feat: add inline message editing and regeneration functionality for webui (#7673)

* feat: add inline message editing and regeneration functionality for webui

- Implemented inline editing for user messages in the chat component.
- Added a regenerate menu for retrying messages with different models.
- Enhanced message handling to include llm_checkpoint_id for better tracking.
- Updated localization files to include new actions for retrying and model selection.
- Introduced tests for checkpoint message handling and chat route functionality.

* feat: thread mode in webui

* feat: enhance message editing functionality to allow only the latest user message to be edited

* feat: add error handling and user feedback for thread creation in chat component

* feat: add thread count display and localization support in chat component

* feat: add RefsSidebar component and integrate reference management in chat UI

* feat: improve message editing validation and cleanup for bot messages

* feat: enhance checkpoint message handling with binding and dumping functionality
# Conflicts:
#	astrbot/core/agent/message.py
#	astrbot/core/agent/runners/tool_loop_agent_runner.py
#	astrbot/core/astr_main_agent.py
#	astrbot/core/db/sqlite.py
#	astrbot/core/pipeline/process_stage/method/agent_sub_stages/internal.py
#	astrbot/core/platform/sources/webchat/webchat_adapter.py
#	astrbot/dashboard/routes/chat.py
#	astrbot/dashboard/routes/live_chat.py
#	dashboard/src/components/chat/Chat.vue
#	dashboard/src/components/chat/ChatInput.vue
#	dashboard/src/components/chat/ChatMessageList.vue
#	dashboard/src/components/chat/ProviderModelMenu.vue
#	dashboard/src/components/shared/StyledMenu.vue
#	dashboard/src/composables/useMessages.ts
#	dashboard/src/i18n/locales/ru-RU/features/chat.json

astrbot/core/agent/message.py

@@ -1,8 +1,7 @@
-from __future__ import annotations
-
 # Inspired by MoonshotAI/kosong, credits to MoonshotAI/kosong authors for the original implementation.
 # License: Apache License 2.0
-from typing import Any, ClassVar, Literal, TypeGuard
+
+from typing import Any, ClassVar, Literal, cast
 
 from pydantic import (
     BaseModel,
@@ -15,14 +14,10 @@ from pydantic import (
 from pydantic_core import core_schema
 
 
-def _is_str_keyed_dict(value: object) -> TypeGuard[dict[str, object]]:
-    return isinstance(value, dict) and all(isinstance(key, str) for key in value)
-
-
 class ContentPart(BaseModel):
     """A part of the content in a message."""
 
-    __content_part_registry: ClassVar[dict[str, type[ContentPart]]] = {}
+    __content_part_registry: ClassVar[dict[str, type["ContentPart"]]] = {}
 
     type: Literal["text", "think", "image_url", "audio_url"]
 
@@ -39,25 +34,23 @@ class ContentPart(BaseModel):
 
     @classmethod
     def __get_pydantic_core_schema__(
-        cls,
-        source_type: object,
-        handler: GetCoreSchemaHandler,
+        cls, source_type: Any, handler: GetCoreSchemaHandler
     ) -> core_schema.CoreSchema:
         # If we're dealing with the base ContentPart class, use custom validation
         if cls.__name__ == "ContentPart":
 
-            def validate_content_part(value: object) -> ContentPart:
+            def validate_content_part(value: Any) -> Any:
                 # if it's already an instance of a ContentPart subclass, return it
-                if isinstance(value, cls):
+                if hasattr(value, "__class__") and issubclass(value.__class__, cls):
                     return value
 
                 # if it's a dict with a type field, dispatch to the appropriate subclass
-                if _is_str_keyed_dict(value):
-                    type_value = value.get("type")
-                    if isinstance(type_value, str):
-                        target_class = cls.__content_part_registry.get(type_value)
-                        if target_class is not None:
-                            return target_class.model_validate(value)
+                if isinstance(value, dict) and "type" in value:
+                    type_value: Any | None = cast(dict[str, Any], value).get("type")
+                    if not isinstance(type_value, str):
+                        raise ValueError(f"Cannot validate {value} as ContentPart")
+                    target_class = cls.__content_part_registry[type_value]
+                    return target_class.model_validate(value)
 
                 raise ValueError(f"Cannot validate {value} as ContentPart")
 
@@ -68,25 +61,27 @@ class ContentPart(BaseModel):
 
 
 class TextPart(ContentPart):
-    """>>> TextPart(text="Hello, world!").model_dump()
+    """
+    >>> TextPart(text="Hello, world!").model_dump()
     {'type': 'text', 'text': 'Hello, world!'}
     """
 
-    type: Literal["text"] = "text"
+    type: str = "text"
     text: str
 
 
 class ThinkPart(ContentPart):
-    """>>> ThinkPart(think="I think I need to think about this.").model_dump()
+    """
+    >>> ThinkPart(think="I think I need to think about this.").model_dump()
     {'type': 'think', 'think': 'I think I need to think about this.', 'encrypted': None}
     """
 
-    type: Literal["think"] = "think"
+    type: str = "think"
     think: str
     encrypted: str | None = None
     """Encrypted thinking content, or signature."""
 
-    def merge_in_place(self, other: object) -> bool:
+    def merge_in_place(self, other: Any) -> bool:
         if not isinstance(other, ThinkPart):
             return False
         if self.encrypted:
@@ -98,7 +93,8 @@ class ThinkPart(ContentPart):
 
 
 class ImageURLPart(ContentPart):
-    """>>> ImageURLPart(image_url="http://example.com/image.jpg").model_dump()
+    """
+    >>> ImageURLPart(image_url="http://example.com/image.jpg").model_dump()
     {'type': 'image_url', 'image_url': 'http://example.com/image.jpg'}
     """
 
@@ -108,12 +104,13 @@ class ImageURLPart(ContentPart):
         id: str | None = None
         """The ID of the image, to allow LLMs to distinguish different images."""
 
-    type: Literal["image_url"] = "image_url"
+    type: str = "image_url"
     image_url: ImageURL
 
 
 class AudioURLPart(ContentPart):
-    """>>> AudioURLPart(audio_url=AudioURLPart.AudioURL(url="https://example.com/audio.mp3")).model_dump()
+    """
+    >>> AudioURLPart(audio_url=AudioURLPart.AudioURL(url="https://example.com/audio.mp3")).model_dump()
     {'type': 'audio_url', 'audio_url': {'url': 'https://example.com/audio.mp3', 'id': None}}
     """
 
@@ -123,12 +120,13 @@ class AudioURLPart(ContentPart):
         id: str | None = None
         """The ID of the audio, to allow LLMs to distinguish different audios."""
 
-    type: Literal["audio_url"] = "audio_url"
+    type: str = "audio_url"
     audio_url: AudioURL
 
 
 class ToolCall(BaseModel):
-    """A tool call requested by the assistant.
+    """
+    A tool call requested by the assistant.
 
     >>> ToolCall(
     ...     id="123",
@@ -150,7 +148,7 @@ class ToolCall(BaseModel):
     """The ID of the tool call."""
     function: FunctionBody
     """The function body of the tool call."""
-    extra_content: dict[str, object] | None = None
+    extra_content: dict[str, Any] | None = None
     """Extra metadata for the tool call."""
 
     @model_serializer(mode="wrap")
@@ -217,7 +215,7 @@ class Message(BaseModel):
         # other all cases: content is required
         if self.content is None:
             raise ValueError(
-                "content is required unless role='assistant' and tool_calls is not None",
+                "content is required unless role='assistant' and tool_calls is not None"
             )
         return self
 
@@ -334,8 +332,6 @@ def dump_messages_with_checkpoints(messages: list[Message]) -> list[dict]:
         dumped.append(message.model_dump())
         if message._checkpoint_after is not None:
             dumped.append(
-                CheckpointMessageSegment(
-                    content=message._checkpoint_after,
-                ).model_dump(),
+                CheckpointMessageSegment(content=message._checkpoint_after).model_dump()
             )
     return dumped

astrbot/core/agent/runners/tool_loop_agent_runner.py

@@ -1,6 +1,5 @@
 import asyncio
 import copy
-import os
 import sys
 import time
 import traceback
@@ -9,6 +8,7 @@ import uuid
 from collections.abc import AsyncIterator
 from contextlib import suppress
 from dataclasses import dataclass, field, replace
+from pathlib import Path
 
 from mcp.types import (
     BlobResourceContents,
@@ -26,24 +26,8 @@ from tenacity import (
 )
 
 from astrbot import logger
-from astrbot.core.agent.context.config import ContextConfig
-from astrbot.core.agent.context.manager import ContextManager
-from astrbot.core.agent.context.token_counter import EstimateTokenCounter
-from astrbot.core.agent.hooks import BaseAgentRunHooks
-from astrbot.core.agent.message import (
-    AssistantMessageSegment,
-    ImageURLPart,
-    Message,
-    TextPart,
-    ThinkPart,
-    ToolCallMessageSegment,
-    bind_checkpoint_messages,
-)
-from astrbot.core.agent.response import AgentResponse, AgentResponseData, AgentStats
-from astrbot.core.agent.run_context import ContextWrapper, TContext
-from astrbot.core.agent.runners.base import AgentState, BaseAgentRunner
+from astrbot.core.agent.message import ImageURLPart, TextPart, ThinkPart
 from astrbot.core.agent.tool import FunctionTool, ToolSet
-from astrbot.core.agent.tool_executor import BaseFunctionToolExecutor
 from astrbot.core.agent.tool_image_cache import tool_image_cache
 from astrbot.core.exceptions import EmptyModelOutputError
 from astrbot.core.message.components import Json
@@ -64,6 +48,22 @@ from astrbot.core.provider.modalities import (
 )
 from astrbot.core.provider.provider import Provider
 
+from ..context.compressor import ContextCompressor
+from ..context.config import ContextConfig
+from ..context.manager import ContextManager
+from ..context.token_counter import EstimateTokenCounter, TokenCounter
+from ..hooks import BaseAgentRunHooks
+from ..message import (
+    AssistantMessageSegment,
+    Message,
+    ToolCallMessageSegment,
+    bind_checkpoint_messages,
+)
+from ..response import AgentResponseData, AgentStats
+from ..run_context import ContextWrapper, TContext
+from ..tool_executor import BaseFunctionToolExecutor
+from .base import AgentResponse, AgentState, BaseAgentRunner
+
 if sys.version_info >= (3, 12):
     from typing import override
 else:
@@ -83,8 +83,7 @@ class _HandleFunctionToolsResult:
 
     @classmethod
     def from_tool_call_result_blocks(
-        cls,
-        blocks: list[ToolCallMessageSegment],
+        cls, blocks: list[ToolCallMessageSegment]
     ) -> "_HandleFunctionToolsResult":
         return cls(kind="tool_call_result_blocks", tool_call_result_blocks=blocks)
 
@@ -184,12 +183,12 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
         self.stats.end_time = time.time()
 
         parts = []
-        if llm_resp.reasoning_content is not None or llm_resp.reasoning_signature:
+        if llm_resp.reasoning_content or llm_resp.reasoning_signature:
             parts.append(
                 ThinkPart(
-                    think=llm_resp.reasoning_content or "",
+                    think=llm_resp.reasoning_content,
                     encrypted=llm_resp.reasoning_signature,
-                ),
+                )
             )
         if llm_resp.completion_text:
             parts.append(TextPart(text=llm_resp.completion_text))
@@ -222,21 +221,14 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
         # truncate by turns compressor
         truncate_turns: int = 1,
         # customize
-        custom_token_counter: T.Any = None,
-        custom_compressor: T.Any = None,
+        custom_token_counter: TokenCounter | None = None,
+        custom_compressor: ContextCompressor | None = None,
         tool_schema_mode: str | None = "full",
         fallback_providers: list[Provider] | None = None,
-        provider_config: dict | None = None,
+        tool_result_overflow_dir: str | None = None,
+        read_tool: FunctionTool | None = None,
         **kwargs: T.Any,
     ) -> None:
-        raw_tool_result_overflow_dir = kwargs.get("tool_result_overflow_dir")
-        tool_result_overflow_dir = (
-            raw_tool_result_overflow_dir
-            if isinstance(raw_tool_result_overflow_dir, str)
-            else None
-        )
-        raw_read_tool = kwargs.get("read_tool")
-        read_tool = raw_read_tool if isinstance(raw_read_tool, FunctionTool) else None
         self.req = request
         self.streaming = streaming
         self.enforce_max_turns = enforce_max_turns
@@ -380,7 +372,7 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
         if self.tool_result_overflow_dir is None:
             raise ValueError("tool_result_overflow_dir is not configured")
 
-        overflow_dir = self.tool_result_overflow_dir
+        overflow_dir = Path(self.tool_result_overflow_dir).resolve(strict=False)
         safe_tool_call_id = (
             "".join(
                 ch if ch.isalnum() or ch in {"-", "_", "."} else "_"
@@ -389,14 +381,12 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
             or "tool_call"
         )
         file_name = f"{safe_tool_call_id}_{uuid.uuid4().hex[:8]}.txt"
+        overflow_path = overflow_dir / file_name
 
         def _run() -> str:
-            normalized_overflow_dir = os.path.abspath(overflow_dir)
-            overflow_path = os.path.join(normalized_overflow_dir, file_name)
-            os.makedirs(normalized_overflow_dir, exist_ok=True)
-            with open(overflow_path, "w", encoding="utf-8") as file:
-                file.write(content)
-            return overflow_path
+            overflow_dir.mkdir(parents=True, exist_ok=True)
+            overflow_path.write_text(content, encoding="utf-8")
+            return str(overflow_path)
 
         return await asyncio.to_thread(_run)
 
@@ -410,7 +400,7 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
             return content
 
         estimated_tokens = self._tool_result_token_counter.count_tokens(
-            [Message(role="tool", content=content, tool_call_id=tool_call_id)],
+            [Message(role="tool", content=content, tool_call_id=tool_call_id)]
         )
         if estimated_tokens <= self.TOOL_RESULT_MAX_ESTIMATED_TOKENS:
             return content
@@ -455,7 +445,7 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
         preview = content
         while preview:
             estimated_tokens = self._tool_result_token_counter.count_tokens(
-                [Message(role="tool", content=preview, tool_call_id=tool_call_id)],
+                [Message(role="tool", content=preview, tool_call_id=tool_call_id)]
             )
             if estimated_tokens <= self.TOOL_RESULT_PREVIEW_MAX_ESTIMATED_TOKENS:
                 return preview
@@ -466,34 +456,25 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
         return preview
 
     async def _iter_llm_responses(
-        self,
-        *,
-        include_model: bool = True,
+        self, *, include_model: bool = True
     ) -> T.AsyncGenerator[LLMResponse, None]:
         """Yields chunks *and* a final LLMResponse."""
-        contexts = self._sanitize_contexts_for_provider(self.run_context.messages)
-        func_tool = self._func_tool_for_provider()
-        model = self.req.model if include_model else None
+        payload = {
+            "contexts": self._sanitize_contexts_for_provider(self.run_context.messages),
+            "func_tool": self._func_tool_for_provider(),
+            "session_id": self.req.session_id,
+            "extra_user_content_parts": self.req.extra_user_content_parts,  # list[ContentPart]
+            "abort_signal": self._abort_signal,
+        }
+        if include_model:
+            # For primary provider we keep explicit model selection if provided.
+            payload["model"] = self.req.model
         if self.streaming:
-            stream = self.provider.text_chat_stream(
-                contexts=contexts,
-                func_tool=func_tool,
-                session_id=self.req.session_id,
-                extra_user_content_parts=self.req.extra_user_content_parts,
-                model=model,
-                abort_signal=self._abort_signal,
-            )
-            async for resp in stream:
+            stream = self.provider.text_chat_stream(**payload)
+            async for resp in stream:  # type: ignore
                 yield resp
         else:
-            yield await self.provider.text_chat(
-                contexts=contexts,
-                func_tool=func_tool,
-                session_id=self.req.session_id,
-                extra_user_content_parts=self.req.extra_user_content_parts,
-                model=model,
-                abort_signal=self._abort_signal,
-            )
+            yield await self.provider.text_chat(**payload)
 
     async def _iter_llm_responses_with_fallback(
         self,
@@ -531,7 +512,7 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                     with attempt:
                         try:
                             async for resp in self._iter_llm_responses(
-                                include_model=idx == 0,
+                                include_model=idx == 0
                             ):
                                 if resp.is_chunk:
                                     has_stream_output = True
@@ -727,25 +708,16 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
         token_usage = self.req.conversation.token_usage if self.req.conversation else 0
         self._simple_print_message_role("[BefCompact]")
         self.run_context.messages = await self.context_manager.process(
-            self.run_context.messages,
-            trusted_token_usage=token_usage,
+            self.run_context.messages, trusted_token_usage=token_usage
         )
         self._simple_print_message_role("[AftCompact]")
 
         async for llm_response in self._iter_llm_responses_with_fallback():
             if llm_response.is_chunk:
+                # update ttft
                 if self.stats.time_to_first_token == 0:
                     self.stats.time_to_first_token = time.time() - self.stats.start_time
 
