diff --git a/mellea/backends/__init__.py b/mellea/backends/__init__.py
index 4a56665a..39ae6d05 100644
--- a/mellea/backends/__init__.py
+++ b/mellea/backends/__init__.py
@@ -3,6 +3,7 @@
 from __future__ import annotations
 
 import abc
+from collections.abc import Sequence
 from typing import TypeVar
 
 import pydantic
@@ -36,12 +37,13 @@ def __init__(
     @abc.abstractmethod
     async def generate_from_context(
         self,
-        action: Component | CBlock,
+        action: Component | CBlock | None,
         ctx: Context,
         *,
         format: type[BaseModelSubclass] | None = None,
         model_options: dict | None = None,
         tool_calls: bool = False,
+        labels: Sequence[str] | None = None,
     ) -> tuple[ModelOutputThunk, Context]:
         """Generates a model output from a context. May not mutate the context. This must be called from a running event loop as it creates a task to run the generation request.
 
@@ -51,6 +53,7 @@ async def generate_from_context(
             format: A response format to used for structured outputs / constrained decoding.
             model_options: Any model options to upsert into the defaults for this call.
             tool_calls: If `True`, then tool calls are extracts from the `action` `Component`. Assumption: if tool_calls is enabled, then the action `Component` has a TemplateRepresentation
+            labels: The labels under which to execute this action.
 
         Returns:
             a tuple of (ModelOutputThunk, Context) where the Context is the new context after the generation has been completed.
diff --git a/mellea/backends/openai.py b/mellea/backends/openai.py
index ba825753..bfe927c8 100644
--- a/mellea/backends/openai.py
+++ b/mellea/backends/openai.py
@@ -6,7 +6,7 @@
 import functools
 import inspect
 import json
-from collections.abc import Callable, Coroutine
+from collections.abc import Callable, Coroutine, Sequence
 from copy import deepcopy
 from enum import Enum
 from typing import TYPE_CHECKING, Any, cast
@@ -286,12 +286,13 @@ def _make_backend_specific_and_remove(
 
     async def generate_from_context(
         self,
-        action: Component | CBlock,
+        action: Component | CBlock | None,
         ctx: Context,
         *,
         format: type[BaseModelSubclass] | None = None,
         model_options: dict | None = None,
         tool_calls: bool = False,
+        labels: Sequence[str] | None = None,
     ):
         """See `generate_from_chat_context`."""
         assert ctx.is_chat_context, NotImplementedError(
@@ -303,18 +304,27 @@ async def generate_from_context(
             _format=format,
             model_options=model_options,
             tool_calls=tool_calls,
+            labels=labels,
         )
 
+        # only add action to context if provided
+        if action is not None:
+            ctx = ctx.add(action, labels=labels)
+
+        # return
+        return mot, ctx.add(mot, labels=labels)
+
     async def generate_from_chat_context(
         self,
-        action: Component | CBlock,
+        action: Component | CBlock | None,
         ctx: Context,
         *,
         _format: type[BaseModelSubclass]
         | None = None,  # Type[BaseModelSubclass] is a class object of a subclass of BaseModel
         model_options: dict | None = None,
         tool_calls: bool = False,
-    ) -> tuple[ModelOutputThunk, Context]:
+        labels: Sequence[str] | None = None,
+    ) -> ModelOutputThunk:
         """Generates a new completion from the provided Context using this backend's `Formatter`."""
         # Requirements can be automatically rerouted to a requirement adapter.
         if isinstance(action, Requirement):
@@ -366,6 +376,7 @@ async def generate_from_chat_context(
             _format=_format,
             model_options=model_options,
             tool_calls=tool_calls,
+            labels=labels,
         )
         return mot, ctx.add(action).add(mot)
 
@@ -564,18 +575,19 @@ def messages_to_docs(msgs: list[Message]) -> list[dict[str, str]]:
 
