From dc639e8d392756f031e44a44aaaeae921c77d13a Mon Sep 17 00:00:00 2001 From: jinye_huang Date: Mon, 4 Aug 2025 13:43:52 +0800 Subject: [PATCH] =?UTF-8?q?=E4=BF=AE=E6=94=B9=E4=BA=86=E6=8E=A5=E5=8F=97?= =?UTF-8?q?=E7=9A=84=E6=A0=BC=E5=BC=8F?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- api/models/__pycache__/poster.cpython-312.pyc | Bin 5741 -> 5819 bytes api/models/__pycache__/tweet.cpython-312.pyc | Bin 9875 -> 10235 bytes api/models/poster.py | 4 +- api/models/tweet.py | 4 +- api/routers/__pycache__/tweet.cpython-312.pyc | Bin 17308 -> 18587 bytes .../database_service.cpython-312.pyc | Bin 51756 -> 47135 bytes .../__pycache__/poster.cpython-312.pyc | Bin 26354 -> 66448 bytes .../__pycache__/tweet.cpython-312.pyc | Bin 20543 -> 36834 bytes api/services/poster.py | 47 +- api/services/tweet.py | 376 ++++++++- config/database.json | 2 +- run_api.py | 2 +- 海报Fabric.js前端对接文档.md | 711 ++++++++++++++++++ 13 files changed, 1110 insertions(+), 36 deletions(-) create mode 100644 海报Fabric.js前端对接文档.md diff --git a/api/models/__pycache__/poster.cpython-312.pyc b/api/models/__pycache__/poster.cpython-312.pyc index a1f538f1f920b6b5f3fe4e9dc69817fb2fc05cf4..baa0d02f87808514096141f0da96eb606b22349f 100644 GIT binary patch delta 1216 zcmZ{i%TE(g6vpSy^xaNNAHzEc@@gYP3sME-8G{r7Z!i81;Ic+YJNwW)3L&AoHZ{hf2ZJNtFdb@i>P zIwb!4+_QB4_lEkAklV0EVpa#U6!F*alN_=;nVq?qg{e>^R}(jM%9X?eNv?TtQ?6CK z%m*8CiQ;Dgc*ma_f9}gABp>WbB`E-1nJg{ju-!+mc5mECjLouRO?xly?X6zly|w)9 z@mgwK@yM-BJY!j6Qk+mJE>l8fs!-FoOwH6nt<*;C;_skN>ROShy5g81apj6T{SW(ahqZ7r1(j`d|$>_#qBg#pXqbRv%j$$AR!>*?m zVMG+p_=})Moo~;W33Eg@qJTIeS`z%MS!0+SgRko0G%zNBRqmHLfr21dVo<@)0`?=Y zAIdxp4$&d*lXtyZYT9#3COSOx_W3a|5He>v2wq>ImW2`q#G%7iIww%V_q@zgSSy$B zXE7kUGvmsFat;M=V8=u!l9!BO+~@Lm5CbUK`mDia5kC5iv_FH~pT*|?ntfnU)+`Bx zCcqsiO>+{$=f1!-G6Zh|<-NIx2OpCd1=}$W=E*9+Fv=jTMcl$H+z*8OMi{2F-e&O; hh`SaPF`{Tm9QzlwV{4n5p_ebP4r3C&YgbLk`vVx+?I8dF delta 1164 zcmZ{i%}*0S7{+&Ym+kgrTj+MnhmDX{DFs?VP!R!*QL92AL5;DR5W;Li6=O2s!2=%$ zh>7tac@Gdn!p&ebF{X(J@#7EhqQL{<{8UY+-Cl(nhd^vTRVGrxJ?XLdXLqtp6i zSph}8%z~k9SG#n&K)2#+8D~8CSW+bzZ{_?&Bssejeb#4V8yB0!3EP9$1+$XhxPPr3vF0 zi}XptvhpqD>>f<-wj|-XFIV3o--)c0OucBuaT=u!e)>*8yE&LbOSGfV%1#`G{zzC3 zX1~KDv&l)OxAf2bqhFI_OCwL()_Yd7JNg)WFh8=6(t`i88uY?!Hr9s;jWoJ2W=f+*ob8AKUE(NRvLoI&YEIg4^s zQ4;0eD;w-ZyBD5?UK!MNFKpV4FlQ|ddb+?hR1FHBZI`;k-xF^SMgxD`v3Ig^y^T5N$`fwuSVSee5e)7PVDznaR5h`!@ScKrm%26 qnz2O=ww-(*T|3<_QK&^KiMIWV+A|04-sAUY+#zur`s4FD@_qwmQq9`{ diff --git a/api/models/__pycache__/tweet.cpython-312.pyc b/api/models/__pycache__/tweet.cpython-312.pyc index c556382903274fc45db51fbe17c1e20b8d91b343..c84d72c78f9e8cf38dbe31c1bde086d6dd735126 100644 GIT binary patch delta 3536 zcmc&$Sxl5y6rO+hXBcK*5g1^=VQ~Ou7fM}FP!`!*LD>|6`2`dPyfYf?L!nI*?UsNi zCgW454^6PP=|a;OThqSuscFLm8pEWCZK4mp)U-)!lRmWP+@Z4p#y2PVzuf!%ch3Fq zIp@3QK>I(P`tNl*wG4lMjl47d)viT-n($z;&@nfq>{kjhx8P2iOrBEptEN)=Qv{h@ z)+BR_Z^+yVNp&lU{w9<4t2wJgHaUjXa8`wEN(`&ztQuKO46Ea;7Fpc}+eC)-oYo_4 zh*@mltPxpL3~S`98CgpVYXX%};#7phwh6BhVO>mm@l2X!2v22>$X)b#7@ecf(aJn z4+Y)wr6jvhY(Trrgz!j?;8HR@5jKJy1hg-+6J){H;;i6+YDIm~E+UE$TxRB^aUMZF zLMVA?$UQweG{jPf(!+ZShl|XGk|sR9uuX~tp&7HQ7_M0D@U6yXmGqJ- zoM03VdL%V`W=xMHRpdSVtBEF6lyzyHCeuc$McLz8r^1Y^1%_=7!3x*4jT(w*Na35F znHU8_wo}Qnkmv@T?n7k`j#v%c)n!{>z~P^CxCeJWfB5mj!-Yjw2ak2t=WA)riwHN> zY#)vH6C5HqOwd5kNN|AQAVEFB5rS|qaMX=y-a^b4F=4IvA}$zhu%sWEiv+`E+ddZD zsFEy;1UxDV8u8HZ-J-d_hh8KIfHn__Bh%B9TwSb?*3j1AaVQOR6EOlhv3C`U(h8rq zFlrKov7VD3aIe(%uI2R2w_Kg|i*LS)+I%9~NG=FrxioRPj2Rzj%IQp$7OVnJm>vl^ zP;V{}YGBO#dR{NmA<;KH=Iy>IhNW_nRua$p5aQxA00ows-e{bR+s7$EGf|^FY&>FQ zp7Br~r%_l?Jv8irA1$7+plD8lf`geQD5qYvgw+R=lF0w!;9llA8=s_cPM4r=$Jk`l>DKL?{&aCfcYC@*!X;vq zK9*n>AMZU>!lCD_ge^)$I^{eP>GI>rftlkj`G9pkFYu#1#>@QbMl zycwyehqp5FlsvqH@I^+Y`7AA`V0E)$#JFgj1GBxRI}(i!mtp&GJgWv`(tn(`9)~aO z=fdevb6!tg!Fu9}>r_6;+^SPq&ve>1bt;ry^hhe$Z%f~zXW5Svvm_&z3vXt4i(`b4t(YWJnmr=4!nJGj&x z?~gPsW$qr z$mTpG^aTk;g2A*yVVI&91k3n%A45w{`SaFB`=%<9YWE*mDeYWK?ZPVITNS%D>V|tQ zM~c=B>4~T%4IzXzM8~3xTdvI235i0gq=Q#M&(6Owv>ndExr9rR--nT_5U;s}7NUXv zA8j1McO!8T$+7b|?RJT5h-iLgouN@50+n#W@Mx@XrX@9Q+& zE}7kEl^G2Qe!$0j1-`LoKx+O4J--5o@4yDV7_R3#26@9BQq5d;4|{wQqfAAAO(Ed@ zHuZ+Qw_v=;@e7vgou?DuC(?{C7cLH|_DxN@FHTAa*k#ZZWQbKi$tuBBa8{(v{{v%C B58D6$ delta 3425 zcmcgudq|sC6wggQlbH9rMs1=^nlx%_t@Pn)?L%klS|2TL6}5}j1hrGs-bDKNV@l~* z84Mx^Hp@2Ju?KeU(anF#9)FB7HW&j%VJM7^Q9JrqyRu?ogYBIAHTuLBK^4o2>&7+oiAvR)Em$qGIt6PGtRC5H1#1+n0a>GhH3`;)tXaWUn+0t_+Nz)} zg0&%QSFl#WI*@fLSR0sF36r3L!)&<|Na%KRHI-oPhwQ*D20Nc^F zJhWdx+xpPHtPU_6+)&Rm)5KLx9xJxszvecC+iHY}mYa!i5qJo42yzMX;f{2M`Jg9j z&rq0%2tvfp*O46{2qMhsqS08QD;ni`qQq)i;x)+>pR-1zodW}jRA;I;F_6Sbw9%ZV zcOWJ2MqyBHNw2gG4-tr6H=t$X6k-7;G?Le#Qd>0?jEn^*D-X>C>xU0q>`A9at4GdG zSqi76`q^;FSo7rW#+h)_@WFJ>XmB)nDKcdbPD@R*kxgT%$-ReXB1eYn(>q3Mt~f8% zO*uo;(vjIv@mS4dRl`iEarl|Ee$+MEb;&zr3rtIm3z8wra8HFGABv6x_q-k`*G(`Z z{HA-4`6pi0_cATHmKVTZ*{8zG{fQ$HH7}zH

