feat:优化AI
This commit is contained in:
@@ -9,6 +9,7 @@ import asyncio
|
||||
import tomllib
|
||||
import aiohttp
|
||||
import json
|
||||
import re
|
||||
from pathlib import Path
|
||||
from datetime import datetime
|
||||
from loguru import logger
|
||||
@@ -650,6 +651,397 @@ class AIChat(PluginBase):
|
||||
return ""
|
||||
return str(content)
|
||||
|
||||
def _sanitize_llm_output(self, text) -> str:
|
||||
"""
|
||||
清洗 LLM 输出，尽量满足：不输出思维链、不使用 Markdown。
|
||||
|
||||
说明：提示词并非强约束，因此在所有“发给用户/写入上下文”的出口统一做后处理。
|
||||
"""
|
||||
if text is None:
|
||||
return ""
|
||||
raw = str(text)
|
||||
cleaned = raw
|
||||
|
||||
output_cfg = (self.config or {}).get("output", {})
|
||||
strip_thinking = output_cfg.get("strip_thinking", True)
|
||||
strip_markdown = output_cfg.get("strip_markdown", True)
|
||||
|
||||
# 先做一次 Markdown 清理，避免 “**思考过程：**/### 思考” 这类包裹导致无法识别
|
||||
if strip_markdown:
|
||||
cleaned = self._strip_markdown_syntax(cleaned)
|
||||
|
||||
if strip_thinking:
|
||||
cleaned = self._strip_thinking_content(cleaned)
|
||||
|
||||
# 再跑一轮：部分模型会把“思考/最终”标记写成 Markdown，或在剥离标签后才露出标记
|
||||
if strip_markdown:
|
||||
cleaned = self._strip_markdown_syntax(cleaned)
|
||||
if strip_thinking:
|
||||
cleaned = self._strip_thinking_content(cleaned)
|
||||
|
||||
cleaned = cleaned.strip()
|
||||
# 兜底：清洗后仍残留明显“思维链/大纲”标记时，再尝试一次“抽取最终段”
|
||||
if strip_thinking and cleaned and self._contains_thinking_markers(cleaned):
|
||||
extracted = self._extract_after_last_answer_marker(cleaned)
|
||||
if not extracted:
|
||||
extracted = self._extract_final_answer_from_outline(cleaned)
|
||||
if extracted:
|
||||
cleaned = extracted.strip()
|
||||
# 仍残留标记：尽量选取最后一个“不含标记”的段落作为最终回复
|
||||
if cleaned and self._contains_thinking_markers(cleaned):
|
||||
parts = [p.strip() for p in re.split(r"\n{2,}", cleaned) if p.strip()]
|
||||
for p in reversed(parts):
|
||||
if not self._contains_thinking_markers(p):
|
||||
cleaned = p
|
||||
break
|
||||
cleaned = cleaned.strip()
|
||||
|
||||
# 最终兜底：仍然像思维链就直接丢弃（宁可不发也不要把思维链发出去）
|
||||
if strip_thinking and cleaned and self._contains_thinking_markers(cleaned):
|
||||
return ""
|
||||
|
||||
if cleaned:
|
||||
return cleaned
|
||||
|
||||
raw_stripped = raw.strip()
|
||||
# 清洗后为空时，不要回退到包含思维链标记的原文（避免把 <think>... 直接发出去）
|
||||
if strip_thinking and self._contains_thinking_markers(raw_stripped):
|
||||
return ""
|
||||
return raw_stripped
|
||||
|
||||
def _contains_thinking_markers(self, text: str) -> bool:
|
||||
"""粗略判断文本是否包含明显的“思考/推理”外显标记，用于决定是否允许回退原文。"""
|
||||
if not text:
|
||||
return False
|
||||
|
||||
lowered = text.lower()
|
||||
tag_tokens = (
|
||||
"<think", "</think",
|
||||
"<analysis", "</analysis",
|
||||
"<reasoning", "</reasoning",
|
||||
"<thought", "</thought",
|
||||
"<thinking", "</thinking",
|
||||
"<thoughts", "</thoughts",
|
||||
"<scratchpad", "</scratchpad",
|
||||
"<think", "</think",
|
||||
"<analysis", "</analysis",
|
||||
"<reasoning", "</reasoning",
|
||||
"<thought", "</thought",
|
||||
"<thinking", "</thinking",
|
||||
"<thoughts", "</thoughts",
|
||||
"<scratchpad", "</scratchpad",
|
||||
)
|
||||
if any(tok in lowered for tok in tag_tokens):
|
||||
return True
|
||||
|
||||
stripped = text.strip()
|
||||
if stripped.startswith("{") and stripped.endswith("}"):
|
||||
# JSON 结构化输出（常见于“analysis/final”）
|
||||
json_keys = (
|
||||
"\"analysis\"",
|
||||
"\"reasoning\"",
|
||||
"\"thought\"",
|
||||
"\"thoughts\"",
|
||||
"\"scratchpad\"",
|
||||
"\"final\"",
|
||||
"\"answer\"",
|
||||
"\"response\"",
|
||||
"\"output\"",
|
||||
"\"text\"",
|
||||
)
|
||||
if any(k in lowered for k in json_keys):
|
||||
return True
|
||||
|
||||
# YAML/KV 风格
|
||||
if re.search(r"(?im)^\s*(analysis|reasoning|thoughts?|scratchpad|final|answer|response|output|text|思考|分析|推理|最终|输出)\s*[:：]", text):
|
||||
return True
|
||||
|
||||
marker_re = re.compile(
|
||||
r"(?mi)^\s*(?:\d+\s*[\.\、:：)）\-–—]\s*)?(?:[-*•]+\s*)?"
|
||||
r"(?:【\s*(?:思考过程|推理过程|分析过程|思考|分析|推理|内心独白|内心os|思维链|思路|"
|
||||
r"chain\s*of\s*thought|reasoning|analysis|thinking|thoughts|thought\s*process|scratchpad)\s*】"
|
||||
r"|(?:思考过程|推理过程|分析过程|思考|分析|推理|内心独白|内心os|思维链|思路|"
|
||||
r"chain\s*of\s*thought|reasoning|analysis|analyze|thinking|thoughts|thought\s*process|scratchpad|internal\s*monologue|mind\s*space|final\s*polish|output\s*generation)"
|
||||
r"(?:\s*】)?\s*(?:[:：]|$|\s+))"
|
||||
)
|
||||
return marker_re.search(text) is not None
|
||||
|
||||
def _extract_after_last_answer_marker(self, text: str) -> str | None:
|
||||
"""从文本中抽取最后一个“最终/输出/答案”标记后的内容（不要求必须是编号大纲）。"""
|
||||
if not text:
|
||||
return None
|
||||
|
||||
# 1) 明确的行首标记：Text:/Final Answer:/输出: ...
|
||||
marker_re = re.compile(
|
||||
r"(?im)^\s*(?:\d+\s*[\.\、:：\)、)）\-–—]\s*)?"
|
||||
r"(?:text|final\s*answer|final\s*response|final\s*output|final|output|answer|response|输出|最终回复|最终答案|最终)\s*[:：]\s*"
|
||||
)
|
||||
matches = list(marker_re.finditer(text))
|
||||
if matches:
|
||||
candidate = text[matches[-1].end():].strip()
|
||||
if candidate:
|
||||
return candidate
|
||||
|
||||
# 2) JSON/YAML 风格：final: ... / \"final\": \"...\"
|
||||
kv_re = re.compile(
|
||||
r"(?im)^\s*\"?(?:final|answer|response|output|text|最终|最终回复|最终答案|输出)\"?\s*[:：]\s*"
|
||||
)
|
||||
kv_matches = list(kv_re.finditer(text))
|
||||
if kv_matches:
|
||||
candidate = text[kv_matches[-1].end():].strip()
|
||||
if candidate:
|
||||
return candidate
|
||||
|
||||
# 3) 纯 JSON 对象（尝试解析）
|
||||
stripped = text.strip()
|
||||
if stripped.startswith("{") and stripped.endswith("}"):
|
||||
try:
|
||||
obj = json.loads(stripped)
|
||||
if isinstance(obj, dict):
|
||||
for key in ("final", "answer", "response", "output", "text"):
|
||||
v = obj.get(key)
|
||||
if isinstance(v, str) and v.strip():
|
||||
return v.strip()
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
return None
|
||||
|
||||
def _extract_final_answer_from_outline(self, text: str) -> str | None:
|
||||
"""从“分析/草稿/输出”这类结构化大纲中提取最终回复正文（用于拦截思维链）。"""
|
||||
if not text:
|
||||
return None
|
||||
|
||||
# 至少包含多个“1./2./3.”段落，才认为可能是大纲/思维链输出
|
||||
heading_re = re.compile(r"(?m)^\s*\d+\s*[\.\、:：\)、)）\-–—]\s*\S+")
|
||||
if len(heading_re.findall(text)) < 2:
|
||||
return None
|
||||
|
||||
# 优先：提取最后一个 “Text:/Final Answer:/Output:” 之后的内容
|
||||
marker_re = re.compile(
|
||||
r"(?im)^\s*(?:\d+\s*[\.\、:：\)、)）\-–—]\s*)?"
|
||||
r"(?:text|final\s*answer|final\s*response|final\s*output|output|answer|response|输出|最终回复|最终答案)\s*[:：]\s*"
|
||||
)
|
||||
matches = list(marker_re.finditer(text))
|
||||
if matches:
|
||||
candidate = text[matches[-1].end():].strip()
|
||||
if candidate:
|
||||
return candidate
|
||||
|
||||
# 没有明确的最终标记时，仅在包含“分析/思考/草稿/输出”等元信息关键词的情况下兜底抽取
|
||||
lowered = text.lower()
|
||||
outline_keywords = (
|
||||
"analyze",
|
||||
"analysis",
|
||||
"reasoning",
|
||||
"internal monologue",
|
||||
"mind space",
|
||||
"draft",
|
||||
"drafting",
|
||||
"outline",
|
||||
"plan",
|
||||
"steps",
|
||||
"formulating response",
|
||||
"final polish",
|
||||
"final answer",
|
||||
"output generation",
|
||||
"system prompt",
|
||||
"chat log",
|
||||
"previous turn",
|
||||
"current situation",
|
||||
)
|
||||
cn_keywords = ("思考", "分析", "推理", "思维链", "草稿", "计划", "步骤", "输出", "最终")
|
||||
if not any(k in lowered for k in outline_keywords) and not any(k in text for k in cn_keywords):
|
||||
return None
|
||||
|
||||
# 次选：取最后一个非空段落（避免返回整段大纲）
|
||||
parts = [p.strip() for p in re.split(r"\n{2,}", text) if p.strip()]
|
||||
if not parts:
|
||||
return None
|
||||
|
||||
last = parts[-1]
|
||||
if len(heading_re.findall(last)) == 0:
|
||||
return last
|
||||
return None
|
||||
|
||||
def _strip_thinking_content(self, text: str) -> str:
|
||||
"""移除常见的“思考/推理”外显内容（如 <think>...</think>、思考：...）。"""
|
||||
if not text:
|
||||
return ""
|
||||
|
||||
t = text.replace("\r\n", "\n").replace("\r", "\n")
|
||||
|
||||
# 1) 先移除显式标签块（常见于某些推理模型）
|
