python-client: resume a conversation

src/gradient_labs/_conversation_assign.py

@@ -31,7 +31,7 @@ class AssignmentParams:
 def assign_conversation(
     *, client: HttpClient, conversation_id: str, params: AssignmentParams
 ) -> None:
-    """run assigns a conversation to a participant."""
+    """assigns a conversation to a participant."""
     body = {"assignee_type": params.participant_type.value}
     if params.assignee_id:
         body["assignee_id"] = params.assignee_id

src/gradient_labs/_conversation_resume.py

@@ -0,0 +1,44 @@
+from typing import Optional
+from datetime import datetime
+
+from dataclasses import dataclass
+from dataclasses_json import dataclass_json
+
+from ._http_client import HttpClient
+from .conversation import ParticipantType
+
+
+@dataclass_json
+@dataclass(frozen=True)
+class ResumeParams:
+    # assignee_type identifies the type of participant that this conversation is
+    # being assigned to. Set this to ParticipantTypeAIAgent to assign the conversation
+    # to the Gradient Labs AI agent.
+    assignee_type: ParticipantType
+
+    # assignee_id optionally identifies the specific user that the conversation
+    # is being assigned to.
+    assignee_id: Optional[str] = None
+
+    # Timestamp optionally defines the time when the conversation was assigned.
+    # If not given, this will default to the current time.
+    timestamp: Optional[datetime] = None
+
+    # reason optionally allows you to describe why this assignment is happening.
+    reason: Optional[str] = None
+
+
+def resume_conversation(
+    *, client: HttpClient, conversation_id: str, params: ResumeParams
+) -> None:
+    """resume_conversation re-opens a conversation that was previously finished."""
+    body = {"assignee_type": params.participant_type.value}
+    if params.assignee_id:
+        body["assignee_id"] = params.assignee_id
+    if params.timestamp:
+        body["timestamp"] = HttpClient.localize(params.timestamp)
+
+    _ = client.put(
+        path=f"conversations/{conversation_id}/resume",
+        body=params.to_dict(),
+    )

src/gradient_labs/client.py

@@ -13,6 +13,7 @@
 from ._conversation_event import add_conversation_event, EventParams
 from ._conversation_finish import finish_conversation, FinishParams
 from ._conversation_rate import rate_conversation, RatingParams
+from ._conversation_resume import resume_conversation, ResumeParams
 from ._conversation_read import read_conversation, ReadParams
 from ._conversation_start import start_conversation, StartConversationParams
 
@@ -158,6 +159,14 @@ def rate_conversation(self, *, conversation_id: str, params: RatingParams) -> No
             params=params,
         )
 
+    def resume_conversation(self, *, conversation_id: str, params: ResumeParams) -> None:
+        """resume_conversation re-opens a conversation that was previously finished."""
+        resume_conversation(
+            client=self.http_client,
+            conversation_id=conversation_id,
+            params=params,
+        )
+
     def read_conversation(
         self, *, conversation_id: str, params: ReadParams
     ) -> Conversation: