Agent Run

An AgentRun represents a complete agent run. It contains a collection of Transcript objects, as well as metadata (scores, experiment info, etc.).

In single-agent (most common) settings, each AgentRun contains a single Transcript.
In multi-agent settings, an AgentRun may contain multiple Transcript objects. For example, in a two-agent debate setting, you'll have one Transcript per agent in the same AgentRun.
Docent's LLM search features operate over complete AgentRun objects. Runs are passed to LLMs in their .text form.

Usage

AgentRun objects require a dictionary of Transcript objects, as well as a metadata dictionary whose keys are strings. The metadata should be JSON-serializable.

from docent.data_models import AgentRun, Transcript
from docent.data_models.chat import UserMessage, AssistantMessage

transcripts = [
    Transcript(
        messages=[
            UserMessage(content="Hello, what's 1 + 1?"),
            AssistantMessage(content="2"),
        ]
    )
]

agent_run = AgentRun(
    transcripts=transcripts,
    metadata={
        "scores": {"correct": True, "reward": 1.0},
    }
)

Rendering

To see how your AgentRun is being rendered to an LLM, you can print(agent_run.text). This might be useful for validating that your metadata is being included properly.

docent.data_models.agent_run

AgentRun

Bases: BaseModel

Represents a complete run of an agent with transcripts and metadata.

An AgentRun encapsulates the execution of an agent, storing all communication transcripts and associated metadata. It must contain at least one transcript.

Attributes:

Name	Type	Description
`id`	`str`	Unique identifier for the agent run, auto-generated by default.
`name`	`str \| None`	Optional human-readable name for the agent run.
`description`	`str \| None`	Optional description of the agent run.
`transcripts`	`list[Transcript]`	List of Transcript objects.
`transcript_groups`	`list[TranscriptGroup]`	List of TranscriptGroup objects.
`metadata`	`dict[str, Any]`	Additional structured metadata about the agent run as a JSON-serializable dictionary.

Source code in docent/data_models/agent_run.py

class AgentRun(BaseModel):
    """Represents a complete run of an agent with transcripts and metadata.

    An AgentRun encapsulates the execution of an agent, storing all communication
    transcripts and associated metadata. It must contain at least one transcript.

    Attributes:
        id: Unique identifier for the agent run, auto-generated by default.
        name: Optional human-readable name for the agent run.
        description: Optional description of the agent run.
        transcripts: List of Transcript objects.
        transcript_groups: List of TranscriptGroup objects.
        metadata: Additional structured metadata about the agent run as a JSON-serializable dictionary.
    """

    id: str = Field(default_factory=lambda: str(uuid4()))
    name: str | None = None
    description: str | None = None

    transcripts: list[Transcript]
    transcript_groups: list[TranscriptGroup] = Field(default_factory=list)
    metadata: dict[str, Any] = Field(default_factory=dict)

    ##############
    # Validators #
    ##############

    @field_validator("transcripts", mode="before")
    @classmethod
    def _validate_transcripts_type(cls, v: Any) -> Any:
        if isinstance(v, dict):
            logger.warning(
                "dict[str, Transcript] for transcripts is deprecated. Use list[Transcript] instead."
            )
            v = cast(dict[str, Transcript], v)
            return [Transcript.model_validate(t) for t in v.values()]
        return v

    @field_validator("transcript_groups", mode="before")
    @classmethod
    def _validate_transcript_groups_type(cls, v: Any) -> Any:
        if isinstance(v, dict):
            logger.warning(
                "dict[str, TranscriptGroup] for transcript_groups is deprecated. Use list[TranscriptGroup] instead."
            )
            v = cast(dict[str, TranscriptGroup], v)
            return [TranscriptGroup.model_validate(tg) for tg in v.values()]
        return v

    @model_validator(mode="after")
    def _validate_transcripts_not_empty(self):
        """Validates that the agent run contains at least one transcript.

