430 lines
14 KiB
Python
430 lines
14 KiB
Python
"""
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多模态文件处理服务
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处理图片、文档等多模态文件，转换为 LLM 可用的格式
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支持的 Provider:
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- DashScope (通义千问): 支持 URL 格式
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- Bedrock/Anthropic: 仅支持 base64 格式
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- OpenAI: 支持 URL 和 base64 格式
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"""
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import uuid
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from typing import List, Dict, Any, Optional, Protocol
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from sqlalchemy.orm import Session
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from app.core.logging_config import get_business_logger
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from app.core.exceptions import BusinessException
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from app.core.error_codes import BizCode
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from app.schemas.app_schema import FileInput, FileType, TransferMethod
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from app.models.generic_file_model import GenericFile
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logger = get_business_logger()
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class ImageFormatStrategy(Protocol):
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"""图片格式策略接口"""
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async def format_image(self, url: str) -> Dict[str, Any]:
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"""将图片 URL 转换为特定 provider 的格式"""
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...
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class DashScopeImageStrategy:
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"""通义千问图片格式策略"""
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async def format_image(self, url: str) -> Dict[str, Any]:
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"""通义千问格式: {"type": "image", "image": "url"}"""
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return {
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"type": "image",
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"image": url
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}
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class BedrockImageStrategy:
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"""Bedrock/Anthropic 图片格式策略"""
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async def format_image(self, url: str) -> Dict[str, Any]:
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"""
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Bedrock/Anthropic 格式: base64 编码
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{"type": "image", "source": {"type": "base64", "media_type": "...", "data": "..."}}
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"""
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import httpx
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import base64
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from mimetypes import guess_type
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logger.info(f"下载并编码图片: {url}")
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# 下载图片
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async with httpx.AsyncClient(timeout=30.0) as client:
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response = await client.get(url)
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response.raise_for_status()
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# 获取图片数据
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image_data = response.content
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# 确定 media type
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content_type = response.headers.get("content-type")
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if content_type and content_type.startswith("image/"):
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media_type = content_type
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else:
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guessed_type, _ = guess_type(url)
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media_type = guessed_type if guessed_type and guessed_type.startswith("image/") else "image/jpeg"
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# 转换为 base64
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base64_data = base64.b64encode(image_data).decode("utf-8")
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logger.info(f"图片编码完成: media_type={media_type}, size={len(base64_data)}")
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return {
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"type": "image",
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"source": {
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"type": "base64",
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"media_type": media_type,
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"data": base64_data
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}
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}
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class OpenAIImageStrategy:
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"""OpenAI 图片格式策略"""
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async def format_image(self, url: str) -> Dict[str, Any]:
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"""OpenAI 格式: {"type": "image_url", "image_url": {"url": "..."}}"""
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return {
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"type": "image_url",
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"image_url": {
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"url": url
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}
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}
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# Provider 到策略的映射
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PROVIDER_STRATEGIES = {
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"dashscope": DashScopeImageStrategy,
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"bedrock": BedrockImageStrategy,
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"anthropic": BedrockImageStrategy,
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"openai": OpenAIImageStrategy,
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}
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class MultimodalService:
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"""多模态文件处理服务"""
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def __init__(self, db: Session, provider: str = "dashscope"):
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"""
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初始化多模态服务
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Args:
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db: 数据库会话
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provider: 模型提供商（dashscope, bedrock, anthropic 等）
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"""
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self.db = db
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self.provider = provider.lower()
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async def process_files(
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self,
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files: Optional[List[FileInput]]
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) -> List[Dict[str, Any]]:
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"""
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处理文件列表，返回 LLM 可用的格式
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Args:
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files: 文件输入列表
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Returns:
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List[Dict]: LLM 可用的内容格式列表（根据 provider 返回不同格式）
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"""
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if not files:
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return []
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result = []
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for idx, file in enumerate(files):
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try:
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if file.type == FileType.IMAGE:
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content = await self._process_image(file)
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result.append(content)
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elif file.type == FileType.DOCUMENT:
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content = await self._process_document(file)
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result.append(content)
