LongjoeAgent/api/routes.py

import base64
from datetime import datetime
from typing import List
from fastapi import APIRouter, HTTPException

from utils.device_id import get_device_id
from .models import (
    ChatRequest, ChatResponse, OCRRequest, MessageCreateBill,
    ImageVectorRequest, ImageVectorResponse, BuildIndexRequest, BuildIndexResponse,
    SearchRequest, SearchResponse, SearchResultItem
)
from core.chat_service import chat_service
from core.agent_manager import agent_manager
from core.image_search_service import image_search_service
from utils.logger import chat_logger
from tools.tool_factory import get_all_tools
import time
from utils.registration_manager import registration_manager
from core.ocr_service import PaddleOCRService
from core.document_processor.document_service import DocumentProcessingService

# 初始化服务
ocr_service = PaddleOCRService(
    api_url="https://a8l0g1qda8zd48nb.aistudio-app.com/ocr",
    token="f97d214abf87d5ea3c156e21257732a3b19661cb",
)
doc_service = DocumentProcessingService(ocr_service=ocr_service)


router = APIRouter()


@router.post("/chat", response_model=ChatResponse)
async def chat_endpoint(request: ChatRequest):
    """聊天接口"""
    try:
        result = await chat_service.process_chat_request(request.model_dump())
        return ChatResponse(**result)
    except Exception as e:
        chat_logger.error(f"API处理失败: {str(e)}")
        raise HTTPException(status_code=500, detail=f"处理失败: {str(e)}")


@router.post("/ocr")
async def orc(request: OCRRequest):
    """OCR接口"""
    try:
        chat_logger.info(f"开始进行图片识别")

        # 1. 解码Base64图片
        try:
            if "," in request.image:
                # 去掉 data:image/xxx;base64, 前缀
                base64_str = request.image.split(",", 1)[1]
            else:
                base64_str = request.image

            image_bytes = base64.b64decode(base64_str)

        except Exception as e:
            chat_logger.error(f"图片解码失败: {e}")
            raise HTTPException(400, f"图片格式错误: {str(e)}")

        # 2. OCR识别
        result = await doc_service.pure_ocr(image_bytes=image_bytes)

        # 3. 返回结果
        return result

    except HTTPException:
        raise
    except Exception as e:
        chat_logger.error(f"处理失败: {e}")
        raise HTTPException(500, f"处理失败: {str(e)}")


@router.post("/ocr_create_bill")
async def ocr_create_bill_endpoint(request: OCRRequest):
    """
    处理单张图片
    请求格式：
    {
        "image": "data:image/jpeg;base64,/9j/4AAQSkZJRg...",
        "type": "invoice",
    }
    """
    try:
        chat_logger.info(f"开始处理 {request.type} 单据")

        # 1. 解码Base64图片
        try:
            if "," in request.image:
                # 去掉 data:image/xxx;base64, 前缀
                base64_str = request.image.split(",", 1)[1]
            else:
                base64_str = request.image

            image_bytes = base64.b64decode(base64_str)

        except Exception as e:
            chat_logger.error(f"图片解码失败: {e}")
            raise HTTPException(400, f"图片格式错误: {str(e)}")

        # 2. 处理单据
        result = await doc_service.ocr_create_bill(
            image_bytes=image_bytes, document_type=request.type
        )

        # 3. 返回结果
        return {
            "success": True,
            "type": request.type,
            "text": result.get("ocr_text", ""),  # 识别出的文本
            "data": result.get("parsed_data", {}),  # 结构化数据
            "timestamp": datetime.now().isoformat(),
        }

    except HTTPException:
        raise
    except Exception as e:
        chat_logger.error(f"处理失败: {e}")
        raise HTTPException(500, f"处理失败: {str(e)}")


@router.post("/message_create_bill")
async def message_create_bill_endpoint(request: MessageCreateBill):
    """
    通过文本消息辅助建立单据
    请求格式：
    {
        "message": "这是一条单据描述",
        "document_type": "invoice",
    }
    """
    try:
        result = await doc_service.message_create_bill(
            message=request.message, document_type=request.document_type
        )
        return result
    except Exception as e:
        chat_logger.error(f"处理失败: {e}")
        raise HTTPException(500, f"处理失败: {str(e)}")


@router.get("/cache/status")
async def cache_status():
    """查看缓存状态 - 修复版本"""
    try:
        cache_status = await agent_manager.get_cache_status()