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"""海报生成请求模型""" templateId: str = Field("vibrant", description="模板ID") - imagesBase64: Optional[str] = Field(None, description="图像base64编码") + imagesBase64: Optional[List[str]] = Field(None, description="图像base64编码列表") posterContent: Optional[Dict[str, Any]] = Field(None, description="海报内容，如果提供则直接使用此内容") contentId: Optional[str] = Field(None, description="内容ID，用于AI生成内容") productId: Optional[str] = Field(None, description="产品ID，用于AI生成内容") @@ -28,7 +28,7 @@ class PosterGenerateRequest(BaseModel): json_schema_extra = { "example": { "templateId": "vibrant", - "imagesBase64": "", + "imagesBase64": ["base64_encoded_image_1", "base64_encoded_image_2"], "numVariations": 1, "forceLlmGeneration":False, "generatePsd": True, diff --git a/api/models/tweet.py b/api/models/tweet.py index 2e8d6a9..2772b2d 100644 --- a/api/models/tweet.py +++ b/api/models/tweet.py @@ -69,7 +69,7 @@ class ContentRequest(BaseModel): audienceIds: Optional[List[Union[int, str]]] = Field(None, description="受众ID列表") scenicSpotIds: Optional[List[Union[int, str]]] = Field(None, description="景区ID列表") productIds: Optional[List[Union[int, str]]] = Field(None, description="产品ID列表") - autoJudge: bool = Field(False, description="是否自动进行内容审核") + autoJudge: Optional[bool] = Field(True, description="是否自动进行内容审核") class Config: schema_extra = { @@ -185,7 +185,7 @@ class PipelineRequest(BaseModel): scenicSpotIds: Optional[List[Union[int, str]]] = Field(None, description="景区ID列表") productIds: Optional[List[Union[int, str]]] = Field(None, description="产品ID列表") skipJudge: bool = Field(False, description="是否跳过内容审核步骤") - autoJudge: bool = Field(False, description="是否在内容生成时进行内嵌审核") + autoJudge: Optional[bool] = Field(None, description="是否在内容生成时进行内嵌审核") class Config: schema_extra = { diff --git a/api/routers/__pycache__/tweet.cpython-312.pyc b/api/routers/__pycache__/tweet.cpython-312.pyc index 7b00885124a2c29321fde408e99e1b92dd5dbd13..774d297a622da8bd15d62eea198a3febed27e13f 100644 GIT binary patch delta 5208 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zPAQ}}nquubdZqd7_+rgQeth1y7ieuyQh68sHg5D5LS94t5qv5UGXiETQiWhZpfRVn zc8MxR_Yxg~9sv&m^N_0BAB%+v^A6^<%u!>0IY-G09GQn)4?;l}@Jz-}QfBZnYQ5k5_SDjyV$#Fy2=N%hlD^mu*d<{n^AJ9yz#IsE68 ziO&PW>FSPrRAi=)gU#&8NS>l}rpU6uo=0*f*s5twguY0^VjKA-74Y;wz8i*4SHPLm P%bde{zU5O6k&XBt0N|cy diff --git a/api/services/poster.py b/api/services/poster.py index e77cce2..ce34516 100644 --- a/api/services/poster.py +++ b/api/services/poster.py @@ -234,26 +234,37 @@ class PosterService: # 获取模板的默认尺寸，如果获取不到则使用标准尺寸 template_size = getattr(template_handler, 'size', (900, 1200)) - if images_base64 and images_base64.strip(): + if images_base64 and len(images_base64) > 0: try: + logger.info(f"🎯 接收到 {len(images_base64)} 张图片的base64数据") + + # 处理第一张图片（目前模板只支持单张图片） + # 未来可以扩展为处理多张图片 + first_image_base64 = images_base64[0] if len(images_base64) > 0 else "" + + if not first_image_base64 or not first_image_base64.strip(): + raise ValueError("第一张图片的base64数据为空") + + logger.info(f"📊 处理第一张图片，base64长度: {len(first_image_base64)}") + # 移除可能存在的MIME类型前缀 - if images_base64.startswith("data:"): - images_base64 = images_base64.split(",", 1)[1] + if first_image_base64.startswith("data:"): + first_image_base64 = first_image_base64.split(",", 1)[1] # 彻底清理base64字符串 - 移除所有空白字符 - images_base64 = ''.join(images_base64.split()) + first_image_base64 = ''.join(first_image_base64.split()) # 验证base64字符串长度（应该是4的倍数） - if len(images_base64) % 4 != 0: + if len(first_image_base64) % 4 != 0: # 添加必要的填充 - images_base64 += '=' * (4 - len(images_base64) % 4) - logger.info(f"为base64字符串添加了填充，最终长度: {len(images_base64)}") + first_image_base64 += '=' * (4 - len(first_image_base64) % 4) + logger.info(f"为base64字符串添加了填充，最终长度: {len(first_image_base64)}") - logger.info(f"准备解码base64数据，长度: {len(images_base64)}, 前20字符: {images_base64[:20]}...") + logger.info(f"准备解码base64数据，长度: {len(first_image_base64)}, 前20字符: {first_image_base64[:20]}...") # 解码base64 - image_bytes = base64.b64decode(images_base64) - logger.info(f"base64解码成功，图片数据大小: {len(image_bytes)} bytes") + image_bytes = base64.b64decode(first_image_base64) + logger.info(f"✅ base64解码成功，图片数据大小: {len(image_bytes)} bytes") # 验证解码后的数据不为空 if len(image_bytes) == 0: @@ -262,11 +273,11 @@ class PosterService: # 检查文件头判断图片格式 file_header = image_bytes[:10] if file_header.startswith(b'\xff\xd8\xff'): - logger.info("检测到JPEG格式图片") + logger.info("✅ 检测到JPEG格式图片") elif file_header.startswith(b'\x89PNG'): - logger.info("检测到PNG格式图片") + logger.info("✅ 检测到PNG格式图片") else: - logger.warning(f"未识别的图片格式，文件头: {file_header.hex()}") + logger.warning(f"⚠️ 未识别的图片格式，文件头: {file_header.hex()}") # 创建PIL Image对象 image_io = BytesIO(image_bytes) @@ -279,16 +290,16 @@ class PosterService: image_io.seek(0) images = Image.open(image_io) - logger.info(f"图片解码成功，格式: {images.format}, 尺寸: {images.size}, 模式: {images.mode}") + logger.info(f"✅ 图片解码成功，格式: {images.format}, 尺寸: {images.size}, 模式: {images.mode}") except binascii.Error as e: - logger.error(f"Base64解码失败: {e}") - logger.error(f"问题数据长度: {len(images_base64) if 'images_base64' in locals() else 'unknown'}") + logger.error(f"❌ Base64解码失败: {e}") + logger.error(f"问题数据长度: {len(first_image_base64) if 'first_image_base64' in locals() else 'unknown'}") # 创建一个与目标大小一致的透明底图 images = Image.new('RGBA', template_size, color=(0, 0, 0, 0)) logger.info(f"创建默认透明背景图，尺寸: {template_size}") except Exception as e: - logger.error(f"图片处理失败: {e}") + logger.error(f"❌ 图片处理失败: {e}") logger.error(f"错误类型: {type(e).