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elif file.type == FileType.AUDIO:
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content = await self._process_audio(file)
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result.append(content)
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elif file.type == FileType.VIDEO:
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content = await self._process_video(file)
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result.append(content)
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else:
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logger.warning(f"不支持的文件类型: {file.type}")
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except Exception as e:
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logger.error(
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f"处理文件失败",
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extra={
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"file_index": idx,
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"file_type": file.type,
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"error": str(e)
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}
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)
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# 继续处理其他文件，不中断整个流程
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result.append({
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"type": "text",
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"text": f"[文件处理失败: {str(e)}]"
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})
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logger.info(f"成功处理 {len(result)}/{len(files)} 个文件，provider={self.provider}")
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return result
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async def _process_image(self, file: FileInput) -> Dict[str, Any]:
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"""
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处理图片文件
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Args:
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file: 图片文件输入
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Returns:
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Dict: 根据 provider 返回不同格式
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- Anthropic/Bedrock: {"type": "image", "source": {"type": "base64", "media_type": "...", "data": "..."}}
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- 通义千问: {"type": "image", "image": "url"}
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"""
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if file.transfer_method == TransferMethod.REMOTE_URL:
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url = file.url
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else:
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# 本地文件，获取访问 URL
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url = await self._get_file_url(file.upload_file_id)
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logger.debug(f"处理图片: {url}, provider={self.provider}")
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# 根据 provider 返回不同格式
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if self.provider in ["bedrock", "anthropic"]:
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# Anthropic/Bedrock 只支持 base64 格式，需要下载并转换
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try:
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logger.info(f"开始下载并编码图片: {url}")
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base64_data, media_type = await self._download_and_encode_image(url)
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result = {
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"type": "image",
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"source": {
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"type": "base64",
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"media_type": media_type,
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"data": base64_data[:100] + "..." # 只记录前100个字符
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}
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}
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logger.info(f"图片编码完成: media_type={media_type}, data_length={len(base64_data)}")
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# 返回完整数据
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result["source"]["data"] = base64_data
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return result
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except Exception as e:
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logger.error(f"下载并编码图片失败: {e}", exc_info=True)
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# 返回错误提示
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return {
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"type": "text",
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"text": f"[图片加载失败: {str(e)}]"
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}
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else:
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# 通义千问等其他格式支持 URL
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return {
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"type": "image",
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"image": url
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}
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async def _download_and_encode_image(self, url: str) -> tuple[str, str]:
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"""
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下载图片并转换为 base64
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Args:
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url: 图片 URL
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Returns:
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tuple: (base64_data, media_type)
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"""
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import httpx
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import base64
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from mimetypes import guess_type
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# 下载图片
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async with httpx.AsyncClient(timeout=30.0) as client:
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response = await client.get(url)
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response.raise_for_status()
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# 获取图片数据
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image_data = response.content
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# 确定 media type
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content_type = response.headers.get("content-type")
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if content_type and content_type.startswith("image/"):
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media_type = content_type
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else:
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# 从 URL 推断
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guessed_type, _ = guess_type(url)
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media_type = guessed_type if guessed_type and guessed_type.startswith("image/") else "image/jpeg"
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# 转换为 base64
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base64_data = base64.b64encode(image_data).decode("utf-8")
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logger.debug(f"图片编码完成: media_type={media_type}, size={len(base64_data)}")
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return base64_data, media_type
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async def _process_document(self, file: FileInput) -> Dict[str, Any]:
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"""
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处理文档文件（PDF、Word 等）
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Args:
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file: 文档文件输入
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Returns:
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Dict: text 格式的内容（包含提取的文本）
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"""
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if file.transfer_method == TransferMethod.REMOTE_URL:
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# 远程文档暂不支持提取
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return {
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"type": "text",
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"text": f"<document url=\"{file.url}\">\n[远程文档，暂不支持内容提取]\n</document>"
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}
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else:
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# 本地文件，提取文本内容
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text = await self._extract_document_text(file.upload_file_id)
