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134 lines
4.5 KiB
Python
134 lines
4.5 KiB
Python
# ========= Copyright 2023-2024 @ CAMEL-AI.org. All Rights Reserved. =========
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ========= Copyright 2023-2024 @ CAMEL-AI.org. All Rights Reserved. =========
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from typing import Optional
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from camel.agents.chat_agent import ChatAgent
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from camel.messages import BaseMessage
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from camel.models import BaseModelBackend
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from camel.prompts import TextPrompt
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from camel.types import RoleType
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from camel.utils import create_chunks
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# AgentOps decorator setting
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try:
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import os
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if os.getenv("AGENTOPS_API_KEY") is not None:
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from agentops import track_agent
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else:
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raise ImportError
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except (ImportError, AttributeError):
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from camel.utils import track_agent
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@track_agent(name="SearchAgent")
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class SearchAgent(ChatAgent):
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r"""An agent that summarizes text based on a query and evaluates the
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relevance of an answer.
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Args:
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model (BaseModelBackend, optional): The model backend to use for
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generating responses. (default: :obj:`OpenAIModel` with
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`GPT_4O_MINI`)
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"""
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def __init__(
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self,
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model: Optional[BaseModelBackend] = None,
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) -> None:
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system_message = BaseMessage(
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role_name="Assistant",
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role_type=RoleType.ASSISTANT,
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meta_dict=None,
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content="You are a helpful assistant.",
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)
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super().__init__(system_message, model=model)
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def summarize_text(self, text: str, query: str) -> str:
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r"""Summarize the information from the text, base on the query.
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Args:
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text (str): Text to summarize.
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query (str): What information you want.
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Returns:
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str: Strings with information.
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"""
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self.reset()
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summary_prompt = TextPrompt(
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'''Gather information from this text that relative to the
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question, but do not directly answer the question.\nquestion:
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{query}\ntext '''
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)
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summary_prompt = summary_prompt.format(query=query)
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# Max length of each chunk
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max_len = 3000
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results = ""
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chunks = create_chunks(text, max_len)
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# Summarize
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for i, chunk in enumerate(chunks, start=1):
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prompt = summary_prompt + str(i) + ": " + chunk
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user_msg = BaseMessage.make_user_message(
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role_name="User",
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content=prompt,
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)
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result = self.step(user_msg).msg.content
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results += result + "\n"
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# Final summarization
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final_prompt = TextPrompt(
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'''Here are some summarized texts which split from one text. Using
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the information to answer the question. If can't find the answer,
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you must answer "I can not find the answer to the query" and
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explain why.\n Query:\n{query}.\n\nText:\n'''
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)
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final_prompt = final_prompt.format(query=query)
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prompt = final_prompt + results
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user_msg = BaseMessage.make_user_message(
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role_name="User",
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content=prompt,
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)
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response = self.step(user_msg).msg.content
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return response
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def continue_search(self, query: str, answer: str) -> bool:
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r"""Ask whether to continue search or not based on the provided answer.
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Args:
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query (str): The question.
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answer (str): The answer to the question.
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Returns:
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bool: `True` if the user want to continue search, `False`
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otherwise.
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"""
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prompt = TextPrompt(
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"Do you think the ANSWER can answer the QUERY? "
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"Use only 'yes' or 'no' to answer.\n"
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"===== QUERY =====\n{query}\n\n"
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"===== ANSWER =====\n{answer}"
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)
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prompt = prompt.format(query=query, answer=answer)
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user_msg = BaseMessage.make_user_message(
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role_name="User",
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content=prompt,
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)
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response = self.step(user_msg).msg.content
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if "yes" in str(response).lower():
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return False
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return True
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