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Merge remote-tracking branch 'upstream/debug' into debug

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This commit is contained in:
tcmofashi
2025-03-12 16:55:37 +08:00
parent fd40c05bf4 23c9211d93
commit 567a7a86fc
21 changed files with 274 additions and 241 deletions
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4
src/plugins/chat/bot.py
View File

@@ -235,10 +235,10 @@ class ChatBot:
is_head=not mark_head,
is_emoji=False,
)
print(f"bot_message: {bot_message}")
logger.debug(f"bot_message: {bot_message}")
if not mark_head:
mark_head = True
print(f"添加消息到message_set: {bot_message}")
logger.debug(f"添加消息到message_set: {bot_message}")
message_set.add_message(bot_message)
# message_set 可以直接加入 message_manager

2
src/plugins/chat/cq_code.py
View File

@@ -4,6 +4,8 @@ import time
from dataclasses import dataclass
from typing import Dict, List, Optional, Union
import os
import requests
# 解析各种CQ码

6
src/plugins/chat/emoji_manager.py
View File

@@ -246,7 +246,7 @@ class EmojiManager:
# 即使表情包已存在，也检查是否需要同步到images集合
description = existing_emoji.get('discription')
# 检查是否在images集合中存在
existing_image = image_manager.db.db.images.find_one({'hash': image_hash})
existing_image = image_manager.db.images.find_one({'hash': image_hash})
if not existing_image:
# 同步到images集合
image_doc = {
@@ -256,7 +256,7 @@ class EmojiManager:
'description': description,
'timestamp': int(time.time())
}
image_manager.db.db.images.update_one(
image_manager.db.images.update_one(
{'hash': image_hash},
{'$set': image_doc},
upsert=True
@@ -318,7 +318,7 @@ class EmojiManager:
'description': description,
'timestamp': int(time.time())
}
image_manager.db.db.images.update_one(
image_manager.db.images.update_one(
{'hash': image_hash},
{'$set': image_doc},
upsert=True

8
src/plugins/chat/utils.py
View File

@@ -88,13 +88,13 @@ def get_cloest_chat_from_db(db, length: int, timestamp: str):
list: 消息记录列表，每个记录包含时间和文本信息
"""
chat_records = []
closest_record = db.db.messages.find_one({"time": {"$lte": timestamp}}, sort=[('time', -1)])
closest_record = db.messages.find_one({"time": {"$lte": timestamp}}, sort=[('time', -1)])
if closest_record:
closest_time = closest_record['time']
chat_id = closest_record['chat_id'] # 获取chat_id
# 获取该时间戳之后的length条消息，保持相同的chat_id
chat_records = list(db.db.messages.find(
chat_records = list(db.messages.find(
{
"time": {"$gt": closest_time},
"chat_id": chat_id # 添加chat_id过滤
@@ -128,7 +128,7 @@ async def get_recent_group_messages(db, chat_id:str, limit: int = 12) -> list:
"""
# 从数据库获取最近消息
recent_messages = list(db.db.messages.find(
recent_messages = list(db.messages.find(
{"chat_id": chat_id},
).sort("time", -1).limit(limit))
@@ -162,7 +162,7 @@ async def get_recent_group_messages(db, chat_id:str, limit: int = 12) -> list:
def get_recent_group_detailed_plain_text(db, chat_stream_id: int, limit: int = 12, combine=False):
recent_messages = list(db.db.messages.find(
recent_messages = list(db.messages.find(
{"chat_id": chat_stream_id},
{
"time": 1, # 返回时间字段

4
src/plugins/chat/utils_image.py
View File

@@ -289,6 +289,7 @@ class ImageManager:
async def get_image_description(self, image_base64: str) -> str:
"""获取普通图片描述，带查重和保存功能"""
try:
print("处理图片中")
# 计算图片哈希
image_bytes = base64.b64decode(image_base64)
image_hash = hashlib.md5(image_bytes).hexdigest()
@@ -296,12 +297,15 @@ class ImageManager:
# 查询缓存的描述
cached_description = self._get_description_from_db(image_hash, 'image')
if cached_description:
print("图片描述缓存中")
return f"[图片：{cached_description}]"
# 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)
print(f"描述是{description}")
if description is None:
logger.warning("AI未能生成图片描述")
return "[图片]"

