Merge b5a360be39 into d7ad3ba699

* Implement tool call history keeping

* Refactor to match single message implementation

* Simplify data representation

* Cleanup chat page rendering

* Include system message to not break cache

* Formatting

* Update tests and update .gitignore

frigate/api/chat.py

@@ -7,7 +7,7 @@ import operator
 import time
 from datetime import datetime
 from functools import reduce
-from typing import Any, Dict, List, Optional
+from typing import Any, Optional
 
 import cv2
 from fastapi import APIRouter, Body, Depends, HTTPException, Request
@@ -59,7 +59,7 @@ class ToolExecuteRequest(BaseModel):
     """Request model for tool execution."""
 
     tool_name: str
-    arguments: Dict[str, Any]
+    arguments: dict[str, Any]
 
 
 class VLMMonitorRequest(BaseModel):
@@ -68,8 +68,8 @@ class VLMMonitorRequest(BaseModel):
     camera: str
     condition: str
     max_duration_minutes: int = 60
-    labels: List[str] = []
-    zones: List[str] = []
+    labels: list[str] = []
+    zones: list[str] = []
 
 
 @router.get(
@@ -91,10 +91,10 @@ def get_tools(request: Request) -> JSONResponse:
 
 
 def _resolve_zones(
-    zones: List[str],
+    zones: list[str],
     config: FrigateConfig,
-    target_cameras: List[str],
-) -> List[str]:
+    target_cameras: list[str],
+) -> list[str]:
     """Map zone names to their canonical config keys, case-insensitively.
 
     LLMs frequently echo a user's casing ("Front Yard") instead of the
@@ -107,7 +107,7 @@ def _resolve_zones(
     if not zones:
         return zones
 
-    lookup: Dict[str, str] = {}
+    lookup: dict[str, str] = {}
     for camera_id in target_cameras:
         camera_config = config.cameras.get(camera_id)
         if camera_config is None:
@@ -120,8 +120,8 @@ def _resolve_zones(
 
 async def _execute_search_objects(
     request: Request,
-    arguments: Dict[str, Any],
-    allowed_cameras: List[str],
+    arguments: dict[str, Any],
+    allowed_cameras: list[str],
 ) -> JSONResponse:
     """
     Execute the search_objects tool.
@@ -213,8 +213,8 @@ async def _execute_search_objects(
 
 async def _execute_search_objects_semantic(
     request: Request,
-    arguments: Dict[str, Any],
-    allowed_cameras: List[str],
+    arguments: dict[str, Any],
+    allowed_cameras: list[str],
     semantic_query: str,
 ) -> JSONResponse:
     """Search objects via fused thumbnail + description embeddings.
@@ -263,8 +263,8 @@ async def _execute_search_objects_semantic(
     limit = int(arguments.get("limit", 25))
     limit = max(1, min(limit, 100))
 
-    visual_distances: Dict[str, float] = {}
-    description_distances: Dict[str, float] = {}
+    visual_distances: dict[str, float] = {}
+    description_distances: dict[str, float] = {}
     try:
         rows = context.search_thumbnail(semantic_query)
         visual_distances = {row[0]: row[1] for row in rows}
@@ -305,7 +305,7 @@ async def _execute_search_objects_semantic(
 
     eligible = {e.id: e for e in Event.select().where(reduce(operator.and_, clauses))}
 
-    scored: List[tuple[str, float]] = []
+    scored: list[tuple[str, float]] = []
     for eid in eligible:
         v_score = (
             distance_to_score(visual_distances[eid], context.thumb_stats)
@@ -331,9 +331,9 @@ async def _execute_search_objects_semantic(
 
 async def _execute_find_similar_objects(
     request: Request,
-    arguments: Dict[str, Any],
-    allowed_cameras: List[str],
-) -> Dict[str, Any]:
+    arguments: dict[str, Any],
+    allowed_cameras: list[str],
+) -> dict[str, Any]:
     """Execute the find_similar_objects tool.
 
     Returns a plain dict (not JSONResponse) so the chat loop can embed it
@@ -403,8 +403,8 @@ async def _execute_find_similar_objects(
     # version (see frigate/embeddings/__init__.py). Mirror the pattern used by
     # frigate/api/event.py events_search: fetch top-k globally, then intersect
     # with the structured filters via Peewee.
-    visual_distances: Dict[str, float] = {}
-    description_distances: Dict[str, float] = {}
+    visual_distances: dict[str, float] = {}
+    description_distances: dict[str, float] = {}
 
     try:
         if similarity_mode in ("visual", "fused"):
@@ -462,7 +462,7 @@ async def _execute_find_similar_objects(
     eligible = {e.id: e for e in Event.select().where(reduce(operator.and_, clauses))}
 
     # 6. Fuse and rank.
-    scored: List[tuple[str, float]] = []
+    scored: list[tuple[str, float]] = []
     for eid in eligible:
         v_score = (
             distance_to_score(visual_distances[eid], context.thumb_stats)
@@ -503,7 +503,7 @@ async def _execute_find_similar_objects(
 async def execute_tool(
     request: Request,
     body: ToolExecuteRequest = Body(...),
-    allowed_cameras: List[str] = Depends(get_allowed_cameras_for_filter),
+    allowed_cameras: list[str] = Depends(get_allowed_cameras_for_filter),
 ) -> JSONResponse:
     """
     Execute a tool function call.
@@ -545,8 +545,8 @@ async def execute_tool(
 async def _execute_get_live_context(
     request: Request,
     camera: str,
-    allowed_cameras: List[str],
-) -> Dict[str, Any]:
+    allowed_cameras: list[str],
+) -> dict[str, Any]:
     # Reject wildcards explicitly so models retry with a real camera name
     # instead of silently fanning out across every camera.
     if camera in ("*", "all"):
@@ -593,7 +593,7 @@ async def _execute_get_live_context(
                     "stationary": obj_dict.get("stationary", False),
                 }
 
-        result: Dict[str, Any] = {
+        result: dict[str, Any] = {
             "camera": camera,
             "timestamp": frame_time,
             "detections": list(tracked_objects_dict.values()),
@@ -620,7 +620,7 @@ async def _execute_get_live_context(
 async def _get_live_frame_image_url(
     request: Request,
     camera: str,
-    allowed_cameras: List[str],
+    allowed_cameras: list[str],
 ) -> Optional[str]:
     """
     Fetch the current live frame for a camera as a base64 data URL.
@@ -659,8 +659,8 @@ async def _get_live_frame_image_url(
 
 async def _execute_set_camera_state(
     request: Request,
-    arguments: Dict[str, Any],
-) -> Dict[str, Any]:
+    arguments: dict[str, Any],
+) -> dict[str, Any]:
     role = request.headers.get("remote-role", "")
     if "admin" not in [r.strip() for r in role.split(",")]:
         return {"error": "Admin privileges required to change camera settings."}
@@ -699,10 +699,10 @@ async def _execute_set_camera_state(
 
 async def _execute_tool_internal(
     tool_name: str,
-    arguments: Dict[str, Any],
+    arguments: dict[str, Any],
     request: Request,
-    allowed_cameras: List[str],
-) -> Dict[str, Any]:
+    allowed_cameras: list[str],
+) -> dict[str, Any]:
     """
     Internal helper to execute a tool and return the result as a dict.
 