||||
thinking_tags = ("think", "analysis", "reasoning", "thought", "thinking", "thoughts", "scratchpad", "reflection")
|
||||
for tag in thinking_tags:
|
||||
t = re.sub(rf"<{tag}\b[^>]*>.*?</{tag}>", "", t, flags=re.IGNORECASE | re.DOTALL)
|
||||
# 兼容被转义的标签（<think>...</think>）
|
||||
t = re.sub(rf"<{tag}\b[^&]*>.*?</{tag}>", "", t, flags=re.IGNORECASE | re.DOTALL)
|
||||
|
||||
# 1.1) 兜底：流式/截断导致标签未闭合时，若开头出现思考标签，直接截断后续内容
|
||||
m = re.search(r"<(think|analysis|reasoning|thought|thinking|thoughts|scratchpad|reflection)\b[^>]*>", t, flags=re.IGNORECASE)
|
||||
if m and m.start() < 200:
|
||||
t = t[: m.start()].rstrip()
|
||||
m2 = re.search(r"<(think|analysis|reasoning|thought|thinking|thoughts|scratchpad|reflection)\b[^&]*>", t, flags=re.IGNORECASE)
|
||||
if m2 and m2.start() < 200:
|
||||
t = t[: m2.start()].rstrip()
|
||||
|
||||
# 2) 再处理“思考：.../最终：...”这种分段格式（尽量只剥离前置思考）
|
||||
lines = t.split("\n")
|
||||
if not lines:
|
||||
return t
|
||||
|
||||
# 若文本中包含明显的“最终/输出/答案”标记（不限是否编号），直接抽取最后一段，避免把大纲整体发出去
|
||||
if self._contains_thinking_markers(t):
|
||||
extracted_anywhere = self._extract_after_last_answer_marker(t)
|
||||
if extracted_anywhere:
|
||||
return extracted_anywhere
|
||||
|
||||
reasoning_kw = (
|
||||
r"思考过程|推理过程|分析过程|思考|分析|推理|思路|内心独白|内心os|思维链|"
|
||||
r"chain\s*of\s*thought|reasoning|analysis|analyze|thinking|thoughts|thought\s*process|scratchpad|plan|steps|draft|outline"
|
||||
)
|
||||
answer_kw = r"最终答案|最终回复|最终|回答|回复|答复|结论|输出|final(?:\s*answer)?|final\s*response|final\s*output|answer|response|output|text"
|
||||
|
||||
# 兼容：
|
||||
# - 思考：... / 最终回复：...
|
||||
# - 【思考】... / 【最终】...
|
||||
# - **思考过程：**（Markdown 会在外层先被剥离）
|
||||
reasoning_start = re.compile(
|
||||
rf"^\s*(?:\d+\s*[\.\、:：\)、)）\-–—]\s*)?(?:[-*•]+\s*)?"
|
||||
rf"(?:【\s*(?:{reasoning_kw})\s*】\s*[:：]?\s*|(?:{reasoning_kw})(?:\s*】)?\s*(?:[:：]|$|\s+))",
|
||||
re.IGNORECASE,
|
||||
)
|
||||
answer_start = re.compile(
|
||||
rf"^\s*(?:\d+\s*[\.\、:：\)、)）\-–—]\s*)?(?:[-*•]+\s*)?"
|
||||
rf"(?:【\s*(?:{answer_kw})\s*】\s*[:：]?\s*|(?:{answer_kw})(?:\s*】)?\s*(?:[:：]|$)\s*)",
|
||||
re.IGNORECASE,
|
||||
)
|
||||
|
||||
# 2.0) 若文本开头就是“最终回复：/Final answer:”之类，直接去掉标记（不强依赖出现“思考块”）
|
||||
for idx, line in enumerate(lines):
|
||||
if line.strip() == "":
|
||||
continue
|
||||
m0 = answer_start.match(line)
|
||||
if m0:
|
||||
lines[idx] = line[m0.end():].lstrip()
|
||||
break
|
||||
|
||||
has_reasoning = any(reasoning_start.match(line) for line in lines[:10])
|
||||
has_answer_marker = any(answer_start.match(line) for line in lines)
|
||||
|
||||
# 2.1) 若同时存在“思考块 + 答案标记”，跳过思考块直到答案标记
|
||||
if has_reasoning and has_answer_marker:
|
||||
out_lines: list[str] = []
|
||||
skipping = False
|
||||
answer_started = False
|
||||
for line in lines:
|
||||
if answer_started:
|
||||
out_lines.append(line)
|
||||
continue
|
||||
|
||||
if not skipping and reasoning_start.match(line):
|
||||
skipping = True
|
||||
continue
|
||||
|
||||
if skipping:
|
||||
m = answer_start.match(line)
|
||||
if m:
|
||||
answer_started = True
|
||||
skipping = False
|
||||
out_lines.append(line[m.end():].lstrip())
|
||||
continue
|
||||
|
||||
m = answer_start.match(line)
|
||||
if m:
|
||||
answer_started = True
|
||||
out_lines.append(line[m.end():].lstrip())
|
||||
else:
|
||||
out_lines.append(line)
|
||||
|
||||
t2 = "\n".join(out_lines).strip()
|
||||
return t2 if t2 else t
|
||||
|
||||
# 2.2) 兜底：若开头就是“思考：”，尝试去掉第一段（到第一个空行）
|
||||
if has_reasoning:
|
||||
first_blank_idx = None
|
||||
for idx, line in enumerate(lines):
|
||||
if line.strip() == "":
|
||||
first_blank_idx = idx
|
||||
break
|
||||
if first_blank_idx is not None and first_blank_idx + 1 < len(lines):
|
||||
candidate = "\n".join(lines[first_blank_idx + 1 :]).strip()
|
||||
if candidate:
|
||||
return candidate
|
||||
|
||||
# 2.3) 兜底：识别“1. Analyze... 2. ... 6. Output ... Text: ...”这类思维链大纲并抽取最终正文
|
||||
outline_extracted = self._extract_final_answer_from_outline("\n".join(lines).strip())
