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Currently translated at 100.0% (809 of 809 strings)

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Translated using Weblate (Chinese (Simplified Han script))

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Co-authored-by: GuoQing Liu <842607283@qq.com>
Co-authored-by: Hosted Weblate <hosted@weblate.org>
Co-authored-by: Yechi Yang <yechiyang93@gmail.com>
Translate-URL: https://hosted.weblate.org/projects/frigate-nvr/components-camera/zh_Hans/
Translate-URL: https://hosted.weblate.org/projects/frigate-nvr/config-cameras/zh_Hans/
Translate-URL: https://hosted.weblate.org/projects/frigate-nvr/config-global/zh_Hans/
Translate-URL: https://hosted.weblate.org/projects/frigate-nvr/views-search/zh_Hans/
Translate-URL: https://hosted.weblate.org/projects/frigate-nvr/views-settings/zh_Hans/
Translate-URL: https://hosted.weblate.org/projects/frigate-nvr/views-system/zh_Hans/
Translation: Frigate NVR/Config - Cameras
Translation: Frigate NVR/Config - Global
Translation: Frigate NVR/components-camera
Translation: Frigate NVR/views-search
Translation: Frigate NVR/views-settings
Translation: Frigate NVR/views-system

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."
+        ),
+    )

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/public/locales/ca/views/system.json

@@ -191,7 +191,22 @@
       },
       "audio": "Àudio:",
       "cameraProbeInfo": "Informació del sondeig de la càmera {{camera}}",
-      "streamDataFromFFPROBE": "Les dades de la transmissió són obtingudes mitjançant <code>ffprobe</code>."
+      "streamDataFromFFPROBE": "Les dades de la transmissió són obtingudes mitjançant <code>ffprobe</code>.",
+      "keyframes": {
+        "title": "Anàlisi de fotogrames clau",
+        "analyzing": "S'estan analitzant els fotogrames clau... queden {{seconds}} segons",
+        "stillAnalyzing": "Encara s'estan analitzant els fotogrames clau...",
+        "recordStream": "Registre de flux:",
+        "keyframeCount": "Fotogrames clau observats:",
+        "observedDuration": "Durada observada:",
+        "gap": "Espai de fotogrames clau (mín / avg / max):",
+        "segmentLength": "Longitud del segment d'enregistrament:",
+        "ok": "Fotogrames clau cada ,{{seconds}}s, bons per enregistrar i reproduir.",
+        "warning": "Els fotogrames clau dispersos o variables (espai més llarg .{{seconds}}s), probablement un còdec intel·ligent (H.264+/H.265+), això no és recomanable.",
+        "error": "El buit dels fotogrames clau ( the{{seconds}}s) excedeix la longitud del segment d'enregistrament ({{segmentTime}}s). Alguns segments poden no tenir un fotograma clau, el qual trenca la reproducció. Desactiva el còdec intel·ligent/+ a la càmera o escurça el seu interval de fotogrames clau.",
+        "unknown": "No s'ha pogut determinar l'espaiat dels fotogrames clau.",
+        "recordDisabled": "L'enregistrament està desactivat per a aquesta càmera."
+      }
     },
     "title": "Càmeres",
     "overview": "Visió general",

web/public/locales/es/config/cameras.json

@@ -24,7 +24,7 @@
         },
         "listen": {
             "label": "Tipos de escucha",
-            "description": "Lista de tipos de eventos de audio a detectar (por ejemplo: ladrido, alarma de incendios, grito, voz, alarido)."
+            "description": "Lista de tipos de eventos de audio a detectar (por ejemplo: ladrar, alarma de incendio, habla, gritar)."
         },
         "filters": {
             "label": "Filtros de audio",
@@ -744,7 +744,7 @@
             "label": "Tiempo de reintento de FFmpeg"
         },
         "path": {
-            "description": "Ruta al binario de FFmpeg que se va a utilizar o un alias de versión (\"5.0\" o \"7.0\").",
+            "description": "Ruta al binario de FFmpeg que se va a utilizar o un alias de versión (\"7.0\" o \"8.0\").",
             "label": "Ruta de FFmpeg"
         },
         "output_args": {