80
src/plugins/chat/willing_manager.py
View File

@@ -5,101 +5,98 @@ from typing import Dict
from .config import global_config
from .chat_stream import ChatStream
from loguru import logger
class WillingManager:
def __init__(self):
self.chat_reply_willing: Dict[str, float] = {} # 存储每个聊天流的回复意愿
self.chat_reply_willing: Dict[str, float] = {} # 存储每个聊天流的回复意愿
self._decay_task = None
self._started = False
async def _decay_reply_willing(self):
"""定期衰减回复意愿"""
while True:
await asyncio.sleep(5)
for chat_id in self.chat_reply_willing:
self.chat_reply_willing[chat_id] = max(0, self.chat_reply_willing[chat_id] * 0.6)
for chat_id in self.chat_reply_willing:
self.chat_reply_willing[chat_id] = max(0, self.chat_reply_willing[chat_id] * 0.6)
def get_willing(self,chat_stream:ChatStream) -> float:
def get_willing(self, chat_stream: ChatStream) -> float:
"""获取指定聊天流的回复意愿"""
stream = chat_stream
if stream:
return self.chat_reply_willing.get(stream.stream_id, 0)
return 0
def set_willing(self, chat_id: str, willing: float):
"""设置指定聊天流的回复意愿"""
self.chat_reply_willing[chat_id] = willing
def set_willing(self, chat_id: str, willing: float):
"""设置指定聊天流的回复意愿"""
self.chat_reply_willing[chat_id] = willing
async def change_reply_willing_received(self,
chat_stream:ChatStream,
topic: str = None,
is_mentioned_bot: bool = False,
config = None,
is_emoji: bool = False,
interested_rate: float = 0) -> float:
async def change_reply_willing_received(
self,
chat_stream: ChatStream,
topic: str = None,
is_mentioned_bot: bool = False,
config=None,
is_emoji: bool = False,
interested_rate: float = 0,
) -> float:
"""改变指定聊天流的回复意愿并返回回复概率"""
# 获取或创建聊天流
stream = chat_stream
chat_id = stream.stream_id
current_willing = self.chat_reply_willing.get(chat_id, 0)
# print(f"初始意愿: {current_willing}")
if is_mentioned_bot and current_willing < 1.0:
current_willing += 0.9
print(f"被提及, 当前意愿: {current_willing}")
logger.debug(f"被提及, 当前意愿: {current_willing}")
elif is_mentioned_bot:
current_willing += 0.05
print(f"被重复提及, 当前意愿: {current_willing}")
logger.debug(f"被重复提及, 当前意愿: {current_willing}")
if is_emoji:
current_willing *= 0.1
print(f"表情包, 当前意愿: {current_willing}")
print(f"放大系数_interested_rate: {global_config.response_interested_rate_amplifier}")
interested_rate *= global_config.response_interested_rate_amplifier #放大回复兴趣度
logger.debug(f"表情包, 当前意愿: {current_willing}")
logger.debug(f"放大系数_interested_rate: {global_config.response_interested_rate_amplifier}")
interested_rate *= global_config.response_interested_rate_amplifier # 放大回复兴趣度
if interested_rate > 0.4:
# print(f"兴趣度: {interested_rate}, 当前意愿: {current_willing}")
current_willing += interested_rate-0.4
current_willing *= global_config.response_willing_amplifier #放大回复意愿
current_willing += interested_rate - 0.4
current_willing *= global_config.response_willing_amplifier # 放大回复意愿
# print(f"放大系数_willing: {global_config.response_willing_amplifier}, 当前意愿: {current_willing}")
reply_probability = max((current_willing - 0.45) * 2, 0)
# 检查群组权限（如果是群聊）
if chat_stream.group_info:
if chat_stream.group_info:
if chat_stream.group_info.group_id in config.talk_frequency_down_groups:
reply_probability = reply_probability / global_config.down_frequency_rate
reply_probability = min(reply_probability, 1)
if reply_probability < 0:
reply_probability = 0
self.chat_reply_willing[chat_id] = min(current_willing, 3.0)
return reply_probability
def change_reply_willing_sent(self, chat_stream:ChatStream):
def change_reply_willing_sent(self, chat_stream: ChatStream):
"""开始思考后降低聊天流的回复意愿"""
stream = chat_stream
if stream:
current_willing = self.chat_reply_willing.get(stream.stream_id, 0)
self.chat_reply_willing[stream.stream_id] = max(0, current_willing - 2)
def change_reply_willing_after_sent(self,chat_stream:ChatStream):
def change_reply_willing_after_sent(self, chat_stream: ChatStream):
"""发送消息后提高聊天流的回复意愿"""
stream = chat_stream
if stream:
current_willing = self.chat_reply_willing.get(stream.stream_id, 0)
if current_willing < 1:
self.chat_reply_willing[stream.stream_id] = min(1, current_willing + 0.2)
async def ensure_started(self):
"""确保衰减任务已启动"""
if not self._started:
@@ -107,5 +104,6 @@ class WillingManager:
self._decay_task = asyncio.create_task(self._decay_reply_willing())
self._started = True
# 创建全局实例
willing_manager = WillingManager()
willing_manager = WillingManager()