@@ -763,8 +763,8 @@ async def _execute_tool_internal(
 
 async def _execute_start_camera_watch(
     request: Request,
-    arguments: Dict[str, Any],
-) -> Dict[str, Any]:
+    arguments: dict[str, Any],
+) -> dict[str, Any]:
     camera = arguments.get("camera", "").strip()
     condition = arguments.get("condition", "").strip()
     max_duration_minutes = int(arguments.get("max_duration_minutes", 60))
@@ -814,14 +814,14 @@ async def _execute_start_camera_watch(
     }
 
 
-def _execute_stop_camera_watch() -> Dict[str, Any]:
+def _execute_stop_camera_watch() -> dict[str, Any]:
     cancelled = stop_vlm_watch_job()
     if cancelled:
         return {"success": True, "message": "Watch job cancelled."}
     return {"success": False, "message": "No active watch job to cancel."}
 
 
-def _execute_get_profile_status(request: Request) -> Dict[str, Any]:
+def _execute_get_profile_status(request: Request) -> dict[str, Any]:
     """Return profile status including active profile and activation timestamps."""
     profile_manager = getattr(request.app, "profile_manager", None)
     if profile_manager is None:
@@ -846,9 +846,9 @@ def _execute_get_profile_status(request: Request) -> Dict[str, Any]:
 
 
 def _execute_get_recap(
-    arguments: Dict[str, Any],
-    allowed_cameras: List[str],
-) -> Dict[str, Any]:
+    arguments: dict[str, Any],
+    allowed_cameras: list[str],
+) -> dict[str, Any]:
     """Fetch review segments with GenAI metadata for a time period."""
     from functools import reduce
 
@@ -909,7 +909,7 @@ def _execute_get_recap(
             .iterator()
         )
 
-        events: List[Dict[str, Any]] = []
+        events: list[dict[str, Any]] = []
 
         for row in rows:
             data = row.get("data") or {}
@@ -920,7 +920,7 @@ def _execute_get_recap(
                     data = {}
 
             camera = row["camera"]
-            event: Dict[str, Any] = {
+            event: dict[str, Any] = {
                 "camera": camera.replace("_", " ").title(),
                 "severity": row.get("severity", "detection"),
             }
@@ -984,10 +984,10 @@ def _execute_get_recap(
 
 
 async def _execute_pending_tools(
-    pending_tool_calls: List[Dict[str, Any]],
+    pending_tool_calls: list[dict[str, Any]],
     request: Request,
-    allowed_cameras: List[str],
-) -> tuple[List[ToolCall], List[Dict[str, Any]], List[Dict[str, Any]]]:
+    allowed_cameras: list[str],
+) -> tuple[list[ToolCall], list[dict[str, Any]], list[dict[str, Any]]]:
     """
     Execute a list of tool calls.
 
@@ -996,9 +996,9 @@ async def _execute_pending_tools(
          tool result dicts for conversation,
          extra messages to inject after tool results — e.g. user messages with images)
     """
-    tool_calls_out: List[ToolCall] = []
-    tool_results: List[Dict[str, Any]] = []
-    extra_messages: List[Dict[str, Any]] = []
+    tool_calls_out: list[ToolCall] = []
+    tool_results: list[dict[str, Any]] = []
+    extra_messages: list[dict[str, Any]] = []
     for tool_call in pending_tool_calls:
         tool_name = tool_call["name"]
         tool_args = tool_call.get("arguments") or {}
@@ -1106,7 +1106,7 @@ async def _execute_pending_tools(
 async def chat_completion(
     request: Request,
     body: ChatCompletionRequest = Body(...),
-    allowed_cameras: List[str] = Depends(get_allowed_cameras_for_filter),
+    allowed_cameras: list[str] = Depends(get_allowed_cameras_for_filter),
 ):
     """
     Chat completion endpoint with tool calling support.
@@ -1138,19 +1138,23 @@ async def chat_completion(
     )
     conversation = []
 
-    system_prompt = build_chat_system_prompt(
-        config=config,
-        allowed_cameras=allowed_cameras,
-        semantic_search_enabled=semantic_search_enabled,
-        attribute_classifications=attribute_classifications,
-    )
-
-    conversation.append(
-        {
-            "role": "system",
-            "content": system_prompt,
-        }
-    )
+    # Build the system message only when the client hasn't already pinned one.
+    # The first turn has no system message; we generate it (with the current
+    # timestamp) and return the whole chain so the client persists it. Later
+    # turns send it back verbatim, freezing the timestamp so the prompt prefix
+    # stays byte-identical and the model server's prompt cache keeps hitting.
+    if not body.messages or body.messages[0].role != "system":
+        conversation.append(
+            {
+                "role": "system",
+                "content": build_chat_system_prompt(
+                    config=config,
+                    allowed_cameras=allowed_cameras,
+                    semantic_search_enabled=semantic_search_enabled,
+                    attribute_classifications=attribute_classifications,
+                ),
+            }
+        )
 
     for msg in body.messages:
         msg_dict = {
@@ -1161,11 +1165,13 @@ async def chat_completion(
             msg_dict["tool_call_id"] = msg.tool_call_id
         if msg.name:
             msg_dict["name"] = msg.name
+        if msg.tool_calls is not None:
+            msg_dict["tool_calls"] = msg.tool_calls
 
         conversation.append(msg_dict)
 
     tool_iterations = 0
-    tool_calls: List[ToolCall] = []
+    tool_calls: list[ToolCall] = []
     max_iterations = body.max_tool_iterations
 
     logger.debug(
@@ -1175,11 +1181,20 @@ async def chat_completion(
 
     # True LLM streaming when client supports it and stream requested
     if body.stream and hasattr(genai_client, "chat_with_tools_stream"):
-        stream_tool_calls: List[ToolCall] = []
         stream_iterations = 0
 
