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refactor(agent): Agent modular refactoring (#1487)
This commit is contained in:
Fangyin Cheng
GitHub
413
dbgpt/agent/core/profile/base.py
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413
dbgpt/agent/core/profile/base.py
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"""Profile module."""
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from abc import ABC, abstractmethod
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from typing import List, Optional
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import cachetools
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from dbgpt._private.pydantic import BaseModel, ConfigDict, Field, model_validator
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from dbgpt.util.configure import ConfigInfo, DynConfig
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VALID_TEMPLATE_KEYS = {
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"role",
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"name",
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"goal",
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"resource_prompt",
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"expand_prompt",
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"language",
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"constraints",
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"examples",
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"out_schema",
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"most_recent_memories",
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"question",
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}
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_DEFAULT_SYSTEM_TEMPLATE = """
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You are a {{ role }}, {% if name %}named {{ name }}, {% endif %}your goal is {{ goal }}.
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Please think step by step to achieve the goal. You can use the resources given below.
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At the same time, please strictly abide by the constraints and specifications in IMPORTANT REMINDER.
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{% if resource_prompt %} {{ resource_prompt }} {% endif %}
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{% if expand_prompt %} {{ expand_prompt }} {% endif %}
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*** IMPORTANT REMINDER ***
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{% if language == 'zh' %}
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Please answer in simplified Chinese.
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{% else %}
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Please answer in English.
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{% endif %}
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{% if constraints %}
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{% for constraint in constraints %}
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{{ loop.index }}. {{ constraint }}
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{% endfor %}
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{% endif %}
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{% if examples %}
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You can refer to the following examples:
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{{ examples }}
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{% endif %}
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{% if out_schema %} {{ out_schema }} {% endif %}
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""" # noqa
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_DEFAULT_USER_TEMPLATE = """
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{% if most_recent_memories %}
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Most recent observations:
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{{ most_recent_memories }}
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{% endif %}
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{% if question %}
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Question: {{ question }}
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{% endif %}
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"""
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_DEFAULT_SAVE_MEMORY_TEMPLATE = """
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{% if question %}Question: {{ question }} {% endif %}
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{% if thought %}Thought: {{ thought }} {% endif %}
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{% if action %}Action: {{ action }} {% endif %}
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{% if observation %}Observation: {{ observation }} {% endif %}
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"""
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class Profile(ABC):
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"""Profile interface."""
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@abstractmethod
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def get_name(self) -> str:
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"""Return the name of current agent."""
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@abstractmethod
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def get_role(self) -> str:
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"""Return the role of current agent."""
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def get_goal(self) -> Optional[str]:
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"""Return the goal of current agent."""
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return None
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def get_constraints(self) -> Optional[List[str]]:
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"""Return the constraints of current agent."""
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return None
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def get_description(self) -> Optional[str]:
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"""Return the description of current agent.
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It will not be used to generate prompt.
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"""
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return None
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def get_expand_prompt(self) -> Optional[str]:
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"""Return the expand prompt of current agent."""
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return None
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def get_examples(self) -> Optional[str]:
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"""Return the examples of current agent."""
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return None
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@abstractmethod
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def get_system_prompt_template(self) -> str:
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"""Return the prompt template of current agent."""
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@abstractmethod
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def get_user_prompt_template(self) -> str:
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"""Return the user prompt template of current agent."""
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@abstractmethod
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def get_save_memory_template(self) -> str:
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"""Return the save memory template of current agent."""
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class DefaultProfile(BaseModel, Profile):
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"""Default profile."""
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name: str = Field("", description="The name of the agent.")
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role: str = Field("", description="The role of the agent.")
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goal: Optional[str] = Field(None, description="The goal of the agent.")
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constraints: Optional[List[str]] = Field(
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None, description="The constraints of the agent."
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)
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desc: Optional[str] = Field(
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None, description="The description of the agent, not used to generate prompt."
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)
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expand_prompt: Optional[str] = Field(
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None, description="The expand prompt of the agent."
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)
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examples: Optional[str] = Field(
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None, description="The examples of the agent prompt."