|
||||
if outline_extracted:
|
||||
return outline_extracted
|
||||
|
||||
# 将行级处理结果合回文本（例如去掉开头的“最终回复：”标记）
|
||||
t = "\n".join(lines).strip()
|
||||
|
||||
# 3) 兼容 <final>...</final> 这类包裹（保留正文，去掉标签）
|
||||
t = re.sub(r"</?\s*(final|answer)\s*>", "", t, flags=re.IGNORECASE).strip()
|
||||
|
||||
return t
|
||||
|
||||
def _strip_markdown_syntax(self, text: str) -> str:
|
||||
"""将常见 Markdown 标记转换为更像纯文本的形式（保留内容，移除格式符）。"""
|
||||
if not text:
|
||||
return ""
|
||||
|
||||
t = text.replace("\r\n", "\n").replace("\r", "\n")
|
||||
|
||||
# 去掉代码块围栏（保留内容）
|
||||
t = re.sub(r"```[^\n]*\n", "", t)
|
||||
t = t.replace("```", "")
|
||||
|
||||
# 图片/链接： / [text](url)
|
||||
def _md_image_repl(m: re.Match) -> str:
|
||||
alt = (m.group(1) or "").strip()
|
||||
url = (m.group(2) or "").strip()
|
||||
if alt and url:
|
||||
return f"{alt}（{url}）"
|
||||
return url or alt or ""
|
||||
|
||||
def _md_link_repl(m: re.Match) -> str:
|
||||
label = (m.group(1) or "").strip()
|
||||
url = (m.group(2) or "").strip()
|
||||
if label and url:
|
||||
return f"{label}（{url}）"
|
||||
return url or label or ""
|
||||
|
||||
t = re.sub(r"!\[([^\]]*)\]\(([^)]+)\)", _md_image_repl, t)
|
||||
t = re.sub(r"\[([^\]]+)\]\(([^)]+)\)", _md_link_repl, t)
|
||||
|
||||
# 行级标记：标题、引用、分割线
|
||||
cleaned_lines: list[str] = []
|
||||
for line in t.split("\n"):
|
||||
line = re.sub(r"^\s{0,3}#{1,6}\s+", "", line) # 标题
|
||||
line = re.sub(r"^\s{0,3}>\s?", "", line) # 引用
|
||||
if re.match(r"^\s*(?:-{3,}|\*{3,}|_{3,})\s*$", line):
|
||||
continue # 分割线整行移除
|
||||
cleaned_lines.append(line)
|
||||
t = "\n".join(cleaned_lines)
|
||||
|
||||
# 行内代码：`code`
|
||||
t = re.sub(r"`([^`]+)`", r"\1", t)
|
||||
|
||||
# 粗体/删除线（保留文本）
|
||||
t = t.replace("**", "")
|
||||
t = t.replace("__", "")
|
||||
t = t.replace("~~", "")
|
||||
|
||||
# 斜体（保留文本，避免误伤乘法/通配符，仅处理成对包裹）
|
||||
t = re.sub(r"(?<!\*)\*([^*\n]+)\*(?!\*)", r"\1", t)
|
||||
t = re.sub(r"(?<!_)_([^_\n]+)_(?!_)", r"\1", t)
|
||||
|
||||
# 压缩过多空行
|
||||
t = re.sub(r"\n{3,}", "\n\n", t)
|
||||
return t.strip()
|
||||
|
||||
def _append_group_history_messages(self, messages: list, recent_history: list):
|
||||
"""将群聊历史按 role 追加到 LLM messages"""
|
||||
for msg in recent_history:
|
||||
@@ -661,6 +1053,8 @@ class AIChat(PluginBase):
|
||||
if role == "assistant":
|
||||
if isinstance(msg_content, list):
|
||||
msg_content = self._extract_text_from_multimodal(msg_content)
|
||||
# 避免旧历史中的 Markdown/思维链污染上下文
|
||||
msg_content = self._sanitize_llm_output(msg_content)
|
||||
messages.append({
|
||||
"role": "assistant",
|
||||
"content": msg_content
|
||||
@@ -971,10 +1365,20 @@ class AIChat(PluginBase):
|
||||
# 获取用户昵称（用于历史记录）- 使用缓存优化
|
||||
nickname = await self._get_user_nickname(bot, from_wxid, user_wxid, is_group)
|
||||
|
||||
# 提取实际消息内容（去除@），仅在需要回复时使用
|
||||
actual_content = ""
|
||||
if should_reply:
|
||||
actual_content = self._extract_content(message, content)
|
||||
|
||||
# 保存到群组历史记录（所有消息都保存，不管是否回复）
|
||||
# 但如果是 AutoReply 触发的，跳过保存（消息已经在正常流程中保存过了）
|
||||
if is_group and not message.get('_auto_reply_triggered'):
|
||||
await self._add_to_history(from_wxid, nickname, content, sender_wxid=user_wxid)
|
||||
# mention 模式下，群聊里@机器人仅作为触发条件，不进入上下文，避免同一句话在上下文中出现两种形式（含@/不含@）
|
||||
trigger_mode = self.config.get("behavior", {}).get("trigger_mode", "mention")
|
||||
history_content = content
|
||||
if trigger_mode == "mention" and should_reply and actual_content:
|
||||
history_content = actual_content
|
||||
await self._add_to_history(from_wxid, nickname, history_content, sender_wxid=user_wxid)
|
||||
|
||||
# 如果不需要回复，直接返回
|
||||
if not should_reply:
|
||||
@@ -990,8 +1394,6 @@ class AIChat(PluginBase):
|
||||
logger.warning(f"用户 {user_wxid} 触发限流，{reset_time}秒后重置")
|
||||
return False
|
||||
|
||||
# 提取实际消息内容（去除@）
|
||||
actual_content = self._extract_content(message, content)
|
||||
if not actual_content:
|
||||
return
|
||||
|
||||