        Raises:
            ValueError: If the transcripts list is empty.

        Returns:
            AgentRun: The validated AgentRun instance.
        """
        if len(self.transcripts) == 0:
            raise ValueError("AgentRun must have at least one transcript")
        return self

    @property
    def transcript_dict(self) -> dict[str, Transcript]:
        """Returns a dictionary mapping transcript IDs to Transcript objects."""
        return {t.id: t for t in self.transcripts}

    @property
    def transcript_group_dict(self) -> dict[str, TranscriptGroup]:
        """Returns a dictionary mapping transcript group IDs to TranscriptGroup objects."""
        return {tg.id: tg for tg in self.transcript_groups}

    def to_text(
        self,
        children_text: str,
        agent_run_alias: int | str = 0,
        indent: int = 0,
        render_metadata: bool = True,
        agent_run_metadata_comments: list[Comment] | None = None,
    ) -> str:
        if not isinstance(agent_run_alias, str):
            agent_run_alias = f"R{agent_run_alias}"

        if render_metadata:
            metadata_text = dump_metadata(self.metadata)
            if metadata_text is not None:
                if indent > 0:
                    metadata_text = textwrap.indent(metadata_text, " " * indent)
                metadata_alias = f"{agent_run_alias}M"
                children_text += f"\n<|agent run metadata {metadata_alias}|>\n{metadata_text}\n</|agent run metadata {metadata_alias}|>"

            # Add agent run metadata comments right underneath the metadata block
            if agent_run_metadata_comments:
                metadata_comments_text = render_metadata_comments(agent_run_metadata_comments)
                if metadata_comments_text:
                    if indent > 0:
                        metadata_comments_text = textwrap.indent(
                            metadata_comments_text, " " * indent
                        )
                    children_text += f"\n<|agent run metadata comments|>\n{metadata_comments_text}\n</|agent run metadata comments|>"

        if indent > 0:
            children_text = textwrap.indent(children_text, " " * indent)

        return (
            f"<|agent run {agent_run_alias}|>\n{children_text}\n</|agent run {agent_run_alias}|>\n"
        )

transcript_dict `property`

transcript_dict: dict[str, Transcript]

Returns a dictionary mapping transcript IDs to Transcript objects.

transcript_group_dict `property`

transcript_group_dict: dict[str, TranscriptGroup]

Returns a dictionary mapping transcript group IDs to TranscriptGroup objects.

AgentRunTree

Bases: BaseModel

Source code in docent/data_models/agent_run.py

class AgentRunTree(BaseModel):
    nodes: dict[str, AgentRunTreeNode]
    transcript_id_to_idx: dict[str, int]
    parent_map: dict[str, str]  # child_id -> parent_id

    @property
    def nodes_pruned(self):
        return self._prune_transcriptless_nodes(self.nodes)

    @classmethod
    def from_agent_run(cls, agent_run: AgentRun) -> AgentRunTree:
        t_dict = agent_run.transcript_dict
        tg_dict = agent_run.transcript_group_dict

        # Init tree and add the root AgentRun node
        nodes: dict[str, AgentRunTreeNode] = {
            GLOBAL_ROOT_ID: AgentRunTreeNode(
                id=GLOBAL_ROOT_ID,
                node_type=NodeType.AGENT_RUN,
                children_ids=[],
            )
        }
        parent_map: dict[str, str] = {}

        # Add all transcript groups to the tree
        for tg_id, tg in tg_dict.items():
            # Add this tg
            if tg_id not in nodes:
                nodes[tg_id] = AgentRunTreeNode(
                    id=tg_id,
                    node_type=NodeType.TRANSCRIPT_GROUP,
                    children_ids=[],
                )
            # Add parent and mark the relationship
            # If the stated ID is None, then it's the global root
            par_id = tg.parent_transcript_group_id or GLOBAL_ROOT_ID
            if par_id not in nodes:
                nodes[par_id] = AgentRunTreeNode(
                    id=par_id,
                    node_type=(
                        NodeType.AGENT_RUN
                        if par_id == GLOBAL_ROOT_ID
                        else NodeType.TRANSCRIPT_GROUP
                    ),
                    children_ids=[],
                )
            nodes[par_id].children_ids.append(tg_id)
            parent_map[tg_id] = par_id