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)
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system_prompt_template: str = Field(
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_DEFAULT_SYSTEM_TEMPLATE, description="The system prompt template of the agent."
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)
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user_prompt_template: str = Field(
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_DEFAULT_USER_TEMPLATE, description="The user prompt template of the agent."
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)
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save_memory_template: str = Field(
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_DEFAULT_SAVE_MEMORY_TEMPLATE,
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description="The save memory template of the agent.",
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)
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def get_name(self) -> str:
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"""Return the name of current agent."""
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return self.name
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def get_role(self) -> str:
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"""Return the role of current agent."""
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return self.role
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def get_goal(self) -> Optional[str]:
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"""Return the goal of current agent."""
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return self.goal
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def get_constraints(self) -> Optional[List[str]]:
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"""Return the constraints of current agent."""
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return self.constraints
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def get_description(self) -> Optional[str]:
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"""Return the description of current agent.
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It will not be used to generate prompt.
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"""
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return self.desc
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def get_expand_prompt(self) -> Optional[str]:
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"""Return the expand prompt of current agent."""
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return self.expand_prompt
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def get_examples(self) -> Optional[str]:
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"""Return the examples of current agent."""
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return self.examples
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def get_system_prompt_template(self) -> str:
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"""Return the prompt template of current agent."""
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return self.system_prompt_template
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def get_user_prompt_template(self) -> str:
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"""Return the user prompt template of current agent."""
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return self.user_prompt_template
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def get_save_memory_template(self) -> str:
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"""Return the save memory template of current agent."""
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return self.save_memory_template
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class ProfileFactory:
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"""Profile factory interface.
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It is used to create a profile.
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"""
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@abstractmethod
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def create_profile(
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self,
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profile_id: int,
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name: Optional[str] = None,
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role: Optional[str] = None,
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goal: Optional[str] = None,
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prefer_prompt_language: Optional[str] = None,
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prefer_model: Optional[str] = None,
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) -> Optional[Profile]:
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"""Create a profile."""
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class LLMProfileFactory(ProfileFactory):
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"""Create a profile by LLM.
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Based on LLM automatic generation, it usually specifies the rules of the generation
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configuration first, clarifies the composition and attributes of the agent
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configuration in the target population, and then gives a small number of samples,
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and finally LLM generates the configuration of all agents.
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"""
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def create_profile(
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self,
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profile_id: int,
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name: Optional[str] = None,
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role: Optional[str] = None,
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goal: Optional[str] = None,
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prefer_prompt_language: Optional[str] = None,
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prefer_model: Optional[str] = None,
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) -> Optional[Profile]:
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"""Create a profile by LLM.
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TODO: Implement this method.
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"""
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pass
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class DatasetProfileFactory(ProfileFactory):
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"""Create a profile by dataset.
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Use existing data sets to generate agent configurations.
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In some cases, the data set contains a large amount of information about real people
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, first organize the information about real people in the data set into a natural
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language prompt, which is then used to generate the agent configuration.
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"""
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def create_profile(
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self,
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profile_id: int,
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name: Optional[str] = None,
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role: Optional[str] = None,
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goal: Optional[str] = None,
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prefer_prompt_language: Optional[str] = None,
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prefer_model: Optional[str] = None,
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) -> Optional[Profile]:
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"""Create a profile by dataset.
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TODO: Implement this method.
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"""
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pass
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class CompositeProfileFactory(ProfileFactory):
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"""Create a profile by combining multiple profile factories."""
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def __init__(self, factories: List[ProfileFactory]):
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"""Create a composite profile factory."""
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self.factories = factories
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def create_profile(
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self,
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profile_id: int,
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name: Optional[str] = None,
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role: Optional[str] = None,
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goal: Optional[str] = None,
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prefer_prompt_language: Optional[str] = None,
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prefer_model: Optional[str] = None,
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) -> Optional[Profile]:
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"""Create a profile by combining multiple profile factories.
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TODO: Implement this method.
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"""
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pass
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class ProfileConfig(BaseModel):
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"""Profile configuration.
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If factory is not specified, name and role must be specified.
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If factory is specified and name and role are also specified, the factory will be
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preferred.
