File size: 9,049 Bytes
594c559 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 |
# =========== Copyright 2023 @ CAMEL-AI.org. All Rights Reserved. ===========
# Licensed under the Apache License, Version 2.0 (the “License”);
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an “AS IS” BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# =========== Copyright 2023 @ CAMEL-AI.org. All Rights Reserved. ===========
from dataclasses import dataclass
from typing import Any, Dict, List, Optional
from tenacity import retry
from tenacity.stop import stop_after_attempt
from tenacity.wait import wait_exponential
from camel.agents import BaseAgent
from camel.configs import ChatGPTConfig
from camel.messages import ChatMessage, MessageType, SystemMessage
from camel.model_backend import ModelBackend, ModelFactory
from camel.typing import ModelType, RoleType
from camel.utils import (
get_model_token_limit,
num_tokens_from_messages,
openai_api_key_required,
)
@dataclass(frozen=True)
class ChatAgentResponse:
r"""Response of a ChatAgent.
Attributes:
msgs (List[ChatMessage]): A list of zero, one or several messages.
If the list is empty, there is some error in message generation.
If the list has one message, this is normal mode.
If the list has several messages, this is the critic mode.
terminated (bool): A boolean indicating whether the agent decided
to terminate the chat session.
info (Dict[str, Any]): Extra information about the chat message.
"""
msgs: List[ChatMessage]
terminated: bool
info: Dict[str, Any]
@property
def msg(self):
if self.terminated:
raise RuntimeError("error in ChatAgentResponse, info:{}".format(str(self.info)))
if len(self.msgs) > 1:
raise RuntimeError("Property msg is only available for a single message in msgs")
elif len(self.msgs) == 0:
if len(self.info) > 0:
raise RuntimeError("Empty msgs in ChatAgentResponse, info:{}".format(str(self.info)))
else:
# raise RuntimeError("Known issue that msgs is empty and there is no error info, to be fix")
return None
return self.msgs[0]
class ChatAgent(BaseAgent):
r"""Class for managing conversations of CAMEL Chat Agents.
Args:
system_message (SystemMessage): The system message for the chat agent.
model (ModelType, optional): The LLM model to use for generating
responses. (default :obj:`ModelType.GPT_3_5_TURBO`)
model_config (Any, optional): Configuration options for the LLM model.
(default: :obj:`None`)
message_window_size (int, optional): The maximum number of previous
messages to include in the context window. If `None`, no windowing
is performed. (default: :obj:`None`)
"""
def __init__(
self,
system_message: SystemMessage,
model: Optional[ModelType] = None,
model_config: Optional[Any] = None,
message_window_size: Optional[int] = None,
) -> None:
self.system_message: SystemMessage = system_message
self.role_name: str = system_message.role_name
self.role_type: RoleType = system_message.role_type
self.model: ModelType = (model if model is not None else ModelType.GPT_3_5_TURBO)
self.model_config: ChatGPTConfig = model_config or ChatGPTConfig()
self.model_token_limit: int = get_model_token_limit(self.model)
self.message_window_size: Optional[int] = message_window_size
self.model_backend: ModelBackend = ModelFactory.create(self.model, self.model_config.__dict__)
self.terminated: bool = False
self.info: bool = False
self.init_messages()
def reset(self) -> List[MessageType]:
r"""Resets the :obj:`ChatAgent` to its initial state and returns the
stored messages.
Returns:
List[MessageType]: The stored messages.
"""
self.terminated = False
self.init_messages()
return self.stored_messages
def get_info(
self,
id: Optional[str],
usage: Optional[Dict[str, int]],
termination_reasons: List[str],
num_tokens: int,
) -> Dict[str, Any]:
r"""Returns a dictionary containing information about the chat session.
Args:
id (str, optional): The ID of the chat session.
usage (Dict[str, int], optional): Information about the usage of
the LLM model.
termination_reasons (List[str]): The reasons for the termination of
the chat session.
num_tokens (int): The number of tokens used in the chat session.
Returns:
Dict[str, Any]: The chat session information.
"""
return {
"id": id,
"usage": usage,
"termination_reasons": termination_reasons,
"num_tokens": num_tokens,
}
def init_messages(self) -> None:
r"""Initializes the stored messages list with the initial system
message.
"""
self.stored_messages: List[MessageType] = [self.system_message]
def update_messages(self, message: ChatMessage) -> List[MessageType]:
r"""Updates the stored messages list with a new message.
Args:
message (ChatMessage): The new message to add to the stored
messages.
Returns:
List[ChatMessage]: The updated stored messages.
"""
self.stored_messages.append(message)
return self.stored_messages
@retry(wait=wait_exponential(min=5, max=60), stop=stop_after_attempt(5))
@openai_api_key_required
def step(
self,
input_message: ChatMessage,
) -> ChatAgentResponse:
r"""Performs a single step in the chat session by generating a response
to the input message.
Args:
input_message (ChatMessage): The input message to the agent.
Returns:
ChatAgentResponse: A struct
containing the output messages, a boolean indicating whether
the chat session has terminated, and information about the chat
session.
"""
messages = self.update_messages(input_message)
if self.message_window_size is not None and len(
messages) > self.message_window_size:
messages = [self.system_message
] + messages[-self.message_window_size:]
openai_messages = [message.to_openai_message() for message in messages]
num_tokens = num_tokens_from_messages(openai_messages, self.model)
# for openai_message in openai_messages:
# # print("{}\t{}".format(openai_message.role, openai_message.content))
# print("{}\t{}\t{}".format(openai_message["role"], hash(openai_message["content"]), openai_message["content"][:60].replace("\n", "")))
# print()
output_messages: Optional[List[ChatMessage]]
info: Dict[str, Any]
if num_tokens < self.model_token_limit:
response = self.model_backend.run(messages=openai_messages)
if not isinstance(response, dict):
raise RuntimeError("OpenAI returned unexpected struct")
output_messages = [
ChatMessage(role_name=self.role_name, role_type=self.role_type,
meta_dict=dict(), **dict(choice["message"]))
for choice in response["choices"]
]
info = self.get_info(
response["id"],
response["usage"],
[str(choice["finish_reason"]) for choice in response["choices"]],
num_tokens,
)
# TODO strict <INFO> check, only in the beginning of the line
# if "<INFO>" in output_messages[0].content:
if output_messages[0].content.split("\n")[-1].startswith("<INFO>"):
self.info = True
else:
self.terminated = True
output_messages = []
info = self.get_info(
None,
None,
["max_tokens_exceeded_by_camel"],
num_tokens,
)
return ChatAgentResponse(output_messages, self.terminated, info)
def __repr__(self) -> str:
r"""Returns a string representation of the :obj:`ChatAgent`.
Returns:
str: The string representation of the :obj:`ChatAgent`.
"""
return f"ChatAgent({self.role_name}, {self.role_type}, {self.model})"
|