web/public/locales/es/config/global.json

@@ -39,7 +39,7 @@
         },
         "listen": {
             "label": "Tipos de escucha",
-            "description": "Lista de tipos de eventos de audio a detectar (por ejemplo: ladrido, alarma de incendios, grito, voz, alarido)."
+            "description": "Lista de tipos de eventos de audio a detectar (por ejemplo: ladrar, alarma de incendio, habla, gritar)."
         },
         "filters": {
             "label": "Filtros de audio",
@@ -1234,7 +1234,7 @@
             "label": "Tiempo de reintento de FFmpeg"
         },
         "path": {
-            "description": "Ruta al binario de FFmpeg que se va a utilizar o un alias de versión (\"5.0\" o \"7.0\").",
+            "description": "Ruta al binario de FFmpeg que se va a utilizar o un alias de versión (\"7.0\" o \"8.0\").",
             "label": "Ruta de FFmpeg"
         },
         "output_args": {

web/public/locales/es/views/settings.json

@@ -2020,6 +2020,9 @@
     },
     "onvif": {
       "autotrackingNoZones": "El seguimiento automático requiere al menos una zona. Define una zona para esta cámara en Máscaras / Zonas y, a continuación, establécela como zona obligatoria a continuación."
+    },
+    "ffmpeg": {
+      "hwaccelManualNotRecommended": "No son remontados los argumentos de aceleración por hardware manual. A no ser que un requisito específico exista, seleccione la preselección que coincida con su hardware."
     }
   },
   "resetToDefaultDescription": "Esto restablecerá todos los ajustes de esta sección a sus valores predeterminados. Esta acción no se puede deshacer.",