20
src/plugins/memory_system/memory.py
View File

@@ -349,7 +349,7 @@ class Hippocampus:
def sync_memory_to_db(self):
"""检查并同步内存中的图结构与数据库"""
# 获取数据库中所有节点和内存中所有节点
db_nodes = list(self.memory_graph.db.db.graph_data.nodes.find())
db_nodes = list(self.memory_graph.db.graph_data.nodes.find())
memory_nodes = list(self.memory_graph.G.nodes(data=True))
# 转换数据库节点为字典格式,方便查找
@@ -377,7 +377,7 @@ class Hippocampus:
'created_time': created_time,
'last_modified': last_modified
}
self.memory_graph.db.db.graph_data.nodes.insert_one(node_data)
self.memory_graph.db.graph_data.nodes.insert_one(node_data)
else:
# 获取数据库中节点的特征值
db_node = db_nodes_dict[concept]
@@ -385,7 +385,7 @@ class Hippocampus:
# 如果特征值不同,则更新节点
if db_hash != memory_hash:
self.memory_graph.db.db.graph_data.nodes.update_one(
self.memory_graph.db.graph_data.nodes.update_one(
{'concept': concept},
{'$set': {
'memory_items': memory_items,
@@ -396,7 +396,7 @@ class Hippocampus:
)
# 处理边的信息
db_edges = list(self.memory_graph.db.db.graph_data.edges.find())
db_edges = list(self.memory_graph.db.graph_data.edges.find())
memory_edges = list(self.memory_graph.G.edges(data=True))
# 创建边的哈希值字典
@@ -428,11 +428,11 @@ class Hippocampus:
'created_time': created_time,
'last_modified': last_modified
}
self.memory_graph.db.db.graph_data.edges.insert_one(edge_data)
self.memory_graph.db.graph_data.edges.insert_one(edge_data)
else:
# 检查边的特征值是否变化
if db_edge_dict[edge_key]['hash'] != edge_hash:
self.memory_graph.db.db.graph_data.edges.update_one(
self.memory_graph.db.graph_data.edges.update_one(
{'source': source, 'target': target},
{'$set': {
'hash': edge_hash,
@@ -451,7 +451,7 @@ class Hippocampus:
self.memory_graph.G.clear()
# 从数据库加载所有节点
nodes = list(self.memory_graph.db.db.graph_data.nodes.find())
nodes = list(self.memory_graph.db.graph_data.nodes.find())
for node in nodes:
concept = node['concept']
memory_items = node.get('memory_items', [])
@@ -468,7 +468,7 @@ class Hippocampus:
if 'last_modified' not in node:
update_data['last_modified'] = current_time
self.memory_graph.db.db.graph_data.nodes.update_one(
self.memory_graph.db.graph_data.nodes.update_one(
{'concept': concept},
{'$set': update_data}
)
@@ -485,7 +485,7 @@ class Hippocampus:
last_modified=last_modified)
# 从数据库加载所有边
edges = list(self.memory_graph.db.db.graph_data.edges.find())
edges = list(self.memory_graph.db.graph_data.edges.find())
for edge in edges:
source = edge['source']
target = edge['target']
@@ -501,7 +501,7 @@ class Hippocampus:
if 'last_modified' not in edge:
update_data['last_modified'] = current_time
self.memory_graph.db.db.graph_data.edges.update_one(
self.memory_graph.db.graph_data.edges.update_one(
{'source': source, 'target': target},
{'$set': update_data}
)