         async def stream_body_llm():
-            nonlocal conversation, stream_tool_calls, stream_iterations
+            nonlocal conversation, stream_iterations
+
+            def _emit_chain(extra: Optional[list[dict[str, Any]]] = None):
+                # Return the full conversation (including the system message) so
+                # the client persists and replays it verbatim next turn.
+                chain = conversation + (extra or [])
+                return (
+                    json.dumps({"type": "messages", "messages": chain}).encode("utf-8")
+                    + b"\n"
+                )
+
             while stream_iterations < max_iterations:
                 if await request.is_disconnected():
                     logger.debug("Client disconnected, stopping chat stream")
@@ -1244,31 +1259,33 @@ async def chat_completion(
                                 )
                                 return
                             (
-                                executed_calls,
+                                _executed_calls,
                                 tool_results,
                                 extra_msgs,
                             ) = await _execute_pending_tools(
                                 pending, request, allowed_cameras
                             )
-                            stream_tool_calls.extend(executed_calls)
                             conversation.extend(tool_results)
                             conversation.extend(extra_msgs)
-                            yield (
-                                json.dumps(
-                                    {
-                                        "type": "tool_calls",
-                                        "tool_calls": [
-                                            tc.model_dump() for tc in stream_tool_calls
-                                        ],
-                                    }
-                                ).encode("utf-8")
-                                + b"\n"
-                            )
+                            # Emit the running chain so the client can render tool
+                            # calls live and replay them verbatim next turn.
+                            yield _emit_chain()
                             break
                         else:
+                            # Streaming never appends the final assistant message
+                            # to the conversation, so add it to the chain.
+                            yield _emit_chain(
+                                extra=[
+                                    {
+                                        "role": "assistant",
+                                        "content": msg.get("content"),
+                                    }
+                                ]
+                            )
                             yield (json.dumps({"type": "done"}).encode("utf-8") + b"\n")
                             return
             else:
+                yield _emit_chain()
                 yield json.dumps({"type": "done"}).encode("utf-8") + b"\n"
 
         return StreamingResponse(
@@ -1315,19 +1332,15 @@ async def chat_completion(
                 if body.stream:
                     final_reasoning = response.get("reasoning")
 
+                    chain = list(conversation)
+
                     async def stream_body() -> Any:
-                        if tool_calls:
-                            yield (
-                                json.dumps(
-                                    {
-                                        "type": "tool_calls",
-                                        "tool_calls": [
-                                            tc.model_dump() for tc in tool_calls
-                                        ],
-                                    }
-                                ).encode("utf-8")
-                                + b"\n"
+                        yield (
+                            json.dumps({"type": "messages", "messages": chain}).encode(
+                                "utf-8"
                             )
+                            + b"\n"
+                        )
                         # Emit the full reasoning trace up front when the
                         # underlying client did not stream it
                         if final_reasoning:
@@ -1363,6 +1376,7 @@ async def chat_completion(
                         finish_reason=response.get("finish_reason", "stop"),
                         tool_iterations=tool_iterations,
                         tool_calls=tool_calls,
+                        messages=list(conversation),
                     ).model_dump(),
                 )
 
@@ -1395,6 +1409,7 @@ async def chat_completion(
                 finish_reason="length",
                 tool_iterations=tool_iterations,
                 tool_calls=tool_calls,
+                messages=list(conversation),
             ).model_dump(),
         )
 

frigate/api/defs/request/chat_body.py

@@ -1,6 +1,6 @@
 """Chat API request models."""
 
-from typing import Optional
+from typing import Any, Optional
 
 from pydantic import BaseModel, Field
 
@@ -11,13 +11,29 @@ class ChatMessage(BaseModel):
     role: str = Field(
         description="Message role: 'user', 'assistant', 'system', or 'tool'"
     )
-    content: str = Field(description="Message content")
+    content: Optional[Any] = Field(
+        default=None,
+        description=(
+            "Message content. Usually a string, but may be a multimodal content "
+            "list (e.g. text + image_url) or null for assistant turns that only "
+            "request tool calls."
+        ),
+    )
     tool_call_id: Optional[str] = Field(
         default=None, description="For tool messages, the ID of the tool call"
     )
     name: Optional[str] = Field(
         default=None, description="For tool messages, the tool name"
     )
+    tool_calls: Optional[list[dict[str, Any]]] = Field(
+        default=None,
+        description=(
+            "For assistant messages replayed from prior turns, the OpenAI-format "
+            "tool calls the model previously requested. Replaying these verbatim "
+            "keeps the conversation prefix byte-for-byte identical so the model "
+            "server's prompt cache hits on follow-up turns."
+        ),
+    )
 
 
 class ChatCompletionRequest(BaseModel):

frigate/api/defs/response/chat_response.py

@@ -56,3 +56,12 @@ class ChatCompletionResponse(BaseModel):
         default_factory=list,
         description="List of tool calls that were executed during this completion",
     )
+    messages: list[dict[str, Any]] = Field(
+        default_factory=list,
+        description=(
+            "The full conversation chain, including the system message. Persist "
+            "and replay this verbatim on the next request so the prompt prefix "
+            "stays byte-identical and the model server's prompt cache keeps "
+            "hitting."
+        ),
+    )

frigate/output/birdseye.py

@@ -595,112 +595,92 @@ class BirdsEyeFrameManager:
     ) -> Optional[list[list[Any]]]:
         """Calculate the optimal layout for 2+ cameras."""
 
-        def map_layout(
-            camera_layout: list[list[Any]], row_height: int
-        ) -> tuple[int, int, Optional[list[list[Any]]]]:
-            """Map the calculated layout."""
-            candidate_layout = []
-            starting_x = 0
-            x = 0
-            max_width = 0
-            y = 0
+        def find_available_x(
+            current_x: int,
+            width: int,
+            reserved_ranges: list[tuple[int, int]],
+            max_width: int,
+        ) -> Optional[int]:
+            """Find the first horizontal slot that does not collide with reservations."""
+            x = current_x
 
-            for row in camera_layout:
-                final_row = []
-                max_width = max(max_width, x)
-                x = starting_x
-                for cameras in row:
-                    camera_dims = self.cameras[cameras[0]]["dimensions"].copy()
-                    camera_aspect = cameras[1]
+            for reserved_start, reserved_end in sorted(reserved_ranges):
+                if x >= reserved_end:
+                    continue
 
-                    if camera_dims[1] > camera_dims[0]:
-                        scaled_height = int(row_height * 2)
-                        scaled_width = int(scaled_height * camera_aspect)
-                        starting_x = scaled_width
-                    else:
-                        scaled_height = row_height
-                        scaled_width = int(scaled_height * camera_aspect)
+                if x + width <= reserved_start:
+                    return x
 
-                    # layout is too large
-                    if (
-                        x + scaled_width > self.canvas.width
-                        or y + scaled_height > self.canvas.height
-                    ):
-                        return x + scaled_width, y + scaled_height, None
+                x = max(x, reserved_end)
 
-                    final_row.append((cameras[0], (x, y, scaled_width, scaled_height)))
-                    x += scaled_width
+            if x + width <= max_width:
+                return x
 
-                y += row_height
-                candidate_layout.append(final_row)
-
-            if max_width == 0:
-                max_width = x
-
-            return max_width, y, candidate_layout
-
-        canvas_aspect_x, canvas_aspect_y = self.canvas.get_aspect(coefficient)
-        camera_layout: list[list[Any]] = []
-        camera_layout.append([])
-        starting_x = 0
-        x = starting_x
-        y = 0
-        y_i = 0
-        max_y = 0
-        for camera in cameras_to_add:
-            camera_dims = self.cameras[camera]["dimensions"].copy()
-            camera_aspect_x, camera_aspect_y = self.canvas.get_camera_aspect(
-                camera, camera_dims[0], camera_dims[1]
-            )
-
-            if camera_dims[1] > camera_dims[0]:
-                portrait = True
-            else:
-                portrait = False
-
-            if (x + camera_aspect_x) <= canvas_aspect_x:
-                # insert if camera can fit on current row
-                camera_layout[y_i].append(
-                    (
-                        camera,
-                        camera_aspect_x / camera_aspect_y,
-                    )
-                )
-
-                if portrait:
-                    starting_x = camera_aspect_x
-                else:
-                    max_y = max(
-                        max_y,
-                        camera_aspect_y,
-                    )
-
-                x += camera_aspect_x
-            else:
-                # move on to the next row and insert
-                y += max_y
-                y_i += 1
-                camera_layout.append([])
-                x = starting_x
-
-                if x + camera_aspect_x > canvas_aspect_x:
-                    return None
-
-                camera_layout[y_i].append(
-                    (
-                        camera,
-                        camera_aspect_x / camera_aspect_y,
-                    )
-                )
-                x += camera_aspect_x
-
-        if y + max_y > canvas_aspect_y:
             return None
 