        # Now add all the transcripts
        for t_id, t in t_dict.items():
            # Add this transcript
            nodes[t_id] = AgentRunTreeNode(
                id=t_id,
                node_type=NodeType.TRANSCRIPT,
                children_ids=[],
            )
            # Mark parent relationship
            par_id = t.transcript_group_id or GLOBAL_ROOT_ID
            # This should never happen, but check anyways for safety; fallback to global root
            if par_id not in nodes:
                logger.error(
                    f"Parent {par_id} not found for transcript {t_id}. Assigning to global root as a fallback"
                )
                par_id = GLOBAL_ROOT_ID
            nodes[par_id].children_ids.append(t_id)
            parent_map[t_id] = par_id

        # Go through each node and sort its children by created_at timestamp
        def _cmp(obj_id: str) -> datetime:
            obj_type = nodes[obj_id].node_type
            if obj_type == NodeType.TRANSCRIPT_GROUP:
                # This should never happen, but check anyways for safety
                if obj_id not in tg_dict:
                    logger.error(f"Transcript group {obj_id} not found")
                    return datetime.max
                return tg_dict[obj_id].created_at or datetime.max
            elif obj_type == NodeType.TRANSCRIPT:
                # This should never happen, but check anyways for safety
                if obj_id not in t_dict:
                    logger.error(f"Transcript {obj_id} not found")
                    return datetime.max
                return t_dict[obj_id].created_at or datetime.max
            else:
                raise ValueError(f"Unknown node type: {obj_type}")

        for node in nodes.values():
            node.children_ids = sorted(node.children_ids, key=_cmp)

        # Combined DFS: mark has_transcript_in_subtree and assign transcript indices
        t_id_to_idx: dict[str, int] = {}

        def _dfs(u_id: str, next_idx: int) -> tuple[bool, int]:
            """Mark has_transcript_in_subtree and assign indices in a single traversal.

            Returns (contains_transcript, next_idx_after).
            """
            node = nodes.get(u_id)
            if node is None:
                return False, next_idx

            if node.node_type == NodeType.TRANSCRIPT:
                # Leaf node: assign index immediately (pre-order)
                t_id_to_idx[u_id] = next_idx
                node.has_transcript_in_subtree = True
                return True, next_idx + 1

            # Non-transcript node: recurse into children
            contains_transcript = False
            for child_id in node.children_ids:
                child_contains, next_idx = _dfs(child_id, next_idx)
                contains_transcript = contains_transcript or child_contains

            node.has_transcript_in_subtree = contains_transcript
            return contains_transcript, next_idx

        _dfs(GLOBAL_ROOT_ID, 0)

        return cls(nodes=nodes, transcript_id_to_idx=t_id_to_idx, parent_map=parent_map)

    def _prune_transcriptless_nodes(self, nodes: dict[str, AgentRunTreeNode]):
        """Return a view of the canonical tree that only includes transcript-bearing branches."""
        return {
            node_id: node
            for node_id, node in nodes.items()
            if node.has_transcript_in_subtree or node_id == GLOBAL_ROOT_ID
        }

SelectionSpec

Bases: BaseModel

Source code in docent/data_models/agent_run.py

class SelectionSpec(BaseModel):
    nodes: dict[str, SelectionSpecNode]

    @classmethod
    def from_agent_run_tree(cls, agent_run_tree: AgentRunTree) -> SelectionSpec:
        return cls(
            nodes={
                node_id: SelectionSpecNode(node_id=node_id)
                for node_id in agent_run_tree.nodes.keys()
            }
        )

    def is_default(self) -> bool:
        """Return True if all nodes have default settings (show everything)."""
        return all(
            node.render_children_default is True
            and len(node.render_children_overrides) == 0
            and node.render_self_metadata is True
            for node in self.nodes.values()
        )

is_default

is_default() -> bool

Return True if all nodes have default settings (show everything).