     async def _generate_from_chat_context_standard(
         self,
-        action: Component | CBlock,
+        action: Component | CBlock | None,
         ctx: Context,
         *,
         _format: type[BaseModelSubclass]
         | None = None,  # Type[BaseModelSubclass] is a class object of a subclass of BaseModel
         model_options: dict | None = None,
         tool_calls: bool = False,
+        labels: Sequence[str] | None = None,
     ) -> ModelOutputThunk:
         model_opts = self._simplify_and_merge(
             model_options, is_chat_context=ctx.is_chat_context
         )
-        linearized_context = ctx.view_for_generation()
+        linearized_context = ctx.view_for_generation(labels=labels)
         assert linearized_context is not None, (
             "Cannot generate from a non-linear context in a FormatterBackend."
         )
@@ -587,6 +599,8 @@ async def _generate_from_chat_context_standard(
                 raise Exception(
                     "The OpenAI backend does not support currently support activated LoRAs."
                 )
+            case None:
+                action = ctx.node_data  # action defaults to node_data if None provided
             case _:
                 messages.extend(self.formatter.to_chat_messages([action]))
         conversation: list[dict] = []
diff --git a/mellea/stdlib/base.py b/mellea/stdlib/base.py
index 111d44f6..b4935660 100644
--- a/mellea/stdlib/base.py
+++ b/mellea/stdlib/base.py
@@ -8,7 +8,7 @@
 import binascii
 import datetime
 import enum
-from collections.abc import Callable, Coroutine, Iterable, Mapping
+from collections.abc import Callable, Coroutine, Iterable, Mapping, Sequence
 from copy import copy, deepcopy
 from dataclasses import dataclass
 from io import BytesIO
@@ -436,18 +436,23 @@ class Context(abc.ABC):
     _data: Component | CBlock | None
     _is_root: bool
     _is_chat_context: bool = True
+    _labels: set[str] | None = None
 
     def __init__(self):
         """Constructs a new root context with no content."""
         self._previous = None
         self._data = None
         self._is_root = True
+        self._labels = set()
 
     # factory functions below this line.
 
     @classmethod
     def from_previous(
-        cls: type[ContextT], previous: Context, data: Component | CBlock
+        cls: type[ContextT],
+        previous: Context,
+        data: Component | CBlock,
+        labels: Sequence[str] | None = None,
     ) -> ContextT:
         """Constructs a new context from an existing context."""
         assert isinstance(previous, Context), (
@@ -460,6 +465,7 @@ def from_previous(
         x._data = data
         x._is_root = False
         x._is_chat_context = previous._is_chat_context
+        x._labels = set(labels) if labels is not None else previous._labels
         return x
 
     @classmethod
@@ -495,9 +501,16 @@ def is_chat_context(self) -> bool:
         """Returns whether this context is a chat context."""
         return self._is_chat_context
 
+    @property
+    def labels(self) -> set[str]:
+        """Returns the list of labels for this context node."""
+        return self._labels
+
     # User functions below this line.
 
-    def as_list(self, last_n_components: int | None = None) -> list[Component | CBlock]:
+    def as_list(
+        self, last_n_components: int | None = None, labels: Sequence[str] | None = None
+    ) -> list[Component | CBlock]:
         """Returns a list of the last n components in the context sorted from FIRST TO LAST.
 
         If `last_n_components` is `None`, then all components are returned.
@@ -505,17 +518,18 @@ def as_list(self, last_n_components: int | None = None) -> list[Component | CBlo
         context_list: list[Component | CBlock] = []
         current_context: Context = self
 
-        last_n_count = 0
         while not current_context.is_root_node and (
-            last_n_components is None or last_n_count < last_n_components
+            last_n_components is None or len(context_list) < last_n_components
         ):
             data = current_context.node_data
             assert data is not None, "Data cannot be None (except for root context)."
             assert data not in context_list, (
                 "There might be a cycle in the context tree. That is not allowed."
             )
-            context_list.append(data)
-            last_n_count += 1
+
+            # append only if no label is specified or label is within allowed label set
+            if labels is None or current_context.labels.intersection(labels):
+                context_list.append(data)
 
             current_context = current_context.previous_node  # type: ignore
             assert current_context is not None, (
@@ -532,19 +546,23 @@ def actions_for_available_tools(self) -> list[Component | CBlock] | None:
         """
         return self.view_for_generation()
 
-    def last_output(self, check_last_n_components: int = 3) -> ModelOutputThunk | None:
+    def last_output(
+        self, check_last_n_components: int = 3, labels: Sequence[str] | None = None
+    ) -> ModelOutputThunk | None:
         """The last output thunk of the context."""
-        for c in self.as_list(last_n_components=check_last_n_components)[::-1]:
+        for c in self.as_list(last_n_components=check_last_n_components, labels=labels)[
+            ::-1
+        ]:
             if isinstance(c, ModelOutputThunk):
                 return c
         return None
 
-    def last_turn(self):
+    def last_turn(self, labels: Sequence[str] | None = None):
         """The last input/output turn of the context.
 
