399 lines
16 KiB
Plaintext
399 lines
16 KiB
Plaintext
import json
|
||
import threading
|
||
import time
|
||
from dotenv import load_dotenv
|
||
from volcengine.ApiInfo import ApiInfo
|
||
from volcengine.Credentials import Credentials
|
||
from volcengine.ServiceInfo import ServiceInfo
|
||
from volcengine.auth.SignerV4 import SignerV4
|
||
from volcengine.base.Service import Service
|
||
from volcenginesdkarkruntime import Ark
|
||
|
||
from Config.Config import VOLC_SECRETKEY, VOLC_API_KEY, VOLC_ACCESSKEY
|
||
|
||
|
||
class VikingDBMemoryException(Exception):
|
||
def __init__(self, code, request_id, message=None):
|
||
self.code = code
|
||
self.request_id = request_id
|
||
self.message = "{}, code:{}，request_id:{}".format(message, self.code, self.request_id)
|
||
|
||
def __str__(self):
|
||
return self.message
|
||
|
||
|
||
class VikingDBMemoryService(Service):
|
||
_instance_lock = threading.Lock()
|
||
|
||
def __new__(cls, *args, **kwargs):
|
||
if not hasattr(VikingDBMemoryService, "_instance"):
|
||
with VikingDBMemoryService._instance_lock:
|
||
if not hasattr(VikingDBMemoryService, "_instance"):
|
||
VikingDBMemoryService._instance = object.__new__(cls)
|
||
return VikingDBMemoryService._instance
|
||
|
||
def __init__(self, host="api-knowledgebase.mlp.cn-beijing.volces.com", region="cn-beijing", ak="", sk="",
|
||
sts_token="", scheme='https',
|
||
connection_timeout=30, socket_timeout=30):
|
||
self.service_info = VikingDBMemoryService.get_service_info(host, region, scheme, connection_timeout,
|
||
socket_timeout)
|
||
self.api_info = VikingDBMemoryService.get_api_info()
|
||
super(VikingDBMemoryService, self).__init__(self.service_info, self.api_info)
|
||
if ak:
|
||
self.set_ak(ak)
|
||
if sk:
|
||
self.set_sk(sk)
|
||
if sts_token:
|
||
self.set_session_token(session_token=sts_token)
|
||
try:
|
||
self.get_body("Ping", {}, json.dumps({}))
|
||
except Exception as e:
|
||
raise VikingDBMemoryException(1000028, "missed", "host or region is incorrect".format(str(e))) from None
|
||
|
||
def setHeader(self, header):
|
||
api_info = VikingDBMemoryService.get_api_info()
|
||
for key in api_info:
|
||
for item in header:
|
||
api_info[key].header[item] = header[item]
|
||
self.api_info = api_info
|
||
|
||
@staticmethod
|
||
def get_service_info(host, region, scheme, connection_timeout, socket_timeout):
|
||
service_info = ServiceInfo(host, {"Host": host},
|
||
Credentials('', '', 'air', region), connection_timeout, socket_timeout,
|
||
scheme=scheme)
|
||
return service_info
|
||
|
||
@staticmethod
|
||
def get_api_info():
|
||
api_info = {
|
||
"CreateCollection": ApiInfo("POST", "/api/memory/collection/create", {}, {},
|
||
{'Accept': 'application/json', 'Content-Type': 'application/json'}),
|
||
"GetCollection": ApiInfo("POST", "/api/memory/collection/info", {}, {},
|
||
{'Accept': 'application/json', 'Content-Type': 'application/json'}),
|
||
"DropCollection": ApiInfo("POST", "/api/memory/collection/delete", {}, {},
|
||
{'Accept': 'application/json', 'Content-Type': 'application/json'}),
|
||
"UpdateCollection": ApiInfo("POST", "/api/memory/collection/update", {}, {},
|
||
{'Accept': 'application/json', 'Content-Type': 'application/json'}),
|
||
|
||
"SearchMemory": ApiInfo("POST", "/api/memory/search", {}, {},
|
||
{'Accept': 'application/json', 'Content-Type': 'application/json'}),
|
||
"AddSession": ApiInfo("POST", "/api/memory/session/add", {}, {},
|
||
{'Accept': 'application/json', 'Content-Type': 'application/json'}),
|
||
|
||
"Ping": ApiInfo("GET", "/api/memory/ping", {}, {},
|
||
{'Accept': 'application/json', 'Content-Type': 'application/json'}),
|
||
}
|
||
return api_info
|
||
|
||
def get_body(self, api, params, body):
|
||
if not (api in self.api_info):
|
||