Source code in docent/data_models/agent_run.py

def is_default(self) -> bool:
    """Return True if all nodes have default settings (show everything)."""
    return all(
        node.render_children_default is True
        and len(node.render_children_overrides) == 0
        and node.render_self_metadata is True
        for node in self.nodes.values()
    )

AgentRunView

Source code in docent/data_models/agent_run.py

class AgentRunView:
    def __init__(
        self,
        agent_run: AgentRun,
        selection_spec: SelectionSpec | None = None,
        comments: list[Comment] | None = None,
    ):
        self.agent_run = agent_run
        self._cached_tree: AgentRunTree | None = None
        if selection_spec is None:
            self.selection_spec = SelectionSpec.from_agent_run_tree(self.tree)
        else:
            self.selection_spec = selection_spec
        self.comments = comments

        # We also need to build an index of which comments belong to each location
        # There are 4 types of comments: AR metadata, transcript metadata, message metadata, and message content metadata
        # TODO(mengk): there's quite a bit of data duplication here

        # agent_run_id -> ...
        self._agent_run_metadata_comment_index: dict[str, list[Comment]] = {}
        # transcript_id -> ...
        self._transcript_metadata_comment_index: dict[str, list[Comment]] = {}
        # (transcript_id, block_idx) -> ...
        self._block_metadata_comment_index: dict[tuple[str, int], list[Comment]] = {}
        # (transcript_id, block_idx) -> ...
        self._block_content_comment_index: dict[tuple[str, int], list[Comment]] = {}

        for comment in self.comments or []:
            for citation in comment.citations:
                citation_item = citation.target.item
                if isinstance(citation_item, AgentRunMetadataItem):
                    self._agent_run_metadata_comment_index.setdefault(
                        citation_item.agent_run_id, []
                    ).append(comment)
                elif isinstance(citation_item, TranscriptMetadataItem):
                    self._transcript_metadata_comment_index.setdefault(
                        citation_item.transcript_id, []
                    ).append(comment)
                elif isinstance(citation_item, TranscriptBlockMetadataItem):
                    self._block_metadata_comment_index.setdefault(
                        (citation_item.transcript_id, citation_item.block_idx), []
                    ).append(comment)
                else:
                    # Must be TranscriptBlockContentItem
                    self._block_content_comment_index.setdefault(
                        (citation_item.transcript_id, citation_item.block_idx), []
                    ).append(comment)

    @property
    def tree(self) -> AgentRunTree:
        if self._cached_tree is None:
            self._cached_tree = AgentRunTree.from_agent_run(self.agent_run)
        return self._cached_tree

    @classmethod
    def from_agent_run(
        cls, agent_run: AgentRun, comments: list[Comment] | None = None
    ) -> AgentRunView:
        return cls(agent_run=agent_run, comments=comments)

    def to_dict(self) -> dict[str, Any]:
        """Serialize the view for storage. Omits selection_spec if it's default."""
        return {
            "agent_run_id": self.agent_run.id,
            "selection_spec": (
                None
                if self.selection_spec.is_default()
                else self.selection_spec.model_dump(mode="json")
            ),
        }

    @classmethod
    def from_dict(cls, data: dict[str, Any], agent_run: AgentRun) -> AgentRunView:
        """Reconstruct a view from serialized data and an AgentRun."""
        spec_data = data.get("selection_spec")
        if spec_data is None:
            return cls(agent_run=agent_run)
        else:
            selection_spec = SelectionSpec.model_validate(spec_data)
            return cls(agent_run=agent_run, selection_spec=selection_spec)