web/public/locales/es/views/system.json

@@ -81,16 +81,16 @@
       "gpuInfo": {
         "vainfoOutput": {
           "title": "Salida de Vainfo",
-          "returnCode": "Código de Retorno: {{code}}",
-          "processOutput": "Salida del Proceso:",
-          "processError": "Error del Proceso:"
+          "returnCode": "Código de retorno: {{code}}",
+          "processOutput": "Salida del proceso:",
+          "processError": "Error del proceso:"
         },
         "nvidiaSMIOutput": {
-          "cudaComputerCapability": "Capacidad de Cómputo CUDA: {{cuda_compute}}",
+          "cudaComputerCapability": "Capacidad de cómputo CUDA: {{cuda_compute}}",
           "title": "Salida de Nvidia SMI",
           "driver": "Controlador: {{driver}}",
           "name": "Nombre: {{name}}",
-          "vbios": "Información de VBios: {{vbios}}"
+          "vbios": "Informe de VBios: {{vbios}}"
         },
         "toast": {
           "success": "Información de GPU copiada al portapapeles"
@@ -104,7 +104,7 @@
       },
       "gpuMemory": "Memoria de GPU",
       "npuMemory": "Memoria de NPU",
-      "npuUsage": "Uso de NPU",
+      "npuUsage": "Modo de empleo de NPU",
       "intelGpuWarning": {
         "title": "Aviso de estadísticas Intel GPU",
         "message": "Estadísticas de GPU no disponibles",
@@ -122,7 +122,7 @@
         "go2rtc": "go2rtc",
         "recording": "grabación",
         "review_segment": "revisar segmento",
-        "embeddings": "embeddings",
+        "embeddings": "empotrados",
         "audio_detector": "detector de audio"
       }
     }
@@ -165,8 +165,8 @@
       "codec": "Codec:",
       "fetching": "Obteniendo Datos de la Cámara",
       "stream": "Flujo {{idx}}",
-      "video": "Video:",
-      "fps": "FPS:",
+      "video": "Vídeo:",
+      "fps": "CPS:",
       "resolution": "Resolución:",
       "error": "Error: {{error}}",
       "unknown": "Desconocido",
@@ -174,7 +174,21 @@
       "tips": {
         "title": "Información de Sondeo de la Cámara"
       },
-      "aspectRatio": "Relación de aspecto"
+      "aspectRatio": "Relación de aspecto",
+      "keyframes": {
+        "title": "Análisis de clave fotograma",
+        "recordStream": "Flujo de grabación:",
+        "segmentLength": "Longitud de segmento en grabación:",
+        "unknown": "No pudo determinar el espaciado del fotograma.",
+        "analyzing": "Analizando fotogramas clave… {{seconds}} segundos restantes",
+        "stillAnalyzing": "Todavía analizando fotogramas clave…",
+        "keyframeCount": "Fotogramas clave observados:",
+        "observedDuration": "Duración observada:",
+        "gap": "Brecha de fotogramas clave (mín / med / máx):",
+        "recordDisabled": "La grabación está desactivada para esta cámara.",
+        "ok": "Cuadros cada ~{{seconds}}s, bueno para grabación y reproducción.",
+        "warning": "Fotograma clave escaso o variable (hueco más largo ~{{seconds}}s), probablemente un códec inteligente (H.264+/H.265+), esto no es recomendado."
+      }
     },
     "framesAndDetections": "Fotogramas / Detecciones",
     "label": {
@@ -204,9 +218,9 @@
     },
     "connectionQuality": {
       "excellent": "Excelente",
-      "poor": "Debil",
-      "title": "Calidad de la conexión",
-      "fps": "Cuadros por segundo",
+      "poor": "Pobre",
+      "title": "Calidad de Conexión",
+      "fps": "CPS",
       "expectedFps": "Cuadros por segundo esperados",
       "reconnectsLastHour": "Reconexiones (última hora)",
       "unusable": "No usable",
@@ -222,25 +236,25 @@
     "infPerSecond": "Inferencias Por Segundo",
     "embeddings": {
       "plate_recognition_speed": "Velocidad de Reconocimiento de Matrículas",
-      "face_embedding_speed": "Velocidad de Incrustación de Rostros",
-      "image_embedding_speed": "Velocidad de Incrustación de Imágenes",
-      "text_embedding_speed": "Velocidad de Incrustación de Texto",
+      "face_embedding_speed": "Velocidad de Empotrado Facial",
+      "image_embedding_speed": "Velocidad de Empotrado de Imagen",
+      "text_embedding_speed": "Velocidad de Empotrado de Texto",
       "face_recognition_speed": "Velocidad de Reconocimiento Facial",
-      "text_embedding": "Incrustación de Texto",
+      "text_embedding": "Empotrado de Texto",
       "face_recognition": "Reconocimiento Facial",
       "plate_recognition": "Reconocimiento de Matrículas",
       "yolov9_plate_detection": "Detección de Matrículas YOLOv9",
-      "image_embedding": "Incrustación de Imágenes",
+      "image_embedding": "Empotrado de Imagen",
       "yolov9_plate_detection_speed": "Velocidad de Detección de Matrículas YOLOv9",
       "review_description": "Revisión de descripción",
-      "review_description_speed": "Velocidad de revisión de la descripción",
-      "review_description_events_per_second": "Revisión de la descripción",
+      "review_description_speed": "Revisión de velocidad de descripción",
+      "review_description_events_per_second": "Revisión de Descripción",
       "object_description": "Descripción de Objeto",
-      "object_description_speed": "Velocidad de descripción de objeto",
-      "object_description_events_per_second": "Descripción de objeto",
+      "object_description_speed": "Velocidad de Descripción de Objeto",
+      "object_description_events_per_second": "Descripción de Objeto",
       "classification": "Clasificación de {{name}}",
-      "classification_speed": "Velocidad de clasificación de {{name}}",
-      "classification_events_per_second": "Clasificacion de eventos por segundo de {{name}}"
+      "classification_speed": "Velocidad de Clasificación de {{name}}",
+      "classification_events_per_second": "Clasificación de Eventos por Segundo de {{name}}"
     },
     "title": "Enriquecimientos",
     "averageInf": "Tiempo promedio de inferencia"
@@ -249,7 +263,7 @@
     "ffmpegHighCpuUsage": "{{camera}} tiene un uso elevado de CPU por FFmpeg ({{ffmpegAvg}}%)",
     "detectHighCpuUsage": "{{camera}} tiene un uso elevado de CPU por detección ({{detectAvg}}%)",
     "healthy": "El sistema está saludable",
-    "reindexingEmbeddings": "Reindexando incrustaciones ({{processed}}% completado)",
+    "reindexingEmbeddings": "Reindexando empotrados ({{processed}}% completado)",
     "detectIsSlow": "{{detect}} es lento ({{speed}} ms)",
     "cameraIsOffline": "{{camera}} está desconectada",
     "detectIsVerySlow": "{{detect}} es muy lento ({{speed}} ms)",