-                if llm_response.reasoning_content:
-                    yield AgentResponse(
-                        type="streaming_delta",
-                        data=AgentResponseData(
-                            chain=MessageChain(type="reasoning").message(
-                                llm_response.reasoning_content,
-                            ),
-                        ),
-                    )
                 if llm_response.result_chain:
                     yield AgentResponse(
                         type="streaming_delta",
@@ -758,6 +730,15 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                             chain=MessageChain().message(llm_response.completion_text),
                         ),
                     )
+                elif llm_response.reasoning_content:
+                    yield AgentResponse(
+                        type="streaming_delta",
+                        data=AgentResponseData(
+                            chain=MessageChain(type="reasoning").message(
+                                llm_response.reasoning_content,
+                            ),
+                        ),
+                    )
                 if self._is_stop_requested():
                     llm_resp_result = LLMResponse(
                         role="assistant",
@@ -811,15 +792,6 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
             await self._complete_with_assistant_response(llm_resp)
 
         # 返回 LLM 结果
-        if llm_resp.reasoning_content:
-            yield AgentResponse(
-                type="llm_result",
-                data=AgentResponseData(
-                    chain=MessageChain(type="reasoning").message(
-                        llm_resp.reasoning_content,
-                    ),
-                ),
-            )
         if llm_resp.result_chain:
             yield AgentResponse(
                 type="llm_result",
@@ -839,17 +811,8 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                 llm_resp, _ = await self._resolve_tool_exec(llm_resp)
                 if not llm_resp.tools_call_name:
                     logger.warning(
-                        "skills_like tool re-query returned no tool calls; fallback to assistant response.",
+                        "skills_like tool re-query returned no tool calls; fallback to assistant response."
                     )
-                    if llm_resp.reasoning_content:
-                        yield AgentResponse(
-                            type="llm_result",
-                            data=AgentResponseData(
-                                chain=MessageChain(type="reasoning").message(
-                                    llm_resp.reasoning_content,
-                                ),
-                            ),
-                        )
                     if llm_resp.result_chain:
                         yield AgentResponse(
                             type="llm_result",
@@ -862,7 +825,6 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                                 chain=MessageChain().message(llm_resp.completion_text),
                             ),
                         )
-
                     await self._complete_with_assistant_response(llm_resp)
                     return
 
@@ -896,12 +858,12 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
 
             # 将结果添加到上下文中
             parts = []
-            if llm_resp.reasoning_content is not None or llm_resp.reasoning_signature:
+            if llm_resp.reasoning_content or llm_resp.reasoning_signature:
                 parts.append(
                     ThinkPart(
-                        think=llm_resp.reasoning_content or "",
+                        think=llm_resp.reasoning_content,
                         encrypted=llm_resp.reasoning_signature,
-                    ),
+                    )
                 )
             if llm_resp.completion_text:
                 parts.append(TextPart(text=llm_resp.completion_text))
@@ -916,7 +878,7 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
             )
             # record the assistant message with tool calls
             self.run_context.messages.extend(
-                tool_calls_result.to_openai_messages_model(),
+                tool_calls_result.to_openai_messages_model()
             )
 
             # If there are cached images and the model supports image input,
@@ -929,37 +891,35 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                     image_parts = []
                     for cached_img in cached_images:
                         img_data = tool_image_cache.get_image_base64_by_path(
-                            cached_img.file_path,
-                            cached_img.mime_type,
+                            cached_img.file_path, cached_img.mime_type
                         )
                         if img_data:
                             base64_data, mime_type = img_data
                             image_parts.append(
                                 TextPart(
-                                    text=f"[Image from tool '{cached_img.tool_name}', path='{cached_img.file_path}']",
-                                ),
+                                    text=f"[Image from tool '{cached_img.tool_name}', path='{cached_img.file_path}']"
+                                )
                             )
                             image_parts.append(
                                 ImageURLPart(
                                     image_url=ImageURLPart.ImageURL(
                                         url=f"data:{mime_type};base64,{base64_data}",
                                         id=cached_img.file_path,
-                                    ),
-                                ),
+                                    )
+                                )
                             )
                     if image_parts:
                         self.run_context.messages.append(
-                            Message(role="user", content=image_parts),
+                            Message(role="user", content=image_parts)
                         )
                         logger.debug(
-                            f"Appended {len(cached_images)} cached image(s) to context for LLM review",
+                            f"Appended {len(cached_images)} cached image(s) to context for LLM review"
                         )
 
             self.req.append_tool_calls_result(tool_calls_result)
 
     async def step_until_done(
-        self,
-        max_step: int,
+        self, max_step: int
     ) -> T.AsyncGenerator[AgentResponse, None]:
         """Process steps until the agent is done."""
         step_count = 0
@@ -971,7 +931,7 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
         #  如果循环结束了但是 agent 还没有完成，说明是达到了 max_step
         if not self.done():
             logger.warning(
-                f"Agent reached max steps ({max_step}), forcing a final response.",
+                f"Agent reached max steps ({max_step}), forcing a final response."
             )
             # 拔掉所有工具
             if self.req:
@@ -981,7 +941,7 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                 Message(
                     role="user",
                     content=self.MAX_STEPS_REACHED_PROMPT,
-                ),
+                )
             )
             # 再执行最后一步
             async for resp in self.step():
@@ -1010,9 +970,7 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
             llm_response.tools_call_name,
             llm_response.tools_call_args,
             llm_response.tools_call_ids,
-            strict=False,
         ):
-            tool_result_blocks_start = len(tool_call_result_blocks)
             tool_call_streak = self._track_tool_call_streak(func_tool_name)
             yield _HandleFunctionToolsResult.from_message_chain(
                 MessageChain(
@@ -1024,10 +982,10 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                                 "name": func_tool_name,
                                 "args": func_tool_args,
                                 "ts": time.time(),
-                            },
-                        ),
+                            }
+                        )
                     ],
-                ),
+                )
             )
             try:
                 if not req.func_tool:
@@ -1126,11 +1084,11 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                                 result_parts.append(
                                     f"Image returned and cached at path='{cached_img.file_path}'. "
                                     f"Review the image below. Use send_message_to_user to send it to the user if satisfied, "
-                                    f"with type='image' and path='{cached_img.file_path}'.",
+                                    f"with type='image' and path='{cached_img.file_path}'."
                                 )
                                 # Yield image info for LLM visibility (will be handled in step())
                                 yield _HandleFunctionToolsResult.from_cached_image(
-                                    cached_img,
+                                    cached_img
                                 )
                             elif isinstance(content_item, EmbeddedResource):
                                 resource = content_item.resource
@@ -1152,15 +1110,15 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                                     result_parts.append(
                                         f"Image returned and cached at path='{cached_img.file_path}'. "
                                         f"Review the image below. Use send_message_to_user to send it to the user if satisfied, "
-                                        f"with type='image' and path='{cached_img.file_path}'.",
+                                        f"with type='image' and path='{cached_img.file_path}'."
                                     )
                                     # Yield image info for LLM visibility
                                     yield _HandleFunctionToolsResult.from_cached_image(
-                                        cached_img,
+                                        cached_img
                                     )
                                 else:
                                     result_parts.append(
-                                        "The tool has returned a data type that is not supported.",
+                                        "The tool has returned a data type that is not supported."
                                     )
                         if result_parts:
                             inline_result = "\n\n".join(result_parts)
@@ -1172,8 +1130,7 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                                 func_tool_id,
                                 inline_result
                                 + self._build_repeated_tool_call_guidance(
-                                    func_tool_name,
-                                    tool_call_streak,
+                                    func_tool_name, tool_call_streak
                                 ),
                             )
 
@@ -1182,7 +1139,7 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                         # 这里我们将直接结束 Agent Loop
                         # 发送消息逻辑在 ToolExecutor 中处理了
                         logger.warning(
-                            f"{func_tool_name} 没有返回值，或者已将结果直接发送给用户。",
+                            f"{func_tool_name} 没有返回值，或者已将结果直接发送给用户。"
                         )
                         self._transition_state(AgentState.DONE)
                         self.stats.end_time = time.time()
@@ -1190,8 +1147,7 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                             func_tool_id,
                             "The tool has no return value, or has sent the result directly to the user."
                             + self._build_repeated_tool_call_guidance(
-                                func_tool_name,
-                                tool_call_streak,
+                                func_tool_name, tool_call_streak
                             ),
                         )
                     else:
@@ -1203,8 +1159,7 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                             func_tool_id,
                             "*The tool has returned an unsupported type. Please tell the user to check the definition and implementation of this tool.*"
                             + self._build_repeated_tool_call_guidance(
-                                func_tool_name,
-                                tool_call_streak,
+                                func_tool_name, tool_call_streak
                             ),
                         )
 
@@ -1225,33 +1180,33 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                     func_tool_id,
                     f"error: {e!s}"
                     + self._build_repeated_tool_call_guidance(
-                        func_tool_name,
-                        tool_call_streak,
+                        func_tool_name, tool_call_streak
                     ),
                 )
 
-            if len(tool_call_result_blocks) > tool_result_blocks_start:
-                tool_result_content = str(tool_call_result_blocks[-1].content)
-                yield _HandleFunctionToolsResult.from_message_chain(
-                    MessageChain(
-                        type="tool_call_result",
-                        chain=[
-                            Json(
-                                data={
-                                    "id": func_tool_id,
-                                    "ts": time.time(),
-                                    "result": tool_result_content,
-                                }
-                            )
-                        ],
-                    )
+        # yield the last tool call result
+        if tool_call_result_blocks:
+            last_tcr_content = str(tool_call_result_blocks[-1].content)
+            yield _HandleFunctionToolsResult.from_message_chain(
+                MessageChain(
+                    type="tool_call_result",
+                    chain=[
+                        Json(
+                            data={
+                                "id": func_tool_id,
+                                "ts": time.time(),
+                                "result": last_tcr_content,
+                            }
+                        )
+                    ],
                 )
-                logger.info(f"Tool `{func_tool_name}` Result: {tool_result_content}")
+            )
+            logger.info(f"Tool `{func_tool_name}` Result: {last_tcr_content}")
 
         # 处理函数调用响应
         if tool_call_result_blocks:
             yield _HandleFunctionToolsResult.from_tool_call_result_blocks(
-                tool_call_result_blocks,
+                tool_call_result_blocks
             )
 
     def _build_tool_requery_context(
@@ -1267,7 +1222,7 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
             elif isinstance(msg, dict):
                 contexts.append(copy.deepcopy(msg))
         instruction = self.SKILLS_LIKE_REQUERY_INSTRUCTION_TEMPLATE.format(
-            tool_names=", ".join(tool_names),
+            tool_names=", ".join(tool_names)
         )
         if extra_instruction:
             instruction = f"{instruction}\n{extra_instruction}"
@@ -1310,8 +1265,7 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
 
         if isinstance(self._tool_schema_param_set, ToolSet):
             param_subset = self._build_tool_subset(
-                self._tool_schema_param_set,
-                tool_names,
+                self._tool_schema_param_set, tool_names
             )
             if param_subset.tools and tool_names:
                 contexts = self._build_tool_requery_context(tool_names)
@@ -1321,7 +1275,7 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                     model=self.req.model,
                     session_id=self.req.session_id,
                     extra_user_content_parts=self.req.extra_user_content_parts,
-                    # tool_choice="required",
+                    tool_choice="required",
                     abort_signal=self._abort_signal,
                 )
                 if requery_resp:
@@ -1335,7 +1289,7 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                     and not self._has_meaningful_assistant_reply(llm_resp)
                 ):
                     logger.warning(
-                        "skills_like tool re-query returned no tool calls and no explanation; retrying with stronger instruction.",
+                        "skills_like tool re-query returned no tool calls and no explanation; retrying with stronger instruction."
                     )
                     repair_contexts = self._build_tool_requery_context(
                         tool_names,
@@ -1347,7 +1301,7 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                         model=self.req.model,
                         session_id=self.req.session_id,
                         extra_user_content_parts=self.req.extra_user_content_parts,
-                        # tool_choice="required",
+                        tool_choice="required",
                         abort_signal=self._abort_signal,
                     )
                     if repair_resp:
@@ -1389,12 +1343,12 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
         self.stats.end_time = time.time()
 
         parts = []
-        if llm_resp.reasoning_content is not None or llm_resp.reasoning_signature:
+        if llm_resp.reasoning_content or llm_resp.reasoning_signature:
             parts.append(
                 ThinkPart(
-                    think=llm_resp.reasoning_content or "",
+                    think=llm_resp.reasoning_content,
                     encrypted=llm_resp.reasoning_signature,
-                ),
+                )
             )
         if llm_resp.completion_text:
             parts.append(TextPart(text=llm_resp.completion_text))
@@ -1423,17 +1377,14 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
         self,
         executor: AsyncIterator[ToolExecutorResultT],
     ) -> T.AsyncGenerator[ToolExecutorResultT, None]:
-        async def _get_next_result() -> ToolExecutorResultT:
-            return await anext(executor)
-
         while True:
             if self._is_stop_requested():
                 await self._close_executor(executor)
                 raise _ToolExecutionInterrupted(
-                    "Tool execution interrupted before reading the next tool result.",
+                    "Tool execution interrupted before reading the next tool result."
                 )
 
-            next_result_task = asyncio.create_task(_get_next_result())
+            next_result_task = asyncio.create_task(anext(executor))
             abort_task = asyncio.create_task(self._abort_signal.wait())
             try:
                 done, _ = await asyncio.wait(
@@ -1450,7 +1401,7 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                     await self._close_executor(executor)
 
                     raise _ToolExecutionInterrupted(
-                        "Tool execution interrupted by a stop request.",
+                        "Tool execution interrupted by a stop request."
                     )
 
                 try:

astrbot/core/astr_main_agent.py

@@ -10,7 +10,6 @@ import zoneinfo
 from collections.abc import Coroutine
 from dataclasses import dataclass, field
 from pathlib import Path
-from typing import Any
 
 from astrbot.core import logger
 from astrbot.core.agent.handoff import HandoffTool
@@ -48,9 +47,6 @@ from astrbot.core.tools.computer_tools import (
     BrowserExecTool,
     CreateSkillCandidateTool,
     CreateSkillPayloadTool,
-    CuaKeyboardTypeTool,
-    CuaMouseClickTool,
-    CuaScreenshotTool,
     EvaluateSkillCandidateTool,
     ExecuteShellTool,
     FileDownloadTool,
@@ -76,12 +72,11 @@ from astrbot.core.tools.knowledge_base_tools import (
     KnowledgeBaseQueryTool,
     retrieve_knowledge_base,
 )
+from astrbot.core.tools.message_tools import SendMessageToUserTool
 from astrbot.core.tools.web_search_tools import (
     BaiduWebSearchTool,
     BochaWebSearchTool,
     BraveWebSearchTool,
-    FirecrawlExtractWebPageTool,
-    FirecrawlWebSearchTool,
     TavilyExtractWebPageTool,
     TavilyWebSearchTool,
     normalize_legacy_web_search_config,
@@ -113,8 +108,7 @@ from astrbot.core.utils.string_utils import normalize_and_dedupe_strings
 @dataclass(slots=True)
 class MainAgentBuildConfig:
     """The main agent build configuration.
-    Most of the configs can be found in the cmd_config.json
-    """
+    Most of the configs can be found in the cmd_config.json"""
 
     tool_call_timeout: int
     """The timeout (in seconds) for a tool call.
@@ -178,8 +172,7 @@ class MainAgentBuildResult:
 
 
 def _select_provider(
-    event: AstrMessageEvent,
-    plugin_context: Context,
+    event: AstrMessageEvent, plugin_context: Context
 ) -> Provider | None:
     """Select chat provider for the event."""
     sel_provider = event.get_extra("selected_provider")
@@ -189,8 +182,7 @@ def _select_provider(
             logger.error("未找到指定的提供商: %s。", sel_provider)
         if not isinstance(provider, Provider):
             logger.error(
-                "选择的提供商类型无效(%s)，跳过 LLM 请求处理。",
-                type(provider),
+                "选择的提供商类型无效(%s)，跳过 LLM 请求处理。", type(provider)
             )
             return None
         return provider
@@ -202,8 +194,7 @@ def _select_provider(
 
 
 async def _get_session_conv(
-    event: AstrMessageEvent,
-    plugin_context: Context,
+    event: AstrMessageEvent, plugin_context: Context
 ) -> Conversation:
     conv_mgr = plugin_context.conversation_manager
     umo = event.unified_msg_origin
@@ -247,8 +238,8 @@ async def _apply_kb(
             req.func_tool = ToolSet()
         req.func_tool.add_tool(
             plugin_context.get_llm_tool_manager().get_builtin_tool(
-                KnowledgeBaseQueryTool,
-            ),
+                KnowledgeBaseQueryTool
+            )
         )
 