    #######################
    # Core text rendering #
    #######################

    def to_text(
        self,
        agent_run_alias: int | str = 0,
        t_idx_map: dict[str, int] | None = None,
        indent: int = 0,
        full_tree: bool = False,
    ):
        ar_tree_nodes = self.tree.nodes if full_tree else self.tree.nodes_pruned
        if t_idx_map is None:
            t_idx_map = self.tree.transcript_id_to_idx
        t_dict = self.agent_run.transcript_dict
        tg_dict = self.agent_run.transcript_group_dict

        # Traverse the tree and render the string
        def _recurse(u_id: str) -> str:
            if (u := ar_tree_nodes.get(u_id)) is None:
                return ""

            children_texts: list[str] = []
            for v_id in u.children_ids:
                # Check if this child should be rendered
                if not self.should_render_child(u_id, v_id):
                    continue

                # Get the node object
                if (v := ar_tree_nodes.get(v_id)) is None:
                    continue

                # Casework on the node type
                if v.node_type == NodeType.TRANSCRIPT_GROUP:
                    children_texts.append(_recurse(v_id))
                elif v.node_type == NodeType.TRANSCRIPT:
                    # Gather comments for this transcript
                    transcript_metadata_comments = self._transcript_metadata_comment_index.get(v_id)
                    block_metadata_comments = {
                        block_idx: comments
                        for (
                            t_id,
                            block_idx,
                        ), comments in self._block_metadata_comment_index.items()
                        if t_id == v_id
                    } or None
                    block_content_comments = {
                        block_idx: comments
                        for (t_id, block_idx), comments in self._block_content_comment_index.items()
                        if t_id == v_id
                    } or None
                    cur_text = t_dict[v_id].to_text(
                        transcript_alias=t_idx_map[v_id],
                        indent=indent,
                        render_metadata=self.should_render_metadata(v_id),
                        transcript_metadata_comments=transcript_metadata_comments,
                        block_metadata_comments=block_metadata_comments,
                        block_content_comments=block_content_comments,
                    )
                    children_texts.append(cur_text)
                else:
                    raise ValueError(f"Unknown node type: {v.node_type}")
            children_text = "\n".join(children_texts)

            # No wrapper for global root
            if u_id == GLOBAL_ROOT_ID:
                # Get agent run metadata comments
                agent_run_metadata_comments = self._agent_run_metadata_comment_index.get(
                    self.agent_run.id
                )
                return self.agent_run.to_text(
                    children_text,
                    agent_run_alias=agent_run_alias,
                    indent=indent,
                    render_metadata=self.should_render_metadata(GLOBAL_ROOT_ID),
                    agent_run_metadata_comments=agent_run_metadata_comments,
                )
            # Delegate rendering to TranscriptGroup
            else:
                tg = tg_dict[u_id]
                return tg.to_text(
                    children_text=children_text,
                    indent=indent,
                    render_metadata=self.should_render_metadata(u_id),
                )

        return _recurse(GLOBAL_ROOT_ID)

    #################
    # Query methods #
    #################

    def should_render_child(self, parent_id: str, child_id: str) -> bool:
        """Determine if a child should be rendered based on parent's render settings."""
        # Default to rendering if no spec
        if (parent_spec := self.selection_spec.nodes.get(parent_id)) is None:
            return True

        # Default include: render all except those in overrides
        if parent_spec.render_children_default:
            return child_id not in parent_spec.render_children_overrides
        # Default exclude: render only those in overrides
        else:
            return child_id in parent_spec.render_children_overrides

    def should_render_metadata(self, node_id: str) -> bool:
        """Determine if a node's metadata should be rendered."""
        # Default to rendering if no spec
        if (node_spec := self.selection_spec.nodes.get(node_id)) is None:
            return True
        return node_spec.render_self_metadata

    #########################################
    # Show/hide parts of the canonical tree #
    #########################################

    def set_metadata_selection(self, node_id: str, selected: bool) -> None:
        """Set whether a node's metadata is rendered.