         This can be partial. If the last event is an input, then the output is None.
         """
-        history = self.as_list(last_n_components=2)
+        history = self.as_list(last_n_components=2, labels=labels)
 
         if len(history) == 0:
             return None
@@ -563,13 +581,17 @@ def last_turn(self):
     # Abstract methods below this line.
 
     @abc.abstractmethod
-    def add(self, c: Component | CBlock) -> Context:
+    def add(
+        self, c: Component | CBlock, labels: Sequence[str] | None = None
+    ) -> Context:
         """Returns a new context obtained by adding `c` to this context."""
         # something along ....from_previous(self, c)
         ...
 
     @abc.abstractmethod
-    def view_for_generation(self) -> list[Component | CBlock] | None:
+    def view_for_generation(
+        self, labels: Sequence[str] | None = None
+    ) -> list[Component | CBlock] | None:
         """Provides a linear list of context components to use for generation, or None if that is not possible to construct."""
         ...
 
@@ -582,25 +604,33 @@ def __init__(self, *, window_size: int | None = None):
         super().__init__()
         self._window_size = window_size
 
-    def add(self, c: Component | CBlock) -> ChatContext:
+    def add(
+        self, c: Component | CBlock, labels: Sequence[str] | None = None
+    ) -> ChatContext:
         """Add a new component/cblock to the context. Returns the new context."""
-        new = ChatContext.from_previous(self, c)
+        new = ChatContext.from_previous(self, c, labels=labels)
         new._window_size = self._window_size
         return new
 
-    def view_for_generation(self) -> list[Component | CBlock] | None:
+    def view_for_generation(
+        self, labels: Sequence[str] | None = None
+    ) -> list[Component | CBlock] | None:
         """Returns the context in a linearized form. Uses the window_size set during initialization."""
-        return self.as_list(self._window_size)
+        return self.as_list(self._window_size, labels=labels)
 
 
 class SimpleContext(Context):
     """A `SimpleContext` is a context in which each interaction is a separate and independent turn. The history of all previous turns is NOT saved.."""
 
-    def add(self, c: Component | CBlock) -> SimpleContext:
+    def add(
+        self, c: Component | CBlock, labels: Sequence[str] | None = None
+    ) -> SimpleContext:
         """Add a new component/cblock to the context. Returns the new context."""
-        return SimpleContext.from_previous(self, c)
+        return SimpleContext.from_previous(self, c, labels=labels)
 
-    def view_for_generation(self) -> list[Component | CBlock] | None:
+    def view_for_generation(
+        self, labels: Sequence[str] | None = None
+    ) -> list[Component | CBlock] | None:
         """Returns an empty list."""
         return []
 
diff --git a/mellea/stdlib/functional.py b/mellea/stdlib/functional.py
index e758be04..51bcc0ff 100644
--- a/mellea/stdlib/functional.py
+++ b/mellea/stdlib/functional.py
@@ -3,7 +3,7 @@
 from __future__ import annotations
 
 import asyncio
-from collections.abc import Coroutine
+from collections.abc import Coroutine, Sequence
 from typing import Any, Literal, overload
 
 from PIL import Image as PILImage
@@ -46,6 +46,7 @@ def act(
     format: type[BaseModelSubclass] | None = None,
     model_options: dict | None = None,
     tool_calls: bool = False,
+    labels: Sequence[str] | None = None,
 ) -> tuple[ModelOutputThunk, Context]: ...
 
 
@@ -61,6 +62,7 @@ def act(
     format: type[BaseModelSubclass] | None = None,
     model_options: dict | None = None,
     tool_calls: bool = False,
+    labels: Sequence[str] | None = None,
 ) -> SamplingResult: ...
 
 
@@ -75,6 +77,7 @@ def act(
     format: type[BaseModelSubclass] | None = None,
     model_options: dict | None = None,
     tool_calls: bool = False,
+    labels: Sequence[str] | None = None,
 ) -> tuple[ModelOutputThunk, Context] | SamplingResult:
     """Runs a generic action, and adds both the action and the result to the context.
 
@@ -88,6 +91,7 @@ def act(
         format: if set, the BaseModel to use for constrained decoding.
         model_options: additional model options, which will upsert into the model/backend's defaults.
         tool_calls: if true, tool calling is enabled.
+        labels: if provided, restrict generation to context nodes with matching types.
 
