diff --git a/src/plugins/chat/emoji_manager.py b/src/plugins/chat/emoji_manager.py index 9532db4f0..1c8a07699 100644 --- a/src/plugins/chat/emoji_manager.py +++ b/src/plugins/chat/emoji_manager.py @@ -6,6 +6,8 @@ import random import time import traceback from typing import Optional, Tuple +from PIL import Image +import io from loguru import logger from nonebot import get_driver @@ -192,11 +194,11 @@ class EmojiManager: logger.error(f"获取标签失败: {str(e)}") return None - async def _check_emoji(self, image_base64: str) -> str: + async def _check_emoji(self, image_base64: str, image_format: str) -> str: try: prompt = f'这是一个表情包，请回答这个表情包是否满足\"{global_config.EMOJI_CHECK_PROMPT}\"的要求，是则回答是，否则回答否，不要出现任何其他内容' - content, _ = await self.vlm.generate_response_for_image(prompt, image_base64) + content, _ = await self.vlm.generate_response_for_image(prompt, image_base64, image_format) logger.debug(f"输出描述: {content}") return content @@ -237,7 +239,7 @@ class EmojiManager: image_bytes = base64.b64decode(image_base64) image_hash = hashlib.md5(image_bytes).hexdigest() - + image_format = Image.open(io.BytesIO(image_bytes)).format.lower() # 检查是否已经注册过 existing_emoji = self.db['emoji'].find_one({'filename': filename}) description = None @@ -278,7 +280,7 @@ class EmojiManager: if global_config.EMOJI_CHECK: - check = await self._check_emoji(image_base64) + check = await self._check_emoji(image_base64, image_format) if '是' not in check: os.remove(image_path) logger.info(f"描述: {description}") diff --git a/src/plugins/chat/utils_image.py b/src/plugins/chat/utils_image.py index fb2428870..94014b5b4 100644 --- a/src/plugins/chat/utils_image.py +++ b/src/plugins/chat/utils_image.py @@ -4,6 +4,8 @@ import time import aiohttp import hashlib from typing import Optional, Union +from PIL import Image +import io from loguru import logger from nonebot import get_driver @@ -119,6 +121,7 @@ class ImageManager: # 计算哈希值 image_hash = hashlib.md5(image_bytes).hexdigest() + image_format = Image.open(io.BytesIO(image_bytes)).format.lower() # 查重 existing = self.db.images.find_one({'hash': image_hash}) @@ -127,7 +130,7 @@ class ImageManager: # 生成文件名和路径 timestamp = int(time.time()) - filename = f"{timestamp}_{image_hash[:8]}.jpg" + filename = f"{timestamp}_{image_hash[:8]}.{image_format}" file_path = os.path.join(self.IMAGE_DIR, filename) # 保存文件 @@ -238,7 +241,8 @@ class ImageManager: # 计算图片哈希 image_bytes = base64.b64decode(image_base64) image_hash = hashlib.md5(image_bytes).hexdigest() - + image_format = Image.open(io.BytesIO(image_bytes)).format.lower() + # 查询缓存的描述 cached_description = self._get_description_from_db(image_hash, 'emoji') if cached_description: @@ -247,13 +251,13 @@ class ImageManager: # 调用AI获取描述 prompt = "这是一个表情包，使用中文简洁的描述一下表情包的内容和表情包所表达的情感" - description, _ = await self._llm.generate_response_for_image(prompt, image_base64) + description, _ = await self._llm.generate_response_for_image(prompt, image_base64, image_format) # 根据配置决定是否保存图片 if global_config.EMOJI_SAVE: # 生成文件名和路径 timestamp = int(time.time()) - filename = f"{timestamp}_{image_hash[:8]}.jpg" + filename = f"{timestamp}_{image_hash[:8]}.