 
@@ -283,13 +274,13 @@ async def _apply_file_extract(
                     config.file_extract_msh_api_key,
                 )
                 for file_path in file_paths
-            ],
+            ]
         )
     else:
         logger.error("Unsupported file extract provider: %s", config.file_extract_prov)
         return
 
-    for file_content, file_name in zip(file_contents, file_names, strict=False):
+    for file_content, file_name in zip(file_contents, file_names):
         req.contexts.append(
             {
                 "role": "system",
@@ -400,8 +391,7 @@ async def _ensure_persona_and_skills(
     )
 
     set_persona_custom_error_message_on_event(
-        event,
-        extract_persona_custom_error_message_from_persona(persona),
+        event, extract_persona_custom_error_message_from_persona(persona)
     )
 
     if persona:
@@ -482,7 +472,7 @@ async def _ensure_persona_and_skills(
                             tool.name
                             for tool in tmgr.func_list
                             if not isinstance(tool, HandoffTool)
-                        ],
+                        ]
                     )
                     continue
                 if not isinstance(tools, list):
@@ -574,7 +564,7 @@ async def _ensure_img_caption(
         )
         if caption:
             req.extra_user_content_parts.append(
-                TextPart(text=f"<image_caption>{caption}</image_caption>"),
+                TextPart(text=f"<image_caption>{caption}</image_caption>")
             )
             req.image_urls = []
     except Exception as exc:  # noqa: BLE001
@@ -586,19 +576,19 @@ async def _ensure_img_caption(
 
 def _append_quoted_image_attachment(req: ProviderRequest, image_path: str) -> None:
     req.extra_user_content_parts.append(
-        TextPart(text=f"[Image Attachment in quoted message: path {image_path}]"),
+        TextPart(text=f"[Image Attachment in quoted message: path {image_path}]")
     )
 
 
 def _append_audio_attachment(req: ProviderRequest, audio_path: str) -> None:
     req.extra_user_content_parts.append(
-        TextPart(text=f"[Audio Attachment: path {audio_path}]"),
+        TextPart(text=f"[Audio Attachment: path {audio_path}]")
     )
 
 
 def _append_quoted_audio_attachment(req: ProviderRequest, audio_path: str) -> None:
     req.extra_user_content_parts.append(
-        TextPart(text=f"[Audio Attachment in quoted message: path {audio_path}]"),
+        TextPart(text=f"[Audio Attachment in quoted message: path {audio_path}]")
     )
 
 
@@ -637,7 +627,7 @@ def _get_quoted_message_parser_settings(
     overrides = provider_settings.get("quoted_message_parser")
     if not isinstance(overrides, dict):
         return DEFAULT_QUOTED_MESSAGE_SETTINGS
-    return DEFAULT_QUOTED_MESSAGE_SETTINGS.with_overrides(overrides)  # type: ignore
+    return DEFAULT_QUOTED_MESSAGE_SETTINGS.with_overrides(overrides)
 
 
 def _get_image_compress_args(
@@ -650,10 +640,8 @@ def _get_image_compress_args(
     if not isinstance(enabled, bool):
         enabled = True
 
-    raw_options = provider_settings.get("image_compress_options")
-    options: dict[str, Any] = {}
-    if isinstance(raw_options, dict):
-        options = {str(k): v for k, v in raw_options.items()}
+    raw_options = provider_settings.get("image_compress_options", {})
+    options = raw_options if isinstance(raw_options, dict) else {}
 
     max_size = options.get("max_size", IMAGE_COMPRESS_DEFAULT_MAX_SIZE)
     if not isinstance(max_size, int):
@@ -753,25 +741,22 @@ async def _process_quote_message(
                 )
                 if llm_resp.completion_text:
                     content_parts.append(
-                        f"[Image Caption in quoted message]: {llm_resp.completion_text}",
+                        f"[Image Caption in quoted message]: {llm_resp.completion_text}"
                     )
             else:
                 logger.warning("No provider found for image captioning in quote.")
         except BaseException as exc:
             logger.error("处理引用图片失败: %s", exc)
         finally:
-            if compress_path and compress_path != path:
-                from anyio import Path as AnyioPath
-
-                compress_file = AnyioPath(compress_path)
-                if await compress_file.exists():
-                    try:
-                        await compress_file.unlink()
-                    except Exception as exc:  # noqa: BLE001
-                        logger.warning(
-                            "Fail to remove temporary compressed image: %s",
-                            exc,
-                        )
+            if (
+                compress_path
+                and compress_path != path
+                and os.path.exists(compress_path)
+            ):
+                try:
+                    os.remove(compress_path)
+                except Exception as exc:  # noqa: BLE001
+                    logger.warning("Fail to remove temporary compressed image: %s", exc)
 
     quoted_content = "\n".join(content_parts)
     quoted_text = f"<Quoted Message>\n{quoted_content}\n</Quoted Message>"
@@ -829,7 +814,7 @@ async def _decorate_llm_request(
     config: MainAgentBuildConfig,
 ) -> None:
     cfg = config.provider_settings or plugin_context.get_config(
-        umo=event.unified_msg_origin,
+        umo=event.unified_msg_origin
     ).get("provider_settings", {})
 
     _apply_prompt_prefix(req, cfg)
@@ -878,7 +863,7 @@ def _plugin_tool_fix(event: AstrMessageEvent, req: ProviderRequest) -> None:
                 # 保留 MCP 工具
                 new_tool_set.add_tool(tool)
                 continue
-            mp = getattr(tool, "handler_module_path", None)
+            mp = tool.handler_module_path
             if not mp:
                 # 没有 plugin 归属信息的工具（如 subagent transfer_to_*）
                 # 不应受到会话插件过滤影响。
@@ -895,9 +880,7 @@ def _plugin_tool_fix(event: AstrMessageEvent, req: ProviderRequest) -> None:
 
 
 async def _handle_webchat(
-    event: AstrMessageEvent,
-    req: ProviderRequest,
-    prov: Provider,
+    event: AstrMessageEvent, req: ProviderRequest, prov: Provider
 ) -> None:
     from astrbot.core import db_helper
 
@@ -932,9 +915,7 @@ async def _handle_webchat(
         if not title or "<None>" in title:
             return
         logger.info(
-            "Generated chatui title for session %s: %s",
-            chatui_session_id,
-            title,
+            "Generated chatui title for session %s: %s", chatui_session_id, title
         )
         await db_helper.update_platform_session(
             session_id=chatui_session_id,
@@ -1032,22 +1013,6 @@ def _apply_sandbox_tools(
         req.func_tool.add_tool(tool_mgr.get_builtin_tool(RollbackSkillReleaseTool))
         req.func_tool.add_tool(tool_mgr.get_builtin_tool(SyncSkillReleaseTool))
 
-    if booter == "cua":
-        req.system_prompt += (
-            "\n[CUA Desktop Control]\n"
-            "Use `astrbot_execute_shell` with `background=true` to launch GUI apps. "
-            'Use Firefox for browser tasks, for example `firefox "https://example.com"`. '
-            "After each visible step, call `astrbot_cua_screenshot` with "
-            "`send_to_user=true` and `return_image_to_llm=true` so the user can "
-            "monitor progress. When typing, inspect the screenshot first and confirm "
-            "the target field is focused and empty or safe to append to. Use "
-            "`astrbot_cua_mouse_click` for coordinates and `astrbot_cua_keyboard_type` "
-            "for text input; use text=`\\n` for Enter.\n"
-        )
-        req.func_tool.add_tool(tool_mgr.get_builtin_tool(CuaScreenshotTool))
-        req.func_tool.add_tool(tool_mgr.get_builtin_tool(CuaMouseClickTool))
-        req.func_tool.add_tool(tool_mgr.get_builtin_tool(CuaKeyboardTypeTool))
-
     req.system_prompt = f"{req.system_prompt or ''}\n{SANDBOX_MODE_PROMPT}\n"
 
 
@@ -1082,16 +1047,12 @@ async def _apply_web_search_tools(
         req.func_tool.add_tool(tool_mgr.get_builtin_tool(BochaWebSearchTool))
     elif provider == "brave":
         req.func_tool.add_tool(tool_mgr.get_builtin_tool(BraveWebSearchTool))
-    elif provider == "firecrawl":
-        req.func_tool.add_tool(tool_mgr.get_builtin_tool(FirecrawlWebSearchTool))
-        req.func_tool.add_tool(tool_mgr.get_builtin_tool(FirecrawlExtractWebPageTool))
     elif provider == "baidu_ai_search":
         req.func_tool.add_tool(tool_mgr.get_builtin_tool(BaiduWebSearchTool))
 
 
 def _get_compress_provider(
-    config: MainAgentBuildConfig,
-    plugin_context: Context,
+    config: MainAgentBuildConfig, plugin_context: Context
 ) -> Provider | None:
     if not config.llm_compress_provider_id:
         return None
@@ -1114,14 +1075,12 @@ def _get_compress_provider(
 
 
 def _get_fallback_chat_providers(
-    provider: Provider,
-    plugin_context: Context,
-    provider_settings: dict,
+    provider: Provider, plugin_context: Context, provider_settings: dict
 ) -> list[Provider]:
     fallback_ids = provider_settings.get("fallback_chat_models", [])
     if not isinstance(fallback_ids, list):
         logger.warning(
-            "fallback_chat_models setting is not a list, skip fallback providers.",
+            "fallback_chat_models setting is not a list, skip fallback providers."
         )
         return []
 
@@ -1184,7 +1143,7 @@ async def build_main_agent(
             if sel_model := event.get_extra("selected_model"):
                 req.model = sel_model
             if config.provider_wake_prefix and not event.message_str.startswith(
-                config.provider_wake_prefix,
+                config.provider_wake_prefix
             ):
                 return None
 
@@ -1202,7 +1161,7 @@ async def build_main_agent(
                         event.track_temporary_local_file(image_path)
                     req.image_urls.append(image_path)
                     req.extra_user_content_parts.append(
-                        TextPart(text=f"[Image Attachment: path {image_path}]"),
+                        TextPart(text=f"[Image Attachment: path {image_path}]")
                     )
                 elif isinstance(comp, Record):
                     audio_path = await comp.convert_to_file_path()
@@ -1213,8 +1172,8 @@ async def build_main_agent(
                     file_name = comp.name or os.path.basename(file_path)
                     req.extra_user_content_parts.append(
                         TextPart(
-                            text=f"[File Attachment: name {file_name}, path {file_path}]",
-                        ),
+                            text=f"[File Attachment: name {file_name}, path {file_path}]"
+                        )
                     )
                 elif isinstance(comp, Video):
                     await _append_video_attachment(req, comp)
@@ -1223,7 +1182,7 @@ async def build_main_agent(
                 comp for comp in event.message_obj.message if isinstance(comp, Reply)
             ]
             quoted_message_settings = _get_quoted_message_parser_settings(
-                config.provider_settings,
+                config.provider_settings
             )
             fallback_quoted_image_count = 0
             for comp in reply_comps:
@@ -1253,8 +1212,8 @@ async def build_main_agent(
                                     text=(
                                         f"[File Attachment in quoted message: "
                                         f"name {file_name}, path {file_path}]"
-                                    ),
-                                ),
+                                    )
+                                )
                             )
                         elif isinstance(reply_comp, Video):
                             await _append_video_attachment(req, reply_comp, quoted=True)
@@ -1268,7 +1227,7 @@ async def build_main_agent(
                                 event,
                                 comp,
                                 settings=quoted_message_settings,
-                            ),
+                            )
                         )
                         remaining_limit = max(
                             config.max_quoted_fallback_images
@@ -1321,8 +1280,8 @@ async def build_main_agent(
                     "The user is asking in a side thread about this selected "
                     "excerpt from the previous assistant answer:\n"
                     f"<selected_excerpt>{thread_selected_text.strip()}</selected_excerpt>"
-                ),
-            ),
+                )
+            )
         )
     req.image_urls = normalize_and_dedupe_strings(req.image_urls)
     req.audio_urls = normalize_and_dedupe_strings(req.audio_urls)
@@ -1371,8 +1330,8 @@ async def build_main_agent(
             req.func_tool = ToolSet()
         req.func_tool.add_tool(
             plugin_context.get_llm_tool_manager().get_builtin_tool(
-                "send_message_to_user",
-            ),
+                SendMessageToUserTool
+            )
         )
 
     if provider.provider_config.get("max_context_tokens", 0) <= 0:
@@ -1423,9 +1382,7 @@ async def build_main_agent(
         enforce_max_turns=config.max_context_length,
         tool_schema_mode=config.tool_schema_mode,
         fallback_providers=_get_fallback_chat_providers(
-            provider,
-            plugin_context,
-            config.provider_settings,
+            provider, plugin_context, config.provider_settings
         ),
         tool_result_overflow_dir=(
             get_astrbot_system_tmp_path()

astrbot/core/pipeline/process_stage/method/agent_sub_stages/internal.py

@@ -86,23 +86,19 @@ class InternalAgentSubStage(Stage):
         self.file_extract_enabled: bool = file_extract_conf.get("enable", False)
         self.file_extract_prov: str = file_extract_conf.get("provider", "moonshotai")
         self.file_extract_msh_api_key: str = file_extract_conf.get(
-            "moonshotai_api_key",
-            "",
+            "moonshotai_api_key", ""
         )
 
         # 上下文管理相关
         self.context_limit_reached_strategy: str = settings.get(
-            "context_limit_reached_strategy",
-            "truncate_by_turns",
+            "context_limit_reached_strategy", "truncate_by_turns"
         )
         self.llm_compress_instruction: str = settings.get(
-            "llm_compress_instruction",
-            "",
+            "llm_compress_instruction", ""
         )
         self.llm_compress_keep_recent: int = settings.get("llm_compress_keep_recent", 4)
         self.llm_compress_provider_id: str = settings.get(
-            "llm_compress_provider_id",
-            "",
+            "llm_compress_provider_id", ""
         )
         self.max_context_length = settings["max_context_length"]  # int
         self.dequeue_context_length: int = min(
@@ -114,8 +110,7 @@ class InternalAgentSubStage(Stage):
 
         self.llm_safety_mode = settings.get("llm_safety_mode", True)
         self.safety_mode_strategy = settings.get(
-            "safety_mode_strategy",
-            "system_prompt",
+            "safety_mode_strategy", "system_prompt"
         )
 
         self.computer_use_runtime = settings.get("computer_use_runtime")
@@ -153,9 +148,7 @@ class InternalAgentSubStage(Stage):
         )
 
     async def process(
-        self,
-        event: AstrMessageEvent,
-        provider_wake_prefix: str,
+        self, event: AstrMessageEvent, provider_wake_prefix: str
     ) -> AsyncGenerator[None, None]:
         follow_up_capture: FollowUpCapture | None = None
         follow_up_consumed_marked = False
@@ -275,13 +268,13 @@ class InternalAgentSubStage(Stage):
                         # 获取 TTS Provider
                         tts_provider = (
                             self.ctx.plugin_manager.context.get_using_tts_provider(
-                                event.unified_msg_origin,
+                                event.unified_msg_origin
                             )
                         )
 
                         if not tts_provider:
                             logger.warning(
-                                "[Live Mode] TTS Provider 未配置，将使用普通流式模式",
+                                "[Live Mode] TTS Provider 未配置，将使用普通流式模式"
                             )
 
                         # 使用 run_live_agent，总是使用流式响应
@@ -376,7 +369,7 @@ class InternalAgentSubStage(Stage):
                             req,
                             agent_runner,
                             final_resp,
-                        ),
+                        )
                     )
 
                     # 检查事件是否被停止，如果被停止则不保存历史记录
@@ -404,7 +397,7 @@ class InternalAgentSubStage(Stage):
         except Exception as e:
             logger.error(f"Error occurred while processing agent: {e}")
             custom_error_message = extract_persona_custom_error_message_from_event(
-                event,
+                event
             )
             error_text = custom_error_message or (
                 f"Error occurred while processing agent request: {e}"
@@ -472,7 +465,7 @@ class InternalAgentSubStage(Stage):
             message_to_save.append(
                 CheckpointMessageSegment(
                     content=CheckpointData(id=checkpoint_id),
-                ).model_dump(),
+                ).model_dump()
             )
 
         # if user_aborted:

astrbot/core/platform/sources/webchat/webchat_adapter.py

@@ -17,9 +17,9 @@ from astrbot.core.platform import (
     PlatformMetadata,
 )
 from astrbot.core.platform.astr_message_event import MessageSesion
-from astrbot.core.platform.register import register_platform_adapter
 from astrbot.core.utils.astrbot_path import get_astrbot_data_path
 