     Returns:
         A (ModelOutputThunk, Context) if `return_sampling_results` is `False`, else returns a `SamplingResult`.
@@ -104,6 +108,7 @@ def act(
             model_options=model_options,
             tool_calls=tool_calls,
             silence_context_type_warning=True,  # We can safely silence this here since it's in a sync function.
+            labels=labels,
         )  # type: ignore[call-overload]
         # Mypy doesn't like the bool for return_sampling_results.
     )
@@ -129,6 +134,7 @@ def instruct(
     format: type[BaseModelSubclass] | None = None,
     model_options: dict | None = None,
     tool_calls: bool = False,
+    labels: Sequence[str] | None = None,
 ) -> tuple[ModelOutputThunk, Context]: ...
 
 
@@ -150,6 +156,7 @@ def instruct(
     format: type[BaseModelSubclass] | None = None,
     model_options: dict | None = None,
     tool_calls: bool = False,
+    labels: Sequence[str] | None = None,
 ) -> SamplingResult: ...
 
 
@@ -170,6 +177,7 @@ def instruct(
     format: type[BaseModelSubclass] | None = None,
     model_options: dict | None = None,
     tool_calls: bool = False,
+    labels: Sequence[str] | None = None,
 ) -> tuple[ModelOutputThunk, Context] | SamplingResult:
     """Generates from an instruction.
 
@@ -189,6 +197,7 @@ def instruct(
         model_options: Additional model options, which will upsert into the model/backend's defaults.
         tool_calls: If true, tool calling is enabled.
         images: A list of images to be used in the instruction or None if none.
+        labels: if provided, restrict generation to context nodes with matching types.
 
     Returns:
         A (ModelOutputThunk, Context) if `return_sampling_results` is `False`, else returns a `SamplingResult`.
@@ -221,6 +230,7 @@ def instruct(
         format=format,
         model_options=model_options,
         tool_calls=tool_calls,
+        labels=labels,
     )  # type: ignore[call-overload]
 
 
@@ -235,6 +245,7 @@ def chat(
     format: type[BaseModelSubclass] | None = None,
     model_options: dict | None = None,
     tool_calls: bool = False,
+    labels: Sequence[str] | None = None,
 ) -> tuple[Message, Context]:
     """Sends a simple chat message and returns the response. Adds both messages to the Context."""
     if user_variables is not None:
@@ -254,6 +265,7 @@ def chat(
         format=format,
         model_options=model_options,
         tool_calls=tool_calls,
+        labels=labels,
     )
     parsed_assistant_message = result.parsed_repr
     assert isinstance(parsed_assistant_message, Message)
@@ -429,6 +441,7 @@ async def aact(
     model_options: dict | None = None,
     tool_calls: bool = False,
     silence_context_type_warning: bool = False,
+    labels: Sequence[str] | None = None,
 ) -> tuple[ModelOutputThunk, Context]: ...
 
 
@@ -445,11 +458,12 @@ async def aact(
     model_options: dict | None = None,
     tool_calls: bool = False,
     silence_context_type_warning: bool = False,
+    labels: Sequence[str] | None = None,
 ) -> SamplingResult: ...
 
 
 async def aact(
-    action: Component,
+    action: Component | None,
     context: Context,
     backend: Backend,
     *,
@@ -460,6 +474,7 @@ async def aact(
     model_options: dict | None = None,
     tool_calls: bool = False,
     silence_context_type_warning: bool = False,
+    labels: Sequence[str] | None = None,
 ) -> tuple[ModelOutputThunk, Context] | SamplingResult:
     """Asynchronous version of .act; runs a generic action, and adds both the action and the result to the context.
 
@@ -474,6 +489,7 @@ async def aact(
         model_options: additional model options, which will upsert into the model/backend's defaults.
         tool_calls: if true, tool calling is enabled.
         silence_context_type_warning: if called directly from an asynchronous function, will log a warning if not using a SimpleContext
+        labels: if provided, restrict generation to context nodes with matching types.
 