web/public/locales/ro/views/system.json

@@ -201,7 +201,22 @@
         "title": "Info Sondă Cameră"
       },
       "fps": "FPS:",
-      "unknown": "Necunoscut"
+      "unknown": "Necunoscut",
+      "keyframes": {
+        "title": "Analiză keyframe",
+        "analyzing": "Se analizează keyframe-urile... {{seconds}} secunde rămase",
+        "stillAnalyzing": "Încă se analizează keyframe-urile...",
+        "keyframeCount": "Keyframe-uri observate:",
+        "recordStream": "Stream de înregistrare:",
+        "observedDuration": "Durată observată:",
+        "gap": "Interval keyframe (min / med / max):",
+        "ok": "Keyframe-uri la fiecare ~{{seconds}}s, bune pentru înregistrare și redare.",
+        "segmentLength": "Lungime segment de înregistrare:",
+        "warning": "Keyframe-uri rare sau variabile (cel mai lung interval ~{{seconds}}s), probabil un codec smart (H.264+/H.265+), acest lucru nu este recomandat.",
+        "error": "Intervalul keyframe (~{{seconds}}s) depășește lungimea segmentului de înregistrare ({{segmentTime}}s). Unele segmente pot să nu aibă niciun keyframe, ceea ce întrerupe redarea. Dezactivează codecul smart/+ de pe cameră sau scurtează intervalul keyframe.",
+        "unknown": "Nu s-a putut determina distanțarea keyframe-urilor.",
+        "recordDisabled": "Înregistrarea este dezactivată pentru această cameră."
+      }
     },
     "label": {
       "capture": "captură",

web/public/locales/ru/common.json

@@ -130,7 +130,11 @@
     "export": "Экспортировать",
     "deleteNow": "Удалить сейчас",
     "next": "Следующий",
-    "continue": "Продолжить"
+    "continue": "Продолжить",
+    "add": "Добавить",
+    "applying": "Применяется…",
+    "undo": "Отменить",
+    "copiedToClipboard": "Скопировано в буфер обмена"
   },
   "label": {
     "back": "Вернуться",

web/public/locales/sv/config/cameras.json

@@ -3,5 +3,27 @@
     "name": {
         "label": "Kameranamn",
         "description": "Kameranamn krävs"
+    },
+    "friendly_name": {
+        "label": "Visningsnamn",
+        "description": "Visningsnamn för kamera i Frigate UI"
+    },
+    "enabled": {
+        "label": "Aktiverad",
+        "description": "Aktiverad"
+    },
+    "audio": {
+        "label": "Ljuddetektering",
+        "description": "Inställningar för ljudbaserad händelsedetektering för denna kamera.",
+        "enabled": {
+            "label": "Aktivera ljuddetektering",
+            "description": "Aktivera eller avaktivera ljudbaserad detektering för denna kamera."
+        },
+        "max_not_heard": {
+            "description": "Antal sekunder utan den konfigurerade ljudtypen innan en ljudbaserad händelse slutar."
+        },
+        "min_volume": {
+            "label": "Minsta ljudvolym"
+        }
     }
 }

