fix(model): fix remote reranker api & fix long_term memory (#2648)

Co-authored-by: dong <dongzhancai@iie2.com>

examples/agents/react_agent_example.py

@@ -2,13 +2,26 @@ import asyncio
 import logging
 import os
 import sys
+from concurrent.futures import ThreadPoolExecutor
+from datetime import datetime
 
 from typing_extensions import Annotated, Doc
 
-from dbgpt.agent import AgentContext, AgentMemory, LLMConfig, UserProxyAgent
+from dbgpt.agent import (
+    AgentContext,
+    AgentMemory,
+    HybridMemory,
+    LLMConfig,
+    LongTermMemory,
+    SensoryMemory,
+    ShortTermMemory,
+    UserProxyAgent,
+)
 from dbgpt.agent.expand.actions.react_action import ReActAction, Terminate
 from dbgpt.agent.expand.react_agent import ReActAgent
 from dbgpt.agent.resource import ToolPack, tool
+from dbgpt.rag.embedding import OpenAPIEmbeddings
+from dbgpt_ext.storage.vector_store.chroma_store import ChromaStore, ChromaVectorConfig
 
 logging.basicConfig(
     stream=sys.stdout,
@@ -57,7 +70,23 @@ async def main():
         provider=os.getenv("LLM_PROVIDER", "proxy/siliconflow"),
         name=os.getenv("LLM_MODEL_NAME", "Qwen/Qwen2.5-Coder-32B-Instruct"),
     )
-    agent_memory = AgentMemory()
+    short_memory = ShortTermMemory(buffer_size=1)
+    sensor_memory = SensoryMemory()
+    embedding_fn = OpenAPIEmbeddings(
+        api_url="https://api.siliconflow.cn/v1/embeddings",
+        api_key=os.getenv("SILICONFLOW_API_KEY"),
+        model_name="BAAI/bge-large-zh-v1.5",
+    )
+    vector_store = ChromaStore(
+        ChromaVectorConfig(persist_path="pilot/data"),
+        name="react_mem",
+        embedding_fn=embedding_fn,
+    )
+    long_memory = LongTermMemory(ThreadPoolExecutor(), vector_store)
+
+    agent_memory = AgentMemory(
+        memory=HybridMemory(datetime.now(), sensor_memory, short_memory, long_memory)
+    )
     agent_memory.gpts_memory.init(conv_id="test456")
 
     # It is important to set the temperature to a low value to get a better result
@@ -81,7 +110,7 @@ async def main():
     await user_proxy.initiate_chat(
         recipient=tool_engineer,
         reviewer=user_proxy,
-        message="Calculate the product of 10 and 99",
+        message="Calculate the product of 10 and 99, and then add 1 to the result, and finally divide the result by 2.",
     )
     await user_proxy.initiate_chat(
         recipient=tool_engineer,