@@ -1004,6 +1406,10 @@ class AIChat(PluginBase):
|
||||
if not message.get('_auto_reply_triggered'):
|
||||
self._add_to_memory(chat_id, "user", actual_content)
|
||||
|
||||
# 群聊：消息已写入 history，则不再重复附加到 LLM messages，避免“同一句话发给AI两次”
|
||||
history_enabled = bool(self.store) and self.config.get("history", {}).get("enabled", True)
|
||||
append_user_message = not (is_group and history_enabled and not message.get('_auto_reply_triggered'))
|
||||
|
||||
# 调用 AI API（带重试机制）
|
||||
max_retries = self.config.get("api", {}).get("max_retries", 2)
|
||||
response = None
|
||||
@@ -1011,7 +1417,16 @@ class AIChat(PluginBase):
|
||||
|
||||
for attempt in range(max_retries + 1):
|
||||
try:
|
||||
response = await self._call_ai_api(actual_content, bot, from_wxid, chat_id, nickname, user_wxid, is_group)
|
||||
response = await self._call_ai_api(
|
||||
actual_content,
|
||||
bot,
|
||||
from_wxid,
|
||||
chat_id,
|
||||
nickname,
|
||||
user_wxid,
|
||||
is_group,
|
||||
append_user_message=append_user_message,
|
||||
)
|
||||
|
||||
# 检查返回值：
|
||||
# - None: 工具调用已异步处理，不需要重试
|
||||
@@ -1040,15 +1455,19 @@ class AIChat(PluginBase):
|
||||
# 发送回复并添加到记忆
|
||||
# 注意：如果返回 None 或空字符串，说明已经以其他形式处理了，不需要再发送文本
|
||||
if response:
|
||||
await bot.send_text(from_wxid, response)
|
||||
self._add_to_memory(chat_id, "assistant", response)
|
||||
# 保存机器人回复到历史记录
|
||||
if is_group:
|
||||
with open("main_config.toml", "rb") as f:
|
||||
main_config = tomllib.load(f)
|
||||
bot_nickname = main_config.get("Bot", {}).get("nickname", "机器人")
|
||||
await self._add_to_history(from_wxid, bot_nickname, response, role="assistant")
|
||||
logger.success(f"AI 回复成功: {response[:50]}...")
|
||||
cleaned_response = self._sanitize_llm_output(response)
|
||||
if cleaned_response:
|
||||
await bot.send_text(from_wxid, cleaned_response)
|
||||
self._add_to_memory(chat_id, "assistant", cleaned_response)
|
||||
# 保存机器人回复到历史记录
|
||||
if is_group:
|
||||
with open("main_config.toml", "rb") as f:
|
||||
main_config = tomllib.load(f)
|
||||
bot_nickname = main_config.get("Bot", {}).get("nickname", "机器人")
|
||||
await self._add_to_history(from_wxid, bot_nickname, cleaned_response, role="assistant")
|
||||
logger.success(f"AI 回复成功: {cleaned_response[:50]}...")
|
||||
else:
|
||||
logger.warning("AI 回复清洗后为空（可能只包含思维链/格式标记），已跳过发送")
|
||||
else:
|
||||
logger.info("AI 回复为空或已通过其他方式发送（如聊天记录）")
|
||||
|
||||
@@ -1134,7 +1553,18 @@ class AIChat(PluginBase):
|
||||
|
||||
return content.strip()
|
||||
|
||||
async def _call_ai_api(self, user_message: str, bot=None, from_wxid: str = None, chat_id: str = None, nickname: str = "", user_wxid: str = None, is_group: bool = False) -> str:
|
||||
async def _call_ai_api(
|
||||
self,
|
||||
user_message: str,
|
||||
bot=None,
|
||||
from_wxid: str = None,
|
||||
chat_id: str = None,
|
||||
nickname: str = "",
|
||||
user_wxid: str = None,
|
||||
is_group: bool = False,
|
||||
*,
|
||||
append_user_message: bool = True,
|
||||
) -> str:
|
||||
"""调用 AI API"""
|
||||
api_config = self.config["api"]
|
||||
|
||||
@@ -1191,7 +1621,8 @@ class AIChat(PluginBase):
|
||||
messages.extend(memory_messages[:-1])
|
||||
|
||||
# 添加当前用户消息
|
||||
messages.append({"role": "user", "content": f"[{nickname}] {user_message}" if is_group and nickname else user_message})
|
||||
if append_user_message:
|
||||
messages.append({"role": "user", "content": f"[{nickname}] {user_message}" if is_group and nickname else user_message})
|
||||
|
||||
payload = {
|
||||
"model": api_config["model"],
|
||||
@@ -1285,8 +1716,12 @@ class AIChat(PluginBase):
|
||||
tool_call_hint_sent = True
|
||||
# 只有当 AI 有文本输出时才发送
|
||||
if full_content and full_content.strip():
|
||||
logger.info(f"[流式] 检测到工具调用，先发送已有文本: {full_content[:30]}...")
|
||||
await bot.send_text(from_wxid, full_content.strip())
|
||||
preview = self._sanitize_llm_output(full_content)
|
||||
if preview:
|
||||
logger.info(f"[流式] 检测到工具调用，先发送已有文本: {preview[:30]}...")