+from ...register import register_platform_adapter
 from .message_parts_helper import (
     message_chain_to_storage_message_parts,
     parse_webchat_message_parts,
@@ -66,11 +66,13 @@ class WebChatAdapter(Platform):
         event_queue: asyncio.Queue,
     ) -> None:
         super().__init__(platform_config, event_queue)
+
         self.settings = platform_settings
         self.imgs_dir = os.path.join(get_astrbot_data_path(), "webchat", "imgs")
         self.attachments_dir = Path(get_astrbot_data_path()) / "attachments"
         os.makedirs(self.imgs_dir, exist_ok=True)
         self.attachments_dir.mkdir(parents=True, exist_ok=True)
+
         self.metadata = PlatformMetadata(
             name="webchat",
             description="webchat",
@@ -87,13 +89,16 @@ class WebChatAdapter(Platform):
     ) -> None:
         conversation_id = _extract_conversation_id(session.session_id)
         active_request_ids = self._webchat_queue_mgr.list_back_request_ids(
-            conversation_id,
+            conversation_id
         )
         stream_request_ids = [
             req_id for req_id in active_request_ids if not req_id.startswith("ws_sub_")
         ]
         target_request_ids = stream_request_ids or active_request_ids
+
         if not target_request_ids:
+            # No active streams to consume this proactive message.
+            # Persist directly and return to avoid creating an unused queue.
             try:
                 await self._save_proactive_message(conversation_id, message_chain)
             except Exception as e:
@@ -103,6 +108,7 @@ class WebChatAdapter(Platform):
                 )
             await super().send_by_session(session, message_chain)
             return
+
         for request_id in target_request_ids:
             await WebChatMessageEvent._send(
                 request_id,
@@ -111,6 +117,10 @@ class WebChatAdapter(Platform):
                 streaming=True,
                 emit_complete=True,
             )
+
+        # If only passive subscription queues exist for this conversation,
+        # keep a proactive save as a fallback since they are not tied to
+        # the normal streaming persistence path.
         if not stream_request_ids:
             try:
                 await self._save_proactive_message(conversation_id, message_chain)
@@ -119,6 +129,7 @@ class WebChatAdapter(Platform):
                     f"[WebChatAdapter] Failed to save proactive message: {e}",
                     exc_info=True,
                 )
+
         await super().send_by_session(session, message_chain)
 
     async def _save_proactive_message(
@@ -133,6 +144,7 @@ class WebChatAdapter(Platform):
         )
         if not message_parts:
             return
+
         await db_helper.insert_platform_message_history(
             platform_id="webchat",
             user_id=conversation_id,
@@ -142,8 +154,7 @@ class WebChatAdapter(Platform):
         )
 
     async def _get_message_history(
-        self,
-        message_id: int,
+        self, message_id: int
     ) -> PlatformMessageHistory | None:
         return await db_helper.get_platform_message_history_by_id(message_id)
 
@@ -153,16 +164,15 @@ class WebChatAdapter(Platform):
         depth: int = 0,
         max_depth: int = 1,
     ) -> tuple[list, list[str]]:
-        """解析消息段列表,返回消息组件列表和纯文本列表
+        """解析消息段列表，返回消息组件列表和纯文本列表
 
         Args:
             message_parts: 消息段列表
             depth: 当前递归深度
-            max_depth: 最大递归深度(用于处理 reply)
+            max_depth: 最大递归深度（用于处理 reply）
 
         Returns:
             tuple[list, list[str]]: (消息组件列表, 纯文本列表)
-
         """
 
         async def get_reply_parts(
@@ -171,10 +181,12 @@ class WebChatAdapter(Platform):
             history = await self._get_message_history(message_id)
             if not history or not history.content:
                 return None
+
             reply_parts = history.content.get("message", [])
             if not isinstance(reply_parts, list):
                 return None
-            return (reply_parts, history.sender_id, history.sender_name)
+
+            return reply_parts, history.sender_id, history.sender_name
 
         components, text_parts, _ = await parse_webchat_message_parts(
             message_parts,
@@ -186,19 +198,27 @@ class WebChatAdapter(Platform):
             max_reply_depth=max_depth,
             cast_reply_id_to_str=False,
         )
-        return (components, text_parts)
+        return components, text_parts
 
     async def convert_message(self, data: tuple) -> AstrBotMessage:
         username, cid, payload = data
+
         abm = AstrBotMessage()
         abm.self_id = "webchat"
         abm.sender = MessageMember(username, username)
+
         abm.type = MessageType.FRIEND_MESSAGE
+
         abm.session_id = f"webchat!{username}!{cid}"
+
         abm.message_id = payload.get("message_id")
+
+        # 处理消息段列表
         message_parts = payload.get("message", [])
         abm.message, message_str_parts = await self._parse_message_parts(message_parts)
+
         logger.debug(f"WebChatAdapter: {abm.message}")
+
         abm.timestamp = int(time.time())
         abm.message_str = "".join(message_str_parts)
         abm.raw_message = data
@@ -222,18 +242,17 @@ class WebChatAdapter(Platform):
             platform_meta=self.meta(),
             session_id=message.session_id,
         )
-        _, _, payload = message.raw_message
+
+        _, _, payload = message.raw_message  # type: ignore
         message_event.set_extra("selected_provider", payload.get("selected_provider"))
         message_event.set_extra("selected_model", payload.get("selected_model"))
         message_event.set_extra(
-            "enable_streaming",
-            payload.get("enable_streaming", True),
+            "enable_streaming", payload.get("enable_streaming", True)
         )
         message_event.set_extra("action_type", payload.get("action_type"))
         message_event.set_extra("llm_checkpoint_id", payload.get("llm_checkpoint_id"))
         message_event.set_extra(
-            "thread_selected_text",
-            payload.get("thread_selected_text"),
+            "thread_selected_text", payload.get("thread_selected_text")
         )
 
         self.commit_event(message_event)

astrbot/dashboard/routes/live_chat.py

@@ -7,7 +7,6 @@ import uuid
 import wave
 from typing import Any
 
-import anyio
 import jwt
 from quart import websocket
 
@@ -24,32 +23,12 @@ from astrbot.core.platform.sources.webchat.webchat_queue_mgr import webchat_queu
 from astrbot.core.utils.astrbot_path import get_astrbot_data_path, get_astrbot_temp_path
 from astrbot.core.utils.datetime_utils import to_utc_isoformat
 
-from .chat import (
-    BotMessageAccumulator,
-    build_bot_history_content,
-    collect_plain_text_from_message_parts,
-)
 from .route import Route, RouteContext
 
 
 class LiveChatSession:
     """Live Chat 会话管理器"""
 
-class _ReceiveTimeoutSentinel:
-    """Sentinel value indicating a receive timeout."""
-
-
-_RECEIVE_TIMEOUT = _ReceiveTimeoutSentinel()
-
-
-class _QueueTimeoutSentinel:
-    pass
-
-
-_QUEUE_TIMEOUT = _QueueTimeoutSentinel()
-
-
-class ClientSession:
     def __init__(self, session_id: str, username: str) -> None:
         self.session_id = session_id
         self.username = username
@@ -77,11 +56,11 @@ class ClientSession:
             self.audio_frames.append(data)
 
     async def end_speaking(self, stamp: str) -> tuple[str | None, float]:
-        """结束说话,返回组装的 WAV 文件路径和耗时"""
+        """结束说话，返回组装的 WAV 文件路径和耗时"""
         start_time = time.time()
         if not self.is_speaking or stamp != self.current_stamp:
             logger.warning(
-                f"[Live Chat] stamp 不匹配或未在说话状态: {stamp} vs {self.current_stamp}",
+                f"[Live Chat] stamp 不匹配或未在说话状态: {stamp} vs {self.current_stamp}"
             )
             return None, 0.0
 
@@ -97,7 +76,7 @@ class ClientSession:
             os.makedirs(temp_dir, exist_ok=True)
             audio_path = os.path.join(temp_dir, f"live_audio_{uuid.uuid4()}.wav")
 
-            # 假设前端发送的是 PCM 数据,采样率 16000Hz,单声道,16位
+            # 假设前端发送的是 PCM 数据，采样率 16000Hz，单声道，16位
             with wave.open(audio_path, "wb") as wav_file:
                 wav_file.setnchannels(1)  # 单声道
                 wav_file.setsampwidth(2)  # 16位 = 2字节
@@ -107,7 +86,7 @@ class ClientSession:
 
             self.temp_audio_path = audio_path
             logger.info(
-                f"[Live Chat] 音频文件已保存: {audio_path}, 大小: {(await anyio.Path(audio_path).stat()).st_size} bytes",
+                f"[Live Chat] 音频文件已保存: {audio_path}, 大小: {os.path.getsize(audio_path)} bytes"
             )
             return audio_path, time.time() - start_time
 
@@ -115,11 +94,11 @@ class ClientSession:
             logger.error(f"[Live Chat] 组装 WAV 文件失败: {e}", exc_info=True)
             return None, 0.0
 
-    async def cleanup(self) -> None:
+    def cleanup(self) -> None:
         """清理临时文件"""
-        if self.temp_audio_path and await anyio.Path(self.temp_audio_path).exists():
+        if self.temp_audio_path and os.path.exists(self.temp_audio_path):
             try:
-                await anyio.Path(self.temp_audio_path).unlink()
+                os.remove(self.temp_audio_path)
                 logger.debug(f"[Live Chat] 已删除临时文件: {self.temp_audio_path}")
             except Exception as e:
                 logger.warning(f"[Live Chat] 删除临时文件失败: {e}")
@@ -140,7 +119,6 @@ class LiveChatRoute(Route):
         self.db = db
         self.plugin_manager = core_lifecycle.plugin_manager
         self.platform_history_mgr = core_lifecycle.platform_message_history_manager
-        assert self.platform_history_mgr
         self.sessions: dict[str, LiveChatSession] = {}
         self.attachments_dir = os.path.join(get_astrbot_data_path(), "attachments")
         self.legacy_img_dir = os.path.join(get_astrbot_data_path(), "webchat", "imgs")
@@ -151,60 +129,17 @@ class LiveChatRoute(Route):
         self.app.websocket("/api/unified_chat/ws")(self.unified_chat_ws)
 
     async def live_chat_ws(self) -> None:
-        """Legacy Live Chat WebSocket 处理器(默认 ct=live)"""
+        """Legacy Live Chat WebSocket 处理器（默认 ct=live）"""
         await self._unified_ws_loop(force_ct="live")
 
     async def unified_chat_ws(self) -> None:
-        """Unified Chat WebSocket 处理器(支持 ct=live/chat)"""
+        """Unified Chat WebSocket 处理器（支持 ct=live/chat）"""
         await self._unified_ws_loop(force_ct=None)
 
-    async def _ensure_runtime_ready(self) -> bool:
-        if is_runtime_request_ready(self.core_lifecycle):
-            return True
-        await websocket.close(
-            1013,
-            get_runtime_guard_message(self.core_lifecycle),
-        )
-        return False
-
-    async def _recv_ws_json_guarded(
-        self,
-        *,
-        wait_timeout: float = 1.0,
-    ) -> dict[str, Any] | _ReceiveTimeoutSentinel | None:
-        if not await self._ensure_runtime_ready():
-            return None
-        try:
-            message = await asyncio.wait_for(
-                websocket.receive_json(),
-                timeout=wait_timeout,
-            )
-        except asyncio.TimeoutError:
-            return _RECEIVE_TIMEOUT
-        if not await self._ensure_runtime_ready():
-            return None
-        return message
-
-    async def _guarded_queue_get(
-        self,
-        back_queue: asyncio.Queue,
-        *,
-        wait_timeout: float,
-    ) -> dict[str, Any] | _QueueTimeoutSentinel | None:
-        if not await self._ensure_runtime_ready():
-            return None
-        try:
-            result = await asyncio.wait_for(back_queue.get(), timeout=wait_timeout)
-        except asyncio.TimeoutError:
-            return _QUEUE_TIMEOUT
-        if not await self._ensure_runtime_ready():
-            return None
-        return result
-
     async def _unified_ws_loop(self, force_ct: str | None = None) -> None:
         """统一 WebSocket 循环"""
-        # WebSocket 不能通过 header 传递 token,需要从 query 参数获取
-        # 注意:WebSocket 上下文使用 websocket.args 而不是 request.args
+        # WebSocket 不能通过 header 传递 token，需要从 query 参数获取
+        # 注意：WebSocket 上下文使用 websocket.args 而不是 request.args
         token = websocket.args.get("token")
         if not token:
             await websocket.close(1008, "Missing authentication token")
@@ -221,9 +156,6 @@ class LiveChatRoute(Route):
             await websocket.close(1008, "Invalid token")
             return
 
-        if not await self._ensure_runtime_ready():
-            return
-
         session_id = f"webchat_live!{username}!{uuid.uuid4()}"
         live_session = LiveChatSession(session_id, username)
         self.sessions[session_id] = live_session
@@ -232,11 +164,7 @@ class LiveChatRoute(Route):
 
         try:
             while True:
-                message = await self._recv_ws_json_guarded()
-                if isinstance(message, _ReceiveTimeoutSentinel):
-                    continue
-                if message is None:
-                    return
+                message = await websocket.receive_json()
                 ct = force_ct or message.get("ct", "live")
                 if ct == "chat":
                     await self._handle_chat_message(live_session, message)
@@ -250,16 +178,14 @@ class LiveChatRoute(Route):
             # 清理会话
             if session_id in self.sessions:
                 await self._cleanup_chat_subscriptions(live_session)
-                await live_session.cleanup()
+                live_session.cleanup()
                 del self.sessions[session_id]
             logger.info(f"[Live Chat] WebSocket 连接关闭: {username}")
 
     async def _create_attachment_from_file(
-        self,
-        filename: str,
-        attach_type: str,
+        self, filename: str, attach_type: str
     ) -> dict | None:
-        """从本地文件创建 attachment 并返回消息部分｡"""
+        """从本地文件创建 attachment 并返回消息部分。"""
         return await create_attachment_part_from_existing_file(
             filename,
             attach_type=attach_type,
@@ -269,12 +195,15 @@ class LiveChatRoute(Route):
         )
 
     def _extract_web_search_refs(
-        self,
-        accumulated_text: str,
-        accumulated_parts: list,
+        self, accumulated_text: str, accumulated_parts: list
     ) -> dict:
-        """从消息中提取 web_search 引用｡"""
-        supported = ["web_search_tavily", "web_search_bocha"]
+        """从消息中提取 web_search 引用。"""
+        supported = [
+            "web_search_baidu",
+            "web_search_tavily",
+            "web_search_bocha",
+            "web_search_brave",
+        ]
         web_search_results = {}
         tool_call_parts = [
             p
@@ -285,7 +214,7 @@ class LiveChatRoute(Route):
         for part in tool_call_parts:
             for tool_call in part["tool_calls"]:
                 if tool_call.get("name") not in supported or not tool_call.get(
-                    "result",
+                    "result"
                 ):
                     continue
                 try:
@@ -321,21 +250,28 @@ class LiveChatRoute(Route):
     async def _save_bot_message(
         self,
         webchat_conv_id: str,
-        message_parts: list[dict],
+        text: str,
+        media_parts: list,
+        reasoning: str,
         agent_stats: dict,
         refs: dict,
         llm_checkpoint_id: str | None = None,
     ):
         """保存 bot 消息到历史记录。"""
-        new_his = build_bot_history_content(
-            message_parts,
-            agent_stats=agent_stats,
-            refs=refs,
-        )
+        bot_message_parts = []
+        bot_message_parts.extend(media_parts)
+        if text:
+            bot_message_parts.append({"type": "plain", "text": text})
 
-        mgr = self.platform_history_mgr
-        assert mgr is not None
-        return await mgr.insert(
+        new_his = {"type": "bot", "message": bot_message_parts}
+        if reasoning:
+            new_his["reasoning"] = reasoning
+        if agent_stats:
+            new_his["agent_stats"] = agent_stats
+        if refs:
+            new_his["refs"] = refs
+
+        return await self.platform_history_mgr.insert(
             platform_id="webchat",
             user_id=webchat_conv_id,
             content=new_his,
@@ -355,16 +291,11 @@ class LiveChatRoute(Route):
         request_id: str,
     ) -> None:
         back_queue = webchat_queue_mgr.get_or_create_back_queue(
-            request_id,
-            chat_session_id,
+            request_id, chat_session_id
         )
         try:
             while True:
-                result = await self._guarded_queue_get(back_queue, wait_timeout=1)
-                if isinstance(result, _QueueTimeoutSentinel):
-                    continue
-                if result is None:
-                    break
+                result = await back_queue.get()
                 if not result:
                     continue
                 await self._send_chat_payload(session, {"ct": "chat", **result})
@@ -413,11 +344,9 @@ class LiveChatRoute(Route):
         session.chat_subscription_tasks.clear()
 
     async def _handle_chat_message(
-        self,
-        session: LiveChatSession,
-        message: dict,
+        self, session: LiveChatSession, message: dict
     ) -> None:
-        """处理 Chat Mode 消息(ct=chat)"""
+        """处理 Chat Mode 消息（ct=chat）"""
         msg_type = message.get("t")
 
         if msg_type == "bind":
@@ -528,7 +457,6 @@ class LiveChatRoute(Route):
         llm_checkpoint_id = str(uuid.uuid4())
 
         try:
-            pending_bot_message_flusher = None
             chat_queue = webchat_queue_mgr.get_or_create_queue(session_id)
             await chat_queue.put(
                 (
@@ -571,76 +499,22 @@ class LiveChatRoute(Route):
                 },
             )
 
