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Introduce Plugins (#13836)
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Chen <52963600+GareArc@users.noreply.github.com>
This commit is contained in:
Yeuoly
@@ -1,6 +1,6 @@
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import json
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from abc import ABC, abstractmethod
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from collections.abc import Generator, Mapping
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from collections.abc import Generator, Mapping, Sequence
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from typing import Any, Optional
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from core.agent.base_agent_runner import BaseAgentRunner
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@@ -18,8 +18,8 @@ from core.model_runtime.entities.message_entities import (
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)
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from core.ops.ops_trace_manager import TraceQueueManager
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from core.prompt.agent_history_prompt_transform import AgentHistoryPromptTransform
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from core.tools.__base.tool import Tool
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from core.tools.entities.tool_entities import ToolInvokeMeta
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from core.tools.tool.tool import Tool
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from core.tools.tool_engine import ToolEngine
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from models.model import Message
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@@ -27,11 +27,11 @@ from models.model import Message
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class CotAgentRunner(BaseAgentRunner, ABC):
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_is_first_iteration = True
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_ignore_observation_providers = ["wenxin"]
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_historic_prompt_messages: list[PromptMessage] | None = None
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_agent_scratchpad: list[AgentScratchpadUnit] | None = None
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_instruction: str = "" # FIXME this must be str for now
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_query: str | None = None
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_prompt_messages_tools: list[PromptMessageTool] = []
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_historic_prompt_messages: list[PromptMessage]
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_agent_scratchpad: list[AgentScratchpadUnit]
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_instruction: str
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_query: str
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_prompt_messages_tools: Sequence[PromptMessageTool]
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def run(
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self,
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@@ -42,6 +42,7 @@ class CotAgentRunner(BaseAgentRunner, ABC):
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"""
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Run Cot agent application
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"""
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app_generate_entity = self.application_generate_entity
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self._repack_app_generate_entity(app_generate_entity)
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self._init_react_state(query)
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@@ -54,17 +55,19 @@ class CotAgentRunner(BaseAgentRunner, ABC):
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app_generate_entity.model_conf.stop.append("Observation")
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app_config = self.app_config
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assert app_config.agent
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# init instruction
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inputs = inputs or {}
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instruction = app_config.prompt_template.simple_prompt_template
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self._instruction = self._fill_in_inputs_from_external_data_tools(instruction=instruction or "", inputs=inputs)
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instruction = app_config.prompt_template.simple_prompt_template or ""
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self._instruction = self._fill_in_inputs_from_external_data_tools(instruction, inputs)
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iteration_step = 1
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max_iteration_steps = min(app_config.agent.max_iteration if app_config.agent else 5, 5) + 1
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# convert tools into ModelRuntime Tool format
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tool_instances, self._prompt_messages_tools = self._init_prompt_tools()
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tool_instances, prompt_messages_tools = self._init_prompt_tools()
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self._prompt_messages_tools = prompt_messages_tools
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function_call_state = True
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llm_usage: dict[str, Optional[LLMUsage]] = {"usage": None}
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@@ -116,14 +119,7 @@ class CotAgentRunner(BaseAgentRunner, ABC):
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callbacks=[],
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)
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if not isinstance(chunks, Generator):
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raise ValueError("Expected streaming response from LLM")
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# check llm result
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if not chunks:
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raise ValueError("failed to invoke llm")
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usage_dict: dict[str, Optional[LLMUsage]] = {"usage": None}
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usage_dict: dict[str, Optional[LLMUsage]] = {}
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react_chunks = CotAgentOutputParser.handle_react_stream_output(chunks, usage_dict)
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scratchpad = AgentScratchpadUnit(
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agent_response="",
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@@ -143,25 +139,25 @@ class CotAgentRunner(BaseAgentRunner, ABC):
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if isinstance(chunk, AgentScratchpadUnit.Action):
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action = chunk
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# detect action
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if scratchpad.agent_response is not None:
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scratchpad.agent_response += json.dumps(chunk.model_dump())
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assert scratchpad.agent_response is not None
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scratchpad.agent_response += json.dumps(chunk.model_dump())
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scratchpad.action_str = json.dumps(chunk.model_dump())
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scratchpad.action = action
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else:
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if scratchpad.agent_response is not None:
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scratchpad.agent_response += chunk
