feat(app):

1. Handling the storage of multimodal messages and adapting to the loading of historical messages for multi-round conversations;
2. Obtain the interface for retrieving the voice status of the reply;
3. File Information Retrieval Interface
This commit is contained in:
Timebomb2018
2026-03-23 17:04:30 +08:00
parent fabc8936ab
commit a3428c2435
4 changed files with 342 additions and 55 deletions

View File

@@ -14,6 +14,9 @@ Routes:
import os
import uuid
from typing import Any
import httpx
import mimetypes
from urllib.parse import urlparse, unquote
from fastapi import APIRouter, Depends, File, HTTPException, Request, UploadFile, status
from fastapi.responses import FileResponse, RedirectResponse
@@ -91,7 +94,7 @@ async def upload_file(
if file_size > settings.MAX_FILE_SIZE:
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
status_code=status.HTTP_413_CONTENT_TOO_LARGE,
detail=f"The file size exceeds the {settings.MAX_FILE_SIZE} byte limit"
)
@@ -172,7 +175,6 @@ async def upload_file_with_share_token(
# Get share and release info from share_token
service = ReleaseShareService(db)
share_info = service.get_shared_release_info(share_token=share_data.share_token)
# Get share object to access app_id
share = service.repo.get_by_share_token(share_data.share_token)
@@ -291,6 +293,101 @@ async def upload_file_with_share_token(
)
@router.get("/files/info-by-url", response_model=ApiResponse)
async def get_file_info_by_url(
url: str,
):
"""
Get file information by network URL (no authentication required).
Fetches file metadata from a remote URL via HTTP HEAD request.
Falls back to GET request if HEAD is not supported.
Returns file type, name, and size.
Args:
url: The network URL of the file.
Returns:
ApiResponse with file information.
"""
api_logger.info(f"File info by URL request: url={url}")
try:
async with httpx.AsyncClient(timeout=10.0) as client:
# Try HEAD request first
response = await client.head(url, follow_redirects=True)
# If HEAD fails, try GET request (some servers don't support HEAD)
if response.status_code != 200:
api_logger.info(f"HEAD request failed with {response.status_code}, trying GET request")
response = await client.get(url, follow_redirects=True)
if response.status_code != 200:
api_logger.error(f"Failed to fetch file info: HTTP {response.status_code}")
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail=f"Unable to access file: HTTP {response.status_code}"
)
# Get file size from Content-Length header or actual content
file_size = response.headers.get("Content-Length")
if file_size:
file_size = int(file_size)
elif hasattr(response, 'content'):
file_size = len(response.content)
else:
file_size = None
# Get content type from Content-Type header
content_type = response.headers.get("Content-Type", "application/octet-stream")
# Remove charset and other parameters from content type
content_type = content_type.split(';')[0].strip()
# Extract filename from Content-Disposition or URL
file_name = None
content_disposition = response.headers.get("Content-Disposition")
if content_disposition and "filename=" in content_disposition:
parts = content_disposition.split("filename=")
if len(parts) > 1:
file_name = parts[1].strip('"').strip("'")
if not file_name:
parsed_url = urlparse(url)
file_name = unquote(os.path.basename(parsed_url.path)) or "unknown"
# Extract file extension from filename
_, file_ext = os.path.splitext(file_name)
# If no extension found, infer from content type
if not file_ext:
ext = mimetypes.guess_extension(content_type)
if ext:
file_ext = ext
file_name = f"{file_name}{file_ext}"
api_logger.info(f"File info retrieved: name={file_name}, size={file_size}, type={content_type}")
return success(
data={
"url": url,
"file_name": file_name,
"file_ext": file_ext.lower() if file_ext else "",
"file_size": file_size,
"content_type": content_type,
},
msg="File information retrieved successfully"
)
except HTTPException:
raise
except Exception as e:
api_logger.error(f"Unexpected error: {e}")
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=f"Failed to retrieve file information: {str(e)}"
)
@router.get("/files/{file_id}", response_model=Any)
async def download_file(
request: Request,
@@ -499,6 +596,51 @@ async def get_file_url(
)
@router.get("/files/{file_id}/public-url", response_model=ApiResponse)
async def get_permanent_file_url(
file_id: uuid.UUID,
db: Session = Depends(get_db),
storage_service: FileStorageService = Depends(get_file_storage_service),
):
"""
获取文件的永久公开 URL无过期时间
- 本地存储:返回 API 永久访问地址(基于 FILE_LOCAL_SERVER_URL 配置)
- 远程存储OSS/S3返回 bucket 公读地址(需 bucket 已配置公共读权限)
"""
file_metadata = db.query(FileMetadata).filter(FileMetadata.id == file_id).first()
if not file_metadata:
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail="The file does not exist")
if file_metadata.status != "completed":
raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST,
detail=f"File upload not completed, status: {file_metadata.status}")
file_key = file_metadata.file_key
storage = storage_service.storage
try:
if isinstance(storage, LocalStorage):
url = f"{settings.FILE_LOCAL_SERVER_URL}/storage/permanent/{file_id}"
else:
url = await storage.get_permanent_url(file_key)
if not url:
raise HTTPException(status_code=status.HTTP_501_NOT_IMPLEMENTED,
detail="Permanent URL not supported for current storage backend")
api_logger.info(f"Generated permanent URL: file_id={file_id}")
return success(
data={"url": url, "expires_in": None, "permanent": True, "file_name": file_metadata.file_name},
msg="Permanent file URL generated successfully"
)
except HTTPException:
raise
except Exception as e:
api_logger.error(f"Failed to generate permanent URL: {e}")
raise HTTPException(status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=f"Failed to generate permanent URL: {str(e)}")
@router.get("/public/{file_id}", response_model=Any)
async def public_download_file(
request: Request,
@@ -653,3 +795,44 @@ async def permanent_download_file(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=f"Failed to retrieve file: {str(e)}"
)
@router.get("/files/{file_id}/status", response_model=ApiResponse)
async def get_file_status(
file_id: uuid.UUID,
db: Session = Depends(get_db),
):
"""
Get file upload/processing status (no authentication required).
This endpoint is used to check if a file (e.g., TTS audio) is ready.
Returns status: pending, completed, or failed.
Args:
file_id: The UUID of the file.
db: Database session.
Returns:
ApiResponse with file status and metadata.
"""
api_logger.info(f"File status request: file_id={file_id}")
# Query file metadata from database
file_metadata = db.query(FileMetadata).filter(FileMetadata.id == file_id).first()
if not file_metadata:
api_logger.warning(f"File not found in database: file_id={file_id}")
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="The file does not exist"
)
return success(
data={
"file_id": str(file_id),
"status": file_metadata.status,
"file_name": file_metadata.file_name,
"file_size": file_metadata.file_size,
"content_type": file_metadata.content_type,
},
msg="File status retrieved successfully"
)