web/public/locales/sv/config/global.json

@@ -1,5 +1,17 @@
 {
     "version": {
         "label": "Nuvarande konfigurations version"
+    },
+    "audio": {
+        "label": "Ljuddetektering",
+        "enabled": {
+            "label": "Aktivera ljuddetektering"
+        },
+        "max_not_heard": {
+            "description": "Antal sekunder utan den konfigurerade ljudtypen innan en ljudbaserad händelse slutar."
+        },
+        "min_volume": {
+            "label": "Minsta ljudvolym"
+        }
     }
 }

web/public/locales/uk/common.json

@@ -179,7 +179,8 @@
       "id": "Bahasa Indonesia (Індонезійська)",
       "ur": "اردو (Урду)",
       "hr": "Hrvatski (Хорватська)",
-      "bs": "Bosanski (Боснійська)"
+      "bs": "Bosanski (Боснійська)",
+      "zhHant": "繁體中文 (Традиційна китайська)"
     },
     "system": "Система",
     "systemMetrics": "Системна метріка",

web/public/locales/uk/components/camera.json

@@ -68,7 +68,10 @@
       "label": "Камери",
       "desc": "Виберіть камери для цієї групи."
     },
-    "icon": "Значок"
+    "icon": "Значок",
+    "showAll": "Відобразити всі групи камер",
+    "showLess": "Показати менше",
+    "editGroups": "Редагувати групи камер"
   },
   "debug": {
     "zones": "Зони",

web/public/locales/uk/components/player.json

@@ -47,5 +47,6 @@
     "error": {
       "submitFrigatePlusFailed": "Не вдалося надіслати фрейм Frigate+"
     }
-  }
+  },
+  "cameraOff": "Камера вимкнена"
 }

web/public/locales/uk/config/cameras.json

@@ -11,5 +11,8 @@
     "enabled": {
         "label": "Увімкнено",
         "description": "Увімкнено"
+    },
+    "audio": {
+        "label": "Виявлення звуку"
     }
 }

web/public/locales/uk/config/global.json

@@ -1 +1,5 @@
-{}
+{
+    "audio": {
+        "label": "Виявлення звуку"
+    }
+}

web/public/locales/zh-CN/config/cameras.json

@@ -33,7 +33,7 @@
         },
         "listen": {
             "label": "监听类型",
-            "description": "要检测的音频事件类型列表（例如：bark、fire_alarm、scream、speech、yell）。"
+            "description": "要检测的音频事件类型列表（例如：bark、fire_alarm、speech、yell）。"
         },
         "filters": {
             "label": "音频过滤器",
@@ -156,7 +156,7 @@
         "description": "FFmpeg 编解码相关设置，包含可执行文件路径、命令行参数、硬件加速选项，以及按不同功能划分的输出参数。",
         "path": {
             "label": "FFmpeg 路径",
-            "description": "要使用的 FFmpeg 可执行文件路径，或版本别名（如 \"5.0\" 或 \"7.0\"）。"
+            "description": "要使用的 FFmpeg 可执行文件路径，或版本别名（如 \"7.0\" 或 \"8.0\"）。"
         },
         "global_args": {
             "label": "FFmpeg 全局参数",