        When enabling (True), this also ensures the path from the root to this
        node is visible by adjusting parent render settings.

        Args:
            node_id: The ID of the node to modify.
            selected: Whether the node's metadata should be rendered.
        """
        if (spec := self.selection_spec.nodes.get(node_id)) is not None:
            spec.render_self_metadata = selected
            if selected:
                self._ensure_path_to_root_selected(node_id)

    def set_node_selection(self, node_id: str, selected: bool) -> None:
        """Set whether a node and its descendants are rendered.

        This recursively sets children selection state for all descendants.
        When enabling (True), this also ensures the path from the root to this
        node is visible by adjusting parent render settings.
        When disabling (False), this ensures the parent excludes this node.

        Notably, this does _not_ affect the metadata rendering state of each node.

        Args:
            node_id: The ID of the node to modify.
            selected: Whether the node and its descendants should be rendered.
        """
        self._set_children_selected_recursive(node_id, selected=selected)

        if selected:
            self._ensure_path_to_root_selected(node_id)
        else:
            self._ensure_node_excluded_from_parent(node_id)

    def _set_children_selected_recursive(self, node_id: str, selected: bool) -> None:
        """Recursively set children selection state for a node and all its descendants."""
        if (node := self.tree.nodes.get(node_id)) is None:
            return
        if (spec := self.selection_spec.nodes.get(node_id)) is None:
            return

        spec.render_children_default = selected
        spec.render_children_overrides.clear()

        for child_id in node.children_ids:
            self._set_children_selected_recursive(child_id, selected=selected)

    def _get_parent_id(self, node_id: str) -> str | None:
        """Get the parent ID for a node, or None if it's the root or not found."""
        # The root node has no parent
        if node_id == GLOBAL_ROOT_ID:
            return None
        return self.tree.parent_map.get(node_id)

    def _set_parent_renders_child(self, parent_id: str, child_id: str, renders: bool) -> None:
        """Update parent's overrides so that it renders (or doesn't render) the child."""
        if (parent_spec := self.selection_spec.nodes.get(parent_id)) is None:
            return
        if renders == parent_spec.render_children_default:
            parent_spec.render_children_overrides.discard(child_id)
        else:
            parent_spec.render_children_overrides.add(child_id)

    def _ensure_path_to_root_selected(self, node_id: str) -> None:
        """Traverse from node_id up to root, ensuring each parent renders its child."""
        u_id = node_id
        while (parent_id := self._get_parent_id(u_id)) is not None:
            self._set_parent_renders_child(parent_id, u_id, renders=True)
            u_id = parent_id

    def _ensure_node_excluded_from_parent(self, node_id: str) -> None:
        """Ensure the parent does not render this node."""
        if (parent_id := self._get_parent_id(node_id)) is not None:
            self._set_parent_renders_child(parent_id, node_id, renders=False)

to_dict

to_dict() -> dict[str, Any]

Serialize the view for storage. Omits selection_spec if it's default.

Source code in docent/data_models/agent_run.py

def to_dict(self) -> dict[str, Any]:
    """Serialize the view for storage. Omits selection_spec if it's default."""
    return {
        "agent_run_id": self.agent_run.id,
        "selection_spec": (
            None
            if self.selection_spec.is_default()
            else self.selection_spec.model_dump(mode="json")
        ),
    }

from_dict `classmethod`

from_dict(data: dict[str, Any], agent_run: AgentRun) -> AgentRunView

Reconstruct a view from serialized data and an AgentRun.

