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42b27b9a9d
* Add isort * Apply isort on py files * Fix circular import * Fix format for notebooks * Fix format --------- Co-authored-by: Chi Wang <wang.chi@microsoft.com>
319 lines
8.6 KiB
Python
319 lines
8.6 KiB
Python
import uuid
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from dataclasses import asdict, field
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from datetime import datetime
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from typing import Any, Callable, Dict, List, Literal, Optional, Union
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from pydantic.dataclasses import dataclass
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@dataclass
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class Message(object):
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user_id: str
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role: str
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content: str
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root_msg_id: Optional[str] = None
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msg_id: Optional[str] = None
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timestamp: Optional[str] = None
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personalize: Optional[bool] = False
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ra: Optional[str] = None
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code: Optional[str] = None
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metadata: Optional[Any] = None
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session_id: Optional[str] = None
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def __post_init__(self):
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if self.msg_id is None:
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self.msg_id = str(uuid.uuid4())
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if self.timestamp is None:
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self.timestamp = datetime.now().isoformat()
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def dict(self):
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result = asdict(self)
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return result
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@dataclass
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class Skill(object):
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title: str
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content: str
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file_name: Optional[str] = None
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id: Optional[str] = None
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description: Optional[str] = None
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timestamp: Optional[str] = None
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user_id: Optional[str] = None
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def __post_init__(self):
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if self.id is None:
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self.id = str(uuid.uuid4())
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if self.timestamp is None:
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self.timestamp = datetime.now().isoformat()
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if self.user_id is None:
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self.user_id = "default"
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def dict(self):
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result = asdict(self)
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return result
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# web api data models
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# autogenflow data models
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@dataclass
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class Model:
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"""Data model for Model Config item in LLMConfig for AutoGen"""
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model: str
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api_key: Optional[str] = None
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base_url: Optional[str] = None
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api_type: Optional[str] = None
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api_version: Optional[str] = None
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id: Optional[str] = None
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timestamp: Optional[str] = None
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user_id: Optional[str] = None
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description: Optional[str] = None
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def dict(self):
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result = asdict(self)
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return result
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def __post_init__(self):
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if self.id is None:
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self.id = str(uuid.uuid4())
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if self.timestamp is None:
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self.timestamp = datetime.now().isoformat()
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if self.user_id is None:
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self.user_id = "default"
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@dataclass
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class LLMConfig:
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"""Data model for LLM Config for AutoGen"""
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config_list: List[Any] = field(default_factory=list)
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temperature: float = 0
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cache_seed: Optional[Union[int, None]] = None
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timeout: Optional[int] = None
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max_tokens: Optional[int] = None
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extra_body: Optional[dict] = None
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def dict(self):
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result = asdict(self)
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result["config_list"] = [c.dict() for c in self.config_list]
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return result
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@dataclass
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class AgentConfig:
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"""Data model for Agent Config for AutoGen"""
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name: str
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llm_config: Optional[Union[LLMConfig, bool]] = False
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human_input_mode: str = "NEVER"
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max_consecutive_auto_reply: int = 10
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system_message: Optional[str] = None
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is_termination_msg: Optional[Union[bool, str, Callable]] = None
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code_execution_config: Optional[Union[bool, str, Dict[str, Any]]] = None
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default_auto_reply: Optional[str] = ""
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description: Optional[str] = None
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def dict(self):
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result = asdict(self)
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if isinstance(result["llm_config"], LLMConfig):
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result["llm_config"] = result["llm_config"].dict()
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return result
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@dataclass
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class AgentFlowSpec:
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"""Data model to help flow load agents from config"""
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type: Literal["assistant", "userproxy"]
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config: AgentConfig
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id: Optional[str] = None
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timestamp: Optional[str] = None
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user_id: Optional[str] = None
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skills: Optional[Union[None, List[Skill]]] = None
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def __post_init__(self):
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if self.timestamp is None:
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self.timestamp = datetime.now().isoformat()
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if self.id is None:
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self.id = str(uuid.uuid4())
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if self.user_id is None:
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self.user_id = "default"
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def dict(self):
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result = asdict(self)
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return result
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@dataclass
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class GroupChatConfig:
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"""Data model for GroupChat Config for AutoGen"""
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agents: List[AgentFlowSpec] = field(default_factory=list)
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admin_name: str = "Admin"
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messages: List[Dict] = field(default_factory=list)
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max_round: Optional[int] = 10
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admin_name: Optional[str] = "Admin"
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speaker_selection_method: Optional[str] = "auto"