web/public/locales/zh-CN/config/global.json

@@ -44,7 +44,7 @@
         },
         "listen": {
             "label": "监听类型",
-            "description": "要检测的音频事件类型列表（例如：bark、fire_alarm、scream、speech、yell）。"
+            "description": "要检测的音频事件类型列表（例如：bark、fire_alarm、speech、yell）。"
         },
         "filters": {
             "label": "音频过滤器",
@@ -292,7 +292,7 @@
         "description": "FFmpeg 编解码相关设置，包含可执行文件路径、命令行参数、硬件加速选项，以及按不同功能划分的输出参数。",
         "path": {
             "label": "FFmpeg 路径",
-            "description": "要使用的 FFmpeg 可执行文件路径，或版本别名（如 \"5.0\" 或 \"7.0\"）。"
+            "description": "要使用的 FFmpeg 可执行文件路径，或版本别名（如 \"7.0\" 或 \"8.0\"）。"
         },
         "global_args": {
             "label": "FFmpeg 全局参数",

web/public/locales/zh-CN/views/search.json

@@ -46,7 +46,7 @@
     "tips": {
       "title": "如何使用文本筛选器",
       "desc": {
-        "text": "筛选器可帮助您缩小搜索范围。注意，目前还暂不支持中文搜索。以下是在输入字段中使用筛选器的方法：",
+        "text": "筛选器可帮助您缩小搜索范围。注意，Jina v1 不支持中文搜索。以下是在输入字段中使用筛选器的方法：",
         "step": "<ul className=\"list-disc pl-5 text-sm text-primary-variant\"><li>输入筛选器名称后跟一个冒号（例如：“cameras:”）。</li><li>从建议中选择一个值或输入您自己的值。</li><li>使用多个筛选器时，可以在它们之间用空格分隔。</li><li>日期筛选器（before: 和 after:）使用 <em>{{DateFormat}}</em> 格式。</li><li>时间范围筛选器使用 <em>{{exampleTime}}</em> 格式。</li><li>点击筛选器旁边的“x”即可移除筛选条件。</li></ul>",
         "example": "示例：<code className=\"text-primary\">cameras:front_door label:person before:01012024 time_range:3:00PM-4:00PM</code>",
         "step2": "选择给出的建议值或自行输入；",

web/public/locales/zh-CN/views/settings.json

@@ -2115,6 +2115,9 @@
     },
     "onvif": {
       "autotrackingNoZones": "自动追踪至少需要一个区域。请先在“遮罩 / 区域”中为此摄像头定义一个区域，然后在下方将其设置为必需区域。"
+    },
+    "ffmpeg": {
+      "hwaccelManualNotRecommended": "不建议手动硬件加速参数。除非存在特定需求，否则选择与你的硬件匹配的预设。"
     }
   },
   "birdseye": {

web/public/locales/zh-CN/views/system.json

@@ -175,7 +175,22 @@
       "tips": {
         "title": "摄像头信息"
       },
-      "aspectRatio": "宽高比"
+      "aspectRatio": "宽高比",
+      "keyframes": {
+        "title": "关键帧分析",
+        "analyzing": "正在分析关键帧... 剩余 {{seconds}} 秒",
+        "stillAnalyzing": "仍在分析关键帧...",
+        "recordStream": "录制视频流：",
+        "keyframeCount": "观察到的关键帧：",
+        "observedDuration": "观测持续时间：",
+        "gap": "关键帧间隔（最小值 / 平均值 / 最大值）：",
+        "segmentLength": "录制片段长度：",
+        "ok": "每 {{seconds}} 秒取一帧，适用于录制和回放。",
+        "warning": "稀疏或不均匀的关键帧（最长间隔约{{seconds}}秒），可能是使用了智能编码器（例如H.264+/H.265+），不建议开启该功能。",
+        "error": "关键帧间隔（~{{seconds}}秒）超过了录制片段长度（{{segmentTime}}秒）。某些片段可能没有关键帧，这会导致播放中断。请尝试禁用摄像头的智能或 + 编解码器或缩短其关键帧间隔。",
+        "unknown": "无法确定关键帧间隔。",
+        "recordDisabled": "此摄像头的录制功能已禁用。"
+      }
     },
     "framesAndDetections": "帧数/检测次数",
     "label": {

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.
  */