-        row_height = int(self.canvas.height / coefficient)
-        total_width, total_height, standard_candidate_layout = map_layout(
-            camera_layout, row_height
-        )
+        def map_layout(row_height: int) -> tuple[int, int, Optional[list[list[Any]]]]:
+            """Lay out cameras row by row while reserving portrait spans for the next row."""
+            candidate_layout: list[list[Any]] = []
+            reserved_ranges: dict[int, list[tuple[int, int]]] = {}
+            current_row: list[Any] = []
+            row_index = 0
+            row_y = 0
+            row_x = 0
+            max_width = 0
+            max_height = 0
+
+            for camera in cameras_to_add:
+                camera_dims = self.cameras[camera]["dimensions"].copy()
+                camera_aspect_x, camera_aspect_y = self.canvas.get_camera_aspect(
+                    camera, camera_dims[0], camera_dims[1]
+                )
+                portrait = camera_dims[1] > camera_dims[0]
+                scaled_height = row_height * 2 if portrait else row_height
+                scaled_width = int(scaled_height * (camera_aspect_x / camera_aspect_y))
+
+                while True:
+                    x = find_available_x(
+                        row_x,
+                        scaled_width,
+                        reserved_ranges.get(row_index, []),
+                        self.canvas.width,
+                    )
+
+                    if x is not None and row_y + scaled_height <= self.canvas.height:
+                        current_row.append(
+                            (camera, (x, row_y, scaled_width, scaled_height))
+                        )
+                        row_x = x + scaled_width
+                        max_width = max(max_width, row_x)
+                        max_height = max(max_height, row_y + scaled_height)
+
+                        if portrait:
+                            reserved_ranges.setdefault(row_index + 1, []).append(
+                                (x, row_x)
+                            )
+
+                        break
+
+                    if current_row:
+                        candidate_layout.append(current_row)
+                        current_row = []
+
+                    row_index += 1
+                    row_y = row_index * row_height
+                    row_x = 0
+
+                    if row_y + scaled_height > self.canvas.height:
+                        overflow_width = max(max_width, scaled_width)
+                        overflow_height = row_y + scaled_height
+                        return overflow_width, overflow_height, None
+
+            if current_row:
+                candidate_layout.append(current_row)
+
+            return max_width, max_height, candidate_layout
+
+        row_height = max(1, int(self.canvas.height / coefficient))
+        total_width, total_height, standard_candidate_layout = map_layout(row_height)
 
         if not standard_candidate_layout:
             # if standard layout didn't work
@@ -709,9 +689,9 @@ class BirdsEyeFrameManager:
                 total_width / self.canvas.width,
                 total_height / self.canvas.height,
             )
-            row_height = int(row_height / scale_down_percent)
+            row_height = max(1, int(row_height / scale_down_percent))
             total_width, total_height, standard_candidate_layout = map_layout(
-                camera_layout, row_height
+                row_height
             )
 
             if not standard_candidate_layout:
@@ -725,8 +705,8 @@ class BirdsEyeFrameManager:
             1 / (total_width / self.canvas.width),
             1 / (total_height / self.canvas.height),
         )
-        row_height = int(row_height * scale_up_percent)
-        _, _, scaled_layout = map_layout(camera_layout, row_height)
+        row_height = max(1, int(row_height * scale_up_percent))
+        _, _, scaled_layout = map_layout(row_height)
 
         if scaled_layout:
             return scaled_layout

frigate/test/test_birdseye.py

@@ -1,11 +1,64 @@
-"""Test camera user and password cleanup."""
+"""Tests for Birdseye canvas sizing and layout behavior."""
 
 import unittest
+from multiprocessing import Event
 
-from frigate.output.birdseye import get_canvas_shape
+from frigate.config import FrigateConfig
+from frigate.output.birdseye import BirdsEyeFrameManager, get_canvas_shape
 