|
||||
await bot.send_text(from_wxid, preview)
|
||||
else:
|
||||
logger.info("[流式] 检测到工具调用，但文本清洗后为空（可能为思维链/无有效正文），跳过发送")
|
||||
else:
|
||||
# AI 没有输出文本，不发送默认提示
|
||||
logger.info("[流式] 检测到工具调用，AI 未输出文本")
|
||||
@@ -1347,7 +1782,7 @@ class AIChat(PluginBase):
|
||||
logger.warning("检测到模型输出了错误的工具调用格式,拦截并返回提示")
|
||||
return "抱歉,我遇到了一些技术问题,请重新描述一下你的需求~"
|
||||
|
||||
return full_content.strip()
|
||||
return self._sanitize_llm_output(full_content)
|
||||
except aiohttp.ClientError as e:
|
||||
logger.error(f"网络请求失败: {type(e).__name__}: {str(e)}")
|
||||
raise Exception(f"网络请求失败: {str(e)}")
|
||||
@@ -1578,6 +2013,11 @@ class AIChat(PluginBase):
|
||||
if not tool_result:
|
||||
continue
|
||||
|
||||
tool_message = self._sanitize_llm_output(tool_result.message) if tool_result.message is not None else ""
|
||||
|
||||
# 工具文本统一做一次输出清洗，避免工具内部/下游LLM把“思维链”发出来
|
||||
tool_message = self._sanitize_llm_output(tool_result.message) if tool_result.message is not None else ""
|
||||
|
||||
if tool_result.success:
|
||||
logger.success(f"[异步] 工具 {function_name} 执行成功")
|
||||
else:
|
||||
@@ -1588,25 +2028,32 @@ class AIChat(PluginBase):
|
||||
need_ai_reply_results.append({
|
||||
"tool_call_id": tool_call_id,
|
||||
"function_name": function_name,
|
||||
"result": tool_result.message
|
||||
"result": tool_message
|
||||
})
|
||||
continue
|
||||
|
||||
# 工具成功且需要回文本时发送
|
||||
if tool_result.success and not tool_result.already_sent and tool_result.message and not tool_result.no_reply:
|
||||
if tool_result.send_result_text:
|
||||
await bot.send_text(from_wxid, tool_result.message)
|
||||
if tool_message:
|
||||
await bot.send_text(from_wxid, tool_message)
|
||||
else:
|
||||
logger.warning(f"[异步] 工具 {function_name} 输出清洗后为空，已跳过发送")
|
||||
|
||||
# 工具失败默认回一条错误提示
|
||||
if not tool_result.success and tool_result.message and not tool_result.no_reply:
|
||||
try:
|
||||
await bot.send_text(from_wxid, f"❌ {tool_result.message}")
|
||||
if tool_message:
|
||||
await bot.send_text(from_wxid, f"❌ {tool_message}")
|
||||
else:
|
||||
await bot.send_text(from_wxid, f"❌ {function_name} 执行失败")
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
# 保存工具结果到记忆（可选）
|
||||
if tool_result.save_to_memory and chat_id:
|
||||
self._add_to_memory(chat_id, "assistant", f"[工具 {function_name} 结果]: {tool_result.message}")
|
||||
if tool_message:
|
||||
self._add_to_memory(chat_id, "assistant", f"[工具 {function_name} 结果]: {tool_message}")
|
||||
|
||||
# 如果有需要 AI 回复的工具结果，调用 AI 继续对话
|
||||
if need_ai_reply_results:
|
||||
@@ -1733,12 +2180,16 @@ class AIChat(PluginBase):
|
||||
|
||||
# 发送 AI 的回复
|
||||
if full_content.strip():
|
||||
await bot.send_text(from_wxid, full_content.strip())
|
||||
logger.success(f"[工具回传] AI 回复完成，长度: {len(full_content)}")
|
||||
cleaned_content = self._sanitize_llm_output(full_content)
|
||||
if cleaned_content:
|
||||
await bot.send_text(from_wxid, cleaned_content)
|
||||
logger.success(f"[工具回传] AI 回复完成，长度: {len(cleaned_content)}")
|
||||
else:
|
||||
logger.warning("[工具回传] AI 回复清洗后为空，已跳过发送")
|
||||
|
||||
# 保存到历史记录
|
||||
if chat_id:
|
||||
self._add_to_memory(chat_id, "assistant", full_content.strip())
|
||||
if chat_id and cleaned_content:
|
||||
self._add_to_memory(chat_id, "assistant", cleaned_content)
|
||||
else:
|
||||
logger.warning("[工具回传] AI 返回空内容")
|
||||
|
||||
@@ -1841,16 +2292,23 @@ class AIChat(PluginBase):
|
||||
|
||||
if tool_result.success and not tool_result.already_sent and tool_result.message and not tool_result.no_reply:
|
||||
if tool_result.send_result_text:
|
||||
await bot.send_text(from_wxid, tool_result.message)
|
||||
if tool_message:
|
||||
await bot.send_text(from_wxid, tool_message)
|
||||
else:
|
||||
logger.warning(f"[异步-图片] 工具 {function_name} 输出清洗后为空，已跳过发送")
|
||||
|
||||
if not tool_result.success and tool_result.message and not tool_result.no_reply:
|
||||
try:
|
||||
await bot.send_text(from_wxid, f"❌ {tool_result.message}")
|
||||
if tool_message:
|
||||
await bot.send_text(from_wxid, f"❌ {tool_message}")
|
||||
else:
|
||||
await bot.send_text(from_wxid, f"❌ {function_name} 执行失败")
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
if tool_result.save_to_memory and chat_id:
|
||||
self._add_to_memory(chat_id, "assistant", f"[工具 {function_name} 结果]: {tool_result.message}")
|
||||
if tool_message:
|
||||
self._add_to_memory(chat_id, "assistant", f"[工具 {function_name} 结果]: {tool_message}")
|
||||
|
||||
logger.info(f"[异步-图片] 所有工具执行完成")
|
||||
|
||||
@@ -2061,20 +2519,36 @@ class AIChat(PluginBase):
|
||||
await self._add_to_history(from_wxid, nickname, title_text, image_base64=image_base64)
|
||||
|
||||
# 调用AI API（带图片）
|
||||
response = await self._call_ai_api_with_image(title_text, image_base64, bot, from_wxid, chat_id, nickname, user_wxid, is_group)
|
||||
history_enabled = bool(self.store) and self.config.get("history", {}).get("enabled", True)
|
||||
append_user_message = not (is_group and history_enabled)
|
||||
response = await self._call_ai_api_with_image(
|
||||
title_text,
|
||||
image_base64,
|
||||
bot,
|
||||
from_wxid,
|
||||
chat_id,
|
||||
nickname,
|
||||
user_wxid,
|
||||
is_group,
|
||||
append_user_message=append_user_message,
|
||||
)
|
||||
|
||||
if response:
|
||||
await bot.send_text(from_wxid, response)
|
||||
self._add_to_memory(chat_id, "assistant", response)
|
||||
# 保存机器人回复到历史记录
|
||||
if is_group:
|
||||
import tomllib
|
||||
with open("main_config.toml", "rb") as f:
|
||||
main_config = tomllib.load(f)
|
||||
bot_nickname = main_config.get("Bot", {}).get("nickname", "机器人")
|
||||
await self._add_to_history(from_wxid, bot_nickname, response, role="assistant")
|
||||
logger.success(f"AI回复成功: {response[:50]}...")