     Returns:
         A (ModelOutputThunk, Context) if `return_sampling_results` is `False`, else returns a `SamplingResult`.
@@ -505,6 +521,7 @@ async def aact(
             format=format,
             model_options=model_options,
             tool_calls=tool_calls,
+            labels=labels,
         )
         await result.avalue()
 
@@ -526,6 +543,7 @@ async def aact(
             format=format,
             model_options=model_options,
             tool_calls=tool_calls,
+            labels=labels,
         )
 
         assert sampling_result.sample_generations is not None
@@ -567,6 +585,7 @@ async def ainstruct(
     format: type[BaseModelSubclass] | None = None,
     model_options: dict | None = None,
     tool_calls: bool = False,
+    labels: Sequence[str] | None = None,
 ) -> tuple[ModelOutputThunk, Context]: ...
 
 
@@ -588,6 +607,7 @@ async def ainstruct(
     format: type[BaseModelSubclass] | None = None,
     model_options: dict | None = None,
     tool_calls: bool = False,
+    labels: Sequence[str] | None = None,
 ) -> SamplingResult: ...
 
 
@@ -608,6 +628,7 @@ async def ainstruct(
     format: type[BaseModelSubclass] | None = None,
     model_options: dict | None = None,
     tool_calls: bool = False,
+    labels: Sequence[str] | None = None,
 ) -> tuple[ModelOutputThunk, Context] | SamplingResult:
     """Generates from an instruction.
 
@@ -627,6 +648,7 @@ async def ainstruct(
         model_options: Additional model options, which will upsert into the model/backend's defaults.
         tool_calls: If true, tool calling is enabled.
         images: A list of images to be used in the instruction or None if none.
+        labels: if provided, restrict generation to context nodes with matching types.
 
     Returns:
         A (ModelOutputThunk, Context) if `return_sampling_results` is `False`, else returns a `SamplingResult`.
@@ -659,6 +681,7 @@ async def ainstruct(
         format=format,
         model_options=model_options,
         tool_calls=tool_calls,
+        labels=labels,
     )  # type: ignore[call-overload]
 
 
@@ -673,6 +696,7 @@ async def achat(
     format: type[BaseModelSubclass] | None = None,
     model_options: dict | None = None,
     tool_calls: bool = False,
+    labels: Sequence[str] | None = None,
 ) -> tuple[Message, Context]:
     """Sends a simple chat message and returns the response. Adds both messages to the Context."""
     if user_variables is not None:
@@ -692,6 +716,7 @@ async def achat(
         format=format,
         model_options=model_options,
         tool_calls=tool_calls,
+        labels=labels,
     )
     parsed_assistant_message = result.parsed_repr
     assert isinstance(parsed_assistant_message, Message)
diff --git a/mellea/stdlib/sampling/base.py b/mellea/stdlib/sampling/base.py
index 06401ec4..f403d190 100644
--- a/mellea/stdlib/sampling/base.py
+++ b/mellea/stdlib/sampling/base.py
@@ -1,6 +1,7 @@
 """Base Sampling Strategies."""
 
 import abc
+from collections.abc import Sequence
 from copy import deepcopy
 
 import tqdm
@@ -94,6 +95,7 @@ async def sample(
         model_options: dict | None = None,
         tool_calls: bool = False,
         show_progress: bool = True,
+        labels: Sequence[str] | None = None,
     ) -> SamplingResult:
         """This method performs a sampling operation based on the given instruction.
 
@@ -107,6 +109,7 @@ async def sample(
             model_options: model options to pass to the backend during generation / validation.
             tool_calls: True if tool calls should be used during this sampling strategy.
             show_progress: if true, a tqdm progress bar is used. Otherwise, messages will still be sent to flog.
+            labels: if provided, restrict generation to context nodes with matching set of labels
 
         Returns:
             SamplingResult: A result object indicating the success or failure of the sampling process.
@@ -157,6 +160,7 @@ async def sample(
                 format=format,
                 model_options=model_options,
                 tool_calls=tool_calls,
+                labels=labels,
             )
             await result.avalue()
 
diff --git a/mellea/stdlib/sampling/best_of_n.py b/mellea/stdlib/sampling/best_of_n.py
index be082159..be7a1ee8 100644
--- a/mellea/stdlib/sampling/best_of_n.py
+++ b/mellea/stdlib/sampling/best_of_n.py
@@ -1,5 +1,6 @@
 """Best of N Sampling Strategy."""
 
+from collections.abc import Sequence
 from copy import deepcopy
 
 import tqdm
@@ -29,6 +30,7 @@ async def sample(
         model_options: dict | None = None,
         tool_calls: bool = False,
         show_progress: bool = True,
+        labels: Sequence[str] | None = None,
     ) -> SamplingResult:
         """This method performs a sampling operation based on the given instruction.
 