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if scratchpad.thought is not None:
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scratchpad.thought += chunk
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assert scratchpad.agent_response is not None
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scratchpad.agent_response += chunk
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assert scratchpad.thought is not None
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scratchpad.thought += chunk
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yield LLMResultChunk(
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model=self.model_config.model,
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prompt_messages=prompt_messages,
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system_fingerprint="",
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delta=LLMResultChunkDelta(index=0, message=AssistantPromptMessage(content=chunk), usage=None),
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)
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if scratchpad.thought is not None:
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scratchpad.thought = scratchpad.thought.strip() or "I am thinking about how to help you"
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if self._agent_scratchpad is not None:
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self._agent_scratchpad.append(scratchpad)
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assert scratchpad.thought is not None
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scratchpad.thought = scratchpad.thought.strip() or "I am thinking about how to help you"
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self._agent_scratchpad.append(scratchpad)
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# get llm usage
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if "usage" in usage_dict:
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@@ -256,8 +252,6 @@ class CotAgentRunner(BaseAgentRunner, ABC):
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answer=final_answer,
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messages_ids=[],
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)
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if self.variables_pool is not None and self.db_variables_pool is not None:
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self.update_db_variables(self.variables_pool, self.db_variables_pool)
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# publish end event
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self.queue_manager.publish(
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QueueMessageEndEvent(
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@@ -275,7 +269,7 @@ class CotAgentRunner(BaseAgentRunner, ABC):
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def _handle_invoke_action(
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self,
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action: AgentScratchpadUnit.Action,
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tool_instances: dict[str, Tool],
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tool_instances: Mapping[str, Tool],
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message_file_ids: list[str],
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trace_manager: Optional[TraceQueueManager] = None,
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) -> tuple[str, ToolInvokeMeta]:
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@@ -315,11 +309,7 @@ class CotAgentRunner(BaseAgentRunner, ABC):
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)
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# publish files
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for message_file_id, save_as in message_files:
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if save_as is not None and self.variables_pool:
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# FIXME the save_as type is confusing, it should be a string or not
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self.variables_pool.set_file(tool_name=tool_call_name, value=message_file_id, name=str(save_as))
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for message_file_id in message_files:
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# publish message file
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self.queue_manager.publish(
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QueueMessageFileEvent(message_file_id=message_file_id), PublishFrom.APPLICATION_MANAGER
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@@ -342,7 +332,7 @@ class CotAgentRunner(BaseAgentRunner, ABC):
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for key, value in inputs.items():
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try:
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instruction = instruction.replace(f"{{{{{key}}}}}", str(value))
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except Exception as e:
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except Exception:
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continue
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return instruction
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@@ -379,7 +369,7 @@ class CotAgentRunner(BaseAgentRunner, ABC):
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return message
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def _organize_historic_prompt_messages(
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self, current_session_messages: Optional[list[PromptMessage]] = None
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self, current_session_messages: list[PromptMessage] | None = None
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) -> list[PromptMessage]:
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"""
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organize historic prompt messages
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@@ -391,8 +381,7 @@ class CotAgentRunner(BaseAgentRunner, ABC):
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for message in self.history_prompt_messages:
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if isinstance(message, AssistantPromptMessage):
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if not current_scratchpad:
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if not isinstance(message.content, str | None):
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raise NotImplementedError("expected str type")
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assert isinstance(message.content, str)
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current_scratchpad = AgentScratchpadUnit(
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agent_response=message.content,
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thought=message.content or "I am thinking about how to help you",
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@@ -411,9 +400,8 @@ class CotAgentRunner(BaseAgentRunner, ABC):
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except:
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pass
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elif isinstance(message, ToolPromptMessage):
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if not current_scratchpad:
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continue
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if isinstance(message.content, str):
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if current_scratchpad:
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assert isinstance(message.content, str)
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current_scratchpad.observation = message.content
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else:
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raise NotImplementedError("expected str type")
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