This commit is contained in:
2025-09-07 07:50:07 +08:00
parent 5c7d8792ec
commit 16ddf94806
3 changed files with 36 additions and 9 deletions

View File

@@ -1,5 +1,10 @@
import os
import time
from volcenginesdkarkruntime import Ark
from Config.Config import VOLC_API_KEY
"""
在记忆库准备好后,我们先模拟一段包含两轮的完整对话。
对话结束后,把这段对话历史消息写入记忆库。然后再开启一个新话题,提出和刚才相关的问题,
@@ -7,7 +12,9 @@ AI 就能用刚写入的记忆来回答。
注意:首次写入需要 35 分钟建立索引,这段时间内检索会报错。
"""
import json
import time
from VikingDBMemoryService import initialize_services, ensure_collection_exists, search_relevant_memories
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)
@@ -71,15 +78,32 @@ def archive_conversation(memory_service, collection_name, user_id, assistant_id,
print(f"归档对话失败: {e}")
return False
def setup_memory_collection(collection_name="emotional_support"):
"""独立封装记忆体创建逻辑返回memory_service供测试使用"""
try:
memory_service, _ = initialize_services()
ensure_collection_exists(memory_service, collection_name)
print(f"记忆体 '{collection_name}' 创建/验证成功")
return memory_service
except Exception as e:
print(f"记忆体创建失败: {e}")
return None
def main():
print("开始端到端记忆测试...")
collection_name="emotional_support"
try:
memory_service, llm_client = initialize_services()
collection_name = "emotional_support"
user_id = "xiaoming" # 用户ID:小明
assistant_id = "assistant1" # 助手ID:助手1
ensure_collection_exists(memory_service, collection_name)
# 调用封装的记忆体创建函数
memory_service = setup_memory_collection()
if not memory_service:
return
llm_client = Ark(
base_url="https://ark.cn-beijing.volces.com/api/v3",
api_key=VOLC_API_KEY
)
user_id = "xiaoming" # 用户ID:小明
assistant_id = "assistant1" # 助手ID:助手1
except Exception as e:
print(f"初始化失败: {e}")
return
@@ -114,4 +138,5 @@ def main():
print("\n端到端记忆测试完成!")
if __name__ == "__main__":
main()
setup_memory_collection()
# main()