@@ -42,6 +44,7 @@ async def sample(
             model_options: model options to pass to the backend during generation / validation.
             tool_calls: True if tool calls should be used during this sampling strategy.
             show_progress: if true, a tqdm progress bar is used. Otherwise, messages will still be sent to flog.
+            labels: if provided, restrict generation to context nodes with matching types.
 
         Returns:
             SamplingResult: A result object indicating the success or failure of the sampling process.
@@ -114,6 +117,7 @@ async def sample(
                 format=format,
                 model_options=model_options,
                 tool_calls=tool_calls,
+                labels=labels,
             )
             sampled_results.append(result)
             sampled_actions.append(next_action)
diff --git a/mellea/stdlib/sampling/budget_forcing.py b/mellea/stdlib/sampling/budget_forcing.py
index 692fae66..760b5aee 100644
--- a/mellea/stdlib/sampling/budget_forcing.py
+++ b/mellea/stdlib/sampling/budget_forcing.py
@@ -1,5 +1,6 @@
 """Sampling Strategies for budget forcing generation."""
 
+from collections.abc import Sequence
 from copy import deepcopy
 
 import tqdm
@@ -82,6 +83,7 @@ async def sample(
         model_options: dict | None = None,
         tool_calls: bool = False,
         show_progress: bool = True,
+        labels: Sequence[str] | None = None,
     ) -> SamplingResult:
         """This method performs a sampling operation based on the given instruction.
 
@@ -95,6 +97,7 @@ async def sample(
             model_options: model options to pass to the backend during generation / validation.
             tool_calls: True if tool calls should be used during this sampling strategy.
             show_progress: if true, a tqdm progress bar is used. Otherwise, messages will still be sent to flog.
+            labels: if provided, restrict generation to context nodes with matching types.
 
         Returns:
             SamplingResult: A result object indicating the success or failure of the sampling process.
diff --git a/mellea/stdlib/sampling/majority_voting.py b/mellea/stdlib/sampling/majority_voting.py
index 8ba99798..f4b12719 100644
--- a/mellea/stdlib/sampling/majority_voting.py
+++ b/mellea/stdlib/sampling/majority_voting.py
@@ -2,6 +2,7 @@
 
 import abc
 import asyncio
+from collections.abc import Sequence
 
 import numpy as np
 from math_verify import ExprExtractionConfig, LatexExtractionConfig, parse, verify
@@ -74,6 +75,7 @@ async def sample(
         model_options: dict | None = None,
         tool_calls: bool = False,
         show_progress: bool = True,
+        labels: Sequence[str] | None = None,
     ) -> SamplingResult:
         """Samples using majority voting.
 
@@ -87,6 +89,7 @@ async def sample(
             model_options: model options to pass to the backend during generation / validation.
             tool_calls: True if tool calls should be used during this sampling strategy.
             show_progress: if true, a tqdm progress bar is used. Otherwise, messages will still be sent to flog.
+            labels: if provided, restrict generation to context nodes with matching types.
 
         Returns:
             SamplingResult: A result object indicating the success or failure of the sampling process.
@@ -104,6 +107,7 @@ async def sample(
                     model_options=model_options,
                     tool_calls=tool_calls,
                     show_progress=show_progress,
+                    labels=labels,
                 )
             )
             tasks.append(task)
diff --git a/mellea/stdlib/sampling/types.py b/mellea/stdlib/sampling/types.py
index 391b2c89..a64713df 100644
--- a/mellea/stdlib/sampling/types.py
+++ b/mellea/stdlib/sampling/types.py
@@ -1,6 +1,7 @@
 """Base types for sampling."""
 
 import abc
+from collections.abc import Sequence
 
 from mellea.backends import Backend, BaseModelSubclass
 from mellea.stdlib.base import CBlock, Component, Context, ModelOutputThunk
@@ -95,6 +96,7 @@ async def sample(
         format: type[BaseModelSubclass] | None = None,
         model_options: dict | None = None,
         tool_calls: bool = False,
+        labels: Sequence[str] | None = None,
     ) -> SamplingResult:
         """This method is the abstract method for sampling a given component.
 
@@ -109,6 +111,7 @@ async def sample(
             format: output format for structured outputs.
             model_options: model options to pass to the backend during generation / validation.
             tool_calls: True if tool calls should be used during this sampling strategy.
+            labels: if provided, restrict generation to context nodes with matching types.
 
