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Merge pull request #674 from SuanmoSuanyangTechnology/feature/agent-tool_xjn

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feat(app)
This commit is contained in:
Mark
2026-03-23 17:20:12 +08:00
committed by GitHub
parent 93deb286a3 95b7df7e38
commit 1060074740
4 changed files with 271 additions and 122 deletions
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139
api/app/controllers/file_storage_controller.py
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
@@ -290,6 +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,
@@ -697,3 +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"
)

104
api/app/services/app_chat_service.py
View File

@@ -129,39 +129,12 @@ 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 = []
for msg in messages:
content = [{"type": "text", "text": msg.content}]
# 处理 meta_data 中的 files
if msg.meta_data and msg.meta_data.get("files"):
files = msg.meta_data.get("files", [])
# 使用 MultimodalService 处理文件
multimodal_service = MultimodalService(self.db, api_config=model_info)
# 将 files 转换为 FileInput 格式
file_inputs = []
for file in files:
from app.schemas.app_schema import FileInput, TransferMethod
file_input = FileInput(
type=file.get("type"),
transfer_method=TransferMethod.REMOTE_URL,
url=file.get("url")
)
file_inputs.append(file_input)
history_processed_files = await multimodal_service.history_process_files(files=file_inputs)
content.extend(history_processed_files)
history.append({
"role": msg.role,
"content": content
})
# 处理多模态文件
processed_files = None
@@ -206,7 +179,8 @@ 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,
@@ -221,6 +195,13 @@ 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
@@ -251,6 +232,7 @@ 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(
@@ -350,39 +332,12 @@ 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 = []
for msg in messages:
content = [{"type": "text", "text": msg.content}]
# 处理 meta_data 中的 files
if msg.meta_data and msg.meta_data.get("files"):
history_files = msg.meta_data.get("files", [])
# 使用 MultimodalService 处理文件
multimodal_service = MultimodalService(self.db, api_config=model_info)
# 将 files 转换为 FileInput 格式
file_inputs = []
for file in history_files:
from app.schemas.app_schema import FileInput, TransferMethod
file_input = FileInput(
type=file.get("type"),
transfer_method=TransferMethod.REMOTE_URL,
url=file.get("url")
)
file_inputs.append(file_input)
history_processed_files = await multimodal_service.history_process_files(files=file_inputs)
content.extend(history_processed_files)
history.append({
"role": msg.role,
"content": content
})
# 处理多模态文件
processed_files = None
@@ -433,7 +388,7 @@ 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"):
@@ -443,11 +398,23 @@ 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,
@@ -457,11 +424,16 @@ 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

71
api/app/services/conversation_service.py
View File

@@ -274,7 +274,8 @@ class ConversationService:
self,
conversation_id: uuid.UUID,
max_history: Optional[int] = None,
api_config: Optional[ModelInfo] = None
current_provider: Optional[str] = None,
current_is_omni: Optional[bool] = None
) -> List[dict]:
"""
Retrieve historical conversation messages formatted as dictionaries.
@@ -282,7 +283,8 @@ class ConversationService:
Args:
conversation_id (uuid.UUID): Conversation UUID.
max_history (Optional[int]): Maximum number of messages to retrieve.
api_config (Optional[ModelInfo]): Model API configuration for multimodal processing.
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'.
@@ -292,38 +294,30 @@ class ConversationService:
limit=max_history
)
# 转换为字典格式
history = []
for msg in messages:
content = [{"type": "text", "text": msg.content}]
# 处理 meta_data 中的 files
if msg.meta_data and msg.meta_data.get("files"):
files = msg.meta_data.get("files", [])
if api_config:
# 使用 MultimodalService 处理文件
from app.services.multimodal_service import MultimodalService
multimodal_service = MultimodalService(self.db, api_config=api_config)
# 将 files 转换为 FileInput 格式
file_inputs = []
for file in files:
from app.schemas.app_schema import FileInput, TransferMethod
file_input = FileInput(
type=file.get("type"),
transfer_method=TransferMethod.REMOTE_URL,
url=file.get("url")
)
file_inputs.append(file_input)
processed_files = await multimodal_service.history_process_files(files=file_inputs)
content.extend(processed_files)
history.append({
msg_dict = {
"role": msg.role,
"content": content
})
"content": [{"type": "text", "text": msg.content}]
}
# 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
@@ -539,6 +533,7 @@ 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(
@@ -546,7 +541,8 @@ 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)
)
@@ -554,15 +550,8 @@ class ConversationService:
conversation_messages = await self.get_conversation_history(
conversation_id=conversation_id,
max_history=20,
api_config=ModelInfo(
model_name=model_name,
provider=provider,
api_key=api_key,
api_base=api_base,
capability=api_config.capability,
is_omni=api_config.is_omni,
model_type=model_type
)
current_provider=provider,
current_is_omni=is_omni
)
if len(conversation_messages) == 0:
return ConversationOut(

79
api/app/services/draft_run_service.py
View File

@@ -592,8 +592,9 @@ class AgentRunService:
# 6. 加载历史消息
history = await self._load_conversation_history(
conversation_id=conversation_id,
api_config=model_info,
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
@@ -661,7 +662,10 @@ 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 = {
@@ -678,6 +682,7 @@ 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(
@@ -830,8 +835,9 @@ class AgentRunService:
# 6. 加载历史消息
history = await self._load_conversation_history(
conversation_id=conversation_id,
api_config=model_info,
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
@@ -909,10 +915,13 @@ 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,
@@ -923,6 +932,17 @@ 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)
@@ -1119,14 +1139,17 @@ class AgentRunService:
async def _load_conversation_history(
self,
conversation_id: str,
api_config: ModelInfo | None = None,
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
@@ -1138,7 +1161,8 @@ class AgentRunService:
history = await conversation_service.get_conversation_history(
conversation_id=uuid.UUID(conversation_id),
max_history=max_history,
api_config=api_config
current_provider=current_provider,
current_is_omni=current_is_omni
)
logger.debug(
@@ -1166,7 +1190,10 @@ 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）
@@ -1177,6 +1204,11 @@ 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
@@ -1186,15 +1218,24 @@ 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,
@@ -1420,8 +1461,9 @@ 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"):
@@ -1808,6 +1850,7 @@ 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
@@ -1885,6 +1928,7 @@ 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],
@@ -2016,6 +2060,7 @@ class AgentRunService:
full_content = ""
returned_conversation_id = model_conversation_id
audio_url = None
audio_status = None
citations = []
suggested_questions = []
@@ -2074,6 +2119,7 @@ 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", [])
@@ -2103,6 +2149,7 @@ class AgentRunService:
"message": full_content,
"elapsed_time": elapsed,
"audio_url": audio_url,
"audio_status": audio_status,
"citations": citations,
"suggested_questions": suggested_questions,
"error": None
@@ -2117,6 +2164,7 @@ 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()
@@ -2253,6 +2301,7 @@ 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")