 
 class TestBirdseye(unittest.TestCase):
+    def _build_manager(
+        self, camera_dimensions: dict[str, tuple[int, int]]
+    ) -> BirdsEyeFrameManager:
+        config = {
+            "mqtt": {"host": "mqtt"},
+            "birdseye": {"width": 1280, "height": 720},
+            "cameras": {},
+        }
+
+        for order, (camera, dimensions) in enumerate(
+            camera_dimensions.items(), start=1
+        ):
+            config["cameras"][camera] = {
+                "ffmpeg": {
+                    "inputs": [
+                        {
+                            "path": f"rtsp://10.0.0.1:554/{camera}",
+                            "roles": ["detect"],
+                        }
+                    ]
+                },
+                "detect": {
+                    "width": dimensions[0],
+                    "height": dimensions[1],
+                    "fps": 5,
+                },
+                "birdseye": {"order": order},
+            }
+
+        return BirdsEyeFrameManager(FrigateConfig(**config), Event())
+
+    def _assert_no_overlaps(
+        self, layout: list[list[tuple[str, tuple[int, int, int, int]]]]
+    ):
+        rectangles = [position for row in layout for _, position in row]
+
+        for index, rect in enumerate(rectangles):
+            x1, y1, width1, height1 = rect
+            for other in rectangles[index + 1 :]:
+                x2, y2, width2, height2 = other
+                overlap = (
+                    x1 < x2 + width2
+                    and x2 < x1 + width1
+                    and y1 < y2 + height2
+                    and y2 < y1 + height1
+                )
+                self.assertFalse(
+                    overlap,
+                    msg=f"Overlapping rectangles found: {rect} and {other}",
+                )
+
     def test_16x9(self):
         """Test 16x9 aspect ratio works as expected for birdseye."""
         width = 1280
@@ -45,3 +98,104 @@ class TestBirdseye(unittest.TestCase):
         canvas_width, canvas_height = get_canvas_shape(width, height)
         assert canvas_width == width  # width will be the same
         assert canvas_height != height
+
+    def test_portrait_camera_does_not_overlap_next_row(self):
+        """Portrait cameras should reserve their real horizontal position on the next row."""
+        manager = self._build_manager(
+            {
+                "cam_a": (1280, 720),
+                "cam_p": (360, 640),
+                "cam_b": (1280, 720),
+                "cam_c": (640, 480),
+            }
+        )
+
+        layout = manager.calculate_layout(["cam_a", "cam_p", "cam_b", "cam_c"], 3)
+
+        self.assertIsNotNone(layout)
+        assert layout is not None
+        self._assert_no_overlaps(layout)
+
+        cam_c = [
+            position for row in layout for camera, position in row if camera == "cam_c"
+        ][0]
+        self.assertEqual(cam_c[0], 0)
+
+    def test_portrait_reservation_only_applies_to_next_row(self):
+        """Portrait reservations should not push later rows after the span ends."""
+        manager = self._build_manager(
+            {
+                "cam_a": (1280, 720),
+                "cam_p": (360, 640),
+                "cam_b": (1280, 720),
+                "cam_c": (1280, 720),
+                "cam_d": (1280, 720),
+                "cam_e": (1280, 720),
+            }
+        )
+
+        layout = manager.calculate_layout(
+            ["cam_a", "cam_p", "cam_b", "cam_c", "cam_d", "cam_e"],
+            3,
+        )
+
+        self.assertIsNotNone(layout)
+        assert layout is not None
+        self._assert_no_overlaps(layout)
+
+        cam_e = [
+            position for row in layout for camera, position in row if camera == "cam_e"
+        ][0]
+        self.assertEqual(cam_e[0], 0)
+
+    def test_multiple_portraits_reserve_distinct_ranges(self):
+        """Multiple portrait cameras in one row should reserve separate spans below them."""
+        manager = self._build_manager(
+            {
+                "cam_a": (640, 480),
+                "cam_p1": (360, 640),
+                "cam_p2": (360, 640),
+                "cam_b": (640, 480),
+                "cam_c": (1280, 720),
+                "cam_d": (640, 480),
+            }
+        )
+
+        layout = manager.calculate_layout(
+            ["cam_a", "cam_p1", "cam_p2", "cam_b", "cam_c", "cam_d"],
+            4,
+        )
+
+        self.assertIsNotNone(layout)
+        assert layout is not None
+        self._assert_no_overlaps(layout)
+
+    def test_two_landscapes_then_portrait_then_two_landscapes(self):
+        """A portrait after two landscapes should reserve only its own tail span."""
+        manager = self._build_manager(
+            {
+                "cam_a": (1280, 720),
+                "cam_b": (1280, 720),
+                "cam_p": (360, 640),
+                "cam_c": (1280, 720),
+                "cam_d": (1280, 720),
+            }
+        )
+
+        layout = manager.calculate_layout(
+            ["cam_a", "cam_b", "cam_p", "cam_c", "cam_d"],
+            3,
+        )
+
+        self.assertIsNotNone(layout)
+        assert layout is not None
+        self._assert_no_overlaps(layout)
+
+        cam_c = [
+            position for row in layout for camera, position in row if camera == "cam_c"
+        ][0]
+        cam_d = [
+            position for row in layout for camera, position in row if camera == "cam_d"
+        ][0]
+        self.assertEqual(cam_c[0], 0)
+        self.assertEqual(cam_d[0], cam_c[0] + cam_c[2])

web/.gitignore

@@ -12,6 +12,10 @@ dist
 dist-ssr
 *.local
 
+# Playwright
+playwright-report
+test-results
+
 # Editor directories and files
 .vscode/*
 !.vscode/extensions.json

web/e2e/specs/chat.spec.ts

@@ -92,6 +92,15 @@ test.describe("Chat — streaming @medium", () => {
     await installChatStreamOverride(frigateApp, [
       { type: "content", delta: "Hel" },
       { type: "content", delta: "lo" },
+      {
+        type: "messages",
+        messages: [
+          { role: "system", content: "sys" },
+          { role: "user", content: "hello chat" },
+          { role: "assistant", content: "Hello" },
+        ],
+      },
+      { type: "done" },
     ]);
     await frigateApp.goto("/chat");
     const input = frigateApp.page.getByPlaceholder(/ask/i);
@@ -137,6 +146,15 @@ test.describe("Chat — streaming @medium", () => {
         { type: "content", delta: "Hel" },
         { type: "content", delta: "lo, " },
         { type: "content", delta: "world!" },
+        {
+          type: "messages",
+          messages: [
+            { role: "system", content: "sys" },
+            { role: "user", content: "greet me" },
+            { role: "assistant", content: "Hello, world!" },
+          ],
+        },
+        { type: "done" },
       ],
       { chunkDelayMs: 50 },
     );
@@ -151,19 +169,39 @@ test.describe("Chat — streaming @medium", () => {
     });
   });
 
-  test("tool_calls chunks render a ToolCallsGroup", async ({ frigateApp }) => {
-    await installChatStreamOverride(frigateApp, [
+  test("tool calls in the chain render a ToolCallsGroup", async ({
+    frigateApp,
+  }) => {
+    const toolTurn = [
+      { role: "system", content: "sys" },
+      { role: "user", content: "find people" },
       {
-        type: "tool_calls",
+        role: "assistant",
+        content: null,
         tool_calls: [
           {
             id: "call_1",
-            name: "search_objects",
-            arguments: { label: "person" },
+            type: "function",
+            function: {
+              name: "search_objects",
+              arguments: '{"label":"person"}',
+            },
           },
         ],
       },
+      { role: "tool", tool_call_id: "call_1", content: "[]" },
+    ];
+    await installChatStreamOverride(frigateApp, [
+      { type: "messages", messages: toolTurn },
       { type: "content", delta: "Searching for people." },
+      {
+        type: "messages",
+        messages: [
+          ...toolTurn,
+          { role: "assistant", content: "Searching for people." },
+        ],
+      },
+      { type: "done" },
     ]);
     await frigateApp.goto("/chat");
     const input = frigateApp.page.getByPlaceholder(/ask/i);
@@ -253,6 +291,15 @@ test.describe("Chat — attachment chip @medium", () => {
     // We use the stream override so the first message completes quickly.
     await installChatStreamOverride(frigateApp, [
       { type: "content", delta: "Done." },
+      {
+        type: "messages",
+        messages: [
+          { role: "system", content: "sys" },
+          { role: "user", content: "hello" },
+          { role: "assistant", content: "Done." },
+        ],
+      },
+      { type: "done" },
     ]);
     await frigateApp.goto("/chat");
 

web/src/pages/Chat.tsx

@@ -13,6 +13,7 @@ import { ChatComposer } from "@/components/chat/ChatComposer";
 import ChatSettings from "@/components/chat/ChatSettings";
 import type {
   ChatMessage,
+  ChatStats,
   GenAIModelsResponse,
   ShowStatsMode,
 } from "@/types/chat";
@@ -22,12 +23,28 @@ import {
   getFindSimilarObjectsFromToolCalls,
   prependAttachment,
   streamChatCompletion,
+  toolCallsForMessage,
+  toolResponsesById,
 } from "@/utils/chatUtil";
 