-            message_accumulator = BotMessageAccumulator()
+            accumulated_parts = []
+            accumulated_text = ""
+            accumulated_reasoning = ""
+            tool_calls = {}
             agent_stats = {}
-            refs: dict[str, Any] = {}
-
-            async def flush_pending_bot_message():
-                nonlocal message_accumulator, agent_stats, refs
-                if not (message_accumulator.has_content() or refs or agent_stats):
-                    return None
-
-                message_parts_to_save = message_accumulator.build_message_parts(
-                    include_pending_tool_calls=True
-                )
-                plain_text = collect_plain_text_from_message_parts(
-                    message_parts_to_save
-                )
-                try:
-                    extracted_refs = self._extract_web_search_refs(
-                        plain_text,
-                        message_parts_to_save,
-                    )
-                except Exception as e:
-                    logger.exception(
-                        f"[Live Chat] Failed to extract web search refs: {e}",
-                        exc_info=True,
-                    )
-                    extracted_refs = refs
-
-                saved_record = await self._save_bot_message(
-                    session_id,
-                    message_parts_to_save,
-                    agent_stats,
-                    extracted_refs,
-                    llm_checkpoint_id,
-                )
-                message_accumulator = BotMessageAccumulator()
-                agent_stats = {}
-                refs = {}
-                return saved_record
-
-            pending_bot_message_flusher = flush_pending_bot_message
-
-            async def send_attachment_saved_event(part: dict | None) -> None:
-                if not part or not part.get("attachment_id") or not part.get("type"):
-                    return
-
-                await self._send_chat_payload(
-                    session,
-                    {
-                        "ct": "chat",
-                        "type": "attachment_saved",
-                        "data": {
-                            "id": part["attachment_id"],
-                            "type": part["type"],
-                        },
-                    },
-                )
+            refs = {}
 
             while True:
-                if not await self._ensure_runtime_ready():
-                    break
                 if session.should_interrupt:
                     session.should_interrupt = False
-                    await flush_pending_bot_message()
                     break
 
-                result = await self._guarded_queue_get(back_queue, wait_timeout=1)
-                if isinstance(result, _QueueTimeoutSentinel):
+                try:
+                    result = await asyncio.wait_for(back_queue.get(), timeout=1)
+                except asyncio.TimeoutError:
                     continue
-                if result is None:
-                    break
 
                 if not result:
                     continue
@@ -671,36 +545,68 @@ class LiveChatRoute(Route):
                 await self._send_chat_payload(session, outgoing)
 
                 if msg_type == "plain":
-                    message_accumulator.add_plain(
-                        result_text,
-                        chain_type=chain_type,
-                        streaming=streaming,
-                    )
+                    if chain_type == "tool_call":
+                        try:
+                            tool_call = json.loads(result_text)
+                            tool_calls[tool_call.get("id")] = tool_call
+                            if accumulated_text:
+                                accumulated_parts.append(
+                                    {"type": "plain", "text": accumulated_text}
+                                )
+                                accumulated_text = ""
+                        except Exception:
+                            pass
+                    elif chain_type == "tool_call_result":
+                        try:
+                            tcr = json.loads(result_text)
+                            tc_id = tcr.get("id")
+                            if tc_id in tool_calls:
+                                tool_calls[tc_id]["result"] = tcr.get("result")
+                                tool_calls[tc_id]["finished_ts"] = tcr.get("ts")
+                                accumulated_parts.append(
+                                    {
+                                        "type": "tool_call",
+                                        "tool_calls": [tool_calls[tc_id]],
+                                    }
+                                )
+                                tool_calls.pop(tc_id, None)
+                        except Exception:
+                            pass
+                    elif chain_type == "reasoning":
+                        accumulated_reasoning += result_text
+                    elif streaming:
+                        accumulated_text += result_text
+                    else:
+                        accumulated_text = result_text
                 elif msg_type == "image":
                     filename = str(result_text).replace("[IMAGE]", "")
                     part = await self._create_attachment_from_file(filename, "image")
-                    message_accumulator.add_attachment(part)
-                    await send_attachment_saved_event(part)
+                    if part:
+                        accumulated_parts.append(part)
                 elif msg_type == "record":
                     filename = str(result_text).replace("[RECORD]", "")
                     part = await self._create_attachment_from_file(filename, "record")
-                    message_accumulator.add_attachment(part)
-                    await send_attachment_saved_event(part)
+                    if part:
+                        accumulated_parts.append(part)
                 elif msg_type == "file":
                     filename = str(result_text).replace("[FILE]", "").split("|", 1)[0]
                     part = await self._create_attachment_from_file(filename, "file")
-                    message_accumulator.add_attachment(part)
-                    await send_attachment_saved_event(part)
+                    if part:
+                        accumulated_parts.append(part)
                 elif msg_type == "video":
                     filename = str(result_text).replace("[VIDEO]", "").split("|", 1)[0]
                     part = await self._create_attachment_from_file(filename, "video")
-                    message_accumulator.add_attachment(part)
-                    await send_attachment_saved_event(part)
+                    if part:
+                        accumulated_parts.append(part)
 
                 should_save = False
                 if msg_type == "end":
                     should_save = bool(
-                        message_accumulator.has_content() or refs or agent_stats
+                        accumulated_parts
+                        or accumulated_text
+                        or accumulated_reasoning
+                        or refs
+                        or agent_stats
                     )
                 elif (streaming and msg_type == "complete") or not streaming:
                     if chain_type not in (
@@ -711,7 +617,26 @@ class LiveChatRoute(Route):
                         should_save = True
 
                 if should_save:
-                    saved_record = await flush_pending_bot_message()
+                    try:
+                        refs = self._extract_web_search_refs(
+                            accumulated_text,
+                            accumulated_parts,
+                        )
+                    except Exception as e:
+                        logger.exception(
+                            f"[Live Chat] Failed to extract web search refs: {e}",
+                            exc_info=True,
+                        )
+
+                    saved_record = await self._save_bot_message(
+                        session_id,
+                        accumulated_text,
+                        accumulated_parts,
+                        accumulated_reasoning,
+                        agent_stats,
+                        refs,
+                        llm_checkpoint_id,
+                    )
                     if saved_record:
                         await self._send_chat_payload(
                             session,
@@ -721,13 +646,19 @@ class LiveChatRoute(Route):
                                 "data": {
                                     "id": saved_record.id,
                                     "created_at": to_utc_isoformat(
-                                        saved_record.created_at,
+                                        saved_record.created_at
                                     ),
                                     "llm_checkpoint_id": llm_checkpoint_id,
                                 },
                             },
                         )
 
+                    accumulated_parts = []
+                    accumulated_text = ""
+                    accumulated_reasoning = ""
+                    agent_stats = {}
+                    refs = {}
+
                 if msg_type == "end":
                     break
 
@@ -738,24 +669,16 @@ class LiveChatRoute(Route):
                 {
                     "ct": "chat",
                     "t": "error",
-                    "data": f"处理失败: {e!s}",
+                    "data": f"处理失败: {str(e)}",
                     "code": "PROCESSING_ERROR",
                 },
             )
         finally:
-            try:
-                if pending_bot_message_flusher is not None:
-                    await pending_bot_message_flusher()
-            except Exception as e:
-                logger.exception(
-                    f"[Live Chat] Failed to persist pending chat message: {e}",
-                    exc_info=True,
-                )
             session.is_processing = False
             webchat_queue_mgr.remove_back_queue(message_id)
 
     async def _build_chat_message_parts(self, message: list[dict]) -> list[dict]:
-        """构建 chat websocket 用户消息段(复用 webchat 逻辑)"""
+        """构建 chat websocket 用户消息段（复用 webchat 逻辑）"""
         return await build_webchat_message_parts(
             message,
             get_attachment_by_id=self.db.get_attachment_by_id,
@@ -801,7 +724,7 @@ class LiveChatRoute(Route):
                 await websocket.send_json({"t": "error", "data": "音频组装失败"})
                 return
 
-            # 处理音频:STT -> LLM -> TTS
+            # 处理音频：STT -> LLM -> TTS
             await self._process_audio(session, audio_path, assemble_duration)
 
         elif msg_type == "interrupt":
@@ -810,16 +733,13 @@ class LiveChatRoute(Route):
             logger.info(f"[Live Chat] 用户打断: {session.username}")
 
     async def _process_audio(
-        self,
-        session: LiveChatSession,
-        audio_path: str,
-        assemble_duration: float,
+        self, session: LiveChatSession, audio_path: str, assemble_duration: float
     ) -> None:
-        """处理音频:STT -> LLM -> 流式 TTS"""
+        """处理音频：STT -> LLM -> 流式 TTS"""
         try:
             # 发送 WAV 组装耗时
             await websocket.send_json(
-                {"t": "metrics", "data": {"wav_assemble_time": assemble_duration}},
+                {"t": "metrics", "data": {"wav_assemble_time": assemble_duration}}
             )
             wav_assembly_finish_time = time.time()
 
@@ -827,14 +747,7 @@ class LiveChatRoute(Route):
             session.should_interrupt = False
 
             # 1. STT - 语音转文字
-            pm = self.plugin_manager
-            if pm is None or pm.context is None:
-                logger.error("[Live Chat] Plugin manager not available")
-                await websocket.send_json(
-                    {"t": "error", "data": "Plugin manager not available"},
-                )
-                return
-            ctx = pm.context
+            ctx = self.plugin_manager.context
             stt_provider = ctx.provider_manager.stt_provider_insts[0]
 
             if not stt_provider:
@@ -843,7 +756,7 @@ class LiveChatRoute(Route):
                 return
 
             await websocket.send_json(
-                {"t": "metrics", "data": {"stt": stt_provider.meta().type}},
+                {"t": "metrics", "data": {"stt": stt_provider.meta().type}}
             )
 
             user_text = await stt_provider.get_text(audio_path)
@@ -857,7 +770,7 @@ class LiveChatRoute(Route):
                 {
                     "t": "user_msg",
                     "data": {"text": user_text, "ts": int(time.time() * 1000)},
-                },
+                }
             )
 
             # 2. 构造消息事件并发送到 pipeline
@@ -883,17 +796,13 @@ class LiveChatRoute(Route):
 
             try:
                 while True:
-                    if not await self._ensure_runtime_ready():
-                        break
                     if session.should_interrupt:
-                        # 用户打断,停止处理
+                        # 用户打断，停止处理
                         logger.info("[Live Chat] 检测到用户打断")
                         await websocket.send_json({"t": "stop_play"})
                         # 保存消息并标记为被打断
                         await self._save_interrupted_message(
-                            session,
-                            user_text,
-                            bot_text,
+                            session, user_text, bot_text
                         )
                         # 清空队列中未处理的消息
                         while not back_queue.empty():
@@ -903,14 +812,10 @@ class LiveChatRoute(Route):
                                 break
                         break
 
-                    result = await self._guarded_queue_get(
-                        back_queue,
-                        wait_timeout=0.5,
-                    )
-                    if isinstance(result, _QueueTimeoutSentinel):
+                    try:
+                        result = await asyncio.wait_for(back_queue.get(), timeout=0.5)
+                    except asyncio.TimeoutError:
                         continue
-                    if result is None:
-                        break
 
                     if not result:
                         continue
@@ -918,7 +823,7 @@ class LiveChatRoute(Route):
                     result_message_id = result.get("message_id")
                     if result_message_id != message_id:
                         logger.warning(
-                            f"[Live Chat] 消息 ID 不匹配: {result_message_id} != {message_id}",
+                            f"[Live Chat] 消息 ID 不匹配: {result_message_id} != {message_id}"
                         )
                         continue
 
@@ -937,7 +842,7 @@ class LiveChatRoute(Route):
                                         "llm_total_time": stats.get("end_time", 0)
                                         - stats.get("start_time", 0),
                                     },
-                                },
+                                }
                             )
                         except Exception as e:
                             logger.error(f"[Live Chat] 解析 AgentStats 失败: {e}")
@@ -950,7 +855,7 @@ class LiveChatRoute(Route):
                                 {
                                     "t": "metrics",
                                     "data": stats,
-                                },
+                                }
                             )
                         except Exception as e:
                             logger.error(f"[Live Chat] 解析 TTSStats 失败: {e}")
@@ -974,9 +879,9 @@ class LiveChatRoute(Route):
                                 {
                                     "t": "metrics",
                                     "data": {
-                                        "speak_to_first_frame": speak_to_first_frame_latency,
+                                        "speak_to_first_frame": speak_to_first_frame_latency
                                     },
-                                },
+                                }
                             )
 
                         text = result.get("text")
@@ -985,7 +890,7 @@ class LiveChatRoute(Route):
                                 {
                                     "t": "bot_text_chunk",
                                     "data": {"text": text},
-                                },
+                                }
                             )
 
                         # 发送音频数据给前端
@@ -993,14 +898,14 @@ class LiveChatRoute(Route):
                             {
                                 "t": "response",
                                 "data": data,  # base64 编码的音频数据
-                            },
+                            }
                         )
 
                     elif result_type in ["complete", "end"]:
                         # 处理完成
                         logger.info(f"[Live Chat] Bot 回复完成: {bot_text}")
 
-                        # 如果没有音频流,发送 bot 消息文本
+                        # 如果没有音频流，发送 bot 消息文本
                         if not audio_playing:
                             await websocket.send_json(
                                 {
@@ -1009,7 +914,7 @@ class LiveChatRoute(Route):
                                         "text": bot_text,
                                         "ts": int(time.time() * 1000),
                                     },
-                                },
+                                }
                             )
 
                         # 发送结束标记
@@ -1021,7 +926,7 @@ class LiveChatRoute(Route):
                             {
                                 "t": "metrics",
                                 "data": {"wav_to_tts_total_time": wav_to_tts_duration},
-                            },
+                            }
                         )
                         break
             finally:
@@ -1029,31 +934,28 @@ class LiveChatRoute(Route):
 
         except Exception as e:
             logger.error(f"[Live Chat] 处理音频失败: {e}", exc_info=True)
-            await websocket.send_json({"t": "error", "data": f"处理失败: {e!s}"})
+            await websocket.send_json({"t": "error", "data": f"处理失败: {str(e)}"})
 
         finally:
             session.is_processing = False
             session.should_interrupt = False
 
     async def _save_interrupted_message(
-        self,
-        session: LiveChatSession,
-        user_text: str,
-        bot_text: str,
+        self, session: LiveChatSession, user_text: str, bot_text: str
     ) -> None:
         """保存被打断的消息"""
         interrupted_text = bot_text + " [用户打断]"
         logger.info(f"[Live Chat] 保存打断消息: {interrupted_text}")
 
