fix: clean extra file & fix agents use zhipu (#1079)

dbgpt/agent/agents/agents_mange.py

@@ -1,92 +0,0 @@
-import logging
-import re
-from collections import defaultdict
-from typing import Dict, List, Optional, Type
-
-from .agent import Agent
-from .expand.code_assistant_agent import CodeAssistantAgent
-from .expand.dashboard_assistant_agent import DashboardAssistantAgent
-from .expand.data_scientist_agent import DataScientistAgent
-from .expand.plugin_assistant_agent import PluginAssistantAgent
-from .expand.retrieve_summary_assistant_agent import RetrieveSummaryAssistantAgent
-from .expand.sql_assistant_agent import SQLAssistantAgent
-from .expand.summary_assistant_agent import SummaryAssistantAgent
-
-logger = logging.getLogger(__name__)
-
-
-def get_all_subclasses(cls):
-    all_subclasses = []
-    direct_subclasses = cls.__subclasses__()
-    all_subclasses.extend(direct_subclasses)
-
-    for subclass in direct_subclasses:
-        all_subclasses.extend(get_all_subclasses(subclass))
-    return all_subclasses
-
-
-def participant_roles(agents: List[Agent] = None) -> str:
-    # Default to all agents registered
-    if agents is None:
-        agents = agents
-
-    roles = []
-    for agent in agents:
-        if agent.system_message.strip() == "":
-            logger.warning(
-                f"The agent '{agent.name}' has an empty system_message, and may not work well with GroupChat."
-            )
-        roles.append(f"{agent.name}: {agent.describe}")
-    return "\n".join(roles)
-
-
-def mentioned_agents(message_content: str, agents: List[Agent]) -> Dict:
-    """
-    Finds and counts agent mentions in the string message_content, taking word boundaries into account.
-
-    Returns: A dictionary mapping agent names to mention counts (to be included, at least one mention must occur)
-    """
-    mentions = dict()
-    for agent in agents:
-        regex = (
-            r"(?<=\W)" + re.escape(agent.name) + r"(?=\W)"
-        )  # Finds agent mentions, taking word boundaries into account
-        count = len(
-            re.findall(regex, " " + message_content + " ")
-        )  # Pad the message to help with matching
-        if count > 0:
-            mentions[agent.name] = count
-    return mentions
-
-
-class AgentsMange:
-    def __init__(self):
-        self._agents = defaultdict()
-
-    def register_agent(self, cls):
-        self._agents[cls.NAME] = cls
-
-    def get_by_name(self, name: str) -> Optional[Type[Agent]]:
-        if name not in self._agents:
-            raise ValueError(f"Agent:{name} not register!")
-        return self._agents[name]
-
-    def get_describe_by_name(self, name: str) -> Optional[Type[Agent]]:
-        return self._agents[name].DEFAULT_DESCRIBE
-
-    def all_agents(self):
-        result = {}
-        for name, cls in self._agents.items():
-            result[name] = cls.DEFAULT_DESCRIBE
-        return result
-
-
-agent_mange = AgentsMange()
-
-agent_mange.register_agent(CodeAssistantAgent)
-agent_mange.register_agent(DashboardAssistantAgent)
-agent_mange.register_agent(DataScientistAgent)
-agent_mange.register_agent(SQLAssistantAgent)
-agent_mange.register_agent(SummaryAssistantAgent)
-agent_mange.register_agent(PluginAssistantAgent)
-agent_mange.register_agent(RetrieveSummaryAssistantAgent)

dbgpt/agent/agents/llm/llm_client.py

@@ -180,7 +180,7 @@ class AIWrapper:
         payload["model_cache_enable"] = self.model_cache_enable
         try:
             model_request = _build_model_request(payload)
-            model_output = await self._llm_client.generate(model_request)
+            model_output = await self._llm_client.generate(model_request.copy())
             parsed_output = self._output_parser.parse_model_nostream_resp(
                 model_output, "###"
             )