+type StreamingTurn = {
+  content: string;
+  reasoning: string;
+  chain: ChatMessage[];
+  stats?: ChatStats;
+};
+
+const hasText = (content: unknown): content is string =>
+  typeof content === "string" && content.trim().length > 0;
+
+const toWire = (messages: ChatMessage[]): ChatMessage[] =>
+  messages.map(({ reasoning: _r, stats: _s, ...rest }) => rest);
+
 export default function ChatPage() {
   const { t } = useTranslation(["views/chat"]);
   const [input, setInput] = useState("");
   const [messages, setMessages] = useState<ChatMessage[]>([]);
+  const [streaming, setStreaming] = useState<StreamingTurn | null>(null);
   const [isLoading, setIsLoading] = useState(false);
   const [error, setError] = useState<string | null>(null);
   const [attachedEventId, setAttachedEventId] = useState<string | null>(null);
@@ -72,28 +89,19 @@ export default function ChatPage() {
     if (isNearBottom) {
       el.scrollTo({ top: el.scrollHeight, behavior: "smooth" });
     }
-  }, [messages, autoScroll]);
+  }, [messages, streaming, autoScroll]);
 
   const submitConversation = useCallback(
     async (messagesToSend: ChatMessage[]) => {
       if (isLoading) return;
       const last = messagesToSend[messagesToSend.length - 1];
-      if (!last || last.role !== "user" || !last.content.trim()) return;
+      if (!last || last.role !== "user" || !hasText(last.content)) return;
 
       setError(null);
-      const assistantPlaceholder: ChatMessage = {
-        role: "assistant",
-        content: "",
-        toolCalls: undefined,
-      };
-      setMessages([...messagesToSend, assistantPlaceholder]);
+      setMessages(messagesToSend);
+      setStreaming({ content: "", reasoning: "", chain: [] });
       setIsLoading(true);
 
-      const apiMessages = messagesToSend.map((m) => ({
-        role: m.role,
-        content: m.content,
-      }));
-
       const baseURL = axios.defaults.baseURL ?? "";
       const url = `${baseURL}chat/completion`;
       const headers: Record<string, string> = {
@@ -104,16 +112,50 @@ export default function ChatPage() {
       const controller = new AbortController();
       abortRef.current = controller;
 
+      let chain: ChatMessage[] = [];
+      let stats: ChatStats | undefined;
+      let reasoning = "";
+      let hadError = false;
+
       await streamChatCompletion(
         url,
         headers,
-        apiMessages,
+        toWire(messagesToSend),
         {
-          updateMessages: (updater) => setMessages(updater),
-          onError: (message) => setError(message),
+          onContentDelta: (delta) =>
+            setStreaming((s) => (s ? { ...s, content: s.content + delta } : s)),
+          onReasoningDelta: (delta) => {
+            reasoning += delta;
+            setStreaming((s) =>
+              s ? { ...s, reasoning: s.reasoning + delta } : s,
+            );
+          },
+          onChain: (fullChain) => {
+            chain = fullChain;
+            setStreaming((s) => (s ? { ...s, chain: fullChain } : s));
+          },
+          onStats: (s) => {
+            stats = s;
+            setStreaming((cur) => (cur ? { ...cur, stats: s } : cur));
+          },
+          onError: (message) => {
+            hadError = true;
+            setError(message);
+          },
           onDone: () => {
             abortRef.current = null;
             setIsLoading(false);
+            setStreaming(null);
+            const lastMsg = chain[chain.length - 1];
+            if (!hadError && lastMsg?.role === "assistant") {
+              setMessages(
+                chain.map((m, i) =>
+                  i === chain.length - 1
+                    ? { ...m, reasoning: reasoning || undefined, stats }
+                    : m,
+                ),
+              );
+            }
           },
           defaultErrorMessage: t("error"),
         },
@@ -125,12 +167,14 @@ export default function ChatPage() {
   );
 
   const recentEventIds = useMemo(() => {
+    const responses = toolResponsesById(messages);
     for (let i = messages.length - 1; i >= 0; i--) {
       const msg = messages[i];
-      if (msg.role !== "assistant" || !msg.toolCalls) continue;
-      const similar = getFindSimilarObjectsFromToolCalls(msg.toolCalls);
+      if (msg.role !== "assistant" || !msg.tool_calls?.length) continue;
+      const calls = toolCallsForMessage(msg, responses);
+      const similar = getFindSimilarObjectsFromToolCalls(calls);
       if (similar) return similar.results.map((e) => e.id);
-      const events = getEventIdsFromSearchObjectsToolCalls(msg.toolCalls);
+      const events = getEventIdsFromSearchObjectsToolCalls(calls);
       if (events.length > 0) return events.map((e) => e.id);
     }
     return [];
@@ -154,12 +198,14 @@ export default function ChatPage() {
     abortRef.current?.abort();
     abortRef.current = null;
     setIsLoading(false);
+    setStreaming(null);
   }, []);
 
   const startNewChat = useCallback(() => {
     abortRef.current?.abort();
     abortRef.current = null;
     setIsLoading(false);
+    setStreaming(null);
     setMessages([]);
     setInput("");
     setAttachedEventId(null);
@@ -181,7 +227,83 @@ export default function ChatPage() {
     setAttachedEventId(null);
   }, []);
 
-  const hasStarted = messages.length > 0;
+  const hasStarted = messages.length > 0 || streaming != null;
+
+  // While streaming, the backend's in-flight chain is the source of truth;
+  // otherwise the committed conversation is.
+  const renderList =
+    streaming && streaming.chain.length ? streaming.chain : messages;
+  const responses = toolResponsesById(renderList);
+  const renderTail = renderList[renderList.length - 1];
+  const finalShown =
+    renderTail?.role === "assistant" && hasText(renderTail.content);
+
+  const renderMessage = (msg: ChatMessage, i: number) => {
+    if (msg.role === "system" || msg.role === "tool") return null;
+
+    if (msg.role === "user") {
+      if (!hasText(msg.content)) return null;
+      return (
+        <div key={i} className="flex flex-col gap-2">
+          <MessageBubble
+            role="user"
+            content={msg.content}
+            messageIndex={i}
+            onEditSubmit={handleEditSubmit}
+            isComplete
+            showStats={showStats}
+          />
+        </div>
+      );
+    }
+
+    const calls = toolCallsForMessage(msg, responses);
+    const contentText = hasText(msg.content) ? msg.content : "";
+    const similar = getFindSimilarObjectsFromToolCalls(calls);
+    const events = similar ? [] : getEventIdsFromSearchObjectsToolCalls(calls);
+
+    return (
+      <div key={i} className="flex flex-col gap-2">
+        {calls.length > 0 && <ToolCallsGroup toolCalls={calls} />}
+        {hasText(msg.reasoning) && (
+          <ReasoningBubble
+            reasoning={msg.reasoning}
+            answerStarted={!!contentText}
+          />
+        )}
+        {contentText && (
+          <MessageBubble
+            role="assistant"
+            content={contentText}
+            messageIndex={i}
+            isComplete
+            stats={msg.stats}
+            showStats={showStats}
+          />
+        )}
+        {similar ? (
+          <ChatEventThumbnailsRow
+            events={similar.results}
+            anchor={similar.anchor}
+            onAttach={setAttachedEventId}
+          />
+        ) : (
+          <ChatEventThumbnailsRow
+            events={events}
+            onAttach={setAttachedEventId}
+          />
+        )}
+      </div>
+    );
+  };
+
+  const processingDots = (
+    <div className="flex items-center gap-2 self-start rounded-2xl bg-muted px-5 py-4">
+      <span className="size-2.5 animate-bounce rounded-full bg-muted-foreground/60 [animation-delay:-0.32s]" />
+      <span className="size-2.5 animate-bounce rounded-full bg-muted-foreground/60 [animation-delay:-0.16s]" />
+      <span className="size-2.5 animate-bounce rounded-full bg-muted-foreground/60" />
+    </div>
+  );
 