-        # 简单记录到日志,实际保存逻辑可以后续完善
+        # 简单记录到日志，实际保存逻辑可以后续完善
         try:
             timestamp = int(time.time() * 1000)
             logger.info(
-                f"[Live Chat] 用户消息: {user_text} (session: {session.session_id}, ts: {timestamp})",
+                f"[Live Chat] 用户消息: {user_text} (session: {session.session_id}, ts: {timestamp})"
             )
             if bot_text:
                 logger.info(
-                    f"[Live Chat] Bot 消息(打断): {interrupted_text} (session: {session.session_id}, ts: {timestamp})",
+                    f"[Live Chat] Bot 消息（打断）: {interrupted_text} (session: {session.session_id}, ts: {timestamp})"
                 )
         except Exception as e:
             logger.error(f"[Live Chat] 记录消息失败: {e}", exc_info=True)

dashboard/src/components/chat/ChatInput.vue

@@ -1,6 +1,7 @@
 <template>
   <div
     class="input-area fade-in"
+    :class="{ 'is-dark': isDark }"
     @dragover.prevent="handleDragOver"
     @dragleave.prevent="handleDragLeave"
     @drop.prevent="handleDrop"
@@ -14,45 +15,41 @@
         border: isDark ? 'none' : '1px solid #e0e0e0',
         borderRadius: '24px',
         boxShadow: isDark ? 'none' : '0px 2px 2px rgba(0, 0, 0, 0.1)',
-        backgroundColor: isDark ? 'rgba(15, 15, 22, 0.6)' : 'transparent',
+        backgroundColor: isDark ? '#2d2d2d' : 'transparent',
         position: 'relative',
-        transition: 'min-height 0.2s ease, padding 0.2s ease',
       }"
     >
       <!-- 拖拽上传遮罩 -->
       <transition name="fade">
         <div v-if="isDragging" class="drop-overlay">
           <div class="drop-overlay-content">
-            <v-icon size="48" color="primary"> mdi-cloud-upload </v-icon>
+            <v-icon size="48" color="primary">mdi-cloud-upload</v-icon>
             <span class="drop-text">{{ tm("input.dropToUpload") }}</span>
           </div>
         </div>
       </transition>
       <!-- 引用预览区 -->
       <transition name="slideReply" @after-leave="handleReplyAfterLeave">
-        <div v-if="props.replyTo && !isReplyClosing" class="reply-preview">
+        <div class="reply-preview" v-if="props.replyTo && !isReplyClosing">
           <div class="reply-content">
-            <v-icon size="small" class="reply-icon"> mdi-reply </v-icon>
+            <v-icon size="small" class="reply-icon">mdi-reply</v-icon>
             "<span class="reply-text">{{ props.replyTo.selectedText }}</span
             >"
           </div>
           <v-btn
+            @click="handleClearReply"
             class="remove-reply-btn"
             icon="mdi-close"
             size="x-small"
             color="grey"
             variant="text"
-            @click="handleClearReply"
           />
         </div>
       </transition>
       <textarea
         ref="inputField"
         v-model="localPrompt"
-        @compositionstart="handleCompositionStart"
-        @compositionend="handleCompositionEnd"
-        @compositioncancel="handleCompositionEnd"
-        @blur="clearCompositionState()"
+        @keydown="handleKeyDown"
         :disabled="disabled"
         placeholder="Ask AstrBot..."
         class="chat-textarea"
@@ -66,17 +63,15 @@
           outline: none;
           border: 1px solid var(--v-theme-border);
           border-radius: 12px;
-          padding: 16px 20px;
-          min-height: 40px;
+          padding: 12px 18px;
+          min-height: 34px;
           max-height: 200px;
           overflow-y: auto;
           font-family: inherit;
           font-size: 16px;
           background-color: var(--v-theme-surface);
-          transition: height 0.16s ease;
         "
-        @keydown="handleKeyDown"
-      />
+      ></textarea>
       <div
         style="
           display: flex;
@@ -103,12 +98,12 @@
             location="top start"
             :close-on-content-click="false"
           >
-            <template #activator="{ props: activatorProps }">
+            <template v-slot:activator="{ props: activatorProps }">
               <v-btn
                 v-bind="activatorProps"
                 icon="mdi-plus"
-                variant="text"
-                color="primary"
+                variant="outlined"
+                class="input-neutral-btn input-outline-control"
               />
             </template>
 
@@ -118,8 +113,8 @@
               rounded="md"
               @click="triggerImageInput"
             >
-              <template #prepend>
-                <v-icon icon="mdi-file-upload-outline" size="small" />
+              <template v-slot:prepend>
+                <v-icon icon="mdi-file-upload" size="small"></v-icon>
               </template>
               <v-list-item-title>
                 {{ tm("input.upload") }}
@@ -141,11 +136,8 @@
               rounded="md"
               @click="$emit('toggleStreaming')"
             >
-              <template #prepend>
-                <v-icon
-                  :icon="enableStreaming ? 'mdi-flash' : 'mdi-flash-off'"
-                  size="small"
-                />
+              <template v-slot:prepend>
+                <v-icon icon="mdi-lightning-bolt" size="small"></v-icon>
               </template>
               <v-list-item-title>
                 {{
@@ -173,11 +165,11 @@
           "
         >
           <input
-            ref="imageInputRef"
             type="file"
+            ref="imageInputRef"
+            @change="handleFileSelect"
             style="display: none"
             multiple
-            @change="handleFileSelect"
           />
           <v-progress-circular
             v-if="disabled && !mobile"
@@ -189,7 +181,7 @@
           <!-- <v-btn @click="$emit('openLiveMode')"
                         icon
                         variant="text"
-                        color="purple"
+                        color="purple" 
                         size="small"
                     >
                         <v-icon icon="mdi-phone-in-talk" variant="text" plain></v-icon>
@@ -198,17 +190,16 @@
                         </v-tooltip>
                     </v-btn> -->
           <v-btn
+            @click="handleRecordClick"
             icon
             variant="text"
-            :color="isRecording ? 'error' : 'primary'"
-            class="record-btn"
-            @click="handleRecordClick"
+            class="record-btn input-icon-btn"
           >
             <v-icon
               :icon="isRecording ? 'mdi-stop-circle' : 'mdi-microphone'"
               variant="text"
               plain
-            />
+            ></v-icon>
             <v-tooltip activator="parent" location="top">
               {{
                 isRecording ? tm("voice.speaking") : tm("voice.startRecording")
@@ -216,26 +207,24 @@
             </v-tooltip>
           </v-btn>
           <v-btn
-            v-if="isRunning && !canSend"
             icon
-            variant="tonal"
-            color="primary"
-            class="send-btn"
+            v-if="isRunning && !canSend"
             @click="$emit('stop')"
+            variant="tonal"
+            class="send-btn input-action-btn"
           >
-            <v-icon icon="mdi-stop" variant="text" plain />
+            <v-icon icon="mdi-stop" variant="text" plain></v-icon>
             <v-tooltip activator="parent" location="top">
               {{ tm("input.stopGenerating") }}
             </v-tooltip>
           </v-btn>
           <v-btn
             v-else
-            icon="mdi-send"
-            variant="tonal"
-            color="primary"
-            :disabled="!canSend"
-            class="send-btn"
             @click="$emit('send')"
+            icon="mdi-arrow-up"
+            variant="tonal"
+            :disabled="!canSend"
+            class="send-btn input-action-btn"
           />
         </div>
       </div>
@@ -243,12 +232,12 @@
 
     <!-- 附件预览区 -->
     <div
+      class="attachments-preview"
       v-if="
         stagedImagesUrl.length > 0 ||
         stagedAudioUrl ||
         (stagedFiles && stagedFiles.length > 0)
       "
-      class="attachments-preview"
     >
       <div
         v-for="(img, index) in stagedImagesUrl"
@@ -257,27 +246,27 @@
       >
         <img :src="img" class="preview-image" />
         <v-btn
+          @click="$emit('removeImage', index)"
           class="remove-attachment-btn"
           icon="mdi-close"
           size="small"
           color="error"
           variant="text"
-          @click="$emit('removeImage', index)"
         />
       </div>
 
       <div v-if="stagedAudioUrl" class="audio-preview">
         <v-chip color="primary" variant="tonal" class="audio-chip">
-          <v-icon start icon="mdi-microphone" size="small" />
+          <v-icon start icon="mdi-microphone" size="small"></v-icon>
           {{ tm("voice.recording") }}
         </v-chip>
         <v-btn
+          @click="$emit('removeAudio')"
           class="remove-attachment-btn"
           icon="mdi-close"
           size="small"
           color="error"
           variant="text"
-          @click="$emit('removeAudio')"
         />
       </div>
 
@@ -287,16 +276,16 @@
         class="file-preview"
       >
         <v-chip color="primary" variant="tonal" class="file-chip">
-          <v-icon start icon="mdi-file-document-outline" size="small" />
+          <v-icon start icon="mdi-file-document-outline" size="small"></v-icon>
           <span class="file-name-preview">{{ file.original_name }}</span>
         </v-chip>
         <v-btn
+          @click="$emit('removeFile', index)"
           class="remove-attachment-btn"
           icon="mdi-close"
           size="small"
           color="error"
           variant="text"
-          @click="$emit('removeFile', index)"
         />
       </div>
     </div>
@@ -315,7 +304,6 @@ import {
 import { useDisplay } from "vuetify";
 import { useModuleI18n } from "@/i18n/composables";
 import { useCustomizerStore } from "@/stores/customizer";
-import { isComposingEnter } from "@/utils/imeInput.mjs";
 import ConfigSelector from "./ConfigSelector.vue";
 import ProviderModelMenu from "./ProviderModelMenu.vue";
 import StyledMenu from "@/components/shared/StyledMenu.vue";
@@ -330,7 +318,7 @@ interface StagedFileInfo {
 }
 
 interface ReplyInfo {
-  messageId: number;
+  messageId: string | number;
   selectedText?: string;
 }
 
@@ -376,8 +364,9 @@ const emit = defineEmits<{
 }>();
 
 const { tm } = useModuleI18n("features/chat");
-// 从新的预设getter获取
-const isDark = computed(() => useCustomizerStore().isDarkTheme);
+const isDark = computed(
+  () => useCustomizerStore().uiTheme === "PurpleThemeDark",
+);
 
 const inputField = ref<HTMLTextAreaElement | null>(null);
 const imageInputRef = ref<HTMLInputElement | null>(null);
@@ -387,8 +376,6 @@ const providerModelMenuRef = ref<InstanceType<typeof ProviderModelMenu> | null>(
 const showProviderSelector = ref(true);
 const isReplyClosing = ref(false);
 const isDragging = ref(false);
-const isComposing = ref(false);
-const lastCompositionEndAt = ref<number | null>(null);
 let dragLeaveTimeout: number | null = null;
 
 const localPrompt = computed({
@@ -410,44 +397,6 @@ const canSend = computed(() => {
   );
 });
 
-const fileTypeStyles: Record<
-  string,
-  { color: string; icon: string; label: string }
-> = {
-  pdf: { color: "#d32f2f", icon: "mdi-file-pdf-box", label: "PDF" },
-  txt: { color: "#1976d2", icon: "mdi-file-document-outline", label: "TXT" },
-  md: { color: "#1976d2", icon: "mdi-language-markdown-outline", label: "MD" },
-  doc: { color: "#2b579a", icon: "mdi-file-word-box", label: "DOC" },
-  docx: { color: "#2b579a", icon: "mdi-file-word-box", label: "DOCX" },
-  xls: { color: "#217346", icon: "mdi-file-excel-box", label: "XLS" },
-  xlsx: { color: "#217346", icon: "mdi-file-excel-box", label: "XLSX" },
-  csv: { color: "#217346", icon: "mdi-file-delimited-outline", label: "CSV" },
-  zip: { color: "#7b5e00", icon: "mdi-folder-zip-outline", label: "ZIP" },
-  py: { color: "#3776ab", icon: "mdi-language-python", label: "PY" },
-  js: { color: "#b8860b", icon: "mdi-language-javascript", label: "JS" },
-  ts: { color: "#3178c6", icon: "mdi-language-typescript", label: "TS" },
-  html: { color: "#e34c26", icon: "mdi-language-html5", label: "HTML" },
-  css: { color: "#264de4", icon: "mdi-language-css3", label: "CSS" },
-  json: { color: "#6a1b9a", icon: "mdi-code-json", label: "JSON" },
-};
-
-function fileExtension(file: StagedFileInfo) {
-  const name = file.original_name || file.filename || "";
-  const extension = name.split(".").pop()?.toLowerCase() || "";
-  return extension === name.toLowerCase() ? "" : extension;
-}
-
-function filePresentation(file: StagedFileInfo) {
-  const extension = fileExtension(file);
-  return (
-    fileTypeStyles[extension] || {
-      color: "#607d8b",
-      icon: "mdi-file-document-outline",
-      label: extension ? extension.slice(0, 4).toUpperCase() : "FILE",
-    }
-  );
-}
-
 // Ctrl+B 长按录音相关
 const ctrlKeyDown = ref(false);
 const ctrlKeyTimer = ref<number | null>(null);
@@ -496,10 +445,6 @@ function handleKeyDown(e: KeyboardEvent) {
     return;
   }
 
-  if (isComposingEnter(e, isComposing.value, lastCompositionEndAt.value)) {
-    return;
-  }
-
   const isSendHotkey =
     e.ctrlKey ||
     e.metaKey ||
@@ -519,23 +464,6 @@ function handleKeyDown(e: KeyboardEvent) {
   }
 }
 
-function handleCompositionStart() {
-  isComposing.value = true;
-  lastCompositionEndAt.value = null;
-}
-
-function handleCompositionEnd(e: CompositionEvent) {
-  lastCompositionEndAt.value = e.timeStamp;
-  clearCompositionState({ keepLastEndAt: true });
-}
-
-function clearCompositionState({ keepLastEndAt = false } = {}) {
-  isComposing.value = false;
-  if (!keepLastEndAt) {
-    lastCompositionEndAt.value = null;
-  }
-}
-
 function handleKeyUp(e: KeyboardEvent) {
   if (e.keyCode === 66) {
     ctrlKeyDown.value = false;
@@ -637,7 +565,6 @@ onBeforeUnmount(() => {
   if (inputField.value) {
     inputField.value.removeEventListener("paste", handlePaste);
   }
-  clearCompositionState();
   document.removeEventListener("keyup", handleKeyUp);
 });
 
@@ -648,44 +575,101 @@ defineExpose({
 </script>
 
 <style scoped>
-/* Dark mode input container glass */
-.v-theme--bluebusinessdarktheme :deep(.input-container),
-.v-theme--bluebusinessdarktheme ::v-deep(.input-container) {
-  background: rgba(15, 15, 22, 0.6) !important;
-  backdrop-filter: blur(16px) saturate(1.2) !important;
-  border: 1px solid rgba(0, 242, 255, 0.08) !important;
-  box-shadow: 0 0 20px rgba(0, 0, 0, 0.3) !important;
-}
-
-/* Light mode: clean white frosted glass */
-.v-theme--bluebusinesstheme :deep(.input-container),
-.v-theme--bluebusinesstheme ::v-deep(.input-container) {
-  background: rgba(255, 255, 255, 0.9) !important;
-  backdrop-filter: blur(20px) saturate(1.1) !important;
-  border: 1px solid rgba(0, 49, 83, 0.1) !important;
-  box-shadow: 0 2px 12px rgba(26, 46, 60, 0.08) !important;
-}
-
-/* Fix placeholder visibility in dark mode */
-.v-theme--bluebusinessdarktheme .chat-textarea::placeholder {
-  color: rgba(228, 225, 230, 0.35) !important;
-  opacity: 1 !important;
-}
-
-/* Fix placeholder visibility in light mode */
-.v-theme--bluebusinesstheme .chat-textarea::placeholder {
-  color: rgba(26, 46, 80, 0.35) !important;
-  opacity: 1 !important;
-}
-
 .input-area {
-  padding: 16px;
+  padding: 12px 16px 0;
   background-color: transparent;
   position: relative;
   border-top: 1px solid var(--v-theme-border);
   flex-shrink: 0;
 }
 
+.input-neutral-btn {
+  color: #6f6f6f !important;
+}
+
+.input-neutral-btn:hover {
+  background: #efefef;
+}
+
+.input-neutral-btn--tonal {
+  background: #efefef;
+  color: #4f4f4f !important;
+}
+
+.input-neutral-btn--tonal:hover {
+  background: #e7e7e7;
+}
+
+.input-action-btn {
+  background: #5594c6 !important;
+  color: #fff !important;
+}
+
+.input-action-btn:hover {
+  background: #4c86b3 !important;
+}
+
+.input-action-btn:disabled {
+  background: rgba(85, 148, 198, 0.24) !important;
+  color: rgba(255, 255, 255, 0.72) !important;
+}
+
+.input-icon-btn {
+  background: transparent !important;
+  color: rgb(var(--v-theme-on-surface)) !important;
+  margin-right: 8px;
+}
+
+.input-icon-btn:hover {
+  background: rgba(var(--v-theme-on-surface), 0.04) !important;
+}
+
+.input-outline-control {
+  width: 36px !important;
+  height: 36px !important;
+  min-width: 36px !important;
+  border-color: rgba(var(--v-theme-on-surface), 0.18) !important;
+  background: transparent !important;
+}
+
+.input-outline-control:hover {
+  border-color: rgba(var(--v-theme-on-surface), 0.34) !important;
+  background: rgba(var(--v-theme-on-surface), 0.04) !important;
+}
+
+.input-area.is-dark .input-neutral-btn {
+  color: rgba(255, 255, 255, 0.78) !important;
+}
+
+.input-area.is-dark .input-neutral-btn:hover,
+.input-area.is-dark .input-neutral-btn--tonal {
+  background: rgba(255, 255, 255, 0.1);
+}
+
+.input-area.is-dark .input-outline-control {
+  border-color: rgba(255, 255, 255, 0.22) !important;
+  background: transparent !important;
+}
+
+.input-area.is-dark .input-outline-control:hover {
+  border-color: rgba(255, 255, 255, 0.42) !important;
+  background: rgba(255, 255, 255, 0.06) !important;
+}
+
+.input-area.is-dark .input-action-btn {
+  background: rgb(var(--v-theme-on-surface)) !important;
+  color: rgb(var(--v-theme-surface)) !important;
+}
+
+.input-area.is-dark .input-action-btn:hover {
+  background: rgba(var(--v-theme-on-surface), 0.86) !important;
+}
+
+.input-area.is-dark .input-action-btn:disabled {
+  background: rgba(var(--v-theme-on-surface), 0.14) !important;
+  color: rgba(var(--v-theme-on-surface), 0.4) !important;
+}
+
 /* 拖拽上传遮罩 */
 .drop-overlay {
   position: absolute;
@@ -882,20 +866,28 @@ defineExpose({
 @media (max-width: 768px) {
   .input-area {
     padding: 0 !important;
-    padding-bottom: 10px !important;
   }
 