30
src/plugins/memory_system/memory_manual_build.py
View File

@@ -56,13 +56,13 @@ def get_cloest_chat_from_db(db, length: int, timestamp: str):
list: 消息记录字典列表，每个字典包含消息内容和时间信息
"""
chat_records = []
closest_record = db.db.messages.find_one({"time": {"$lte": timestamp}}, sort=[('time', -1)])
closest_record = db.messages.find_one({"time": {"$lte": timestamp}}, sort=[('time', -1)])
if closest_record and closest_record.get('memorized', 0) < 4:
closest_time = closest_record['time']
group_id = closest_record['group_id']
# 获取该时间戳之后的length条消息，且groupid相同
records = list(db.db.messages.find(
records = list(db.messages.find(
{"time": {"$gt": closest_time}, "group_id": group_id}
).sort('time', 1).limit(length))
@@ -74,7 +74,7 @@ def get_cloest_chat_from_db(db, length: int, timestamp: str):
return ''
# 更新memorized值
db.db.messages.update_one(
db.messages.update_one(
{"_id": record["_id"]},
{"$set": {"memorized": current_memorized + 1}}
)
@@ -323,7 +323,7 @@ class Hippocampus:
self.memory_graph.G.clear()
# 从数据库加载所有节点
nodes = self.memory_graph.db.db.graph_data.nodes.find()
nodes = self.memory_graph.db.graph_data.nodes.find()
for node in nodes:
concept = node['concept']
memory_items = node.get('memory_items', [])
@@ -334,7 +334,7 @@ class Hippocampus:
self.memory_graph.G.add_node(concept, memory_items=memory_items)
# 从数据库加载所有边
edges = self.memory_graph.db.db.graph_data.edges.find()
edges = self.memory_graph.db.graph_data.edges.find()
for edge in edges:
source = edge['source']
target = edge['target']
@@ -371,7 +371,7 @@ class Hippocampus:
使用特征值(哈希值)快速判断是否需要更新
"""
# 获取数据库中所有节点和内存中所有节点
db_nodes = list(self.memory_graph.db.db.graph_data.nodes.find())
db_nodes = list(self.memory_graph.db.graph_data.nodes.find())
memory_nodes = list(self.memory_graph.G.nodes(data=True))
# 转换数据库节点为字典格式，方便查找
@@ -394,7 +394,7 @@ class Hippocampus:
'memory_items': memory_items,
'hash': memory_hash
}
self.memory_graph.db.db.graph_data.nodes.insert_one(node_data)
self.memory_graph.db.graph_data.nodes.insert_one(node_data)
else:
# 获取数据库中节点的特征值
db_node = db_nodes_dict[concept]
@@ -403,7 +403,7 @@ class Hippocampus:
# 如果特征值不同，则更新节点
if db_hash != memory_hash:
# logger.info(f"更新节点内容: {concept}")
self.memory_graph.db.db.graph_data.nodes.update_one(
self.memory_graph.db.graph_data.nodes.update_one(
{'concept': concept},
{'$set': {
'memory_items': memory_items,
@@ -416,10 +416,10 @@ class Hippocampus:
for db_node in db_nodes:
if db_node['concept'] not in memory_concepts:
# logger.info(f"删除多余节点: {db_node['concept']}")
self.memory_graph.db.db.graph_data.nodes.delete_one({'concept': db_node['concept']})
self.memory_graph.db.graph_data.nodes.delete_one({'concept': db_node['concept']})
# 处理边的信息
db_edges = list(self.memory_graph.db.db.graph_data.edges.find())
db_edges = list(self.memory_graph.db.graph_data.edges.find())
memory_edges = list(self.memory_graph.G.edges())
# 创建边的哈希值字典
@@ -445,12 +445,12 @@ class Hippocampus:
'num': 1,
'hash': edge_hash
}
self.memory_graph.db.db.graph_data.edges.insert_one(edge_data)
self.memory_graph.db.graph_data.edges.insert_one(edge_data)
else:
# 检查边的特征值是否变化
if db_edge_dict[edge_key]['hash'] != edge_hash:
logger.info(f"更新边: {source} - {target}")
self.memory_graph.db.db.graph_data.edges.update_one(
self.memory_graph.db.graph_data.edges.update_one(
{'source': source, 'target': target},
{'$set': {'hash': edge_hash}}
)
@@ -461,7 +461,7 @@ class Hippocampus:
if edge_key not in memory_edge_set:
source, target = edge_key
logger.info(f"删除多余边: {source} - {target}")
self.memory_graph.db.db.graph_data.edges.delete_one({
self.memory_graph.db.graph_data.edges.delete_one({
'source': source,
'target': target
})
@@ -487,9 +487,9 @@ class Hippocampus:
topic: 要删除的节点概念
"""
# 删除节点
self.memory_graph.db.db.graph_data.nodes.delete_one({'concept': topic})
self.memory_graph.db.graph_data.nodes.delete_one({'concept': topic})
# 删除所有涉及该节点的边
self.memory_graph.db.db.graph_data.edges.delete_many({
self.memory_graph.db.graph_data.edges.delete_many({
'$or': [
{'source': topic},
{'target': topic}