__name__}") if 'image_bytes' in locals(): logger.error(f"图片数据大小: {len(image_bytes)} bytes, 前20字节: {image_bytes[:20].hex()}") @@ -296,7 +307,7 @@ class PosterService: images = Image.new('RGBA', template_size, color=(0, 0, 0, 0)) logger.info(f"创建默认透明背景图，尺寸: {template_size}") else: - logger.warning("未提供图片数据，使用默认透明背景图") + logger.warning("⚠️ 未提供图片数据，使用默认透明背景图") # 创建一个与目标大小一致的透明底图 images = Image.new('RGBA', template_size, color=(0, 0, 0, 0)) logger.info(f"创建默认透明背景图，尺寸: {template_size}") diff --git a/api/services/tweet.py b/api/services/tweet.py index 028afbe..e07d3c4 100644 --- a/api/services/tweet.py +++ b/api/services/tweet.py @@ -10,6 +10,8 @@ import logging import uuid from typing import List, Dict, Any, Optional, Tuple from datetime import datetime +import re +from difflib import SequenceMatcher from core.config import ConfigManager, GenerateTopicConfig, GenerateContentConfig from core.ai import AIAgent @@ -24,6 +26,249 @@ from api.services.database_service import DatabaseService logger = logging.getLogger(__name__) +class TopicIDMappingManager: + """选题ID映射管理器 - 专门处理选题中的对象ID映射""" + + def __init__(self): + """初始化映射管理器""" + self.name_to_id = {} # 名称 -> ID映射 + self.mapping_data = { + 'styles': {}, + 'audiences': {}, + 'scenic_spots': {}, + 'products': {} + } + + def add_objects_mapping(self, + style_objects: Optional[List[Dict[str, Any]]] = None, + audience_objects: Optional[List[Dict[str, Any]]] = None, + scenic_spot_objects: Optional[List[Dict[str, Any]]] = None, + product_objects: Optional[List[Dict[str, Any]]] = None): + """ + 批量添加对象映射关系 + + Args: + style_objects: 风格对象列表 + audience_objects: 受众对象列表 + scenic_spot_objects: 景区对象列表 + product_objects: 产品对象列表 + """ + logger.info("开始建立选题ID映射关系") + mapping_count = 0 + + if style_objects: + logger.info(f"处理 {len(style_objects)} 个风格对象") + for obj in style_objects: + name = obj.get('styleName', '') + obj_id = obj.get('id') + if name and obj_id: + self.mapping_data['styles'][name] = str(obj_id) + self._add_name_variants('styles', name, str(obj_id)) + mapping_count += 1 + logger.info(f"添加风格映射: {name} -> ID {obj_id}") + + if audience_objects: + logger.info(f"处理 {len(audience_objects)} 个受众对象") + for obj in audience_objects: + name = obj.get('audienceName', '') + obj_id = obj.get('id') + if name and obj_id: + self.mapping_data['audiences'][name] = str(obj_id) + self._add_name_variants('audiences', name, str(obj_id)) + mapping_count += 1 + logger.info(f"添加受众映射: {name} -> ID {obj_id}") + + if scenic_spot_objects: + logger.info(f"处理 {len(scenic_spot_objects)} 个景区对象") + for obj in scenic_spot_objects: + name = obj.get('name', '') + obj_id = obj.get('id') + if name and obj_id: + self.mapping_data['scenic_spots'][name] = str(obj_id) + self._add_name_variants('scenic_spots', name, str(obj_id)) + mapping_count += 1 + logger.info(f"添加景区映射: {name} -> ID {obj_id}") + + if product_objects: + logger.info(f"处理 {len(product_objects)} 个产品对象") + for obj in product_objects: + name = obj.get('productName', '') + obj_id = obj.get('id') + if name and obj_id: + self.mapping_data['products'][name] = str(obj_id) + self._add_name_variants('products', name, str(obj_id)) + mapping_count += 1 + logger.info(f"添加产品映射: {name} -> ID {obj_id}") + + total_variants = len(self.name_to_id) + logger.info(f"ID映射关系建立完成: {mapping_count} 个对象，生成 {total_variants} 个名称变体") + + def _add_name_variants(self, category: str, name: str, obj_id: str): + """为名称添加各种变体以支持模糊匹配""" + variants = [name] + + # 去除标点符号版本 + clean_name = re.sub(r'[^\w\s]', '', name) + if clean_name != name: + variants.append(clean_name) + + # 去除空格版本 + no_space_name = name.replace(' ', '') + if no_space_name != name: + variants.append(no_space_name) + + # 添加简化版本（去除常见后缀） + simplified = re.sub(r'(风格|类型|系列|产品|景区|公园)$', '', name) + if simplified != name and simplified: + variants.append(simplified) + + # 为所有变体添加映射 + for variant in variants: + self.name_to_id[variant.lower()] = { + 'category': category, + 'id': obj_id, + 'original_name': name + } + + # 记录生成的变体（仅在有多个变体时记录） + if len(variants) > 1: + variants_str = ', '.join(f"'{v}'" for v in variants) + logger.info(f" 为 '{name}' 生成 {len(variants)} 个变体: {variants_str}") + + def find_ids_in_topic(self, topic: Dict[str, Any]) -> Dict[str, List[str]]: + """ + 在选题中查找相关的对象ID + + Args: + topic: 选题字典 + + Returns: + 按类型分组的ID列表 + """ + topic_index = topic.get('index', 'N/A') + + found_ids = { + 'style_ids': [], + 'audience_ids': [], + 'scenic_spot_ids': [], + 'product_ids': [] + } + + # 提取选题中的所有文本 + topic_text = self._extract_topic_text(topic) + topic_text_lower = topic_text.lower() + + logger.info(f"开始为选题 {topic_index} 进行ID匹配") + logger.info(f"选题 {topic_index} 提取的文本内容: '{topic_text}'") + logger.info(f"当前映射库包含 {len(self.name_to_id)} 个名称变体") + + # 显示映射库内容 + logger.info("映射库内容:") + for variant, info in self.name_to_id.items(): + logger.info(f" '{variant}' -> {info['original_name']} ({info['category']}, ID: {info['id']})") + + # 记录匹配过程 + match_details = [] + + # 在文本中查找匹配的名称 + for name_variant, mapping_info in self.name_to_id.items(): + if name_variant in topic_text_lower: + category = mapping_info['category'] + obj_id = mapping_info['id'] + original_name = mapping_info['original_name'] + + # 记录匹配详情 + match_details.append({ + 'variant': name_variant, + 'original_name': original_name, + 'category': category, + 'id': obj_id + }) + + # 映射到返回格式 + if category == 'styles' and obj_id not in found_ids['style_ids']: + found_ids['style_ids'].append(obj_id) + logger.info(f"选题 {topic_index} 匹配到风格: '{name_variant}' -> {original_name} (ID: {obj_id})") + elif category == 'audiences' and obj_id not in found_ids['audience_ids']: + found_ids['audience_ids'].append(obj_id) + logger.info(f"选题 {topic_index} 匹配到受众: '{name_variant}' -> {original_name} (ID: {obj_id})") + elif category == 'scenic_spots' and obj_id not in found_ids['scenic_spot_ids']: + found_ids['scenic_spot_ids'].append(obj_id) + logger.info(f"选题 {topic_index} 匹配到景区: '{name_variant}' -> {original_name} (ID: {obj_id})") + elif category == 'products' and obj_id not in found_ids['product_ids']: + found_ids['product_ids'].append(obj_id) + logger.info(f"选题 {topic_index} 匹配到产品: '{name_variant}' -> {original_name} (ID: {obj_id})") + + # 统计匹配结果 + total_found = sum(len(ids) for ids in found_ids.values()) + total_available = len(set(info['category'] + '_' + info['id'] for info in self.name_to_id.values())) + match_rate = (total_found / total_available * 100) if total_available > 0 else 0 + + # 输出详细的匹配结果 + if total_found > 0: + logger.info(f"选题 {topic_index} ID匹配完成: 找到 {total_found} 个相关对象，匹配率: {match_rate:.1f}%") + logger.info(f"选题 {topic_index} 匹配详情: {match_details}") + + # 按类别显示匹配结果 + for category, ids in found_ids.items(): + if ids: + category_name = { + 'style_ids': '风格', + 'audience_ids': '受众', + 'scenic_spot_ids': '景区', + 'product_ids': '产品' + }.get(category, category) + + # 获取匹配的原始名称 + matched_names = [] + # 建立正确的分类映射关系 + category_mapping = { + 'style_ids': 'styles', + 'audience_ids': 'audiences', + 'scenic_spot_ids': 'scenic_spots', + 'product_ids': 'products' + } + target_category = category_mapping.get(category) + + logger.info(f"选题 {topic_index} 处理分类 {category} -> {target_category}, IDs: {ids}") + + for detail in match_details: + if detail['id'] in ids and detail['category'] == target_category: + matched_names.append(f"{detail['original_name']}({detail['id']})") + + # 显示分类结果 + names_str = ', '.join(matched_names) if matched_names else '(无匹配名称)' + logger.info(f" {category_name}: {names_str}") + + # 如果没有匹配名称，输出调试信息 + if not matched_names: + logger.info(f"选题 {topic_index} {category_name}无匹配名称，详情检查:") + logger.info(f" IDs: {ids}") + logger.info(f" 目标分类: {target_category}") + for detail in match_details: + if detail['id'] in ids: + logger.info(f" 详情: {detail}") + else: + logger.info(f"选题 {topic_index} 未匹配到任何相关对象ID") + + return found_ids + + def _extract_topic_text(self, topic: Dict[str, Any]) -> str: + """提取选题中的所有文本内容""" + text_parts = [] + + # 提取主要字段的文本 + text_fields = ['object', 'style', 'targetAudience', 'product', 'logic', + 'productLogic', 'styleLogic', 'targetAudienceLogic'] + + for field in text_fields: + if field in topic and topic[field]: + text_parts.append(str(topic[field])) + + return ' '.join(text_parts) + + + class TweetService: """文字内容服务类""" @@ -49,6 +294,9 @@ class TweetService: self.prompt_service = PromptService(config_manager) self.prompt_builder = PromptBuilderService(config_manager, self.prompt_service) + # 初始化选题ID映射管理器 + self.topic_id_mapping_manager = TopicIDMappingManager() + async def generate_topics(self, dates: Optional[str] = None, numTopics: int = 5, styles: Optional[List[str]] = None, audiences: Optional[List[str]] = None, @@ -84,6 +332,14 @@ class TweetService: topic_config.topic.date = dates topic_config.topic.num = numTopics + # 建立ID映射关系（用于后续的ID反向映射） + self.topic_id_mapping_manager.add_objects_mapping( + style_objects=style_objects, + audience_objects=audience_objects, + scenic_spot_objects=scenic_spot_objects, + product_objects=product_objects + ) + # 使用PromptBuilderService构建提示词 system_prompt, user_prompt = self.prompt_builder.build_topic_prompt( products=products, @@ -103,12 +359,35 @@ class TweetService: if not topics: logger.error("未能生成任何选题") return str(uuid.uuid4()), [] + + # 为每个选题添加相关的对象ID + logger.info(f"开始为 {len(topics)} 个选题进行ID映射分析") + enhanced_topics = [] + total_mapped_topics = 0 + + for topic in topics: + enhanced_topic = topic.copy() + + # 查找选题中涉及的对象ID + related_object_ids = self.topic_id_mapping_manager.find_ids_in_topic(topic) + + # 只有当找到相关ID时才添加字段 + if any(related_object_ids.values()): + enhanced_topic['related_object_ids'] = related_object_ids + total_mapped_topics += 1 + logger.info(f"选题 {topic.get('index', 'N/A')} 找到相关ID: {related_object_ids}") + + enhanced_topics.append(enhanced_topic) + + # 统计总体映射情况 + mapping_coverage = (total_mapped_topics / len(topics) * 100) if topics else 0 + logger.info(f"选题ID映射完成: {total_mapped_topics}/{len(topics)} 个选题包含相关对象ID，覆盖率: {mapping_coverage:.1f}%") # 生成请求ID requestId = f"topic-{datetime.now().strftime('%Y%m%d-%H%M%S')}-{str(uuid.uuid4())[:8]}" - logger.info(f"选题生成完成，请求ID: {requestId}, 数量: {len(topics)}") - return requestId, topics + logger.info(f"选题生成完成，请求ID: {requestId}, 数量: {len(enhanced_topics)}") + return requestId, enhanced_topics async def generate_content(self, topic: Optional[Dict[str, Any]] = None, autoJudge: bool = False, style_objects: Optional[List[Dict[str, Any]]] = None, @@ -198,10 +477,10 @@ class TweetService: async def _enhance_topic_with_database_data(self, topic: Dict[str, Any]) -> Dict[str, Any]: """ - 使用数据库数据增强选题信息 + 使用数据库数据增强选题信息，优先使用related_object_ids中的反射ID Args: - topic: 原始选题数据 + topic: 原始选题数据（可能包含related_object_ids字段） Returns: 增强后的选题数据 @@ -216,46 +495,119 @@ class TweetService: logger.warning("数据库服务不可用，无法增强选题数据") return enhanced_topic + # 优先使用related_object_ids中的反射ID（更精确） + related_ids = topic.get('related_object_ids', {}) + if related_ids: + logger.info(f"选题包含反射ID信息，优先使用: {related_ids}") + enhanced_topic = await self._enhance_with_related_ids(enhanced_topic, db_service, related_ids) + return enhanced_topic + # 处理风格ID if 'styleIds' in topic and topic['styleIds']: style_id = topic['styleIds'][0] if isinstance(topic['styleIds'], list) else topic['styleIds'] style_data = db_service.get_style_by_id(style_id) if style_data: + style_name = style_data.get('styleName') enhanced_topic['style_object'] = style_data - enhanced_topic['style'] = style_data.get('styleName') - logger.info(f"从数据库加载风格数据: {style_data.get('styleName')} (ID: {style_id})") + enhanced_topic['style'] = style_name + logger.info(f"从数据库加载风格数据: {style_name} (ID: {style_id})") # 处理受众ID if 'audienceIds' in topic and topic['audienceIds']: audience_id = topic['audienceIds'][0] if isinstance(topic['audienceIds'], list) else topic['audienceIds'] audience_data = db_service.get_audience_by_id(audience_id) if audience_data: + audience_name = audience_data.get('audienceName') enhanced_topic['audience_object'] = audience_data - enhanced_topic['targetAudience'] = audience_data.get('audienceName') - logger.info(f"从数据库加载受众数据: {audience_data.get('audienceName')} (ID: {audience_id})") + enhanced_topic['targetAudience'] = audience_name + logger.info(f"从数据库加载受众数据: {audience_name} (ID: {audience_id})") # 处理景区ID if 'scenicSpotIds' in topic and topic['scenicSpotIds']: spot_id = topic['scenicSpotIds'][0] if isinstance(topic['scenicSpotIds'], list) else topic['scenicSpotIds'] spot_data = db_service.get_scenic_spot_by_id(spot_id) if spot_data: + spot_name = spot_data.get('name') enhanced_topic['scenic_spot_object'] = spot_data - enhanced_topic['object'] = spot_data.get('name') - logger.info(f"从数据库加载景区数据: {spot_data.get('name')} (ID: {spot_id})") + enhanced_topic['object'] = spot_name + logger.info(f"从数据库加载景区数据: {spot_name} (ID: {spot_id})") # 处理产品ID if 'productIds' in topic and topic['productIds']: product_id = topic['productIds'][0] if isinstance(topic['productIds'], list) else topic['productIds'] product_data = db_service.get_product_by_id(product_id) if product_data: + product_name = product_data.get('productName') enhanced_topic['product_object'] = product_data - enhanced_topic['product'] = product_data.get('productName') - logger.info(f"从数据库加载产品数据: {product_data.get('productName')} (ID: {product_id})") + enhanced_topic['product'] = product_name + logger.info(f"从数据库加载产品数据: {product_name} (ID: {product_id})") except Exception as e: logger.error(f"增强选题数据时发生错误: {e}", exc_info=True) return enhanced_topic + + async def _enhance_with_related_ids(self, enhanced_topic: Dict[str, Any], db_service, related_ids: Dict[str, List[str]]) -> Dict[str, Any]: + """ + 使用related_object_ids中的反射ID进行数据库查询和增强 + + Args: + enhanced_topic: 待增强的选题数据 + db_service: 数据库服务实例 + related_ids: 反射的ID字典 + + Returns: + 增强后的选题数据 + """ + logger.info("开始使用反射ID进行选题数据增强") + + try: + # 处理风格ID + style_ids = related_ids.get('style_ids', []) + if style_ids: + style_id = int(style_ids[0]) # 取第一个ID + style_data = db_service.get_style_by_id(style_id) + if style_data: + enhanced_topic['style_object'] = style_data + enhanced_topic['style'] = style_data.get('styleName') + logger.info(f"通过反射ID加载风格数据: {style_data.get('styleName')} (ID: {style_id})") + + # 处理受众ID + audience_ids = related_ids.get('audience_ids', []) + if audience_ids: + audience_id = int(audience_ids[0]) # 取第一个ID + audience_data = db_service.get_audience_by_id(audience_id) + if audience_data: + enhanced_topic['audience_object'] = audience_data + enhanced_topic['targetAudience'] = audience_data.get('audienceName') + logger.info(f"通过反射ID加载受众数据: {audience_data.get('audienceName')} (ID: {audience_id})") + + # 处理景区ID + scenic_spot_ids = related_ids.get('scenic_spot_ids', []) + if scenic_spot_ids: + spot_id = int(scenic_spot_ids[0]) # 取第一个ID + spot_data = db_service.get_scenic_spot_by_id(spot_id) + if spot_data: + enhanced_topic['scenic_spot_object'] = spot_data + enhanced_topic['object'] = spot_data.get('name') + logger.info(f"通过反射ID加载景区数据: {spot_data.get('name')} (ID: {spot_id})") + + # 处理产品ID + product_ids = related_ids.get('product_ids', []) + if product_ids: + product_id = int(product_ids[0]) # 取第一个ID + product_data = db_service.get_product_by_id(product_id) + if product_data: + enhanced_topic['product_object'] = product_data + enhanced_topic['product'] = product_data.get('productName') + logger.info(f"通过反射ID加载产品数据: {product_data.get('productName')} (ID: {product_id})") + + logger.info("反射ID数据增强完成") + + except Exception as e: + logger.error(f"使用反射ID增强选题数据时发生错误: {e}", exc_info=True) + + return enhanced_topic async def generate_content_with_prompt(self, topic: Dict[str, Any], system_prompt: str, user_prompt: str) -> Tuple[str, str, Dict[str, Any]]: """ diff --git a/config/database.json b/config/database.json index fc9ad20..4ec8470 100644 --- a/config/database.json +++ b/config/database.json @@ -1,7 +1,7 @@ { "host": "localhost", "user": "root", - "password": "civmek-rezTed-0hovre", + "password": "Kj#9mP2$", "database": "travel_content", "port": 3306, "charset": "utf8mb4", diff --git a/run_api.py b/run_api.py index 2d0a05d..6886aae 100644 --- a/run_api.py +++ b/run_api.py @@ -32,7 +32,7 @@ def build_arg_parser() -> argparse.ArgumentParser: parser.add_argument( "--port", type=int, - default=int(os.getenv("PORT", 8000)), + default=int(os.getenv("PORT", 2714)), help="监听端口", ) parser.add_argument( diff --git a/海报Fabric.js前端对接文档.md b/海报Fabric.js前端对接文档.md new file mode 100644 index 0000000..797bc94 --- /dev/null +++ b/海报Fabric.js前端对接文档.md @@ -0,0 +1,711 @@ +# 海报Fabric.js前端对接文档 + +## 📋 概述 + +本文档详细说明如何在前端使用新的海报生成API返回的Fabric.js JSON数据，包括图层加载、图片替换、图层管理等功能。 + +## 🔄 核心变化 + +### **从PSD到Fabric.js JSON** +- **原先**: 返回PSD文件的base64编码 +- **现在**: 返回Fabric.js JSON文件的base64编码 + 原始JSON数据 +- **优势**: 可以直接在前端使用，支持实时编辑和图片替换 + +## 🎯 API接口说明 + +### 1. **生成海报接口** + +#### **请求示例** +```javascript +const generatePosterRequest = { + posterNumber: 1, + posters: [{ + templateId: "vibrant", + imagesBase64: "图片ID列表", + contentId: "内容ID", + productId: "产品ID", + generatePsd: true, // 现在实际生成JSON + numVariations: 1 + }] +}; + +const response = await fetch('/poster/generate', { + method: 'POST', + headers: {'Content-Type': 'application/json'}, + body: JSON.stringify(generatePosterRequest) +}); + +const result = await response.json(); +``` + +#### **响应结构** +```javascript +{ + "code": 0, + "message": "操作成功", + "data": [{ + "requestId": "poster-20250104-123456", + "templateId": "vibrant", + "resultImagesBase64": [{ + "id": "vibrant_v1", + "image": "base64编码的PNG图片", + "format": "PNG", + "size": [1350, 1800] + }], + "psdFiles": [{ // 现在是JSON文件 + "id": "vibrant_v1_json", + "filename": "template_fabric_v1_20250104.json", + "data": "base64编码的JSON文件", + "size": 15672, + "format": "JSON", + "jsonData": { // 原始JSON数据，可直接使用 + "version": "5.3.0", + "objects": [...], + "background": "white", + "width": 1350, + "height": 1800 + } + }] + }] +} +``` + +### 2. **获取Fabric.js JSON数据** +```javascript +// 获取指定海报的JSON数据 +const fabricJson = await fetch(`/poster/fabric-json/${posterId}`) + .then(res => res.json()) + .then(data => data.data); +``` + +### 3. **替换底层图片** +```javascript +// 单个图片替换 +const replaceImage = async (posterId, newImageBase64) => { + const formData = new FormData(); + formData.append('posterId', posterId); + formData.append('newImageBase64', newImageBase64); + + const response = await fetch('/poster/replace-image', { + method: 'POST', + body: formData + }); + + return response.json(); +}; +``` + +### 4. **获取图层信息** +```javascript +// 获取图层管理信息 +const layers = await fetch(`/poster/layers/${posterId}`) + .then(res => res.json()) + .then(data => data.data); + +// 图层信息结构 +// [{ +// "name": "图片层", +// "type": "image", +// "level": 0, +// "visible": true, +// "selectable": true, +// "replaceable": true +// }] +``` + +## 🛠️ 前端集成实现 + +### 1. **基础环境准备** + +#### **HTML结构** +```html + + + + + 海报编辑器 + + + +

+ + +``` + +#### **CSS样式** +```css +#poster-editor { + display: flex; + gap: 20px; + padding: 20px; +} + +.canvas-container { + flex: 1; + border: 1px solid #ddd; + border-radius: 8px; + padding: 10px; + background: #f5f5f5; +} + +.layer-panel, .image-replace-panel { + width: 250px; + border: 1px solid #ddd; + border-radius: 8px; + padding: 15px; + background: white; +} + +.layer-item { + padding: 8px; + margin: 5px 0; + border: 1px solid #eee; + border-radius: 4px; + cursor: pointer; +} + +.layer-item:hover { + background: #f0f0f0; +} + +.layer-item.active { + background: #e3f2fd; + border-color: #2196f3; +} +``` + +### 2. **JavaScript核心实现** + +#### **初始化画布** +```javascript +class PosterEditor { + constructor(canvasId) { + this.canvas = new fabric.Canvas(canvasId, { + preserveObjectStacking: true, + selection: true + }); + this.currentPosterId = null; + this.layers = []; + + this.initEventListeners(); + } + + // 加载海报JSON数据 + async loadPosterFromJson(fabricJsonData, posterId) { + try { + console.log('开始加载Fabric.js JSON数据...'); + + // 清空画布 + this.canvas.clear(); + this.currentPosterId = posterId; + + // 加载JSON数据到画布 + await new Promise((resolve, reject) => { + this.canvas.loadFromJSON(fabricJsonData, () => { + console.log('Fabric.js JSON数据加载成功'); + this.canvas.renderAll(); + resolve(); + }, (error) => { + console.error('加载JSON数据失败:', error); + reject(error); + }); + }); + + // 加载图层信息 + await this.loadLayerInfo(posterId); + + console.log('海报加载完成'); + + } catch (error) { + console.error('加载海报失败:', error); + throw error; + } + } + + // 从API获取并加载海报 + async loadPosterFromApi(posterId) { + try { + const response = await fetch(`/poster/fabric-json/${posterId}`); + const result = await response.json(); + + if (result.code === 0) { + await this.loadPosterFromJson(result.data, posterId); + } else { + throw new Error(result.message || '获取海报数据失败'); + } + } catch (error) { + console.error('从API加载海报失败:', error); + throw error; + } + } + + // 加载图层信息 + async loadLayerInfo(posterId) { + try { + const response = await fetch(`/poster/layers/${posterId}`); + const result = await response.json(); + + if (result.code === 0) { + this.layers = result.data; + this.renderLayerPanel(); + } + } catch (error) { + console.error('加载图层信息失败:', error); + } + } + + // 渲染图层管理面板 + renderLayerPanel() { + const layerList = document.getElementById('layer-list'); + layerList.innerHTML = ''; + + this.layers.forEach((layer, index) => { + const layerItem = document.createElement('div'); + layerItem.className = 'layer-item'; + layerItem.innerHTML = ` +
+ ${layer.name} + (${layer.type}) +
+
+ + ${layer.replaceable ? ` + + ` : ''} +
+ `; + + layerList.appendChild(layerItem); + }); + } + + // 替换底层图片 + async replaceBackgroundImage(imageFile) { + try { + if (!this.currentPosterId) { + throw new Error('没有加载的海报'); + } + + // 转换图片为base64 + const imageBase64 = await this.fileToBase64(imageFile); + + // 调用后端API替换图片 + const formData = new FormData(); + formData.append('posterId', this.currentPosterId); + formData.append('newImageBase64', imageBase64); + + const response = await fetch('/poster/replace-image', { + method: 'POST', + body: formData + }); + + const result = await response.json(); + + if (result.code === 0) { + // 重新加载画布 + await this.loadPosterFromJson(result.data, this.currentPosterId); + console.log('图片替换成功'); + } else { + throw new Error(result.message || '图片替换失败'); + } + + } catch (error) { + console.error('替换图片失败:', error); + alert('替换图片失败: ' + error.message); + } + } + + // 文件转base64 + fileToBase64(file) { + return new Promise((resolve, reject) => { + const reader = new FileReader(); + reader.onload = () => { + // 移除data:image/xxx;base64,前缀 + const base64 = reader.result.split(',')[1]; + resolve(base64); + }; + reader.onerror = reject; + reader.readAsDataURL(file); + }); + } + + // 切换图层可见性 + toggleLayerVisibility(layerIndex) { + const layer = this.layers[layerIndex]; + if (layer) { + layer.visible = !layer.visible; + // 这里可以实现图层显示/隐藏的逻辑 + // 需要根据具体的图层结构来实现 + } + } + + // 初始化事件监听 + initEventListeners() { + // 图片上传事件 + document.getElementById('image-upload').addEventListener('change', (e) => { + const file = e.target.files[0]; + if (file) { + this.replaceBackgroundImage(file); + } + }); + + // 替换按钮事件 + document.getElementById('replace-btn').addEventListener('click', () => { + document.getElementById('image-upload').click(); + }); + } + + // 导出当前画布为图片 + exportAsImage(format = 'png', quality = 1.0) { + return this.canvas.toDataURL({ + format: format, + quality: quality, + multiplier: 1 + }); + } + + // 获取当前的Fabric.js JSON数据 + getCurrentJson() { + return this.canvas.toJSON(); + } +} + +// 初始化编辑器 +const editor = new PosterEditor('poster-canvas'); +``` + +### 3. **完整使用示例** + +#### **生成海报并加载到编辑器** +```javascript +// 完整的海报生成和加载流程 +async function generateAndLoadPoster() { + try { + // 1. 生成海报 + const generateRequest = { + posterNumber: 1, + posters: [{ + templateId: "vibrant", + imagesBase64: "123,456", // 图片ID列表 + generatePsd: true, + numVariations: 1 + }] + }; + + console.log('正在生成海报...'); + const generateResponse = await fetch('/poster/generate', { + method: 'POST', + headers: {'Content-Type': 'application/json'}, + body: JSON.stringify(generateRequest) + }); + + const generateResult = await generateResponse.json(); + + if (generateResult.code !== 0) { + throw new Error('海报生成失败: ' + generateResult.message); + } + + const posterData = generateResult.data[0]; + const fabricJsonData = posterData.psdFiles[0].jsonData; + const posterId = posterData.psdFiles[0].id; + + console.log('海报生成成功，开始加载到编辑器...'); + + // 2. 加载到编辑器 + await editor.loadPosterFromJson(fabricJsonData, posterId); + + console.log('海报加载到编辑器成功！'); + + // 3. 显示预览图 + const previewImage = posterData.resultImagesBase64[0].image; + showPreviewImage(previewImage); + + } catch (error) { + console.error('生成和加载海报失败:', error); + alert('操作失败: ' + error.message); + } +} + +// 显示预览图 +function showPreviewImage(base64Image) { + const previewDiv = document.createElement('div'); + previewDiv.innerHTML = ` +