View File

@@ -119,14 +119,12 @@ class AppChatService:
)
# 加载历史消息
messages = self.conversation_service.get_messages(
history = self.conversation_service.get_conversation_history(
conversation_id=conversation_id,
limit=10
max_history=10,
current_provider=api_key_obj.provider,
current_is_omni=api_key_obj.is_omni
)
history = [
{"role": msg.role, "content": msg.content}
for msg in messages
]
# 处理多模态文件
processed_files = None
@@ -180,7 +178,8 @@ class AppChatService:
# 构建用户消息内容(含多模态文件)
human_meta = {
"files": []
"files": [],
"history_files": {}
}
assistant_meta = {
"model": api_key_obj.model_name,
@@ -195,6 +194,13 @@ class AppChatService:
"url": f.url
})
if processed_files:
human_meta["history_files"] = {
"content": processed_files,
"provider": api_key_obj.provider,
"is_omni": api_key_obj.is_omni
}
# 保存消息
if audio_url:
assistant_meta["audio_url"] = audio_url
@@ -225,6 +231,7 @@ class AppChatService:
"suggested_questions": suggested_questions,
"citations": self.agent_service._filter_citations(features_config, result.get("citations", [])),
"audio_url": audio_url,
"audio_status": "pending"
}
async def agnet_chat_stream(
@@ -314,17 +321,12 @@ class AppChatService:
)
# 加载历史消息
history = []
memory_config = {"enabled": True, 'max_history': 10}
if memory_config.get("enabled"):
messages = self.conversation_service.get_messages(
conversation_id=conversation_id,
limit=memory_config.get("max_history", 10)
)
history = [
{"role": msg.role, "content": msg.content}
for msg in messages
]
history = self.conversation_service.get_conversation_history(
conversation_id=conversation_id,
max_history=10,
current_provider=api_key_obj.provider,
current_is_omni=api_key_obj.is_omni
)
# 处理多模态文件
processed_files = None
@@ -347,8 +349,14 @@ class AppChatService:
total_tokens = 0
text_queue: asyncio.Queue = asyncio.Queue()
api_key_config = {
"model_name": api_key_obj.model_name,
"api_key": api_key_obj.api_key,
"api_base": api_key_obj.api_base,
"provider": api_key_obj.provider,
}
stream_audio_url, tts_task = await self.agent_service._generate_tts_streaming(
features_config, api_key_obj,
features_config, api_key_config,
text_queue=text_queue,
tenant_id=tenant_id, workspace_id=workspace_id
)
@@ -378,7 +386,7 @@ class AppChatService:
elapsed_time = time.time() - start_time
ModelApiKeyService.record_api_key_usage(self.db, api_key_obj.id)
# 发送结束事件(包含 suggested_questions、tts、citations
# 发送结束事件(包含 suggested_questions、tts、audio_status、citations
end_data: dict = {"elapsed_time": elapsed_time, "message_length": len(full_content), "error": None}
sq_config = features_config.get("suggested_questions_after_answer", {})
if isinstance(sq_config, dict) and sq_config.get("enabled"):
@@ -388,11 +396,23 @@ class AppChatService:
"api_base": api_key_obj.api_base}, {}
)
end_data["audio_url"] = stream_audio_url
# 检查TTS是否已完成非阻塞不取消任务
audio_status = "pending"
if tts_task is not None and tts_task.done():
# 任务已完成,检查是否有异常
try:
tts_task.result()
audio_status = "completed"
except Exception as e:
logger.warning(f"TTS任务异常: {e}")
audio_status = "failed"
end_data["audio_status"] = audio_status if stream_audio_url else None
end_data["citations"] = self.agent_service._filter_citations(features_config, [])
# 保存消息
human_meta = {
"files":[]
"files":[],
"history_files": {}
}
assistant_meta = {
"model": api_key_obj.model_name,
@@ -402,11 +422,16 @@ class AppChatService:
if files:
for f in files:
# url = await MultimodalService(self.db).get_file_url(f)
human_meta["files"].append({
"type": f.type,