|
||||
|
||||
cleaned_response = self._sanitize_llm_output(response)
|
||||
if cleaned_response:
|
||||
await bot.send_text(from_wxid, cleaned_response)
|
||||
self._add_to_memory(chat_id, "assistant", cleaned_response)
|
||||
# 保存机器人回复到历史记录
|
||||
if is_group:
|
||||
import tomllib
|
||||
with open("main_config.toml", "rb") as f:
|
||||
main_config = tomllib.load(f)
|
||||
bot_nickname = main_config.get("Bot", {}).get("nickname", "机器人")
|
||||
await self._add_to_history(from_wxid, bot_nickname, cleaned_response, role="assistant")
|
||||
logger.success(f"AI回复成功: {cleaned_response[:50]}...")
|
||||
else:
|
||||
logger.warning("AI 回复清洗后为空，已跳过发送")
|
||||
|
||||
return False
|
||||
|
||||
except Exception as e:
|
||||
@@ -2182,16 +2656,20 @@ class AIChat(PluginBase):
|
||||
response = await self._call_ai_api(combined_message, bot, from_wxid, chat_id, nickname, user_wxid, is_group)
|
||||
|
||||
if response:
|
||||
await bot.send_text(from_wxid, response)
|
||||
self._add_to_memory(chat_id, "assistant", response)
|
||||
# 保存机器人回复到历史记录
|
||||
if is_group:
|
||||
import tomllib
|
||||
with open("main_config.toml", "rb") as f:
|
||||
main_config = tomllib.load(f)
|
||||
bot_nickname = main_config.get("Bot", {}).get("nickname", "机器人")
|
||||
await self._add_to_history(from_wxid, bot_nickname, response, role="assistant")
|
||||
logger.success(f"[聊天记录] AI 回复成功: {response[:50]}...")
|
||||
cleaned_response = self._sanitize_llm_output(response)
|
||||
if cleaned_response:
|
||||
await bot.send_text(from_wxid, cleaned_response)
|
||||
self._add_to_memory(chat_id, "assistant", cleaned_response)
|
||||
# 保存机器人回复到历史记录
|
||||
if is_group:
|
||||
import tomllib
|
||||
with open("main_config.toml", "rb") as f:
|
||||
main_config = tomllib.load(f)
|
||||
bot_nickname = main_config.get("Bot", {}).get("nickname", "机器人")
|
||||
await self._add_to_history(from_wxid, bot_nickname, cleaned_response, role="assistant")
|
||||
logger.success(f"[聊天记录] AI 回复成功: {cleaned_response[:50]}...")
|
||||
else:
|
||||
logger.warning("[聊天记录] AI 回复清洗后为空，已跳过发送")
|
||||
else:
|
||||
await bot.send_text(from_wxid, "❌ AI 回复生成失败")
|
||||
|
||||
@@ -2268,16 +2746,20 @@ class AIChat(PluginBase):
|
||||
response = await self._call_ai_api(combined_message, bot, from_wxid, chat_id, nickname, user_wxid, is_group)
|
||||
|
||||
if response:
|
||||
await bot.send_text(from_wxid, response)
|
||||
self._add_to_memory(chat_id, "assistant", response)
|
||||
# 保存机器人回复到历史记录
|
||||
if is_group:
|
||||
import tomllib
|
||||
with open("main_config.toml", "rb") as f:
|
||||
main_config = tomllib.load(f)
|
||||
bot_nickname = main_config.get("Bot", {}).get("nickname", "机器人")
|
||||
await self._add_to_history(from_wxid, bot_nickname, response, role="assistant")
|
||||
logger.success(f"[视频识别] 主AI回复成功: {response[:50]}...")
|
||||
cleaned_response = self._sanitize_llm_output(response)
|
||||
if cleaned_response:
|
||||
await bot.send_text(from_wxid, cleaned_response)
|
||||
self._add_to_memory(chat_id, "assistant", cleaned_response)
|
||||
# 保存机器人回复到历史记录
|
||||
if is_group:
|
||||
import tomllib
|
||||
with open("main_config.toml", "rb") as f:
|
||||
main_config = tomllib.load(f)
|
||||
bot_nickname = main_config.get("Bot", {}).get("nickname", "机器人")
|
||||
await self._add_to_history(from_wxid, bot_nickname, cleaned_response, role="assistant")
|
||||
logger.success(f"[视频识别] 主AI回复成功: {cleaned_response[:50]}...")
