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| # ========= Copyright 2023-2024 @ 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 2023-2024 @ CAMEL-AI.org. All Rights Reserved. ========= | |
| from typing import Optional | |
| from camel.agents.chat_agent import ChatAgent | |
| from camel.messages import BaseMessage | |
| from camel.models import BaseModelBackend | |
| from camel.prompts import TextPrompt | |
| from camel.types import RoleType | |
| from camel.utils import create_chunks | |
| # AgentOps decorator setting | |
| try: | |
| import os | |
| if os.getenv("AGENTOPS_API_KEY") is not None: | |
| from agentops import track_agent | |
| else: | |
| raise ImportError | |
| except (ImportError, AttributeError): | |
| from camel.utils import track_agent | |
| class SearchAgent(ChatAgent): | |
| r"""An agent that summarizes text based on a query and evaluates the | |
| relevance of an answer. | |
| Args: | |
| model (BaseModelBackend, optional): The model backend to use for | |
| generating responses. (default: :obj:`OpenAIModel` with | |
| `GPT_4O_MINI`) | |
| """ | |
| def __init__( | |
| self, | |
| model: Optional[BaseModelBackend] = None, | |
| ) -> None: | |
| system_message = BaseMessage( | |
| role_name="Assistant", | |
| role_type=RoleType.ASSISTANT, | |
| meta_dict=None, | |
| content="You are a helpful assistant.", | |
| ) | |
| super().__init__(system_message, model=model) | |
| def summarize_text(self, text: str, query: str) -> str: | |
| r"""Summarize the information from the text, base on the query. | |
| Args: | |
| text (str): Text to summarize. | |
| query (str): What information you want. | |
| Returns: | |
| str: Strings with information. | |
| """ | |
| self.reset() | |
| summary_prompt = TextPrompt( | |
| '''Gather information from this text that relative to the | |
| question, but do not directly answer the question.\nquestion: | |
| {query}\ntext ''' | |
| ) | |
| summary_prompt = summary_prompt.format(query=query) | |
| # Max length of each chunk | |
| max_len = 3000 | |
| results = "" | |
| chunks = create_chunks(text, max_len) | |
| # Summarize | |
| for i, chunk in enumerate(chunks, start=1): | |
| prompt = summary_prompt + str(i) + ": " + chunk | |
| user_msg = BaseMessage.make_user_message( | |
| role_name="User", | |
| content=prompt, | |
| ) | |
| result = self.step(user_msg).msg.content | |
| results += result + "\n" | |
| # Final summarization | |
| final_prompt = TextPrompt( | |
| '''Here are some summarized texts which split from one text. Using | |
| the information to answer the question. If can't find the answer, | |
| you must answer "I can not find the answer to the query" and | |
| explain why.\n Query:\n{query}.\n\nText:\n''' | |
| ) | |
| final_prompt = final_prompt.format(query=query) | |
| prompt = final_prompt + results | |
| user_msg = BaseMessage.make_user_message( | |
| role_name="User", | |
| content=prompt, | |
| ) | |
| response = self.step(user_msg).msg.content | |
| return response | |
| def continue_search(self, query: str, answer: str) -> bool: | |
| r"""Ask whether to continue search or not based on the provided answer. | |
| Args: | |
| query (str): The question. | |
| answer (str): The answer to the question. | |
| Returns: | |
| bool: `True` if the user want to continue search, `False` | |
| otherwise. | |
| """ | |
| prompt = TextPrompt( | |
| "Do you think the ANSWER can answer the QUERY? " | |
| "Use only 'yes' or 'no' to answer.\n" | |
| "===== QUERY =====\n{query}\n\n" | |
| "===== ANSWER =====\n{answer}" | |
| ) | |
| prompt = prompt.format(query=query, answer=answer) | |
| user_msg = BaseMessage.make_user_message( | |
| role_name="User", | |
| content=prompt, | |
| ) | |
| response = self.step(user_msg).msg.content | |
| if "yes" in str(response).lower(): | |
| return False | |
| return True | |