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调整对应的调用

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UnCLAS-Prommer
2025-07-30 17:07:55 +08:00
parent 3c40ceda4c
commit 6c0edd0ad7
40 changed files with 580 additions and 1236 deletions
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60
src/chat/emoji_system/emoji_manager.py
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@@ -8,15 +8,15 @@ import traceback
import io
import re
import binascii
from typing import Optional, Tuple, List, Any
from PIL import Image
from rich.traceback import install
from src.common.database.database_model import Emoji
from src.common.database.database import db as peewee_db
from src.common.logger import get_logger
from src.config.config import global_config
from src.config.config import global_config, model_config
from src.chat.utils.utils_image import image_path_to_base64, get_image_manager
from src.llm_models.utils_model import LLMRequest
@@ -379,9 +379,9 @@ class EmojiManager:
self._scan_task = None
self.vlm = LLMRequest(model=global_config.model.vlm, temperature=0.3, max_tokens=1000, request_type="emoji")
self.vlm = LLMRequest(model_set=model_config.model_task_config.vlm, request_type="emoji")
self.llm_emotion_judge = LLMRequest(
model=global_config.model.utils, max_tokens=600, request_type="emoji"
model_set=model_config.model_task_config.utils, request_type="emoji"
) # 更高的温度，更少的token（后续可以根据情绪来调整温度）
self.emoji_num = 0
@@ -492,6 +492,7 @@ class EmojiManager:
return None
def _levenshtein_distance(self, s1: str, s2: str) -> int:
# sourcery skip: simplify-empty-collection-comparison, simplify-len-comparison, simplify-str-len-comparison
"""计算两个字符串的编辑距离
Args:
@@ -629,11 +630,11 @@ class EmojiManager:
if success:
# 注册成功则跳出循环
break
else:
# 注册失败则删除对应文件
file_path = os.path.join(EMOJI_DIR, filename)
os.remove(file_path)
logger.warning(f"[清理] 删除注册失败的表情包文件: {filename}")
# 注册失败则删除对应文件
file_path = os.path.join(EMOJI_DIR, filename)
os.remove(file_path)
logger.warning(f"[清理] 删除注册失败的表情包文件: {filename}")
except Exception as e:
logger.error(f"[错误] 扫描表情包目录失败: {str(e)}")
@@ -694,6 +695,7 @@ class EmojiManager:
return []
async def get_emoji_from_manager(self, emoji_hash: str) -> Optional["MaiEmoji"]:
# sourcery skip: use-next
"""从内存中的 emoji_objects 列表获取表情包
参数:
@@ -709,10 +711,10 @@ class EmojiManager:
async def get_emoji_description_by_hash(self, emoji_hash: str) -> Optional[str]:
"""根据哈希值获取已注册表情包的描述
Args:
emoji_hash: 表情包的哈希值
Returns:
Optional[str]: 表情包描述，如果未找到则返回None
"""
@@ -722,7 +724,7 @@ class EmojiManager:
if emoji and emoji.description:
logger.info(f"[缓存命中] 从内存获取表情包描述: {emoji.description[:50]}...")
return emoji.description
# 如果内存中没有，从数据库查找
self._ensure_db()
try:
@@ -732,9 +734,9 @@ class EmojiManager:
return emoji_record.description
except Exception as e:
logger.error(f"从数据库查询表情包描述时出错: {e}")
return None
except Exception as e:
logger.error(f"获取表情包描述失败 (Hash: {emoji_hash}): {str(e)}")
return None
@@ -779,6 +781,7 @@ class EmojiManager:
return False
async def replace_a_emoji(self, new_emoji: "MaiEmoji") -> bool:
# sourcery skip: use-getitem-for-re-match-groups
"""替换一个表情包
Args:
@@ -820,7 +823,7 @@ class EmojiManager:
)
# 调用大模型进行决策
decision, _ = await self.llm_emotion_judge.generate_response_async(prompt, temperature=0.8)
decision, _ = await self.llm_emotion_judge.generate_response_async(prompt, temperature=0.8, max_tokens=600)
logger.info(f"[决策] 结果: {decision}")
# 解析决策结果
@@ -828,9 +831,7 @@ class EmojiManager:
logger.info("[决策] 不删除任何表情包")
return False
# 尝试从决策中提取表情包编号
match = re.search(r"删除编号(\d+)", decision)
if match:
if match := re.search(r"删除编号(\d+)", decision):
emoji_index = int(match.group(1)) - 1 # 转换为0-based索引
# 检查索引是否有效
@@ -889,6 +890,7 @@ class EmojiManager:
existing_description = None
try:
from src.common.database.database_model import Images
existing_image = Images.get_or_none((Images.emoji_hash == image_hash) & (Images.type == "emoji"))
if existing_image and existing_image.description:
existing_description = existing_image.description
@@ -902,15 +904,21 @@ class EmojiManager:
logger.info("[优化] 复用已有的详细描述，跳过VLM调用")
else:
logger.info("[VLM分析] 生成新的详细描述")
if image_format == "gif" or image_format == "GIF":
if image_format in ["gif", "GIF"]:
image_base64 = get_image_manager().transform_gif(image_base64) # type: ignore
if not image_base64:
raise RuntimeError("GIF表情包转换失败")
prompt = "这是一个动态图表情包，每一张图代表了动态图的某一帧，黑色背景代表透明，描述一下表情包表达的情感和内容，描述细节，从互联网梗,meme的角度去分析"
description, _ = await self.vlm.generate_response_for_image(prompt, image_base64, "jpg")
description, _ = await self.vlm.generate_response_for_image(
prompt, image_base64, "jpg", temperature=0.3, max_tokens=1000
)
else:
prompt = "这是一个表情包，请详细描述一下表情包所表达的情感和内容，描述细节，从互联网梗,meme的角度去分析"
description, _ = await self.vlm.generate_response_for_image(prompt, image_base64, image_format)
prompt = (
"这是一个表情包，请详细描述一下表情包所表达的情感和内容，描述细节，从互联网梗,meme的角度去分析"
)
description, _ = await self.vlm.generate_response_for_image(
prompt, image_base64, image_format, temperature=0.3, max_tokens=1000
)
# 审核表情包
if global_config.emoji.content_filtration:
@@ -922,7 +930,9 @@ class EmojiManager:
4. 不要出现5个以上文字
请回答这个表情包是否满足上述要求，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, image_format)
content, _ = await self.vlm.generate_response_for_image(
prompt, image_base64, image_format, temperature=0.3, max_tokens=1000
)
if content == "否":
return "", []
@@ -933,7 +943,9 @@ class EmojiManager:
你可以关注其幽默和讽刺意味，动用贴吧，微博，小红书的知识，必须从互联网梗,meme的角度去分析
请直接输出描述，不要出现任何其他内容，如果有多个描述，可以用逗号分隔
"""
emotions_text, _ = await self.llm_emotion_judge.generate_response_async(emotion_prompt, temperature=0.7)
emotions_text, _ = await self.llm_emotion_judge.generate_response_async(
emotion_prompt, temperature=0.7, max_tokens=600
)
# 处理情感列表
emotions = [e.strip() for e in emotions_text.split(",") if e.strip()]