   return (
     <div className="flex size-full flex-col">
@@ -212,102 +334,31 @@ export default function ChatPage() {
           <div className="flex w-full flex-col xl:w-[50%] 3xl:w-[35%]">
             {hasStarted ? (
               <div className="flex w-full flex-1 flex-col gap-3 pb-3">
-                {messages.map((msg, i) => {
-                  const isLastAssistant =
-                    i === messages.length - 1 && msg.role === "assistant";
-                  const isComplete =
-                    msg.role === "user" || !isLoading || !isLastAssistant;
-                  const hasToolCalls =
-                    msg.toolCalls && msg.toolCalls.length > 0;
-                  const hasContent = !!msg.content?.trim();
-                  const hasReasoning = !!msg.reasoning?.trim();
-                  const showProcessing =
-                    isLastAssistant &&
-                    isLoading &&
-                    !hasContent &&
-                    !hasReasoning;
-
-                  // Hide empty placeholder only when there are no tool calls
-                  // and no reasoning streaming yet
-                  if (
-                    isLastAssistant &&
-                    isLoading &&
-                    !hasContent &&
-                    !hasToolCalls &&
-                    !hasReasoning
-                  )
-                    return (
-                      <div
-                        key={i}
-                        className="flex items-center gap-2 self-start rounded-2xl bg-muted px-5 py-4"
-                      >
-                        <span className="size-2.5 animate-bounce rounded-full bg-muted-foreground/60 [animation-delay:-0.32s]" />
-                        <span className="size-2.5 animate-bounce rounded-full bg-muted-foreground/60 [animation-delay:-0.16s]" />
-                        <span className="size-2.5 animate-bounce rounded-full bg-muted-foreground/60" />
-                      </div>
-                    );
-
-                  return (
-                    <div key={i} className="flex flex-col gap-2">
-                      {msg.role === "assistant" && hasToolCalls && (
-                        <ToolCallsGroup toolCalls={msg.toolCalls!} />
-                      )}
-                      {msg.role === "assistant" && hasReasoning && (
+                {renderList.map((msg, i) => renderMessage(msg, i))}
+                {streaming &&
+                  !finalShown &&
+                  (streaming.content || streaming.reasoning ? (
+                    <div className="flex flex-col gap-2">
+                      {hasText(streaming.reasoning) && (
                         <ReasoningBubble
-                          reasoning={msg.reasoning!}
-                          answerStarted={hasContent}
+                          reasoning={streaming.reasoning}
+                          answerStarted={!!streaming.content}
                         />
                       )}
-                      {showProcessing ? (
-                        <div className="flex items-center gap-2 self-start rounded-2xl bg-muted px-5 py-4">
-                          <span className="size-2 animate-bounce rounded-full bg-muted-foreground/60 [animation-delay:-0.3s]" />
-                          <span className="size-2 animate-bounce rounded-full bg-muted-foreground/60 [animation-delay:-0.15s]" />
-                          <span className="size-2 animate-bounce rounded-full bg-muted-foreground/60" />
-                        </div>
-                      ) : msg.role === "assistant" &&
-                        !hasContent &&
-                        hasReasoning &&
-                        !isComplete ? null : (
+                      {streaming.content && (
                         <MessageBubble
-                          role={msg.role}
-                          content={msg.content}
-                          messageIndex={i}
-                          onEditSubmit={
-                            msg.role === "user" ? handleEditSubmit : undefined
-                          }
-                          isComplete={isComplete}
-                          stats={msg.stats}
+                          role="assistant"
+                          content={streaming.content}
+                          messageIndex={-1}
+                          isComplete={false}
+                          stats={streaming.stats}
                           showStats={showStats}
                         />
                       )}
-                      {msg.role === "assistant" &&
-                        isComplete &&
-                        (() => {
-                          const similar = getFindSimilarObjectsFromToolCalls(
-                            msg.toolCalls,
-                          );
-                          if (similar) {
-                            return (
-                              <ChatEventThumbnailsRow
-                                events={similar.results}
-                                anchor={similar.anchor}
-                                onAttach={setAttachedEventId}
-                              />
-                            );
-                          }
-                          const events = getEventIdsFromSearchObjectsToolCalls(
-                            msg.toolCalls,
-                          );
-                          return (
-                            <ChatEventThumbnailsRow
-                              events={events}
-                              onAttach={setAttachedEventId}
-                            />
-                          );
-                        })()}
                     </div>
-                  );
-                })}
+                  ) : (
+                    processingDots
+                  ))}
                 {error && (
                   <p
                     className="flex items-center gap-1.5 self-start text-sm text-destructive"

web/src/types/chat.ts

@@ -1,17 +1,30 @@
+export type ToolCallFunction = {
+  name: string;
+  arguments: string;
+};
+
+export type WireToolCall = {
+  id: string;
+  type?: string;
+  function: ToolCallFunction;
+};
+
+export type ChatMessage = {
+  role: "system" | "user" | "assistant" | "tool";
+  content: unknown;
+  tool_call_id?: string;
+  name?: string;
+  tool_calls?: WireToolCall[];
+  reasoning?: string;
+  stats?: ChatStats;
+};
+
 export type ToolCall = {
   name: string;
   arguments?: Record<string, unknown>;
   response?: string;
 };
 
-export type ChatMessage = {
-  role: "user" | "assistant";
-  content: string;
-  reasoning?: string;
-  toolCalls?: ToolCall[];
-  stats?: ChatStats;
-};
-
 export type StartingRequest = {
   label: string;
   prompt: string;

web/src/utils/chatUtil.ts

@@ -1,16 +1,20 @@
 import type { ChatMessage, ChatStats, ToolCall } from "@/types/chat";
 
 export type StreamChatCallbacks = {
-  /** Update the messages array (e.g. pass to setState). */
-  updateMessages: (updater: (prev: ChatMessage[]) => ChatMessage[]) => void;
+  /** Streamed delta of the assistant's final answer text. */
+  onContentDelta: (delta: string) => void;
+  /** Streamed delta of the assistant's reasoning trace. */
+  onReasoningDelta: (delta: string) => void;
+  /** The full conversation chain so far (system message, history, this turn's
+   * tool-call turns, tool results, and — on the final emission — the final
+   * assistant message). */
+  onChain: (chain: ChatMessage[]) => void;
+  /** Token/timing stats for the turn. */
+  onStats: (stats: ChatStats) => void;
   /** Called when the stream sends an error or fetch fails. */
   onError: (message: string) => void;
   /** Called when the stream finishes (success or error). */
   onDone: () => void;
-  /** Called when the stream emits token/timing stats. The stats are also
-   * attached to the last assistant message in updateMessages, so consumers
-   * can usually rely on the message itself rather than wiring this up. */
-  onStats?: (stats: ChatStats) => void;
   /** Message used when fetch throws and no server error is available. */
   defaultErrorMessage?: string;
 };
@@ -25,7 +29,7 @@ type StatsChunk = {
 