34
src/plugins/memory_system/memory_test1.py
View File

@@ -115,13 +115,13 @@ def get_cloest_chat_from_db(db, length: int, timestamp: str):
list: 消息记录字典列表，每个字典包含消息内容和时间信息
"""
chat_records = []
closest_record = db.db.messages.find_one({"time": {"$lte": timestamp}}, sort=[('time', -1)])
closest_record = db.messages.find_one({"time": {"$lte": timestamp}}, sort=[('time', -1)])
if closest_record and closest_record.get('memorized', 0) < 4:
closest_time = closest_record['time']
group_id = closest_record['group_id']
# 获取该时间戳之后的length条消息，且groupid相同
records = list(db.db.messages.find(
records = list(db.messages.find(
{"time": {"$gt": closest_time}, "group_id": group_id}
).sort('time', 1).limit(length))
@@ -133,7 +133,7 @@ def get_cloest_chat_from_db(db, length: int, timestamp: str):
return ''
# 更新memorized值
db.db.messages.update_one(
db.messages.update_one(
{"_id": record["_id"]},
{"$set": {"memorized": current_memorized + 1}}
)
@@ -163,7 +163,7 @@ class Memory_cortex:
default_time = datetime.datetime.now().timestamp()
# 从数据库加载所有节点
nodes = self.memory_graph.db.db.graph_data.nodes.find()
nodes = self.memory_graph.db.graph_data.nodes.find()
for node in nodes:
concept = node['concept']
memory_items = node.get('memory_items', [])
@@ -180,7 +180,7 @@ class Memory_cortex:
created_time = default_time
last_modified = default_time
# 更新数据库中的节点
self.memory_graph.db.db.graph_data.nodes.update_one(
self.memory_graph.db.graph_data.nodes.update_one(
{'concept': concept},
{'$set': {
'created_time': created_time,
@@ -196,7 +196,7 @@ class Memory_cortex:
last_modified=last_modified)
# 从数据库加载所有边
edges = self.memory_graph.db.db.graph_data.edges.find()
edges = self.memory_graph.db.graph_data.edges.find()
for edge in edges:
source = edge['source']
target = edge['target']
@@ -212,7 +212,7 @@ class Memory_cortex:
created_time = default_time
last_modified = default_time
# 更新数据库中的边
self.memory_graph.db.db.graph_data.edges.update_one(
self.memory_graph.db.graph_data.edges.update_one(
{'source': source, 'target': target},
{'$set': {
'created_time': created_time,
@@ -256,7 +256,7 @@ class Memory_cortex:
current_time = datetime.datetime.now().timestamp()
# 获取数据库中所有节点和内存中所有节点
db_nodes = list(self.memory_graph.db.db.graph_data.nodes.find())
db_nodes = list(self.memory_graph.db.graph_data.nodes.find())
memory_nodes = list(self.memory_graph.G.nodes(data=True))
# 转换数据库节点为字典格式，方便查找
@@ -280,7 +280,7 @@ class Memory_cortex:
'created_time': data.get('created_time', current_time),
'last_modified': data.get('last_modified', current_time)
}
self.memory_graph.db.db.graph_data.nodes.insert_one(node_data)
self.memory_graph.db.graph_data.nodes.insert_one(node_data)
else:
# 获取数据库中节点的特征值
db_node = db_nodes_dict[concept]
@@ -288,7 +288,7 @@ class Memory_cortex:
# 如果特征值不同，则更新节点
if db_hash != memory_hash:
self.memory_graph.db.db.graph_data.nodes.update_one(
self.memory_graph.db.graph_data.nodes.update_one(
{'concept': concept},
{'$set': {
'memory_items': memory_items,
@@ -301,10 +301,10 @@ class Memory_cortex:
memory_concepts = set(node[0] for node in memory_nodes)
for db_node in db_nodes:
if db_node['concept'] not in memory_concepts:
self.memory_graph.db.db.graph_data.nodes.delete_one({'concept': db_node['concept']})
self.memory_graph.db.graph_data.nodes.delete_one({'concept': db_node['concept']})
# 处理边的信息
db_edges = list(self.memory_graph.db.db.graph_data.edges.find())
db_edges = list(self.memory_graph.db.graph_data.edges.find())
memory_edges = list(self.memory_graph.G.edges(data=True))
# 创建边的哈希值字典
@@ -332,11 +332,11 @@ class Memory_cortex:
'created_time': data.get('created_time', current_time),
'last_modified': data.get('last_modified', current_time)
}
self.memory_graph.db.db.graph_data.edges.insert_one(edge_data)
self.memory_graph.db.graph_data.edges.insert_one(edge_data)
else:
# 检查边的特征值是否变化
if db_edge_dict[edge_key]['hash'] != edge_hash:
self.memory_graph.db.db.graph_data.edges.update_one(
self.memory_graph.db.graph_data.edges.update_one(
{'source': source, 'target': target},
{'$set': {
'hash': edge_hash,
@@ -350,7 +350,7 @@ class Memory_cortex:
for edge_key in db_edge_dict:
if edge_key not in memory_edge_set:
source, target = edge_key
self.memory_graph.db.db.graph_data.edges.delete_one({
self.memory_graph.db.graph_data.edges.delete_one({
'source': source,
'target': target
})
@@ -365,9 +365,9 @@ class Memory_cortex:
topic: 要删除的节点概念
"""
# 删除节点
self.memory_graph.db.db.graph_data.nodes.delete_one({'concept': topic})
self.memory_graph.db.graph_data.nodes.delete_one({'concept': topic})
# 删除所有涉及该节点的边
self.memory_graph.db.db.graph_data.edges.delete_many({
self.memory_graph.db.graph_data.edges.delete_many({
'$or': [
{'source': topic},
{'target': topic}