   .input-container {
     width: 100% !important;
     max-width: 100% !important;
+    border-bottom-left-radius: 0 !important;
+    border-bottom-right-radius: 0 !important;
+  }
+
+  .input-outline-control {
+    width: 32px !important;
+    height: 32px !important;
+    min-width: 32px !important;
   }
 
   .input-area textarea,
   .chat-textarea {
-    min-height: 32px !important;
-    max-height: 160px !important;
+    min-height: 28px !important;
+    max-height: 140px !important;
     font-size: 16px !important;
-    padding: 16px 16px 12px 16px !important;
+    line-height: 20px !important;
+    padding: 8px 14px 7px !important;
   }
 }
 </style>

dashboard/src/components/chat/ChatMessageList.vue

@@ -24,54 +24,6 @@
 
         <div class="message-stack">
           <div
-            v-if="isUserMessage(msg) && userAttachmentParts(msg).length"
-            class="sent-attachments"
-            :class="{ 'images-only': hasImageOnlyAttachments(msg) }"
-          >
-            <template
-              v-for="(part, attachmentIndex) in userAttachmentParts(msg)"
-              :key="`${msgIndex}-attachment-${attachmentIndex}-${part.type}`"
-            >
-              <button
-                v-if="part.type === 'image'"
-                class="sent-attachment-card sent-image-card"
-                type="button"
-                @click="openImage(partUrl(part))"
-              >
-                <img :src="partUrl(part)" :alt="part.filename || 'image'" />
-              </button>
-
-              <div v-else class="sent-attachment-card sent-file-card">
-                <div
-                  class="sent-attachment-icon"
-                  :style="{ color: attachmentPresentation(part).color }"
-                >
-                  <v-icon :icon="attachmentPresentation(part).icon" size="24" />
-                  <span class="sent-attachment-ext">
-                    {{ attachmentPresentation(part).label }}
-                  </span>
-                </div>
-                <span class="sent-attachment-name">
-                  {{ attachmentName(part) }}
-                </span>
-                <v-btn
-                  v-if="part.type === 'file'"
-                  icon="mdi-download"
-                  size="x-small"
-                  variant="text"
-                  :loading="
-                    downloadingFiles.has(
-                      part.attachment_id || part.filename || '',
-                    )
-                  "
-                  @click="downloadPart(part)"
-                />
-              </div>
-            </template>
-          </div>
-
-          <div
-            v-if="shouldShowMessageBubble(msg)"
             class="message-bubble"
             :class="{ user: isUserMessage(msg), bot: !isUserMessage(msg) }"
             @mouseup="handleMouseUp($event, msg)"
@@ -129,7 +81,7 @@
               />
 
               <template
-                v-for="(part, partIndex) in bubbleParts(msg)"
+                v-for="(part, partIndex) in messageParts(msg)"
                 :key="`${msgIndex}-${partIndex}-${part.type}`"
               >
                 <button
@@ -465,37 +417,6 @@ function messageParts(message: ChatRecord): MessagePart[] {
   return [];
 }
 
-function isAttachmentPart(part: MessagePart) {
-  return ["image", "record", "video", "file"].includes(part.type);
-}
-
-function userAttachmentParts(message: ChatRecord) {
-  if (!isUserMessage(message)) return [];
-  return messageParts(message).filter(isAttachmentPart);
-}
-
-function hasImageOnlyAttachments(message: ChatRecord) {
-  const attachments = userAttachmentParts(message);
-  return (
-    attachments.length > 0 &&
-    attachments.every((part) => part.type === "image")
-  );
-}
-
-function bubbleParts(message: ChatRecord) {
-  if (!isUserMessage(message)) return messageParts(message);
-  return messageParts(message).filter((part) => !isAttachmentPart(part));
-}
-
-function shouldShowMessageBubble(message: ChatRecord) {
-  return (
-    !isUserMessage(message) ||
-    isEditingMessage(message) ||
-    messageContent(message).isLoading ||
-    bubbleParts(message).length > 0
-  );
-}
-
 function isMessageStreaming(message: ChatRecord, messageIndex: number) {
   return (
     props.isStreaming &&
@@ -561,74 +482,6 @@ function hasNonReasoningContent(message: ChatRecord) {
   });
 }
 
-const attachmentTypeStyles: Record<
-  string,
-  { color: string; icon: string; label: string }
-> = {
-  pdf: { color: "#d32f2f", icon: "mdi-file-pdf-box", label: "PDF" },
-  txt: { color: "#1976d2", icon: "mdi-file-document-outline", label: "TXT" },
-  md: { color: "#1976d2", icon: "mdi-language-markdown-outline", label: "MD" },
-  markdown: {
-    color: "#1976d2",
-    icon: "mdi-language-markdown-outline",
-    label: "MD",
-  },
-  doc: { color: "#2b579a", icon: "mdi-file-word-box", label: "DOC" },
-  docx: { color: "#2b579a", icon: "mdi-file-word-box", label: "DOCX" },
-  xls: { color: "#217346", icon: "mdi-file-excel-box", label: "XLS" },
-  xlsx: { color: "#217346", icon: "mdi-file-excel-box", label: "XLSX" },
-  csv: { color: "#217346", icon: "mdi-file-delimited-outline", label: "CSV" },
-  ppt: { color: "#d24726", icon: "mdi-file-powerpoint-box", label: "PPT" },
-  pptx: { color: "#d24726", icon: "mdi-file-powerpoint-box", label: "PPTX" },
-  zip: { color: "#7b5e00", icon: "mdi-folder-zip-outline", label: "ZIP" },
-  rar: { color: "#7b5e00", icon: "mdi-folder-zip-outline", label: "RAR" },
-  "7z": { color: "#7b5e00", icon: "mdi-folder-zip-outline", label: "7Z" },
-  tar: { color: "#7b5e00", icon: "mdi-folder-zip-outline", label: "TAR" },
-  gz: { color: "#7b5e00", icon: "mdi-folder-zip-outline", label: "GZ" },
-  json: { color: "#6a1b9a", icon: "mdi-code-json", label: "JSON" },
-  yaml: { color: "#6a1b9a", icon: "mdi-code-braces", label: "YAML" },
-  yml: { color: "#6a1b9a", icon: "mdi-code-braces", label: "YML" },
-  js: { color: "#b8860b", icon: "mdi-language-javascript", label: "JS" },
-  ts: { color: "#3178c6", icon: "mdi-language-typescript", label: "TS" },
-  html: { color: "#e34c26", icon: "mdi-language-html5", label: "HTML" },
-  css: { color: "#264de4", icon: "mdi-language-css3", label: "CSS" },
-  py: { color: "#3776ab", icon: "mdi-language-python", label: "PY" },
-  java: { color: "#b07219", icon: "mdi-language-java", label: "JAVA" },
-  mp3: { color: "#00897b", icon: "mdi-file-music-outline", label: "MP3" },
-  wav: { color: "#00897b", icon: "mdi-file-music-outline", label: "WAV" },
-  flac: { color: "#00897b", icon: "mdi-file-music-outline", label: "FLAC" },
-  mp4: { color: "#5e35b1", icon: "mdi-file-video-outline", label: "MP4" },
-  mov: { color: "#5e35b1", icon: "mdi-file-video-outline", label: "MOV" },
-  webm: { color: "#5e35b1", icon: "mdi-file-video-outline", label: "WEBM" },
-};
-
-function attachmentName(part: MessagePart) {
-  return part.embedded_file?.filename || part.filename || part.type || "file";
-}
-
-function attachmentExtension(part: MessagePart) {
-  const name = attachmentName(part);
-  const extension = name.split(".").pop()?.toLowerCase() || "";
-  return extension === name.toLowerCase() ? "" : extension;
-}
-
-function attachmentPresentation(part: MessagePart) {
-  if (part.type === "record") {
-    return { color: "#00897b", icon: "mdi-microphone", label: "AUDIO" };
-  }
-  if (part.type === "video") {
-    return { color: "#5e35b1", icon: "mdi-file-video-outline", label: "VIDEO" };
-  }
-  const extension = attachmentExtension(part);
-  return (
-    attachmentTypeStyles[extension] || {
-      color: "#607d8b",
-      icon: "mdi-file-document-outline",
-      label: extension ? extension.slice(0, 4).toUpperCase() : "FILE",
-    }
-  );
-}
-
 function handleMouseUp(event: MouseEvent, message: ChatRecord) {
   if (props.enableThreadSelection && !isUserMessage(message)) {
     emit("selectBotText", event, message);
@@ -895,8 +748,6 @@ function formatDuration(seconds: number) {
 }
 
 .message-stack {
-  display: flex;
-  flex-direction: column;
   max-width: min(760px, 82%);
 }
 
@@ -905,95 +756,6 @@ function formatDuration(seconds: number) {
   max-width: 60%;
 }
 
-.sent-attachments {
-  display: flex;
-  max-width: 100%;
-  gap: 10px;
-  margin-bottom: 8px;
-  padding: 2px 2px 4px;
-  overflow-x: auto;
-  overflow-y: hidden;
-  scrollbar-width: thin;
-}
-
-.sent-attachment-card {
-  position: relative;
-  display: inline-flex;
-  flex: 0 0 auto;
-  align-items: center;
-  justify-content: flex-start;
-  gap: 8px;
-  height: 64px;
-  overflow: hidden;
-  border: 1px solid rgba(var(--v-theme-on-surface), 0.1);
-  border-radius: 12px;
-  background: rgba(var(--v-theme-on-surface), 0.04);
-  color: rgb(var(--v-theme-on-surface));
-}
-
-.sent-image-card {
-  width: 64px;
-  padding: 0;
-  border: 0;
-  cursor: zoom-in;
-}
-
-.sent-image-card img {
-  width: 100%;
-  height: 100%;
-  border-radius: 11px;
-  object-fit: cover;
-}
-
-.sent-attachments.images-only {
-  max-width: min(420px, 100%);
-}
-
-.sent-attachments.images-only .sent-image-card {
-  width: 180px;
-  height: 180px;
-}
-
-.sent-attachments.images-only .sent-image-card img {
-  object-fit: cover;
-  background: rgba(var(--v-theme-on-surface), 0.04);
-}
-
-.sent-file-card {
-  width: 220px;
-  padding: 8px 10px;
-}
-
-.sent-attachment-icon {
-  display: inline-flex;
-  flex-shrink: 0;
-  min-width: 34px;
-  flex-direction: column;
-  align-items: center;
-  justify-content: center;
-  gap: 1px;
-}
-
-.sent-attachment-ext {
-  max-width: 58px;
-  overflow: hidden;
-  text-overflow: ellipsis;
-  white-space: nowrap;
-  font-size: 10px;
-  font-weight: 700;
-  line-height: 12px;
-}
-
-.sent-attachment-name {
-  min-width: 0;
-  flex: 1;
-  overflow: hidden;
-  text-overflow: ellipsis;
-  white-space: nowrap;
-  font-size: 13px;
-  line-height: 18px;
-}
-
 .bot-avatar {
   margin-top: 2px;
   color: rgb(var(--v-theme-primary));
@@ -1335,21 +1097,6 @@ function formatDuration(seconds: number) {
     max-width: 82%;
   }
 
-  .sent-file-card {
-    width: min(220px, calc(100vw - 28px));
-    height: 58px;
-  }
-
-  .sent-image-card {
-    width: 58px;
-    height: 58px;
-  }
-
-  .sent-attachments.images-only .sent-image-card {
-    width: min(180px, calc(100vw - 52px));
-    height: min(180px, calc(100vw - 52px));
-  }
-
   .message-bubble {
     padding: 9px 12px;
   }

dashboard/src/components/chat/ProviderModelMenu.vue

@@ -1,8 +1,7 @@
 <template>
-
     <v-menu v-model="menuOpen" :close-on-content-click="false" location="top" @update:model-value="handleMenuToggle">
         <template v-slot:activator="{ props: menuProps }">
-            <v-chip v-bind="menuProps" class="text-none provider-chip" variant="tonal" :size="chipSize">
+            <v-chip v-bind="menuProps" class="text-none provider-chip" variant="outlined" size="small">
                 <v-icon start size="14">mdi-creation</v-icon>
                 <span v-if="selectedProviderId">
                     {{ selectedProviderId }}
@@ -61,88 +60,78 @@
             </v-card-text>
         </v-card>
     </v-menu>
-
 </template>
 
 <script setup lang="ts">
-import { ref, computed, onMounted } from "vue";
-import { useDisplay } from "vuetify";
-import axios from "@/utils/request";
+import { ref, computed, onMounted } from 'vue';
+import axios from 'axios';
 
 interface ModelMetadata {
-  modalities?: { input?: string[] };
-  tool_call?: boolean;
-  reasoning?: boolean;
+    modalities?: { input?: string[] };
+    tool_call?: boolean;
+    reasoning?: boolean;
 }
 
 interface ProviderConfig {
-  id: string;
-  model: string;
-  api_base?: string;
-  model_metadata?: ModelMetadata;
-  enable?: boolean;
+    id: string;
+    model: string;
+    api_base?: string;
+    model_metadata?: ModelMetadata;
+    enable?: boolean;
 }
 
-const { mobile } = useDisplay();
-
 const providerConfigs = ref<ProviderConfig[]>([]);
-const selectedProviderId = ref("");
-const searchQuery = ref("");
+const selectedProviderId = ref('');
+const searchQuery = ref('');
 const menuOpen = ref(false);
 
-const chipSize = computed(() => (mobile.value ? "x-small" : "small"));
-
 const filteredProviders = computed(() => {
-  if (!searchQuery.value) {
-    return providerConfigs.value;
-  }
-  const query = searchQuery.value.toLowerCase();
-  return providerConfigs.value.filter(
-    (p) =>
-      p.id.toLowerCase().includes(query) ||
-      p.model.toLowerCase().includes(query),
-  );
+    if (!searchQuery.value) {
+        return providerConfigs.value;
+    }
+    const query = searchQuery.value.toLowerCase();
+    return providerConfigs.value.filter(p => 
+        p.id.toLowerCase().includes(query) || 
+        p.model.toLowerCase().includes(query)
+    );
 });
 
 function loadFromStorage() {
-  const savedProvider = localStorage.getItem("selectedProvider");
-  if (savedProvider) {
-    selectedProviderId.value = savedProvider;
-  }
+    const savedProvider = localStorage.getItem('selectedProvider');
+    if (savedProvider) {
+        selectedProviderId.value = savedProvider;
+    }
 }
 
 function saveToStorage() {
-  if (selectedProviderId.value) {
-    localStorage.setItem("selectedProvider", selectedProviderId.value);
-  }
+    if (selectedProviderId.value) {
+        localStorage.setItem('selectedProvider', selectedProviderId.value);
+    }
 }
 
 function loadProviderConfigs() {
-  axios
-    .get("/api/config/provider/list", {
-      params: { provider_type: "chat_completion" },
-    })
-    .then((response) => {
-      if (response.data.status === "ok") {
-        // 过滤掉 enable 为 false 的配置
-        providerConfigs.value = (response.data.data || []).filter(
-          (p: ProviderConfig) => p.enable !== false,
-        );
-      }
-    })
-    .catch((error) => {
-      console.error("获取提供商列表失败:", error);
+    axios.get('/api/config/provider/list', {
+        params: { provider_type: 'chat_completion' }
+    }).then(response => {
+        if (response.data.status === 'ok') {
+            // 过滤掉 enable 为 false 的配置
+            providerConfigs.value = (response.data.data || []).filter(
+                (p: ProviderConfig) => p.enable !== false
+            );
+        }
+    }).catch(error => {
+        console.error('获取提供商列表失败:', error);
     });
 }
 
 function selectProvider(provider: ProviderConfig) {
-  selectedProviderId.value = provider.id;
-  saveToStorage();
+    selectedProviderId.value = provider.id;
+    saveToStorage();
 }
 
 function supportsImageInput(provider: ProviderConfig): boolean {
-  const inputs = provider.model_metadata?.modalities?.input || [];
-  return inputs.includes("image");
+    const inputs = provider.model_metadata?.modalities?.input || [];
+    return inputs.includes('image');
 }
 
 function supportsAudioInput(provider: ProviderConfig): boolean {
@@ -151,90 +140,105 @@ function supportsAudioInput(provider: ProviderConfig): boolean {
 }
 
 function supportsToolCall(provider: ProviderConfig): boolean {
-  return Boolean(provider.model_metadata?.tool_call);
+    return Boolean(provider.model_metadata?.tool_call);
 }
 
 function supportsReasoning(provider: ProviderConfig): boolean {
-  return Boolean(provider.model_metadata?.reasoning);
+    return Boolean(provider.model_metadata?.reasoning);
 }
 
 function getCurrentSelection() {
-  const provider = providerConfigs.value.find(
-    (p) => p.id === selectedProviderId.value,
-  );
-  return {
-    providerId: selectedProviderId.value,
-    modelName: provider?.model || "",
-  };
+    const provider = providerConfigs.value.find(p => p.id === selectedProviderId.value);
+    return {
+        providerId: selectedProviderId.value,
+        modelName: provider?.model || ''
+    };
 }
 
 function handleMenuToggle(isOpen: boolean) {
-  if (isOpen) {
-    // 每次打开菜单时重新获取数据
-    loadProviderConfigs();
-  }
+    if (isOpen) {
+        // 每次打开菜单时重新获取数据
+        loadProviderConfigs();
+    }
 }
 
 onMounted(() => {
-  loadFromStorage();
-  loadProviderConfigs();
+    loadFromStorage();
+    loadProviderConfigs();
 });
 
 defineExpose({
-  getCurrentSelection,
+    getCurrentSelection
 });
 </script>
 
 <style scoped>
 .provider-chip {
-  cursor: pointer;
+    cursor: pointer;
+    height: 36px !important;
+    min-height: 36px !important;
+    border-color: rgba(var(--v-theme-on-surface), 0.18) !important;
+    background: transparent !important;
+    color: rgba(var(--v-theme-on-surface), 0.78) !important;
+}
+
+.provider-chip:hover {
+    border-color: rgba(var(--v-theme-on-surface), 0.34) !important;
+    background: rgba(var(--v-theme-on-surface), 0.04) !important;
 }
 