        # ✅ 确保返回完整信息
        return {
            "success": True,
            "cache_size": cache_status.get("cache_size", 0),
            "cache_expiry_seconds": cache_status.get("cache_expiry_seconds", 3600),
            "cache_entries_count": len(cache_status.get("cache_entries", [])),
            "cache_entries": cache_status.get("cache_entries", []),
            "timestamp": time.time(),
        }
    except Exception as e:
        chat_logger.error(f"获取缓存状态失败: {str(e)}")
        return {
            "success": False,
            "error": str(e),
            "cache_size": 0,
            "cache_entries_count": 0,
            "cache_entries": [],
        }


@router.delete("/cache/clear")
async def clear_cache():
    """清空缓存"""
    try:
        # ✅ 使用异步版本
        cleared = await agent_manager.clear_cache()
        chat_logger.info(f"清空agent缓存, 清理数量={cleared}")
        return {
            "cleared_entries": cleared,
            "message": "缓存已清空",
            "status": "success",
        }
    except Exception as e:
        chat_logger.error(f"清空缓存失败: {str(e)}")
        raise HTTPException(status_code=500, detail=f"清空缓存失败: {str(e)}")


@router.get("/health")
async def health_check():
    """健康检查"""
    try:
        # ✅ 使用异步版本

        registration_status = await registration_manager.check_registration()

        return {
            "status": "healthy",
            "service": "龙嘉软件AI助手API",
            "registration_status": (
                "已注册" if registration_status else "未注册或注册过期"
            ),
            "device_id": get_device_id(),
            "timestamp": time.time(),
        }
    except Exception as e:
        return {
            "status": "unhealthy",
            "service": "龙嘉软件AI助手API",
            "error": str(e),
            "timestamp": time.time(),
        }


@router.get("/tools/status")
async def tools_status():
    """查看工具状态"""
    try:
        tools = get_all_tools()
        tool_info = []

        for i, tool in enumerate(tools):
            tool_info.append(
                {
                    "index": i + 1,
                    "name": getattr(tool, "name", "unknown"),
                    "description": getattr(tool, "description", "unknown")[:100]
                    + "...",
                }
            )

        return {"total_tools": len(tools), "tools": tool_info, "status": "success"}
    except Exception as e:
        chat_logger.error(f"获取工具状态失败: {str(e)}")
        raise HTTPException(status_code=500, detail=f"获取工具状态失败: {str(e)}")


@router.post("/cache/initialize")
async def initialize_cache():
    """初始化缓存系统"""
    try:
        # ✅ 使用异步版本
        await agent_manager.initialize()
        chat_logger.info("缓存系统初始化完成")
        return {"status": "success", "message": "缓存系统初始化完成"}
    except Exception as e:
        chat_logger.error(f"初始化缓存失败: {str(e)}")
        raise HTTPException(status_code=500, detail=f"初始化缓存失败: {str(e)}")


@router.post("/cache/shutdown")
async def shutdown_cache():
    """关闭缓存系统"""
    try:
        # ✅ 使用异步版本
        cleared = await agent_manager.shutdown()
        chat_logger.info(f"缓存系统已关闭，清理了 {cleared} 个实例")
        return {
            "cleared_entries": cleared,
            "message": "缓存系统已关闭",
            "status": "success",
        }
    except Exception as e:
        chat_logger.error(f"关闭缓存失败: {str(e)}")
        raise HTTPException(status_code=500, detail=f"关闭缓存失败: {str(e)}")


@router.post("/admin/refresh-registration")
async def refresh_registration():
    """手动刷新注册状态（管理员用）"""
    registration_manager.force_refresh()
    return {"status": "success", "message": "注册状态已刷新"}


@router.get("/admin/registration-status")
async def get_registration_status():
    """获取注册状态（管理员用）"""
    status = await registration_manager.check_registration()
    status_info = registration_manager.get_status()
    return {"is_registered": status, "status_info": status_info}


