+    { name = "frozenlist" },
+    { name = "typing-extensions", marker = "python_full_version < '3.13'" },
 ]
 sdist = { url = "https://files.pythonhosted.org/packages/61/62/06741b579156360248d1ec624842ad0edf697050bbaf7c3e46394e106ad1/aiosignal-1.4.0.tar.gz", hash = "sha256:f47eecd9468083c2029cc99945502cb7708b082c232f9aca65da147157b251c7", size = 25007, upload-time = "2025-07-03T22:54:43.528Z" }
 wheels = [
@@ -653,7 +649,7 @@ resolution-markers = [
     "python_full_version < '3.12' and sys_platform != 'darwin'",
 ]
 dependencies = [
-    { name = "numpy", marker = "python_full_version < '3.12'" },
+    { name = "numpy" },
 ]
 sdist = { url = "https://files.pythonhosted.org/packages/58/01/1253e6698a07380cd31a736d248a3f2a50a7c88779a1813da27503cadc2a/contourpy-1.3.3.tar.gz", hash = "sha256:083e12155b210502d0bca491432bb04d56dc3432f95a979b429f2848c3dbe880", size = 13466174, upload-time = "2025-07-26T12:03:12.549Z" }
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-    "python_full_version >= '3.12' and python_full_version < '3.15' and sys_platform == 'darwin'",
     "python_full_version >= '3.15' and sys_platform != 'darwin'",
+    "python_full_version == '3.12.*' and platform_machine == 'x86_64' and sys_platform == 'linux'",
+    "python_full_version >= '3.12' and python_full_version < '3.15' and sys_platform == 'darwin'",
     "(python_full_version >= '3.12' and python_full_version < '3.15' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version >= '3.13' and python_full_version < '3.15' and platform_machine == 'x86_64' and sys_platform == 'linux') or (python_full_version >= '3.12' and python_full_version < '3.15' and sys_platform != 'darwin' and sys_platform != 'linux')",
 ]
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-    { name = "numpy", marker = "python_full_version >= '3.12'" },
+    { name = "numpy" },
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 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "cffi", marker = "platform_python_implementation != 'PyPy' and sys_platform != 'darwin'" },
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+    { name = "httpx" },
+    { name = "huggingface-hub" },
+    { name = "multiprocess" },
+    { name = "numpy" },
+    { name = "packaging" },
+    { name = "pandas" },
+    { name = "pyarrow" },
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-    { name = "docling", version = "2.129.0", source = { registry = "https://pypi.org/simple" }, marker = "sys_platform != 'darwin'" },
     { name = "docling-core" },
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     { name = "mellea" },
     { name = "pandas" },
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+]
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+    { name = "docling-slim", extra = ["models-vlm-inline", "standard"] },
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-    { name = "docling", extras = ["vlm"], marker = "extra == 'vlm'", specifier = "~=2.53" },
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+    { name = "docling-slim", extras = ["standard"], marker = "extra == 'local'", specifier = "~=2.140" },
+    { name = "docling-slim", extras = ["standard", "models-vlm-inline"], marker = "extra == 'evaluation'", specifier = "~=2.140" },
+    { name = "docling-slim", extras = ["standard", "models-vlm-inline"], marker = "extra == 'vlm'", specifier = "~=2.140" },
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 ]
-provides-extras = ["vlm", "evaluation"]
+provides-extras = ["local", "vlm", "evaluation"]
 
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-    { name = "requests", marker = "sys_platform == 'darwin'" },
-    { name = "tqdm", marker = "sys_platform == 'darwin'" },
+    { name = "certifi" },
+    { name = "docling-core" },
+    { name = "filetype" },
+    { name = "langcodes" },
+    { name = "pluggy" },
+    { name = "pydantic" },
+    { name = "pydantic-settings" },
+    { name = "requests" },
+    { name = "tqdm" },
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-    { name = "qwen-vl-utils", marker = "sys_platform == 'darwin'" },
-    { name = "transformers", marker = "sys_platform == 'darwin'" },
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-    { name = "beautifulsoup4", marker = "sys_platform == 'darwin'" },
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-    { name = "typer", marker = "sys_platform == 'darwin'" },
-    { name = "websockets", marker = "sys_platform == 'darwin'" },
+format-markdown = [
+    { name = "marko" },
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-
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+    { name = "open-clip-torch" },
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+]
+service-client = [
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+    { name = "python-dotenv" },
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+    { name = "typer" },
+    { name = "websockets" },
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-    { name = "typer", marker = "sys_platform != 'darwin'" },
-    { name = "websockets", marker = "sys_platform != 'darwin'" },
+    { name = "accelerate" },
+    { name = "beautifulsoup4" },
+    { name = "defusedxml" },
+    { name = "docling-core", extra = ["chunking"] },
+    { name = "docling-ibm-models" },
+    { name = "docling-parse" },
+    { name = "httpx" },
+    { name = "huggingface-hub" },
+    { name = "mail-parser" },
+    { name = "marko" },
+    { name = "numpy" },
+    { name = "openpyxl" },
+    { name = "pillow" },
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+    { name = "pypdfium2" },
+    { name = "python-docx" },
+    { name = "python-dotenv" },
+    { name = "python-oxmsg" },
+    { name = "python-pptx" },
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+    { name = "torch" },
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 [[package]]
@@ -1665,11 +1569,11 @@ name = "fastapi"
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-    { name = "typing-inspection", marker = "sys_platform == 'darwin'" },
+    { name = "annotated-doc" },
+    { name = "pydantic" },
+    { name = "starlette" },
+    { name = "typing-extensions" },
+    { name = "typing-inspection" },
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 wheels = [
@@ -1857,7 +1761,7 @@ wheels = [
 
 [package.optional-dependencies]
 http = [
-    { name = "aiohttp", marker = "sys_platform == 'darwin'" },
+    { name = "aiohttp" },
 ]
 
 [[package]]
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@@ -6397,9 +6332,9 @@ name = "yarl"
 version = "1.25.1"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "idna", marker = "sys_platform == 'darwin'" },
-    { name = "multidict", marker = "sys_platform == 'darwin'" },
-    { name = "propcache", marker = "sys_platform == 'darwin'" },
+    { name = "idna" },
+    { name = "multidict" },
+    { name = "propcache" },
 ]
 sdist = { url = "https://files.pythonhosted.org/packages/75/16/e8be8e2fb175bbf41a0680381a319f1199fae256588241a2ac8677eafb49/yarl-1.25.1.tar.gz", hash = "sha256:03dd38de09bc213e9a8b29761eec33ee1d5318dac0e49d8af36e4d27830e23a7", size = 246245, upload-time = "2026-09-15T19:35:02.264Z" }
 wheels = [