"url": f.url
})
if processed_files:
human_meta["history_files"] = {
"content": processed_files,
"provider": api_key_obj.provider,
"is_omni": api_key_obj.is_omni
}
if stream_audio_url:
assistant_meta["audio_url"] = stream_audio_url

View File

@@ -119,25 +119,27 @@ class ConversationService:
def get_user_conversations(
self,
user_id: uuid.UUID
) -> list[Conversation]:
user_id: uuid.UUID,
page: int = 1,
page_size: int = 20
) -> tuple[list[Conversation], int]:
"""
Retrieve recent conversations for a specific user
This method delegates persistence logic to the repository layer and
applies service-level defaults (e.g. recent conversation limit).
Retrieve recent conversations for a specific user with pagination.
Args:
user_id (uuid.UUID): Unique identifier of the user.
page (int): Page number (1-based). Defaults to 1.
page_size (int): Number of items per page. Defaults to 20.
Returns:
list[Conversation]: A list of recent conversation entities.
tuple[list[Conversation], int]: A list of recent conversation entities and total count.
"""
conversations = self.conversation_repo.get_conversation_by_user_id(
conversations, total = self.conversation_repo.get_conversation_by_user_id(
user_id,
limit=10
page=page,
page_size=page_size
)
return conversations
return conversations, total
def list_conversations(
self,
@@ -270,7 +272,9 @@ class ConversationService:
def get_conversation_history(
self,
conversation_id: uuid.UUID,
max_history: Optional[int] = None
max_history: Optional[int] = None,
current_provider: Optional[str] = None,
current_is_omni: Optional[bool] = None
) -> List[dict]:
"""
Retrieve historical conversation messages formatted as dictionaries.
@@ -278,6 +282,8 @@ class ConversationService:
Args:
conversation_id (uuid.UUID): Conversation UUID.
max_history (Optional[int]): Maximum number of messages to retrieve.
current_provider (Optional[str]): Current provider for file handling.
current_is_omni (Optional[bool]): Current omni flag for file handling.
Returns:
List[dict]: List of message dictionaries with keys 'role' and 'content'.
@@ -287,14 +293,30 @@ class ConversationService:
limit=max_history
)
# 转换为字典格式
history = [
{
history = []
for msg in messages:
msg_dict = {
"role": msg.role,
"content": msg.content
"content": [{"type": "text", "text": msg.content}]
}
for msg in messages
]
# 处理用户消息中的多模态文件
if msg.role == "user" and msg.meta_data:
history_files = msg.meta_data.get("history_files", {})
if history_files and current_provider and current_is_omni is not None:
# 检查是否需要重新处理文件
stored_provider = history_files.get("provider")
stored_is_omni = history_files.get("is_omni")
# 如果provider或is_omni不匹配需要重新处理
if stored_provider != current_provider or stored_is_omni != current_is_omni:
continue
# provider和is_omni匹配直接使用存储的内容
msg_dict["content"].extend(history_files.get("content"))
history.append(msg_dict)
return history
@@ -510,6 +532,7 @@ class ConversationService:
provider = api_config.provider
api_key = api_config.api_key
api_base = api_config.api_base
is_omni = api_config.is_omni
model_type = config.type
llm = RedBearLLM(
@@ -517,14 +540,17 @@ class ConversationService:
model_name=model_name,
provider=provider,
api_key=api_key,
base_url=api_base
base_url=api_base,
is_omni=is_omni
),
type=ModelType(model_type)
)
conversation_messages = self.get_conversation_history(
conversation_id=conversation_id,
max_history=20
max_history=20,
current_provider=provider,
current_is_omni=is_omni
)
if len(conversation_messages) == 0:
return ConversationOut(

