This commit is contained in:
2025-09-07 07:25:00 +08:00
parent 7b6c3ffa5b
commit da55b8e5c9
6 changed files with 418 additions and 6 deletions

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@@ -99,4 +99,11 @@ LIBLIB_SECRETKEY="PUe8QTRG9i0G9EbpedHmIpLQ0FyxoYY9"
# 科大讯飞
XF_APPID="5b83f8d6"
XF_APISECRET="604fa6cb9c5ab664a0d153fe0ccc6802"
XF_APIKEY="5beb887923204000bfcb402046bb05a6"
XF_APIKEY="5beb887923204000bfcb402046bb05a6"
# 方舟模型专用API
# https://console.volcengine.com/iam/keymanage/
VOLC_ACCESSKEY="AKLTZjVlOGU1NzA1YWZkNDExMzkzYzY5YTNlOTRmMTMxODg"
VOLC_SECRETKEY="WkdabU9UTXdNVEJpTmpWbE5HVTJZVGxtTnpWbU5XSTBaRGN5TW1NMk5tRQ=="
# https://console.volcengine.com/ark/region:ark+cn-beijing/apiKey?apikey=%7B%7D
VOLC_API_KEY= "f6150e6c-422a-4265-8b63-4d941b271220"

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@@ -1,8 +1,9 @@
import json
import requests
import logging
from JiMeng.Kit.VolcanoConst import VOLCANO_API_KEY
import requests
from Config.Config import VOLC_API_KEY
# 配置日志
logger = logging.getLogger(__name__)
@@ -14,7 +15,7 @@ console_handler.setFormatter(formatter)
logger.addHandler(console_handler)
class FenJingTouGenerator:
def __init__(self, api_key=VOLCANO_API_KEY):
def __init__(self, api_key=VOLC_API_KEY):
"""
初始化分镜头提示词生成器
:param api_key: 火山引擎API密钥

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@@ -1,2 +0,0 @@
# 火山API_KEY
VOLCANO_API_KEY="f6150e6c-422a-4265-8b63-4d941b271220"

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@@ -0,0 +1,195 @@
"""
pip install volcengine
pip install --upgrade "volcengine-python-sdk[ark]"
"""
import json
import threading
from volcengine.ApiInfo import ApiInfo
from volcengine.Credentials import Credentials
from volcengine.base.Service import Service
from volcengine.ServiceInfo import ServiceInfo
from volcengine.auth.SignerV4 import SignerV4
from volcengine.base.Request import Request
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)

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@@ -0,0 +1,211 @@
import json
import os
import time
from dotenv import load_dotenv
from volcenginesdkarkruntime import Ark
from Config.Config import VOLC_ACCESSKEY, VOLC_SECRETKEY, VOLC_API_KEY
from VikingDBMemoryService import VikingDBMemoryService
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()