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generic_file = self.db.query(GenericFile).filter(
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GenericFile.id == file.upload_file_id
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).first()
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file_name = generic_file.file_name if generic_file else "unknown"
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return {
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"type": "text",
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"text": f"<document name=\"{file_name}\">\n{text}\n</document>"
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}
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async def _process_audio(self, file: FileInput) -> Dict[str, Any]:
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"""
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处理音频文件
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Args:
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file: 音频文件输入
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Returns:
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Dict: 音频内容（暂时返回占位符）
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"""
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# TODO: 实现音频转文字功能
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return {
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"type": "text",
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"text": "[音频文件，暂不支持处理]"
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}
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async def _process_video(self, file: FileInput) -> Dict[str, Any]:
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"""
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处理视频文件
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Args:
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file: 视频文件输入
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Returns:
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Dict: 视频内容（暂时返回占位符）
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"""
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# TODO: 实现视频处理功能
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return {
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"type": "text",
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"text": "[视频文件，暂不支持处理]"
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}
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async def _get_file_url(self, file_id: uuid.UUID) -> str:
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"""
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获取文件的访问 URL
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Args:
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file_id: 文件ID
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Returns:
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str: 文件访问 URL
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Raises:
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BusinessException: 文件不存在
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"""
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generic_file = self.db.query(GenericFile).filter(
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GenericFile.id == file_id,
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GenericFile.status == "active"
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).first()
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if not generic_file:
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raise BusinessException(
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f"文件不存在或已删除: {file_id}",
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BizCode.NOT_FOUND
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)
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# 如果有 access_url，直接返回
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if generic_file.access_url:
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return generic_file.access_url
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# 否则，根据 storage_path 生成 URL
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# TODO: 根据实际存储方式生成 URL（本地存储、OSS 等）
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# 这里暂时返回一个占位 URL
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return f"/api/files/{file_id}/download"
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async def _extract_document_text(self, file_id: uuid.UUID) -> str:
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"""
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提取文档文本内容
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Args:
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file_id: 文件ID
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Returns:
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str: 提取的文本内容
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"""
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generic_file = self.db.query(GenericFile).filter(
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GenericFile.id == file_id,
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GenericFile.status == "active"
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).first()
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if not generic_file:
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raise BusinessException(
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f"文件不存在或已删除: {file_id}",
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BizCode.NOT_FOUND
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)
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# TODO: 根据文件类型提取文本
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# - PDF: 使用 PyPDF2 或 pdfplumber
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# - Word: 使用 python-docx
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# - TXT/MD: 直接读取
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file_ext = generic_file.file_ext.lower()
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if file_ext in ['.txt', '.md', '.markdown']:
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return await self._read_text_file(generic_file.storage_path)
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elif file_ext == '.pdf':
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return await self._extract_pdf_text(generic_file.storage_path)
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elif file_ext in ['.doc', '.docx']:
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return await self._extract_word_text(generic_file.storage_path)
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else:
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return f"[不支持的文档格式: {file_ext}]"
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async def _read_text_file(self, storage_path: str) -> str:
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"""读取纯文本文件"""
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try:
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with open(storage_path, 'r', encoding='utf-8') as f:
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return f.read()
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except Exception as e:
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logger.error(f"读取文本文件失败: {e}")
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return f"[文件读取失败: {str(e)}]"
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async def _extract_pdf_text(self, storage_path: str) -> str:
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"""提取 PDF 文本"""
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try:
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# TODO: 实现 PDF 文本提取
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# import PyPDF2 或 pdfplumber
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return "[PDF 文本提取功能待实现]"
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except Exception as e:
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logger.error(f"提取 PDF 文本失败: {e}")
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return f"[PDF 提取失败: {str(e)}]"
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async def _extract_word_text(self, storage_path: str) -> str:
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"""提取 Word 文档文本"""
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try:
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# TODO: 实现 Word 文本提取
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# import docx
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return "[Word 文本提取功能待实现]"
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except Exception as e:
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logger.error(f"提取 Word 文本失败: {e}")
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return f"[Word 提取失败: {str(e)}]"
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def get_multimodal_service(db: Session) -> MultimodalService:
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"""获取多模态服务实例（依赖注入）"""
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return MultimodalService(db)
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