 type StreamChunk =
   | { type: "error"; error: string }
-  | { type: "tool_calls"; tool_calls: ToolCall[] }
+  | { type: "messages"; messages: ChatMessage[] }
   | { type: "content"; delta: string }
   | { type: "reasoning"; delta: string }
   | StatsChunk;
@@ -41,16 +45,18 @@ export type StreamChatOptions = {
 export async function streamChatCompletion(
   url: string,
   headers: Record<string, string>,
-  apiMessages: { role: string; content: string }[],
+  apiMessages: ChatMessage[],
   callbacks: StreamChatCallbacks,
   signal?: AbortSignal,
   options: StreamChatOptions = {},
 ): Promise<void> {
   const {
-    updateMessages,
+    onContentDelta,
+    onReasoningDelta,
+    onChain,
+    onStats,
     onError,
     onDone,
-    onStats,
     defaultErrorMessage = "Something went wrong. Please try again.",
   } = callbacks;
 
@@ -91,65 +97,27 @@ export async function streamChatCompletion(
     const applyChunk = (data: StreamChunk) => {
       if (data.type === "error") {
         onError(data.error);
-        updateMessages((prev) =>
-          prev.filter((m) => !(m.role === "assistant" && m.content === "")),
-        );
         return "break";
       }
-      if (data.type === "tool_calls" && data.tool_calls?.length) {
-        updateMessages((prev) => {
-          const next = [...prev];
-          const lastMsg = next[next.length - 1];
-          if (lastMsg?.role === "assistant")
-            next[next.length - 1] = {
-              ...lastMsg,
-              toolCalls: data.tool_calls,
-            };
-          return next;
-        });
+      if (data.type === "messages") {
+        onChain(data.messages ?? []);
         return "continue";
       }
       if (data.type === "content" && data.delta !== undefined) {
-        updateMessages((prev) => {
-          const next = [...prev];
-          const lastMsg = next[next.length - 1];
-          if (lastMsg?.role === "assistant")
-            next[next.length - 1] = {
-              ...lastMsg,
-              content: lastMsg.content + data.delta,
-            };
-          return next;
-        });
+        onContentDelta(data.delta);
         return "continue";
       }
       if (data.type === "reasoning" && data.delta !== undefined) {
-        updateMessages((prev) => {
-          const next = [...prev];
-          const lastMsg = next[next.length - 1];
-          if (lastMsg?.role === "assistant")
-            next[next.length - 1] = {
-              ...lastMsg,
-              reasoning: (lastMsg.reasoning ?? "") + data.delta,
-            };
-          return next;
-        });
+        onReasoningDelta(data.delta);
         return "continue";
       }
       if (data.type === "stats") {
-        const stats: ChatStats = {
+        onStats({
           promptTokens: data.prompt_tokens,
           completionTokens: data.completion_tokens,
           completionDurationMs: data.completion_duration_ms,
           tokensPerSecond: data.tokens_per_second,
-        };
-        updateMessages((prev) => {
-          const next = [...prev];
-          const lastMsg = next[next.length - 1];
-          if (lastMsg?.role === "assistant")
-            next[next.length - 1] = { ...lastMsg, stats };
-          return next;
         });
-        onStats?.(stats);
         return "continue";
       }
       return "continue";
@@ -165,9 +133,8 @@ export async function streamChatCompletion(
         const trimmed = line.trim();
         if (!trimmed) continue;
         try {
-          const data = JSON.parse(trimmed) as StreamChunk & { type: string };
-          const result = applyChunk(data as StreamChunk);
-          if (result === "break") {
+          const data = JSON.parse(trimmed) as StreamChunk;
+          if (applyChunk(data) === "break") {
             hadStreamError = true;
             break;
           }
@@ -181,50 +148,63 @@ export async function streamChatCompletion(
     // Flush remaining buffer
     if (!hadStreamError && buffer.trim()) {
       try {
-        const data = JSON.parse(buffer.trim()) as StreamChunk & {
-          type: string;
-          delta?: string;
-        };
-        if (data.type === "content" && data.delta !== undefined) {
-          updateMessages((prev) => {
-            const next = [...prev];
-            const lastMsg = next[next.length - 1];
-            if (lastMsg?.role === "assistant")
-              next[next.length - 1] = {
-                ...lastMsg,
-                content: lastMsg.content + data.delta!,
-              };
-            return next;
-          });
-        }
+        const data = JSON.parse(buffer.trim()) as StreamChunk;
+        applyChunk(data);
       } catch {
         // ignore final malformed chunk
       }
     }
-
-    if (!hadStreamError) {
-      updateMessages((prev) => {
-        const next = [...prev];
-        const lastMsg = next[next.length - 1];
-        if (lastMsg?.role === "assistant" && lastMsg.content === "")
-          next[next.length - 1] = { ...lastMsg, content: " " };
-        return next;
-      });
-    }
   } catch (err) {
     if (err instanceof DOMException && err.name === "AbortError") {
       // User stopped generation — not an error
     } else {
       onError(defaultErrorMessage);
-      updateMessages((prev) =>
-        prev.filter((m) => !(m.role === "assistant" && m.content === "")),
-      );
     }
   } finally {
     onDone();
   }
 }
 
+/** Map each tool result message to its tool_call_id for response lookup. */
+export function toolResponsesById(
+  messages: ChatMessage[],
+): Map<string, string> {
+  const map = new Map<string, string>();
+  for (const m of messages) {
+    if (m.role === "tool" && typeof m.tool_call_id === "string") {
+      map.set(
+        m.tool_call_id,
+        typeof m.content === "string" ? m.content : JSON.stringify(m.content),
+      );
+    }
+  }
+  return map;
+}
+
+/** Derive the display tool calls for one assistant message. */
+export function toolCallsForMessage(
+  message: ChatMessage,
+  responses: Map<string, string>,
+): ToolCall[] {
+  if (!message.tool_calls?.length) return [];
+  return message.tool_calls.map((tc) => {
+    let args: Record<string, unknown> | undefined;
+    const raw = tc.function?.arguments;
+    if (typeof raw === "string") {
+      try {
+        args = JSON.parse(raw) as Record<string, unknown>;
+      } catch {
+        args = undefined;
+      }
+    }
+    return {
+      name: tc.function?.name ?? "",
+      arguments: args,
+      response: responses.get(tc.id),
+    };
+  });
+}
+
 /**
  * Parse search_objects tool call response(s) into event ids for thumbnails.
  */