|
||||
else:
|
||||
logger.warning("[视频识别] 主AI回复清洗后为空，已跳过发送")
|
||||
else:
|
||||
await bot.send_text(from_wxid, "❌ AI 回复生成失败")
|
||||
|
||||
@@ -2388,7 +2870,7 @@ class AIChat(PluginBase):
|
||||
if "text" in part:
|
||||
text = part["text"]
|
||||
logger.info(f"[视频AI] 分析完成，长度: {len(text)}")
|
||||
return text
|
||||
return self._sanitize_llm_output(text)
|
||||
|
||||
# 记录失败原因
|
||||
if "usageMetadata" in result:
|
||||
@@ -2697,7 +3179,7 @@ class AIChat(PluginBase):
|
||||
video_config
|
||||
)
|
||||
|
||||
return full_content.strip()
|
||||
return self._sanitize_llm_output(full_content)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"[视频识别] API 调用失败: {e}")
|
||||
@@ -2761,7 +3243,7 @@ class AIChat(PluginBase):
|
||||
if "text" in part:
|
||||
text = part["text"]
|
||||
logger.info(f"[视频识别-简化] 成功，长度: {len(text)}")
|
||||
return text
|
||||
return self._sanitize_llm_output(text)
|
||||
|
||||
logger.error(f"[视频识别-简化] 仍然没有 candidates: {str(result)[:300]}")
|
||||
return ""
|
||||
@@ -2809,7 +3291,19 @@ class AIChat(PluginBase):
|
||||
|
||||
return False
|
||||
|
||||
async def _call_ai_api_with_image(self, user_message: str, image_base64: str, bot=None, from_wxid: str = None, chat_id: str = None, nickname: str = "", user_wxid: str = None, is_group: bool = False) -> str:
|
||||
async def _call_ai_api_with_image(
|
||||
self,
|
||||
user_message: str,
|
||||
image_base64: str,
|
||||
bot=None,
|
||||
from_wxid: str = None,
|
||||
chat_id: str = None,
|
||||
nickname: str = "",
|
||||
user_wxid: str = None,
|
||||
is_group: bool = False,
|
||||
*,
|
||||
append_user_message: bool = True,
|
||||
) -> str:
|
||||
"""调用AI API（带图片）"""
|
||||
api_config = self.config["api"]
|
||||
tools = self._collect_tools()
|
||||
@@ -2854,14 +3348,15 @@ class AIChat(PluginBase):
|
||||
messages.extend(memory_messages[:-1])
|
||||
|
||||
# 添加当前用户消息（带图片）
|
||||
text_value = f"[{nickname}] {user_message}" if is_group and nickname else user_message
|
||||
messages.append({
|
||||
"role": "user",
|
||||
"content": [
|
||||
{"type": "text", "text": text_value},
|
||||
{"type": "image_url", "image_url": {"url": image_base64}}
|
||||
]
|
||||
})
|
||||
if append_user_message:
|
||||
text_value = f"[{nickname}] {user_message}" if is_group and nickname else user_message
|
||||
messages.append({
|
||||
"role": "user",
|
||||
"content": [
|
||||
{"type": "text", "text": text_value},
|
||||
{"type": "image_url", "image_url": {"url": image_base64}}
|
||||
]
|
||||
})
|
||||
|
||||
payload = {
|
||||
"model": api_config["model"],
|
||||
@@ -2943,8 +3438,12 @@ class AIChat(PluginBase):
|
||||
if not tool_call_hint_sent and bot and from_wxid:
|
||||
tool_call_hint_sent = True
|
||||
if full_content and full_content.strip():
|
||||
logger.info(f"[流式-图片] 检测到工具调用，先发送已有文本")
|
||||
await bot.send_text(from_wxid, full_content.strip())
|
||||
preview = self._sanitize_llm_output(full_content)
|
||||
if preview:
|
||||
logger.info("[流式-图片] 检测到工具调用，先发送已有文本")
|
||||
await bot.send_text(from_wxid, preview)
|
||||
else:
|
||||
logger.info("[流式-图片] 检测到工具调用，但文本清洗后为空（可能为思维链/无有效正文），跳过发送")
|
||||
else:
|
||||
logger.info("[流式-图片] 检测到工具调用，AI 未输出文本")
|
||||
|
||||
@@ -3001,7 +3500,7 @@ class AIChat(PluginBase):
|
||||
logger.warning("检测到模型输出了错误的工具调用格式,拦截并返回提示")
|
||||
return "抱歉,我遇到了一些技术问题,请重新描述一下你的需求~"
|
||||
|
||||
return full_content.strip()
|
||||
return self._sanitize_llm_output(full_content)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"调用AI API失败: {e}")
|
||||
@@ -3212,8 +3711,9 @@ class AIChat(PluginBase):
|
||||
description = await self._generate_image_description(image_base64, description_prompt, image_desc_config)
|
||||
|
||||
if description:
|
||||
await self._update_history_by_id(from_wxid, placeholder_id, f"[图片: {description}]")
|
||||
logger.success(f"已更新图片描述: {nickname} - {description[:30]}...")
|
||||
cleaned_description = self._sanitize_llm_output(description)
|
||||
await self._update_history_by_id(from_wxid, placeholder_id, f"[图片: {cleaned_description}]")
|
||||
logger.success(f"已更新图片描述: {nickname} - {cleaned_description[:30]}...")
|
||||
else:
|
||||
await self._update_history_by_id(from_wxid, placeholder_id, "[图片]")
|
||||
logger.warning(f"图片描述生成失败")
|
||||
|
||||
Reference in New Issue
Block a user