@router.get("/")
async def root():
    registration_status = await registration_manager.check_registration()

    base_info = {
        "service": "龙嘉软件AI助手API",
        "version": "1.0.0",
        "registration_status": "active" if registration_status else "expired",
        "device_id": get_device_id(),
    }

    if registration_status:
        base_info.update(
            {
                "endpoints": {
                    "POST /chat": "聊天",
                    "GET /health": "健康检查",
                    "GET /cache/status": "查看agent缓存状态",
                    "DELETE /cache/clear": "清空agent缓存",
                    "GET /": "API信息",
                }
            }
        )
    else:
        base_info.update(
            {
                "message": "⚠️ 服务注册已过期，部分功能受限",
                "available_endpoints": {
                    "GET /health": "健康检查",
                    "GET /registration/status": "查看注册状态",
                    "GET /service/info": "服务完整信息",
                    "GET /": "API信息",
                },
                "restricted_endpoints": {"POST /chat": "AI聊天功能（需续费）"},
                "support_contact": "请联系管理员续费服务",
            }
        )

    return base_info


@router.post("/image/vector/batch", response_model=List[ImageVectorResponse])
async def batch_calculate_vectors_endpoint(requests: List[ImageVectorRequest]):
    """批量计算图片特征向量"""
    try:
        # 构建请求数据
        image_items = []
        for req in requests:
            image_items.append({
                "image": req.image,
                "image_id": req.image_id
            })
        
        # 调用服务
        results = await image_search_service.batch_calculate_vectors(image_items)
        
        # 构建响应
        responses = []
        for result in results:
            response = ImageVectorResponse(
                success=result.get("success", False),
                image_id=result.get("image_id"),
                vector=result.get("vector"),
                error=result.get("error")
            )
            responses.append(response)
        
        return responses
        
    except Exception as e:
        chat_logger.error(f"批量计算图片特征向量失败: {str(e)}")
        raise HTTPException(status_code=500, detail=f"处理失败: {str(e)}")


@router.post("/image/index/build", response_model=BuildIndexResponse)
async def build_index_endpoint(request: BuildIndexRequest):
    """构建索引及映射关系"""
    try:
        # 构建请求数据
        image_vectors = []
        for item in request.image_vectors:
            image_vectors.append({
                "image_id": item.image_id,
                "vector": item.vector,
                "image_name": item.image_name,
                "image_path": item.image_path
            })
        
        # 调用服务
        indexed_count = await image_search_service.build_index(image_vectors)
        
        # 构建响应
        response = BuildIndexResponse(
            success=True,
            indexed_count=indexed_count
        )
        
        return response
        
    except Exception as e:
        chat_logger.error(f"构建索引失败: {str(e)}")
        raise HTTPException(status_code=500, detail=f"处理失败: {str(e)}")


@router.post("/image/search", response_model=SearchResponse)
async def search_endpoint(request: SearchRequest):
    """搜索相似图片（支持以图搜图和以文搜图）"""
    try:
        import time
        start_time = time.time()
        
        # 处理图片数据
        image_bytes = None
        if request.image:
            try:
                if "," in request.image:
                    base64_str = request.image.split(",", 1)[1]
                else:
                    base64_str = request.image
                
                image_bytes = base64.b64decode(base64_str)
                
            except Exception as e:
                chat_logger.error(f"图片解码失败: {e}")
                raise HTTPException(400, f"图片格式错误: {str(e)}")
        
        # 调用服务
        results = await image_search_service.search(
            image_bytes=image_bytes,
            text=request.text,
            top_k=request.top_k
        )
        
        # 计算处理时间
        processing_time = time.time() - start_time
        
        # 构建响应
        search_results = []
        for result in results:
            item = SearchResultItem(
                image_id=result.get("image_id"),
                similarity=result.get("similarity"),
                image_name=result.get("image_name"),
                image_path=result.get("image_path")
            )
            search_results.append(item)
        
        response = SearchResponse(
            success=True,
            results=search_results,
            total_count=len(search_results),
            processing_time=round(processing_time, 4)
        )
        
        return response
        
    except HTTPException:
        raise
    except Exception as e:
        chat_logger.error(f"搜索失败: {str(e)}")
        raise HTTPException(status_code=500, detail=f"处理失败: {str(e)}")


@router.get("/image/index/status")
async def get_index_status_endpoint():
    """获取索引状态"""
    try:
        status = await image_search_service.get_index_status()
        return {
            "success": True,
            "status": status
        }
        
    except Exception as e:
        chat_logger.error(f"获取索引状态失败: {str(e)}")
        raise HTTPException(status_code=500, detail=f"处理失败: {str(e)}")


@router.post("/image/index/clear")
async def clear_index_endpoint():
    """清空索引"""
    try:
        await image_search_service.clear_index()
        return {
            "success": True,
            "message": "索引已清空"
        }
        
    except Exception as e:
        chat_logger.error(f"清空索引失败: {str(e)}")
        raise HTTPException(status_code=500, detail=f"处理失败: {str(e)}")