View File

@@ -582,7 +582,9 @@ class AgentRunService:
# 6. 加载历史消息
history = await self._load_conversation_history(
conversation_id=conversation_id,
max_history=10
max_history=10,
current_provider=api_key_config.get("provider"),
current_is_omni=api_key_config.get("is_omni", False)
)
# 6. 处理多模态文件
@@ -659,7 +661,10 @@ class AgentRunService:
})
},
files=files,
audio_url=audio_url
processed_files=processed_files,
audio_url=audio_url,
provider=api_key_config.get("provider"),
is_omni=api_key_config.get("is_omni", False)
)
response = {
@@ -676,6 +681,7 @@ class AgentRunService:
) if not sub_agent else [],
"citations": self._filter_citations(features_config, result.get("citations", [])),
"audio_url": audio_url,
"audio_status": "pending"
}
logger.info(
@@ -818,7 +824,9 @@ class AgentRunService:
# 6. 加载历史消息
history = await self._load_conversation_history(
conversation_id=conversation_id,
max_history=memory_config.get("max_history", 10)
max_history=memory_config.get("max_history", 10),
current_provider=api_key_config.get("provider"),
current_is_omni=api_key_config.get("is_omni", False)
)
# 6. 处理多模态文件
@@ -905,10 +913,13 @@ class AgentRunService:
"usage": {"prompt_tokens": 0, "completion_tokens": 0, "total_tokens": total_tokens}
},
files=files,
audio_url=stream_audio_url
processed_files=processed_files,
audio_url=stream_audio_url,
provider=api_key_config.get("provider"),
is_omni=api_key_config.get("is_omni", False)
)
# 12. 发送结束事件(包含 suggested_questions 和 tts
# 12. 发送结束事件(包含 suggested_questions、audio_url 和 audio_status
end_data: Dict[str, Any] = {
"conversation_id": conversation_id,
"elapsed_time": elapsed_time,
@@ -919,6 +930,17 @@ class AgentRunService:
features_config, full_content, api_key_config, effective_params
)
end_data["audio_url"] = stream_audio_url
# 检查TTS是否已完成非阻塞不取消任务
audio_status = "pending"
if tts_task is not None and tts_task.done():
# 任务已完成,检查是否有异常
try:
tts_task.result()
audio_status = "completed"
except Exception as e:
logger.warning(f"TTS任务异常: {e}")
audio_status = "failed"
end_data["audio_status"] = audio_status if stream_audio_url else None
end_data["citations"] = self._filter_citations(features_config, [])
yield self._format_sse_event("end", end_data)
@@ -1115,13 +1137,17 @@ class AgentRunService:
async def _load_conversation_history(
self,
conversation_id: str,
max_history: int = 10
max_history: int = 10,
current_provider: Optional[str] = None,
current_is_omni: Optional[bool] = None
) -> List[Dict[str, str]]:
"""加载会话历史消息
"""加载会话历史消息,并根据当前模型配置处理多模态文件
Args:
conversation_id: 会话ID
max_history: 最大历史消息数量
current_provider: 当前模型的provider
current_is_omni: 当前模型的is_omni
Returns:
List[Dict]: 历史消息列表
@@ -1131,7 +1157,9 @@ class AgentRunService:
conversation_service = ConversationService(self.db)
history = conversation_service.get_conversation_history(
conversation_id=uuid.UUID(conversation_id),
max_history=max_history
max_history=max_history,
current_provider=current_provider,
current_is_omni=current_is_omni
)
logger.debug(
@@ -1159,7 +1187,10 @@ class AgentRunService:
app_id: Optional[uuid.UUID] = None,
user_id: Optional[str] = None,
files: Optional[List[FileInput]] = None,
audio_url: Optional[str] = None
processed_files: Optional[List[Dict[str, Any]]] = None,
audio_url: Optional[str] = None,