raise Exception("no such api")
|
||
api_info = self.api_info[api]
|
||
r = self.prepare_request(api_info, params)
|
||
r.headers['Content-Type'] = 'application/json'
|
||
r.headers['Traffic-Source'] = 'SDK'
|
||
r.body = body
|
||
|
||
SignerV4.sign(r, self.service_info.credentials)
|
||
|
||
url = r.build()
|
||
resp = self.session.get(url, headers=r.headers, data=r.body,
|
||
timeout=(self.service_info.connection_timeout, self.service_info.socket_timeout))
|
||
if resp.status_code == 200:
|
||
return json.dumps(resp.json())
|
||
else:
|
||
raise Exception(resp.text.encode("utf-8"))
|
||
|
||
def get_body_exception(self, api, params, body):
|
||
try:
|
||
res = self.get_body(api, params, body)
|
||
except Exception as e:
|
||
try:
|
||
res_json = json.loads(e.args[0].decode("utf-8"))
|
||
except:
|
||
raise VikingDBMemoryException(1000028, "missed", "json load res error, res:{}".format(str(e))) from None
|
||
code = res_json.get("code", 1000028)
|
||
request_id = res_json.get("request_id", 1000028)
|
||
message = res_json.get("message", None)
|
||
|
||
raise VikingDBMemoryException(code, request_id, message)
|
||
|
||
if res == '':
|
||
raise VikingDBMemoryException(1000028, "missed",
|
||
"empty response due to unknown error, please contact customer service") from None
|
||
return res
|
||
|
||
def get_exception(self, api, params):
|
||
try:
|
||
res = self.get(api, params)
|
||
except Exception as e:
|
||
try:
|
||
res_json = json.loads(e.args[0].decode("utf-8"))
|
||
except:
|
||
raise VikingDBMemoryException(1000028, "missed", "json load res error, res:{}".format(str(e))) from None
|
||
code = res_json.get("code", 1000028)
|
||
request_id = res_json.get("request_id", 1000028)
|
||
message = res_json.get("message", None)
|
||
raise VikingDBMemoryException(code, request_id, message)
|
||
if res == '':
|
||
raise VikingDBMemoryException(1000028, "missed",
|
||
"empty response due to unknown error, please contact customer service") from None
|
||
return res
|
||
|
||
def create_collection(self, collection_name, description="", custom_event_type_schemas=[],
|
||
custom_entity_type_schemas=[], builtin_event_types=[], builtin_entity_types=[]):
|
||
params = {
|
||
"CollectionName": collection_name, "Description": description,
|
||
"CustomEventTypeSchemas": custom_event_type_schemas, "CustomEntityTypeSchemas": custom_entity_type_schemas,
|
||
"BuiltinEventTypes": builtin_event_types, "BuiltinEntityTypes": builtin_entity_types,
|
||
}
|
||
res = self.json("CreateCollection", {}, json.dumps(params))
|
||
return json.loads(res)
|
||
|
||
def get_collection(self, collection_name):
|
||
params = {"CollectionName": collection_name}
|
||
res = self.json("GetCollection", {}, json.dumps(params))
|
||
return json.loads(res)
|
||
|
||
def drop_collection(self, collection_name):
|
||
params = {"CollectionName": collection_name}
|
||
res = self.json("DropCollection", {}, json.dumps(params))
|
||
return json.loads(res)
|
||
|
||
def update_collection(self, collection_name, custom_event_type_schemas=[], custom_entity_type_schemas=[],
|
||
builtin_event_types=[], builtin_entity_types=[]):
|
||
params = {
|
||
"CollectionName": collection_name,
|
||
"CustomEventTypeSchemas": custom_event_type_schemas, "CustomEntityTypeSchemas": custom_entity_type_schemas,
|
||
"BuiltinEventTypes": builtin_event_types, "BuiltinEntityTypes": builtin_entity_types,
|
||
}
|
||
res = self.json("UpdateCollection", {}, json.dumps(params))
|
||
return json.loads(res)
|
||
|
||
def search_memory(self, collection_name, query, filter, limit=10):
|
||
params = {
|
||
"collection_name": collection_name,
|
||
"query": query,
|
||
"limit": limit,
|
||
"filter": filter,
|
||
}
|
||
res = self.json("SearchMemory", {}, json.dumps(params))
|
||
return json.loads(res)
|