2
src/plugins/models/utils_model.py
View File

@@ -235,7 +235,7 @@ class LLM_request:
delta_content = ""
accumulated_content += delta_content
# 检测流式输出文本是否结束
finish_reason = chunk["choices"][0]["finish_reason"]
finish_reason = chunk["choices"][0].get("finish_reason")
if finish_reason == "stop":
usage = chunk.get("usage", None)
if usage:

6
src/plugins/utils/typo_generator.py
View File

@@ -13,6 +13,8 @@ from pathlib import Path
import jieba
from pypinyin import Style, pinyin
from loguru import logger
class ChineseTypoGenerator:
def __init__(self,
@@ -38,7 +40,9 @@ class ChineseTypoGenerator:
self.max_freq_diff = max_freq_diff
# 加载数据
print("正在加载汉字数据库，请稍候...")
# print("正在加载汉字数据库，请稍候...")
logger.info("正在加载汉字数据库，请稍候...")
self.pinyin_dict = self._create_pinyin_dict()
self.char_frequency = self._load_or_create_char_frequency()

10
src/plugins/zhishi/knowledge_library.py
View File

@@ -176,7 +176,7 @@ class KnowledgeLibrary:
try:
current_hash = self.calculate_file_hash(file_path)
processed_record = self.db.db.processed_files.find_one({"file_path": file_path})
processed_record = self.db.processed_files.find_one({"file_path": file_path})
if processed_record:
if processed_record.get("hash") == current_hash:
@@ -197,14 +197,14 @@ class KnowledgeLibrary:
"split_length": knowledge_length,
"created_at": datetime.now()
}
self.db.db.knowledges.insert_one(knowledge)
self.db.knowledges.insert_one(knowledge)
result["chunks_processed"] += 1
split_by = processed_record.get("split_by", []) if processed_record else []
if knowledge_length not in split_by:
split_by.append(knowledge_length)
self.db.db.processed_files.update_one(
self.db.knowledges.processed_files.update_one(
{"file_path": file_path},
{
"$set": {
@@ -322,7 +322,7 @@ class KnowledgeLibrary:
{"$project": {"content": 1, "similarity": 1, "file_path": 1}}
]
results = list(self.db.db.knowledges.aggregate(pipeline))
results = list(self.db.knowledges.aggregate(pipeline))
return results
# 创建单例实例
@@ -346,7 +346,7 @@ if __name__ == "__main__":
elif choice == '2':
confirm = input("确定要删除所有知识吗？这个操作不可撤销！(y/n): ").strip().lower()
if confirm == 'y':
knowledge_library.db.db.knowledges.delete_many({})
knowledge_library.db.knowledges.delete_many({})
console.print("[green]已清空所有知识！[/green]")
continue
elif choice == '1':