Source code in docent/data_models/agent_run.py

@classmethod
def from_dict(cls, data: dict[str, Any], agent_run: AgentRun) -> AgentRunView:
    """Reconstruct a view from serialized data and an AgentRun."""
    spec_data = data.get("selection_spec")
    if spec_data is None:
        return cls(agent_run=agent_run)
    else:
        selection_spec = SelectionSpec.model_validate(spec_data)
        return cls(agent_run=agent_run, selection_spec=selection_spec)

should_render_child

should_render_child(parent_id: str, child_id: str) -> bool

Determine if a child should be rendered based on parent's render settings.

Source code in docent/data_models/agent_run.py

def should_render_child(self, parent_id: str, child_id: str) -> bool:
    """Determine if a child should be rendered based on parent's render settings."""
    # Default to rendering if no spec
    if (parent_spec := self.selection_spec.nodes.get(parent_id)) is None:
        return True

    # Default include: render all except those in overrides
    if parent_spec.render_children_default:
        return child_id not in parent_spec.render_children_overrides
    # Default exclude: render only those in overrides
    else:
        return child_id in parent_spec.render_children_overrides

should_render_metadata

should_render_metadata(node_id: str) -> bool

Determine if a node's metadata should be rendered.

Source code in docent/data_models/agent_run.py

def should_render_metadata(self, node_id: str) -> bool:
    """Determine if a node's metadata should be rendered."""
    # Default to rendering if no spec
    if (node_spec := self.selection_spec.nodes.get(node_id)) is None:
        return True
    return node_spec.render_self_metadata

set_metadata_selection

set_metadata_selection(node_id: str, selected: bool) -> None

Set whether a node's metadata is rendered.

When enabling (True), this also ensures the path from the root to this node is visible by adjusting parent render settings.

Parameters:

Name	Type	Description	Default
`node_id`	`str`	The ID of the node to modify.	required
`selected`	`bool`	Whether the node's metadata should be rendered.	required

Source code in docent/data_models/agent_run.py

def set_metadata_selection(self, node_id: str, selected: bool) -> None:
    """Set whether a node's metadata is rendered.

    When enabling (True), this also ensures the path from the root to this
    node is visible by adjusting parent render settings.

    Args:
        node_id: The ID of the node to modify.
        selected: Whether the node's metadata should be rendered.
    """
    if (spec := self.selection_spec.nodes.get(node_id)) is not None:
        spec.render_self_metadata = selected
        if selected:
            self._ensure_path_to_root_selected(node_id)

set_node_selection

set_node_selection(node_id: str, selected: bool) -> None

Set whether a node and its descendants are rendered.

This recursively sets children selection state for all descendants. When enabling (True), this also ensures the path from the root to this node is visible by adjusting parent render settings. When disabling (False), this ensures the parent excludes this node.

Notably, this does not affect the metadata rendering state of each node.

Parameters:

Name	Type	Description	Default
`node_id`	`str`	The ID of the node to modify.	required
`selected`	`bool`	Whether the node and its descendants should be rendered.	required

Source code in docent/data_models/agent_run.py

def set_node_selection(self, node_id: str, selected: bool) -> None:
    """Set whether a node and its descendants are rendered.

    This recursively sets children selection state for all descendants.
    When enabling (True), this also ensures the path from the root to this
    node is visible by adjusting parent render settings.
    When disabling (False), this ensures the parent excludes this node.

    Notably, this does _not_ affect the metadata rendering state of each node.

    Args:
        node_id: The ID of the node to modify.
        selected: Whether the node and its descendants should be rendered.
    """
    self._set_children_selected_recursive(node_id, selected=selected)

    if selected:
        self._ensure_path_to_root_selected(node_id)
    else:
        self._ensure_node_excluded_from_parent(node_id)

Agent Run

Usage

Rendering

docent.data_models.agent_run

AgentRun

transcript_dict property

transcript_group_dict property

AgentRunTree

SelectionSpec

is_default

AgentRunView

to_dict

from_dict classmethod

should_render_child

should_render_metadata

set_metadata_selection

set_node_selection

transcript_dict `property`

transcript_group_dict `property`

from_dict `classmethod`