||
|
||
def add_session(self, collection_name, session_id, messages, metadata, entities=None):
|
||
params = {
|
||
"collection_name": collection_name,
|
||
"session_id": session_id,
|
||
"messages": messages,
|
||
"metadata": metadata,
|
||
}
|
||
if entities is not None:
|
||
params["entities"] = entities
|
||
res = self.json("AddSession", {}, json.dumps(params))
|
||
return json.loads(res)
|
||
|
||
|
||
|
||
|
||
def initialize_services():
|
||
load_dotenv()
|
||
ak = VOLC_ACCESSKEY
|
||
sk = VOLC_SECRETKEY
|
||
ark_api_key = VOLC_API_KEY
|
||
|
||
if not all([ak, sk, ark_api_key]):
|
||
raise ValueError("必须在环境变量中设置 VOLC_ACCESSKEY, VOLC_SECRETKEY, 和 ARK_API_KEY。")
|
||
|
||
memory_service = VikingDBMemoryService(ak=ak, sk=sk)
|
||
llm_client = Ark(
|
||
base_url="https://ark.cn-beijing.volces.com/api/v3",
|
||
api_key=ark_api_key,
|
||
)
|
||
return memory_service, llm_client
|
||
|
||
|
||
def ensure_collection_exists(memory_service, collection_name):
|
||
"""检查记忆集合是否存在，如果不存在则创建。"""
|
||
try:
|
||
memory_service.get_collection(collection_name)
|
||
print(f"记忆集合 '{collection_name}' 已存在。")
|
||
except Exception as e:
|
||
error_message = str(e)
|
||
if "collection not exist" in error_message:
|
||
print(f"记忆集合 '{collection_name}' 未找到，正在创建...")
|
||
try:
|
||
memory_service.create_collection(
|
||
collection_name=collection_name,
|
||
description="中文情感陪伴场景测试",
|
||
builtin_event_types=["sys_event_v1", "sys_profile_collect_v1"],
|
||
builtin_entity_types=["sys_profile_v1"]
|
||
)
|
||
print(f"记忆集合 '{collection_name}' 创建成功。")
|
||
print("等待集合准备就绪...")
|
||
except Exception as create_e:
|
||
print(f"创建集合失败: {create_e}")
|
||
raise
|
||
else:
|
||
print(f"检查集合时出错: {e}")
|
||
raise
|
||
|
||
|
||
def search_relevant_memories(memory_service, collection_name, user_id, query):
|
||
"""搜索与用户查询相关的记忆，并在索引构建中时重试。"""
|
||
print(f"正在搜索与 '{query}' 相关的记忆...")
|
||
retry_attempt = 0
|
||
while True:
|
||
try:
|
||
filter_params = {
|
||
"user_id": [user_id],
|
||
"memory_type": ["sys_event_v1", "sys_profile_v1"]
|
||
}
|
||
response = memory_service.search_memory(
|
||
collection_name=collection_name,
|
||
query=query,
|
||
filter=filter_params,
|
||
limit=3
|
||
)
|
||
|
||
memories = []
|
||
if response.get('data', {}).get('count', 0) > 0:
|
||
for result in response['data']['result_list']:
|
||
if 'memory_info' in result and result['memory_info']:
|
||
memories.append({
|
||
'memory_info': result['memory_info'],
|
||
'score': result['score']
|
||
})
|
||
|
||
if memories:
|
||
if retry_attempt > 0:
|
||
print("重试后搜索成功。")
|
||
print(f"找到 {len(memories)} 条相关记忆:")
|
||
for i, memory in enumerate(memories, 1):
|
||
print(
|
||
f" {i}. (相关度: {memory['score']:.3f}): {json.dumps(memory['memory_info'], ensure_ascii=False, indent=2)}")
|
||
else:
|
||
print("未找到相关记忆。")
|
||
return memories
|
||
|
||
except Exception as e:
|
||
error_message = str(e)
|
||
if "1000023" in error_message:
|
||
retry_attempt += 1
|
||
print(f"记忆索引正在构建中。将在60秒后重试... (尝试次数 {retry_attempt})")
|
||
time.sleep(60)
|
||
else:
|
||
print(f"搜索记忆时出错 (不可重试): {e}")
|
||
return []
|
||
|
||
|
||
def handle_conversation_turn(memory_service, llm_client, collection_name, user_id, user_message, conversation_history):
|
||
"""处理一轮对话，包括记忆搜索和LLM响应。"""
|
||
print("\n" + "=" * 60)
|
||
print(f"用户: {user_message}")
|
||
|
||
relevant_memories = search_relevant_memories(memory_service, collection_name, user_id, user_message)
|
||
|
||
system_prompt = "你是一个富有同情心、善于倾听的AI伙伴，拥有长期记忆能力。你的目标是为用户提供情感支持和温暖的陪伴。"
|
||
if relevant_memories:
|
||
memory_context = "\n".join(
|
||
[f"- {json.dumps(mem['memory_info'], ensure_ascii=False)}" for mem in relevant_memories])
|
||
system_prompt += f"\n\n这是我们过去的一些对话记忆，请参考：\n{memory_context}\n\n请利用这些信息来更好地理解和回应用户。"
|
||
|
||
print("AI正在思考...")