 .provider-menu-card {
-  border-radius: 12px !important;
+    border-radius: 12px !important;
 }
 
 .provider-menu-list {
-  max-height: 280px;
-  overflow-y: auto;
+    max-height: 280px;
+    overflow-y: auto;
 }
 
 .provider-menu-item {
-  margin-bottom: 2px;
-  border-radius: 8px !important;
-  min-height: 44px !important;
+    margin-bottom: 2px;
+    border-radius: 8px !important;
+    min-height: 44px !important;
 }
 
 .provider-menu-item:hover {
-  background-color: rgba(103, 58, 183, 0.05);
+    background-color: rgba(103, 58, 183, 0.05);
 }
 
 .provider-menu-item.v-list-item--active {
-  background-color: rgba(103, 58, 183, 0.1);
+    background-color: rgba(103, 58, 183, 0.1);
 }
 
 .provider-subtitle {
-  display: flex;
-  align-items: center;
-  gap: 8px;
+    display: flex;
+    align-items: center;
+    gap: 8px;
 }
 
 .model-name {
-  font-size: 12px;
-  color: var(--v-theme-secondaryText);
+    font-size: 12px;
+    color: var(--v-theme-secondaryText);
 }
 
 .meta-icons {
-  display: flex;
-  align-items: center;
-  gap: 4px;
+    display: flex;
+    align-items: center;
+    gap: 4px;
 }
 
 .empty-hint {
-  font-size: 12px;
-  color: var(--v-theme-secondaryText);
-  text-align: center;
-  padding: 16px;
-  opacity: 0.6;
+    font-size: 12px;
+    color: var(--v-theme-secondaryText);
+    text-align: center;
+    padding: 16px;
+    opacity: 0.6;
+}
+
+@media (max-width: 768px) {
+    .provider-chip {
+        height: 32px !important;
+        min-height: 32px !important;
+    }
 }
 </style>

dashboard/src/components/shared/StyledMenu.vue

@@ -1,12 +1,17 @@
 <template>
   <v-menu v-bind="$attrs" :close-on-content-click="closeOnContentClick">
-    <template #activator="{ props: activatorProps }">
-      <slot name="activator" :props="activatorProps" />
+    <template v-slot:activator="{ props: activatorProps }">
+      <slot name="activator" :props="activatorProps"></slot>
     </template>
-
-    <v-card class="styled-menu-card" elevation="8" rounded="lg">
+    
+    <v-card
+      class="styled-menu-card"
+      :class="{ 'styled-menu-card-borderless': noBorder }"
+      elevation="8"
+      rounded="lg"
+    >
       <v-list density="compact" class="styled-menu-list pa-1">
-        <slot />
+        <slot></slot>
       </v-list>
     </v-card>
   </v-menu>
@@ -14,17 +19,16 @@
 
 <script setup lang="ts">
 defineOptions({
-  inheritAttrs: false,
-});
+  inheritAttrs: false
+})
 
-withDefaults(
-  defineProps<{
-    closeOnContentClick?: boolean;
-  }>(),
-  {
-    closeOnContentClick: true,
-  },
-);
+withDefaults(defineProps<{
+  closeOnContentClick?: boolean
+  noBorder?: boolean
+}>(), {
+  closeOnContentClick: true,
+  noBorder: false
+})
 </script>
 
 <style>

dashboard/src/i18n/locales/ru-RU/features/chat.json

@@ -1,151 +1,167 @@
-{
-    "title": "Давай пообщаемся!",
-    "subtitle": "Общение с AI-помощником",
-    "input": {
-        "placeholder": "Введите сообщение...",
-        "send": "Отправить",
-        "clear": "Очистить",
-        "upload": "Загрузить файл",
-        "voice": "Голосовой ввод",
-        "recordingPrompt": "Запись... говорите",
-        "chatPrompt": "Давай пообщаемся!",
-        "dropToUpload": "Отпустите, чтобы загрузить файл",
-        "stopGenerating": "Остановить генерацию"
-    },
-    "message": {
-        "user": "Вы",
-        "assistant": "Ассистент",
-        "system": "Система",
-        "error": "Ошибка в сообщении",
-        "loading": "Думаю..."
-    },
-    "voice": {
-        "start": "Начать запись",
-        "stop": "Стоп",
-        "recording": "Запись",
-        "processing": "Обработка...",
-        "error": "Ошибка записи",
-        "listening": "Слушаю...",
-        "speaking": "Говорю",
-        "startRecording": "Начать голосовой ввод",
-        "liveMode": "Общение в реальном времени"
-    },
-    "welcome": {
-        "title": "Добро пожаловать в AstrBot",
-        "subtitle": "Ваш умный помощник",
-        "quickActions": "Быстрые действия",
-        "examples": "Примеры вопросов"
-    },
-    "actions": {
-        "copy": "Копировать",
-        "regenerate": "Перегенерировать",
-        "like": "Нравится",
-        "dislike": "Не нравится",
-        "share": "Поделиться",
-        "newChat": "Новый чат",
-        "deleteChat": "Удалить чат",
-        "editTitle": "Изменить заголовок",
-        "fullscreen": "На весь экран",
-        "exitFullscreen": "Выход из полноэкранного режима",
-        "reply": "Ответить",
-        "providerConfig": "Настройки AI",
-        "toolsUsed": "Использованные инструменты",
-        "toolCallUsed": "Использован инструмент {name}",
-        "pythonCodeAnalysis": "Использован анализ кода Python"
-    },
-    "ipython": {
-        "output": "Вывод"
-    },
-    "conversation": {
-        "newConversation": "Новый чат",
-        "noHistory": "История диалогов пуста",
-        "systemStatus": "Статус системы",
-        "llmService": "Сервис LLM",
-        "speechToText": "Преобразование речи",
-        "editDisplayName": "Изменить имя чата",
-        "displayName": "Имя чата",
-        "displayNameUpdated": "Имя чата обновлено",
-        "displayNameUpdateFailed": "Не удалось обновить имя чата",
-        "confirmDelete": "Вы уверены, что хотите удалить «{name}»? Это действие необратимо."
-    },
-    "modes": {
-        "darkMode": "Темная тема",
-        "lightMode": "Светлая тема"
-    },
-    "shortcuts": {
-        "help": "Справка",
-        "voiceRecord": "Запись голоса",
-        "pasteImage": "Вставить изображение",
-        "sendKey": {
-            "title": "Клавиша отправки",
-            "enterToSend": "Enter для отправки",
-            "shiftEnterToSend": "Shift+Enter для отправки"
-        }
-    },
-    "streaming": {
-        "enabled": "Потоковый ответ включен",
-        "disabled": "Потоковый ответ выключен",
-        "on": "Поток",
-        "off": "Обычный"
-    },
-    "transport": {
-        "title": "Протокол передачи",
-        "sse": "SSE",
-        "websocket": "WebSocket"
-    },
-    "config": {
-        "title": "Конфигурация"
-    },
-    "reasoning": {
-        "thinking": "Рассуждение"
-    },
-    "reply": {
-        "replyTo": "В ответ на",
-        "notFound": "Сообщение не найдено"
-    },
-    "project": {
-        "title": "Проект",
-        "create": "Создать проект",
-        "edit": "Изменить проект",
-        "name": "Имя проекта",
-        "emoji": "Иконка (Emoji)",
-        "description": "Описание проекта (опционально)",
-        "noSessions": "В этом проекте пока нет диалогов",
-        "confirmDelete": "Вы уверены, что хотите удалить проект «{title}»? Диалоги внутри проекта не будут удалены."
-    },
-    "time": {
-        "today": "Сегодня",
-        "yesterday": "Вчера"
-    },
-    "stats": {
-        "tokens": "Токены",
-        "inputTokens": "Входящие",
-        "outputTokens": "Исходящие",
-        "cachedTokens": "Кэшированные",
-        "duration": "Время",
-        "ttft": "Время до первого токена"
-    },
-    "refs": {
-        "title": "Ссылки",
-        "sources": "Источники"
-    },
-    "connection": {
-        "title": "Статус подключения",
-        "message": "Системе необходимо переустановить соединение с чатом.",
-        "reasons": "Это может быть вызвано следующими причинами:",
-        "reasonWindowResize": "Изменение размера окна (нормально)",
-        "reasonMultipleTabs": "Страница чата открыта в другой вкладке",
-        "reasonNetworkIssue": "Временная проблема с сетью",
-        "notice": "Примечание: для стабильной работы допускается только одно активное соединение. Если вы используете чат в нескольких вкладках, рекомендуем оставить только одну.",
-        "understand": "Понятно",
-        "status": {
-            "reconnecting": "Переподключение...",
-            "reconnected": "Соединение восстановлено",
-            "failed": "Ошибка подключения, обновите страницу"
-        }
-    },
-    "errors": {
-        "sendMessageFailed": "Ошибка отправки сообщения, попробуйте еще раз",
-        "createSessionFailed": "Ошибка создания сессии, обновите страницу"
+{
+  "title": "Давай пообщаемся!",
+  "subtitle": "Общение с AI-помощником",
+  "input": {
+    "placeholder": "Введите сообщение...",
+    "send": "Отправить",
+    "clear": "Очистить",
+    "upload": "Загрузить файл",
+    "voice": "Голосовой ввод",
+    "recordingPrompt": "Запись... говорите",
+    "chatPrompt": "Давай пообщаемся!",
+    "dropToUpload": "Отпустите, чтобы загрузить файл",
+    "stopGenerating": "Остановить генерацию"
+  },
+  "message": {
+    "user": "Вы",
+    "assistant": "Ассистент",
+    "system": "Система",
+    "error": "Ошибка в сообщении",
+    "loading": "Думаю..."
+  },
+  "voice": {
+    "start": "Начать запись",
+    "stop": "Стоп",
+    "recording": "Запись",
+    "processing": "Обработка...",
+    "error": "Ошибка записи",
+    "listening": "Слушаю...",
+    "speaking": "Говорю",
+    "startRecording": "Начать голосовой ввод",
+    "liveMode": "Общение в реальном времени"
+  },
+  "welcome": {
+    "title": "Добро пожаловать в AstrBot",
+    "subtitle": "Ваш умный помощник",
+    "quickActions": "Быстрые действия",
+    "examples": "Примеры вопросов"
+  },
+  "actions": {
+    "copy": "Копировать",
+    "regenerate": "Перегенерировать",
+    "retry": "Повторить",
+    "retryWithModel": "Использовать другую модель",
+    "noAvailableModels": "Нет доступных моделей",
+    "like": "Нравится",
+    "dislike": "Не нравится",
+    "share": "Поделиться",
+    "newChat": "Новый чат",
+    "deleteChat": "Удалить чат",
+    "editTitle": "Изменить заголовок",
+    "fullscreen": "На весь экран",
+    "exitFullscreen": "Выход из полноэкранного режима",
+    "reply": "Ответить",
+    "providerConfig": "Настройки AI",
+    "toolsUsed": "Использованные инструменты",
+    "toolCallUsed": "Использован инструмент {name}",
+    "pythonCodeAnalysis": "Использован анализ кода Python"
+  },
+  "ipython": {
+    "output": "Вывод"
+  },
+  "toolStatus": {
+    "done": "Готово",
+    "running": "Выполняется"
+  },
+  "thread": {
+    "title": "Thread",
+    "askInThread": "Спросить в ветке",
+    "count": "Веток: {count}",
+    "createFailed": "Не удалось создать ветку",
+    "delete": "Удалить ветку",
+    "confirmDelete": "Удалить эту ветку? Это действие необратимо.",
+    "placeholder": "Спросить об этом фрагменте..."
+  },
+  "conversation": {
+    "newConversation": "Новый чат",
+    "noHistory": "История диалогов пуста",
+    "systemStatus": "Статус системы",
+    "llmService": "Сервис LLM",
+    "speechToText": "Преобразование речи",
+    "editDisplayName": "Изменить имя чата",
+    "displayName": "Имя чата",
+    "displayNameUpdated": "Имя чата обновлено",
+    "displayNameUpdateFailed": "Не удалось обновить имя чата",
+    "confirmDelete": "Вы уверены, что хотите удалить «{name}»? Это действие необратимо."
+  },
+  "modes": {
+    "darkMode": "Темная тема",
+    "lightMode": "Светлая тема"
+  },
+  "shortcuts": {
+    "help": "Справка",
+    "voiceRecord": "Запись голоса",
+    "pasteImage": "Вставить изображение",
+    "sendKey": {
+      "title": "Клавиша отправки",
+      "enterToSend": "Enter для отправки",
+      "shiftEnterToSend": "Shift+Enter для отправки"
     }
+  },
+  "streaming": {
+    "enabled": "Потоковый ответ включен",
+    "disabled": "Потоковый ответ выключен",
+    "on": "Поток",
+    "off": "Обычный"
+  },
+  "transport": {
+    "title": "Протокол передачи",
+    "sse": "SSE",
+    "websocket": "WebSocket"
+  },
+  "config": {
+    "title": "Конфигурация"
+  },
+  "reasoning": {
+    "thinking": "Рассуждение"
+  },
+  "reply": {
+    "replyTo": "В ответ на",
+    "notFound": "Сообщение не найдено"
+  },
+  "project": {
+    "title": "Проект",
+    "create": "Создать проект",
+    "edit": "Изменить проект",
+    "name": "Имя проекта",
+    "emoji": "Иконка (Emoji)",
+    "description": "Описание проекта (опционально)",
+    "noSessions": "В этом проекте пока нет диалогов",
+    "confirmDelete": "Вы уверены, что хотите удалить проект «{title}»? Диалоги внутри проекта не будут удалены."
+  },
+  "time": {
+    "today": "Сегодня",
+    "yesterday": "Вчера"
+  },
+  "stats": {
+    "tokens": "Токены",
+    "inputTokens": "Входящие",
+    "outputTokens": "Исходящие",
+    "cachedTokens": "Кэшированные",
+    "duration": "Время",
+    "ttft": "Время до первого токена"
+  },
+  "refs": {
+    "title": "Ссылки",
+    "sources": "Источники"
+  },
+  "connection": {
+    "title": "Статус подключения",
+    "message": "Системе необходимо переустановить соединение с чатом.",
+    "reasons": "Это может быть вызвано следующими причинами:",
+    "reasonWindowResize": "Изменение размера окна (нормально)",
+    "reasonMultipleTabs": "Страница чата открыта в другой вкладке",
+    "reasonNetworkIssue": "Временная проблема с сетью",
+    "notice": "Примечание: для стабильной работы допускается только одно активное соединение. Если вы используете чат в нескольких вкладках, рекомендуем оставить только одну.",
+    "understand": "Понятно",
+    "status": {
+      "reconnecting": "Переподключение...",
+      "reconnected": "Соединение восстановлено",
+      "failed": "Ошибка подключения, обновите страницу"
+    }
+  },
+  "errors": {
+    "sendMessageFailed": "Ошибка отправки сообщения, попробуйте еще раз",
+    "createSessionFailed": "Ошибка создания сессии, обновите страницу"
+  }
 }