provider: Optional[str] = None,
is_omni: Optional[bool] = None
) -> None:
"""保存会话消息(会话已通过 _ensure_conversation 确保存在)
@@ -1170,6 +1201,11 @@ class AgentRunService:
app_id: 应用ID未使用保留用于兼容性
user_id: 用户ID未使用保留用于兼容性
meta_data: token消耗
files: 原始文件输入
processed_files: 处理后的文件
audio_url: 音频URL
provider: 模型供应商
is_omni: 是否为全模态模型
"""
try:
from app.services.conversation_service import ConversationService
@@ -1179,15 +1215,24 @@ class AgentRunService:
# 保存消息(会话已经存在)
human_meta = {
"files": []
"files": [],
"history_files": {}
}
if files:
for f in files:
# url = await MultimodalService(self.db).get_file_url(f)
human_meta["files"].append({
"type": f.type,
"url": f.url
})
# 保存 history_files包含 provider 和 is_omni 信息
if processed_files:
human_meta["history_files"] = {
"content": processed_files,
"provider": provider,
"is_omni": is_omni
}
# 保存用户消息
conversation_service.add_message(
conversation_id=conv_uuid,
@@ -1413,8 +1458,9 @@ class AgentRunService:
workspace_id: Optional[uuid.UUID] = None,
) -> tuple[Optional[str], Optional[asyncio.Task]]:
"""文本流式输入并行合成音频。
返回 (audio_url, task)audio_url 立即可用task 完成后文件内容就绪。
返回 (audio_url, task)audio_url 立即可用pending状态task 完成后文件内容就绪。
调用方向 text_queue put 文本 chunk结束时 put None。
前端可通过 GET /storage/files/{file_id}/status 轮询检查音频是否就绪。
"""
tts_config = features_config.get("text_to_speech", {})
if not isinstance(tts_config, dict) or not tts_config.get("enabled"):
@@ -1801,6 +1847,7 @@ class AgentRunService:
),
"cost_estimate": self._estimate_cost(usage, model_info["model_config"]),
"audio_url": result.get("audio_url"),
"audio_status": result.get("audio_status"),
"citations": result.get("citations", []),
"suggested_questions": result.get("suggested_questions", []),
"error": None
@@ -1878,6 +1925,7 @@ class AgentRunService:
"results": [{
**r,
"audio_url": r.get("audio_url"),
"audio_status": r.get("audio_status"),
"citations": r.get("citations", []),
"suggested_questions": r.get("suggested_questions", []),
} for r in results],
@@ -2009,6 +2057,7 @@ class AgentRunService:
full_content = ""
returned_conversation_id = model_conversation_id
audio_url = None
audio_status = None
citations = []
suggested_questions = []
@@ -2067,6 +2116,7 @@ class AgentRunService:
# 从 end 事件中提取 features 输出字段
if event_type == "end" and event_data:
audio_url = event_data.get("audio_url")
audio_status = event_data.get("audio_status")
citations = event_data.get("citations", [])
suggested_questions = event_data.get("suggested_questions", [])
@@ -2096,6 +2146,7 @@ class AgentRunService:
"message": full_content,
"elapsed_time": elapsed,
"audio_url": audio_url,
"audio_status": audio_status,
"citations": citations,
"suggested_questions": suggested_questions,
"error": None
@@ -2110,6 +2161,7 @@ class AgentRunService:
"elapsed_time": elapsed,
"message_length": len(full_content),
"audio_url": audio_url,
"audio_status": audio_status,
"citations": citations,
"suggested_questions": suggested_questions,
"timestamp": time.time()
@@ -2246,6 +2298,7 @@ class AgentRunService:
"message": r.get("message"),
"elapsed_time": r.get("elapsed_time", 0),
"audio_url": r.get("audio_url"),
"audio_status": r.get("audio_status"),
"citations": r.get("citations", []),
"suggested_questions": r.get("suggested_questions", []),
"error": r.get("error")