生成的海报预览

+ + `; + document.body.appendChild(previewDiv); +} +``` + +#### **图片替换功能示例** +```javascript +// 高级图片替换功能 +class ImageReplacer { + constructor(editor) { + this.editor = editor; + this.setupUI(); + } + + setupUI() { + const replacePanel = document.querySelector('.image-replace-panel'); + replacePanel.innerHTML = ` +

图片替换

+
+

拖拽图片到这里或点击选择

+ +
+ + `; + + this.bindEvents(); + } + + bindEvents() { + const uploadArea = document.getElementById('upload-area'); + const fileInput = document.getElementById('image-upload'); + const previewDiv = document.getElementById('image-preview'); + const previewImg = document.getElementById('preview-img'); + + // 点击上传 + uploadArea.addEventListener('click', () => { + fileInput.click(); + }); + + // 拖拽上传 + uploadArea.addEventListener('dragover', (e) => { + e.preventDefault(); + uploadArea.style.backgroundColor = '#f0f0f0'; + }); + + uploadArea.addEventListener('dragleave', () => { + uploadArea.style.backgroundColor = ''; + }); + + uploadArea.addEventListener('drop', (e) => { + e.preventDefault(); + uploadArea.style.backgroundColor = ''; + + const files = e.dataTransfer.files; + if (files.length > 0) { + this.handleFileSelect(files[0]); + } + }); + + // 文件选择 + fileInput.addEventListener('change', (e) => { + const file = e.target.files[0]; + if (file) { + this.handleFileSelect(file); + } + }); + + // 确认替换 + document.getElementById('confirm-replace').addEventListener('click', () => { + this.confirmReplace(); + }); + + // 取消 + document.getElementById('cancel-replace').addEventListener('click', () => { + this.cancelReplace(); + }); + } + + handleFileSelect(file) { + const reader = new FileReader(); + reader.onload = (e) => { + const previewImg = document.getElementById('preview-img'); + const previewDiv = document.getElementById('image-preview'); + const uploadArea = document.getElementById('upload-area'); + + previewImg.src = e.target.result; + previewDiv.style.display = 'block'; + uploadArea.style.display = 'none'; + + this.selectedFile = file; + }; + reader.readAsDataURL(file); + } + + async confirmReplace() { + try { + await this.editor.replaceBackgroundImage(this.selectedFile); + this.cancelReplace(); + alert('图片替换成功！'); + } catch (error) { + alert('图片替换失败: ' + error.message); + } + } + + cancelReplace() { + document.getElementById('image-preview').style.display = 'none'; + document.getElementById('upload-area').style.display = 'block'; + this.selectedFile = null; + } +} + +// 初始化图片替换器 +const imageReplacer = new ImageReplacer(editor); +``` + +## 🚀 快速开始 + +### **1. 基础集成** +```html + + + + + + + + + + + + +``` + +### **2. 图片替换示例** +```javascript +// 简单的图片替换 +async function replaceImage() { + const input = document.createElement('input'); + input.type = 'file'; + input.accept = 'image/*'; + + input.onchange = async (e) => { + const file = e.target.files[0]; + if (!file) return; + + const reader = new FileReader(); + reader.onload = async (event) => { + const base64 = event.target.result.split(',')[1]; + + try { + const response = await fetch('/poster/replace-image', { + method: 'POST', + headers: {'Content-Type': 'application/x-www-form-urlencoded'}, + body: `posterId=your-poster-id&newImageBase64=${encodeURIComponent(base64)}` + }); + + const result = await response.json(); + if (result.code === 0) { + // 重新加载画布 + canvas.loadFromJSON(result.data, () => { + canvas.renderAll(); + }); + } + } catch (error) { + console.error('替换失败:', error); + } + }; + reader.readAsDataURL(file); + }; + + input.click(); +} +``` + +## ⚠️ 注意事项 + +### **1. 浏览器兼容性** +- 需要支持Canvas API +- 需要支持File API +- 建议使用现代浏览器（Chrome 80+, Firefox 75+, Safari 13+） + +### **2. 性能优化** +```javascript +// 优化Canvas性能 +canvas.set({ + renderOnAddRemove: false, // 添加/删除对象时不自动渲染 + skipTargetFind: true // 跳过目标查找（如果不需要交互） +}); + +// 批量操作后手动渲染 +canvas.renderAll(); +``` + +### **3. 错误处理** +```javascript +// 完善的错误处理 +try { + await editor.loadPosterFromApi(posterId); +} catch (error) { + if (error.message.includes('404')) { + console.error('海报不存在'); + } else if (error.message.includes('网络')) { + console.error('网络错误，请重试'); + } else { + console.error('未知错误:', error); + } +} +``` + +### **4. 内存管理** +```javascript +// 清理资源 +function cleanup() { + canvas.dispose(); // 销毁画布 + canvas = null; +} + +// 页面卸载时清理 +window.addEventListener('beforeunload', cleanup); +``` + +## 📞 技术支持 + +如在集成过程中遇到问题： +- **API问题**: 检查请求格式和响应状态码 +- **Canvas问题**: 查看浏览器控制台错误信息 +- **性能问题**: 检查图片大小和Canvas尺寸 +- **兼容性问题**: 确认Fabric.js版本和浏览器支持 + +## 🔗 相关链接 + +- [Fabric.js官方文档](http://fabricjs.com/docs/) +- [Canvas API文档](https://developer.mozilla.org/en-US/docs/Web/API/Canvas_API) +- [File API文档](https://developer.mozilla.org/en-US/docs/Web/API/File) \ No newline at end of file