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"""
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model_config = ConfigDict(arbitrary_types_allowed=True)
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profile_id: int = Field(0, description="The profile ID.")
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name: str | ConfigInfo | None = DynConfig(..., description="The name of the agent.")
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role: str | ConfigInfo | None = DynConfig(..., description="The role of the agent.")
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goal: str | ConfigInfo | None = DynConfig(None, description="The goal.")
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constraints: List[str] | ConfigInfo | None = DynConfig(None, is_list=True)
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desc: str | ConfigInfo | None = DynConfig(
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None, description="The description of the agent."
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)
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expand_prompt: str | ConfigInfo | None = DynConfig(
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None, description="The expand prompt."
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)
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examples: str | ConfigInfo | None = DynConfig(None, description="The examples.")
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system_prompt_template: str | ConfigInfo | None = DynConfig(
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_DEFAULT_SYSTEM_TEMPLATE, description="The prompt template."
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)
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user_prompt_template: str | ConfigInfo | None = DynConfig(
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_DEFAULT_USER_TEMPLATE, description="The user prompt template."
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)
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save_memory_template: str | ConfigInfo | None = DynConfig(
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_DEFAULT_SAVE_MEMORY_TEMPLATE, description="The save memory template."
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)
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factory: ProfileFactory | None = Field(None, description="The profile factory.")
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@model_validator(mode="before")
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@classmethod
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def check_before(cls, values):
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"""Check before validation."""
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if isinstance(values, dict):
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return values
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if values["factory"] is None:
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if values["name"] is None:
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raise ValueError("name must be specified if factory is not specified")
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if values["role"] is None:
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raise ValueError("role must be specified if factory is not specified")
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return values
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@cachetools.cached(cachetools.TTLCache(maxsize=100, ttl=10))
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def create_profile(
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self,
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profile_id: Optional[int] = None,
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prefer_prompt_language: Optional[str] = None,
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prefer_model: Optional[str] = None,
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) -> Profile:
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"""Create a profile.
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If factory is specified, use the factory to create the profile.
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"""
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factory_profile = None
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if profile_id is None:
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profile_id = self.profile_id
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name = self.name
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role = self.role
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goal = self.goal
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constraints = self.constraints
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desc = self.desc
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expand_prompt = self.expand_prompt
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system_prompt_template = self.system_prompt_template
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user_prompt_template = self.user_prompt_template
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save_memory_template = self.save_memory_template
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examples = self.examples
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call_args = {
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"prefer_prompt_language": prefer_prompt_language,
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"prefer_model": prefer_model,
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}
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if isinstance(name, ConfigInfo):
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name = name.query(**call_args)
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if isinstance(role, ConfigInfo):
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role = role.query(**call_args)
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if isinstance(goal, ConfigInfo):
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goal = goal.query(**call_args)
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if isinstance(constraints, ConfigInfo):
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constraints = constraints.query(**call_args)
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if isinstance(desc, ConfigInfo):
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desc = desc.query(**call_args)
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if isinstance(expand_prompt, ConfigInfo):
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expand_prompt = expand_prompt.query(**call_args)
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if isinstance(examples, ConfigInfo):
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examples = examples.query(**call_args)
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if isinstance(system_prompt_template, ConfigInfo):
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system_prompt_template = system_prompt_template.query(**call_args)
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if isinstance(user_prompt_template, ConfigInfo):
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user_prompt_template = user_prompt_template.query(**call_args)
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if isinstance(save_memory_template, ConfigInfo):
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save_memory_template = save_memory_template.query(**call_args)
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if self.factory is not None:
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factory_profile = self.factory.create_profile(
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profile_id,
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name,
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role,
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goal,
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prefer_prompt_language,
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prefer_model,
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)
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if factory_profile is not None:
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return factory_profile
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return DefaultProfile(
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name=name,
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role=role,
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goal=goal,
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constraints=constraints,
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desc=desc,
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expand_prompt=expand_prompt,
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examples=examples,
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system_prompt_template=system_prompt_template,
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user_prompt_template=user_prompt_template,
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save_memory_template=save_memory_template,
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)
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def __hash__(self):
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"""Return the hash value."""
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return hash(self.profile_id)
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