{image_format}" file_path = os.path.join(self.IMAGE_DIR, 'emoji',filename) try: @@ -293,7 +297,8 @@ class ImageManager: # 计算图片哈希 image_bytes = base64.b64decode(image_base64) image_hash = hashlib.md5(image_bytes).hexdigest() - + image_format = Image.open(io.BytesIO(image_bytes)).format.lower() + # 查询缓存的描述 cached_description = self._get_description_from_db(image_hash, 'image') if cached_description: @@ -302,7 +307,7 @@ class ImageManager: # 调用AI获取描述 prompt = "请用中文描述这张图片的内容。如果有文字，请把文字都描述出来。并尝试猜测这个图片的含义。最多200个字。" - description, _ = await self._llm.generate_response_for_image(prompt, image_base64) + description, _ = await self._llm.generate_response_for_image(prompt, image_base64, image_format) print(f"描述是{description}") @@ -314,7 +319,7 @@ class ImageManager: if global_config.EMOJI_SAVE: # 生成文件名和路径 timestamp = int(time.time()) - filename = f"{timestamp}_{image_hash[:8]}.jpg" + filename = f"{timestamp}_{image_hash[:8]}.{image_format}" file_path = os.path.join(self.IMAGE_DIR,'image', filename) try: diff --git a/src/plugins/models/utils_model.py b/src/plugins/models/utils_model.py index 5335e3d65..aa07bb55d 100644 --- a/src/plugins/models/utils_model.py +++ b/src/plugins/models/utils_model.py @@ -104,6 +104,7 @@ class LLM_request: endpoint: str, prompt: str = None, image_base64: str = None, + image_format: str = None, payload: dict = None, retry_policy: dict = None, response_handler: callable = None, @@ -115,6 +116,7 @@ class LLM_request: endpoint: API端点路径 (如 "chat/completions") prompt: prompt文本 image_base64: 图片的base64编码 + image_format: 图片格式 payload: 请求体数据 retry_policy: 自定义重试策略 response_handler: 自定义响应处理器 @@ -151,7 +153,7 @@ class LLM_request: # 构建请求体 if image_base64: - payload = await self._build_payload(prompt, image_base64) + payload = await self._build_payload(prompt, image_base64, image_format) elif payload is None: payload = await self._build_payload(prompt) @@ -172,7 +174,7 @@ class LLM_request: if response.status == 413: logger.warning("请求体过大，尝试压缩...") image_base64 = compress_base64_image_by_scale(image_base64) - payload = await self._build_payload(prompt, image_base64) + payload = await self._build_payload(prompt, image_base64, image_format) elif response.status in [500, 503]: logger.error(f"错误码: {response.status} - {error_code_mapping.get(response.status)}") raise RuntimeError("服务器负载过高，模型恢复失败QAQ") @@ -294,7 +296,7 @@ class LLM_request: new_params["max_completion_tokens"] = new_params.pop("max_tokens") return new_params - async def _build_payload(self, prompt: str, image_base64: str = None) -> dict: + async def _build_payload(self, prompt: str, image_base64: str = None, image_format: str = None) -> dict: """构建请求体""" # 复制一份参数，避免直接修改 self.params params_copy = await self._transform_parameters(self.params) @@ -306,7 +308,7 @@ class LLM_request: "role": "user", "content": [ {"type": "text", "text": prompt}, - {"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{image_base64}"}} + {"type": "image_url", "image_url": {"url": f"data:image/{image_format.lower()};base64,{image_base64}"}} ] } ], @@ -391,13 +393,14 @@ class LLM_request: ) return content, reasoning_content - async def generate_response_for_image(self, prompt: str, image_base64: str) -> Tuple[str, str]: + async def generate_response_for_image(self, prompt: str, image_base64: str, image_format: str) -> Tuple[str, str]: """根据输入的提示和图片生成模型的异步响应""" content, reasoning_content = await self._execute_request( endpoint="/chat/completions", prompt=prompt, - image_base64=image_base64 + image_base64=image_base64, + image_format=image_format ) return content, reasoning_content