1) Do some rename refactor ,prepare for LLMProcess refactor

2) Fix merge bugs.

rootfs/agents/Jarvis/agent.toml

@@ -5,7 +5,6 @@ max_token_size = 128000
 enable_timestamp = "true"
 owner_prompt = "I am your master{name}"
 contact_prompt = "I am your master's friend{name}"
-owner_env = "calender"
 
 [[prompt]]
 role = "system"

rootfs/agents/TextSummary/agent.py

@@ -1,6 +1,6 @@
 import copy
 
-from aios.agent.agent_base import CustomAIAgent, AgentPrompt
+from aios.agent.agent_base import CustomAIAgent, LLMPrompt
 from aios.knowledge.data.writer import split_text
 from aios.proto.agent_msg import AgentMsg, AgentMsgType
 from aios.proto.compute_task import ComputeTaskResultCode
@@ -19,10 +19,10 @@ class TextSummaryAgent(CustomAIAgent):
 
         chunks = split_text(msg.body, separators=["\n\n", "\n"], chunk_size=4000, chunk_overlap=200, length_function=len)
 
-        prompt = AgentPrompt()
-        prompt.system_message = {"role":"system","content":"Your job is to generate a summary based on the input."}
+        prompt = LLMPrompt()
+        prompt.system_message = "Your job is to generate a summary based on the input."
         if len(chunks) == 1:
-            prompt.append(AgentPrompt(chunks[0]))
+            prompt.append(LLMPrompt(chunks[0]))
             resp = await self.do_llm_complection(prompt)
             if resp.result_code != ComputeTaskResultCode.OK:
                 return msg.create_error_resp(resp.error_str)
@@ -31,14 +31,14 @@ class TextSummaryAgent(CustomAIAgent):
         segments = []
         for i, chunk in enumerate(chunks):
             seg_prompt = copy.deepcopy(prompt)
-            seg_prompt.append(AgentPrompt(chunk))
+            seg_prompt.append(LLMPrompt(chunk))
             resp = await self.do_llm_complection(seg_prompt)
             if resp.result_code != ComputeTaskResultCode.OK:
                 return msg.create_error_resp(resp.error_str)
             segments.append(resp.result_str)
 
         segments_str = "\n".join(segments)
-        prompt.append(AgentPrompt(f"以下文本分段之后的各段摘要，请合并生成一个完整摘要：\n{segments_str}"))
+        prompt.append(LLMPrompt(f"以下文本分段之后的各段摘要，请合并生成一个完整摘要：\n{segments_str}"))
         resp = await self.do_llm_complection(prompt)
         if resp.result_code != ComputeTaskResultCode.OK:
             return msg.create_error_resp(resp.error_str)