| import pytz |
| from flask_login import current_user |
|
|
| from core.app.app_config.easy_ui_based_app.agent.manager import AgentConfigManager |
| from core.tools.tool_manager import ToolManager |
| from extensions.ext_database import db |
| from models.account import Account |
| from models.model import App, Conversation, EndUser, Message, MessageAgentThought |
|
|
|
|
| class AgentService: |
| @classmethod |
| def get_agent_logs(cls, app_model: App, conversation_id: str, message_id: str) -> dict: |
| """ |
| Service to get agent logs |
| """ |
| conversation: Conversation = ( |
| db.session.query(Conversation) |
| .filter( |
| Conversation.id == conversation_id, |
| Conversation.app_id == app_model.id, |
| ) |
| .first() |
| ) |
|
|
| if not conversation: |
| raise ValueError(f"Conversation not found: {conversation_id}") |
|
|
| message: Message = ( |
| db.session.query(Message) |
| .filter( |
| Message.id == message_id, |
| Message.conversation_id == conversation_id, |
| ) |
| .first() |
| ) |
|
|
| if not message: |
| raise ValueError(f"Message not found: {message_id}") |
|
|
| agent_thoughts: list[MessageAgentThought] = message.agent_thoughts |
|
|
| if conversation.from_end_user_id: |
| |
| executor = ( |
| db.session.query(EndUser, EndUser.name).filter(EndUser.id == conversation.from_end_user_id).first() |
| ) |
| else: |
| executor = ( |
| db.session.query(Account, Account.name).filter(Account.id == conversation.from_account_id).first() |
| ) |
|
|
| if executor: |
| executor = executor.name |
| else: |
| executor = "Unknown" |
|
|
| timezone = pytz.timezone(current_user.timezone) |
|
|
| result = { |
| "meta": { |
| "status": "success", |
| "executor": executor, |
| "start_time": message.created_at.astimezone(timezone).isoformat(), |
| "elapsed_time": message.provider_response_latency, |
| "total_tokens": message.answer_tokens + message.message_tokens, |
| "agent_mode": app_model.app_model_config.agent_mode_dict.get("strategy", "react"), |
| "iterations": len(agent_thoughts), |
| }, |
| "iterations": [], |
| "files": message.message_files, |
| } |
|
|
| agent_config = AgentConfigManager.convert(app_model.app_model_config.to_dict()) |
| agent_tools = agent_config.tools |
|
|
| def find_agent_tool(tool_name: str): |
| for agent_tool in agent_tools: |
| if agent_tool.tool_name == tool_name: |
| return agent_tool |
|
|
| for agent_thought in agent_thoughts: |
| tools = agent_thought.tools |
| tool_labels = agent_thought.tool_labels |
| tool_meta = agent_thought.tool_meta |
| tool_inputs = agent_thought.tool_inputs_dict |
| tool_outputs = agent_thought.tool_outputs_dict |
| tool_calls = [] |
| for tool in tools: |
| tool_name = tool |
| tool_label = tool_labels.get(tool_name, tool_name) |
| tool_input = tool_inputs.get(tool_name, {}) |
| tool_output = tool_outputs.get(tool_name, {}) |
| tool_meta_data = tool_meta.get(tool_name, {}) |
| tool_config = tool_meta_data.get("tool_config", {}) |
| if tool_config.get("tool_provider_type", "") != "dataset-retrieval": |
| tool_icon = ToolManager.get_tool_icon( |
| tenant_id=app_model.tenant_id, |
| provider_type=tool_config.get("tool_provider_type", ""), |
| provider_id=tool_config.get("tool_provider", ""), |
| ) |
| if not tool_icon: |
| tool_entity = find_agent_tool(tool_name) |
| if tool_entity: |
| tool_icon = ToolManager.get_tool_icon( |
| tenant_id=app_model.tenant_id, |
| provider_type=tool_entity.provider_type, |
| provider_id=tool_entity.provider_id, |
| ) |
| else: |
| tool_icon = "" |
|
|
| tool_calls.append( |
| { |
| "status": "success" if not tool_meta_data.get("error") else "error", |
| "error": tool_meta_data.get("error"), |
| "time_cost": tool_meta_data.get("time_cost", 0), |
| "tool_name": tool_name, |
| "tool_label": tool_label, |
| "tool_input": tool_input, |
| "tool_output": tool_output, |
| "tool_parameters": tool_meta_data.get("tool_parameters", {}), |
| "tool_icon": tool_icon, |
| } |
| ) |
|
|
| result["iterations"].append( |
| { |
| "tokens": agent_thought.tokens, |
| "tool_calls": tool_calls, |
| "tool_raw": { |
| "inputs": agent_thought.tool_input, |
| "outputs": agent_thought.observation, |
| }, |
| "thought": agent_thought.thought, |
| "created_at": agent_thought.created_at.isoformat(), |
| "files": agent_thought.files, |
| } |
| ) |
|
|
| return result |
|
|