|
||
|
||
try:
|
||
messages = [{"role": "system", "content": system_prompt}] + conversation_history + [
|
||
{"role": "user", "content": user_message}]
|
||
completion = llm_client.chat.completions.create(
|
||
model="doubao-seed-1-6-flash-250715",
|
||
messages=messages
|
||
)
|
||
assistant_reply = completion.choices[0].message.content
|
||
except Exception as e:
|
||
print(f"LLM调用失败: {e}")
|
||
assistant_reply = "抱歉，我现在有点混乱，无法回应。我们可以稍后再聊吗？"
|
||
|
||
print(f"伙伴: {assistant_reply}")
|
||
|
||
conversation_history.extend([
|
||
{"role": "user", "content": user_message},
|
||
{"role": "assistant", "content": assistant_reply}
|
||
])
|
||
return assistant_reply
|
||
|
||
|
||
def archive_conversation(memory_service, collection_name, user_id, assistant_id, conversation_history, topic_name):
|
||
"""将对话历史归档到记忆数据库。"""
|
||
if not conversation_history:
|
||
print("没有对话可以归档。")
|
||
return False
|
||
|
||
print(f"\n正在归档关于 '{topic_name}' 的对话...")
|
||
session_id = f"{topic_name}_{int(time.time())}"
|
||
metadata = {
|
||
"default_user_id": user_id,
|
||
"default_assistant_id": assistant_id,
|
||
"time": int(time.time() * 1000)
|
||
}
|
||
|
||
try:
|
||
memory_service.add_session(
|
||
collection_name=collection_name,
|
||
session_id=session_id,
|
||
messages=conversation_history,
|
||
metadata=metadata
|
||
)
|
||
print(f"对话已成功归档，会话ID: {session_id}")
|
||
print("正在等待记忆索引更新...")
|
||
return True
|
||
except Exception as e:
|
||
print(f"归档对话失败: {e}")
|
||
return False
|
||
|
||
|
||
def main():
|
||
print("开始端到端记忆测试...")
|
||
|
||
try:
|
||
memory_service, llm_client = initialize_services()
|
||
collection_name = "emotional_support"
|
||
user_id = "xiaoming"
|
||
assistant_id = "assistant"
|
||
ensure_collection_exists(memory_service, collection_name)
|
||
except Exception as e:
|
||
print(f"初始化失败: {e}")
|
||
return
|
||
|
||
print("\n--- 阶段 1: 初始对话 ---")
|
||
initial_conversation_history = []
|
||
handle_conversation_turn(
|
||
memory_service, llm_client, collection_name, user_id,
|
||
"你好，我是小明，今年18岁，但压力好大。",
|
||
initial_conversation_history
|
||
)
|
||
handle_conversation_turn(
|
||
memory_service, llm_client, collection_name, user_id,
|
||
"马上就要高考了，家里人的期待好高。",
|
||
initial_conversation_history
|
||
)
|
||
|
||
print("\n--- 阶段 2: 归档记忆 ---")
|
||
archive_conversation(
|
||
memory_service, collection_name, user_id, assistant_id,
|
||
initial_conversation_history, "study_stress_discussion"
|
||
)
|
||
|
||
print("\n--- 阶段 3: 验证记忆 ---")
|
||
verification_conversation_history = []
|
||
handle_conversation_turn(
|
||
memory_service, llm_client, collection_name, user_id,
|
||
"我最近很焦虑，不知道该怎么办。",
|
||
verification_conversation_history
|
||
)
|
||
|
||
print("\n端到端记忆测试完成！")
|
||
|
||
|
||
if __name__ == "__main__":
|
||
main() |