         Returns:
             SamplingResult: A result object indicating the success or failure of the sampling process.
diff --git a/mellea/stdlib/session.py b/mellea/stdlib/session.py
index 91d1be24..c356a691 100644
--- a/mellea/stdlib/session.py
+++ b/mellea/stdlib/session.py
@@ -4,6 +4,7 @@
 
 import contextvars
 import inspect
+from collections.abc import Sequence
 from copy import copy
 from typing import Any, Literal, overload
 
@@ -237,6 +238,12 @@ def cleanup(self) -> None:
         if hasattr(self.backend, "close"):
             self.backend.close()  # type: ignore
 
+    def append_to_ctx(
+        self, c: Component | CBlock, labels: Sequence[str] | None = None
+    ) -> None:
+        """Adds new component to current context."""
+        self.ctx = self.ctx.add(c, labels=labels)
+
     @overload
     def act(
         self,
@@ -524,7 +531,7 @@ def transform(
     @overload
     async def aact(
         self,
-        action: Component,
+        action: Component | None,
         *,
         requirements: list[Requirement] | None = None,
         strategy: SamplingStrategy | None = RejectionSamplingStrategy(loop_budget=2),
@@ -532,12 +539,13 @@ async def aact(
         format: type[BaseModelSubclass] | None = None,
         model_options: dict | None = None,
         tool_calls: bool = False,
+        labels: Sequence[str] | None = None,
     ) -> ModelOutputThunk: ...
 
     @overload
     async def aact(
         self,
-        action: Component,
+        action: Component | None,
         *,
         requirements: list[Requirement] | None = None,
         strategy: SamplingStrategy | None = RejectionSamplingStrategy(loop_budget=2),
@@ -545,11 +553,12 @@ async def aact(
         format: type[BaseModelSubclass] | None = None,
         model_options: dict | None = None,
         tool_calls: bool = False,
+        labels: Sequence[str] | None = None,
     ) -> SamplingResult: ...
 
     async def aact(
         self,
-        action: Component,
+        action: Component | None,
         *,
         requirements: list[Requirement] | None = None,
         strategy: SamplingStrategy | None = RejectionSamplingStrategy(loop_budget=2),
@@ -557,6 +566,7 @@ async def aact(
         format: type[BaseModelSubclass] | None = None,
         model_options: dict | None = None,
         tool_calls: bool = False,
+        labels: Sequence[str] | None = None,
     ) -> ModelOutputThunk | SamplingResult:
         """Runs a generic action, and adds both the action and the result to the context.
 
@@ -568,6 +578,7 @@ async def aact(
             format: if set, the BaseModel to use for constrained decoding.
             model_options: additional model options, which will upsert into the model/backend's defaults.
             tool_calls: if true, tool calling is enabled.
+            labels: labels to filter on
 
         Returns:
             A ModelOutputThunk if `return_sampling_results` is `False`, else returns a `SamplingResult`.
@@ -582,6 +593,7 @@ async def aact(
             format=format,
             model_options=model_options,
             tool_calls=tool_calls,
+            labels=labels,
         )  # type: ignore
 
         if isinstance(r, SamplingResult):
diff --git a/test/stdlib_basics/test_base_context.py b/test/stdlib_basics/test_base_context.py
index 0c1a5620..46987305 100644
--- a/test/stdlib_basics/test_base_context.py
+++ b/test/stdlib_basics/test_base_context.py
@@ -67,5 +67,22 @@ def test_actions_for_available_tools():
         assert actions[i] == for_generation[i]
 
 
+def test_render_view_for_chat_context_with_labels():
+    ctx = ChatContext(window_size=3)
+    for i in range(5):
+        ctx = ctx.add(CBlock(f"a {i}"), labels=[str(i // 2)])
+
+    # no labels
+    assert len(ctx.as_list()) == 5, "Context size must be 5"
+    assert len(ctx.view_for_generation()) == 3, "Render size must be 3"
+
+    # with explicit labels
+    for labels, al_sz, vg_sz in [(None, 5, 3), ([str(0)], 2, 2), ([str(2)], 1, 1)]:
+        assert len(ctx.as_list(labels=labels)) == al_sz, f"Context size must be {al_sz}"
+        assert len(ctx.view_for_generation(labels=labels)) == vg_sz, (
+            f"Render size must be {vg_sz}"
+        )
+
+
 if __name__ == "__main__":
     pytest.main([__file__])