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# TODO: match the new group chat default and support transition spec
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allow_repeat_speaker: Optional[Union[bool, List[AgentConfig]]] = True
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def dict(self):
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result = asdict(self)
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result["agents"] = [a.dict() for a in self.agents]
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return result
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@dataclass
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class GroupChatFlowSpec:
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"""Data model to help flow load agents from config"""
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type: Literal["groupchat"]
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config: AgentConfig = field(default_factory=AgentConfig)
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groupchat_config: Optional[GroupChatConfig] = field(default_factory=GroupChatConfig)
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id: Optional[str] = None
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timestamp: Optional[str] = None
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user_id: Optional[str] = None
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skills: Optional[Union[None, List[Skill]]] = None
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def __post_init__(self):
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if self.timestamp is None:
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self.timestamp = datetime.now().isoformat()
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if self.id is None:
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self.id = str(uuid.uuid4())
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if self.user_id is None:
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self.user_id = "default"
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def dict(self):
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result = asdict(self)
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# result["config"] = self.config.dict()
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# result["groupchat_config"] = self.groupchat_config.dict()
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return result
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@dataclass
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class AgentWorkFlowConfig:
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"""Data model for Flow Config for AutoGen"""
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name: str
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description: str
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sender: AgentFlowSpec
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receiver: Union[AgentFlowSpec, GroupChatFlowSpec]
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type: Literal["twoagents", "groupchat"] = "twoagents"
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id: Optional[str] = None
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user_id: Optional[str] = None
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timestamp: Optional[str] = None
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# how the agent message summary is generated. last: only last message is used, none: no summary, llm: use llm to generate summary
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summary_method: Optional[Literal["last", "none", "llm"]] = "last"
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def init_spec(self, spec: Dict):
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"""initialize the agent spec"""
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if not isinstance(spec, dict):
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spec = spec.dict()
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if spec["type"] == "groupchat":
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return GroupChatFlowSpec(**spec)
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else:
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return AgentFlowSpec(**spec)
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def __post_init__(self):
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if self.id is None:
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self.id = str(uuid.uuid4())
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self.sender = self.init_spec(self.sender)
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self.receiver = self.init_spec(self.receiver)
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if self.user_id is None:
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self.user_id = "default"
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if self.timestamp is None:
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self.timestamp = datetime.now().isoformat()
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def dict(self):
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result = asdict(self)
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result["sender"] = self.sender.dict()
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result["receiver"] = self.receiver.dict()
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return result
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@dataclass
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class Session(object):
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"""Data model for AutoGen Chat Session"""
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user_id: str
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id: Optional[str] = None
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timestamp: Optional[str] = None
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flow_config: AgentWorkFlowConfig = None
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name: Optional[str] = None
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description: Optional[str] = None
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def __post_init__(self):
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if self.timestamp is None:
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self.timestamp = datetime.now().isoformat()
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if self.id is None:
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self.id = str(uuid.uuid4())
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def dict(self):
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result = asdict(self)
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result["flow_config"] = self.flow_config.dict()
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return result
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@dataclass
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class Gallery(object):
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"""Data model for Gallery Item"""
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session: Session
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messages: List[Message]
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tags: List[str]
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id: Optional[str] = None
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timestamp: Optional[str] = None
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def __post_init__(self):
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if self.timestamp is None:
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self.timestamp = datetime.now().isoformat()
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if self.id is None:
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self.id = str(uuid.uuid4())
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def dict(self):
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result = asdict(self)
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return result
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@dataclass
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class ChatWebRequestModel(object):
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"""Data model for Chat Web Request for Web End"""
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message: Message
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flow_config: AgentWorkFlowConfig
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@dataclass
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class DeleteMessageWebRequestModel(object):
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user_id: str
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msg_id: str
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session_id: Optional[str] = None
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@dataclass
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class DBWebRequestModel(object):
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user_id: str
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msg_id: Optional[str] = None
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session: Optional[Session] = None
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skill: Optional[Skill] = None
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tags: Optional[List[str]] = None
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agent: Optional[AgentFlowSpec] = None
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workflow: Optional[AgentWorkFlowConfig] = None
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model: Optional[Model] = None
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message: Optional[Message] = None
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connection_id: Optional[str] = None
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@dataclass
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class SocketMessage(object):
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connection_id: str
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data: Dict[str, Any]
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type: str
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def dict(self):
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result = asdict(self)
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return result
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